Improving the Overall Efficiency of Automotive Inverters ...

Manuscript ID TPEL-Reg-2018-01-0186.R1 1

Abstract— In order to improve the driving range and

reduce the cost of battery electric vehicles (BEV) through a

higher efficiency, this paper proposes to adopt multilevel

converters using low voltage Si MOSFETs in the electric

powertrains. A multilevel Si MOSFET inverter, a

conventional IGBT inverter and a SiC MOSFET inverter

are modelled and compared using a reference vehicle over

various driving cycles. The costs of the three solutions are

also compared. It is shown that the multilevel Si MOSFET

inverter has a rather high efficiency and realizes the lowest

cost among the three solutions even when the worst case of

cost is considered. Sensitivity analysis also shows that the

multilevel Si MOSFET inverter is suitable for a wide range

of vehicle concepts in addition to the reference vehicle.

Moreover, the multilevel topology also features lower

electromagnetic interference (EMI) and provides

modularity. Therefore, Si MOSFET-based multilevel

inverters are proved in this paper to be an appropriate

option to improve the efficiency and reduce the cost of

electric powertrains.

Index Terms— Cost, driving cycle, efficiency, energy

consumption, SiC MOSFET, Si MOSFET, modelling

NOMENCLATURE

a acceleration of the vehicle

aDiode switching loss coefficient of the anti-parallel diode

aIGBT switching loss coefficient of the IGBT

aSiC switching loss coefficient of the SiC MOSFET

bDiode switching loss coefficient of the anti-parallel diode

bIGBT switching loss coefficient of the IGBT

bSiC switching loss coefficient of the SiC MOSFET

cosθ power factor of the inverter AC output

This work was financially supported by the Singapore National Research

Foundation under its Campus for Research Excellence And Technological

Enterprise (CREATE) programme. The authors would also like to thank

ANSYS, Inc for providing results for verification. This paper was presented in part on the 19th European Conference on Power Electronics and Applications

(EPE'17 ECCE Europe), Warsaw, Poland, September, 11-14, 2017.

Mr. Fengqi Chang (e-mail: [email protected]) and Mr. Prof. Dr. -Ing. Markus Lienkamp (e-mail: [email protected]) are with

TUMCREATE Ltd., 1 Create Way #10-02 CREATE Tower Singapore 138602,

and the Institute of Automotive Technology, Technical University of Munich, Boltzmannstr. 15, 85748 Garching, Germany.

Ms. Dr. Olga Ilina (e-mail: [email protected]) and Mr. Dr. Leon Voss

(e-mail: [email protected]) are with ANSYS Germany GmbH, Staudenfeldweg 20, 80224 Otterfing, Germany.

ES_Diode switching loss energy of the anti-parallel diode

ES_MOS switching loss energy of the MOSFET body

fc frequency of the carrier wave of the CHB inverter

fs switching frequency of the output AC voltage

i output AC current of the inverter (RMS)

iDS drain to source current of the MOSFET

IP_RMS RMS value of the output AC phase current

ma modulation index of the inverter

n number of submodules in each phase of the CHB

nM spinning speed of the electric motor

Pbattery the output power of the battery pack

PC_CHB conduction loss power of the CHB inverter

PC_diode conduction loss power of anti-paralleled diode

PC_IGBT conduction loss power of IGBT body

PC_MOS conduction loss power of MOSFET channel

PC_SiC conduction loss power of SiC MOSFET channel

PCHB_Loss total loss of the CHB inverter

PIGBT_Loss total loss of the IGBT inverter

Ploss total loss of any type of inverter

PS_SiC switching loss power of the SiC inverter

PSiC_Loss total loss of the SiC MOSFET inverter

Qrr recovered charge of the anti-paralleled diode

RC dynamic resistance of the IGBT body

RD dynamic resistance of the anti-paralleled diode

RDth(j-c) junction to case thermal resistance of the diode

Ron On state resistance of the MOSFET channel

Rth(c-s) case to heatsink thermal resistance

RTth(j-c) junction to case thermal resistance of the transistor

tfi current falling time during turn-off

tfu voltage falling time during turn-on

tri current rising time during turn-on

tru voltage rising time during turn-off

T output torque of the electric motor

Tj junction temperature

u output AC voltage of the inverter (RMS)

uCE0 collector-emitter voltage at 0 A

uDC DC input voltage of the inverter

uF0 forward voltage of the diode at 0 A

v velocity of the vehicle

I. INTRODUCTION

S the emission standards of combustion engines are

growing stricter and different countries have declared their

road maps toward a pure electric mobility society,

electrification of transport is now more concretely confirmed

by both researchers and industry as an inevitable trend [1]–[6].

Improving the Overall Efficiency of Automotive

Inverters Using a Multilevel Converter

Composed of Low Voltage Si MOSFETs

Fengqi Chang, Student Member, IEEE, Olga Ilina, Markus Lienkamp, and Leon Voss

A


Nonetheless, particularly due to the high price of batteries, the

acceptance of electric vehicles (EVs) by the general public is

still hindered, even for an EV with a limited range [7]–[10].

Besides waiting for the price of the battery to decrease, an

alternative solution is to improve the efficiency of the electric

powertrain. A higher efficiency can reduce the requirement of

battery pack capacity for the same range, thus resulting in a

lower initial purchasing cost. Moreover, a higher efficiency

also lowers the total cost of ownership (TCO) due to the saved

driving energy cost.

In general, the electric powertrain, especially the inverter,

has a rather high nominal efficiency [11]–[13]. For an IGBT

inverter with conventional six-pack structure, the efficiency in

nominal or peak power operation can be in excess of 97 %

[12]–[14]. However, in partial load operation, e.g., 10 % of the

nominal power, the efficiency can be as low as 80 % [15]–[17].

This is not a problem for industrial applications where inverters

continuously operate at the nominal power [18], [19], while for

automotive applications the low partial load efficiency

considerably deteriorates the overall efficiency, due to the

fluctuating power demand of vehicles over the driving cycle

[15]–[17]. According to [11], [20], [21], in comprehensive

driving cycles, e.g., WLTP or NEDC cycle, the overall

efficiency of the conventional inverter is in the range of

85-90 %. Therefore, to further improve the overall efficiency of

automotive inverters for realistic use cases, major research

focus should be on the improvement of partial load efficiency.

During past years, although the partial load efficiency of

conventional IGBT inverters has not been the focus in the field

of power electronic, efforts have already been taken by

different researchers to solve this problem. [21]–[31] used

different methods to vary the DC bus voltage of the inverter at

different driving speeds to optimize the efficiency at partial

load. Among those, [21]–[25] used a DC/DC converter

between the inverter and the battery pack, while [27]–[29]

proposed to control the DC voltage using a Z-source inverter.

To remove the passive components required by the DC/DC

conversion, [30], [31] used an active battery pack that actively

parallels or cascades the battery modules to generate different

DC voltages at different speeds. Sharing the idea of enhancing

the flexibility, [15]–[17] paralleled multiple IGBTs in the

inverter, and the number of IGBTs used to conduct the load

current was actively controlled at partial load to realize an

optimal trade-off between conduction loss and switching loss.

The partial load efficiency is therefore improved.

In the previously mentioned studies, conventional six-pack

IGBT inverters are used in combination with additional control

measures. Other researchers proposed to completely replace the

IGBTs with MOSFET devices made with wide band gap

(WBG) material, especially SiC MOSETs, and proposed this

approach as the ultimate solution of the powertrain efficiency

problem [32]–[36]. The benefits of SiC regarding efficiency

and high temperature endurance have been researched and

proved in many studies, but it is still controversial whether or

when these benefits are able to pay off the high price of a SiC

inverter in automotive applications, especially for light duty

private urban vehicles [36]–[44]. To partially avoid the high

price of a pure SiC inverter, [42]–[44] proposed to parallel a

small SiC MOSFET next to each IGBT in the six-pack structure

to absorb the switching transient of the IGBT and handle the

low power. In these circuits IGBTs are operating under soft

switching conditions. However significant challenges

regarding the switching transient control must be overcome. In

[45] a low voltage Si MOSFET inverter with only a 48V DC

input is built to drive a 300 kW multiphase motor. This

approach avoids the high price of SiC while obtaining the

desired low switching loss. Experimental results prove that

both switching loss and conduction loss are considerably lower

than a conventional IGBT inverter at partial load. Due to the

low price of 48 V Si MOSFETs, the system also has a low cost.

However, challenges regarding high current (up to higher than

2000 A) have to be managed [45].

Based on previous studies, two essential methods shared by

all studies can be summarized: firstly, enough degrees of

freedom should be given to improve the partial load efficiency;

secondly, unipolar power electronic switches (both SiC and Si

MOSFETs) have a significantly better partial load performance

than IGBTs because of their resistive conduction features and

their intrinsically low switching loss. Therefore, combining the

two essential methods, considering the high price of SiC

switches, and also the trend to use higher voltage in EVs to

reduce the current density of fast charging [46], this paper

proposes to use multilevel converters composed of low voltage

Si MOSFETs in the powertrains of EVs.

The idea to use multilevel converters in EVs is not

completely new. Multilevel converters have also been used in

EVs by other previous studies [47]–[53], which, however,

majorly focused on the benefit of battery balancing and did not

necessarily specify the use of Si MOSFETs. The efficiency

benefit in EV applications has not been sufficiently discussed

either. [48] compared the efficiency of a MOSFET multilevel

converter to a conventional IGBT converter by sweeping the

output power from 0 until 100 % of the rated power. [51]

assessed the efficiency of a modular multilevel converter

(MMC) with one driving profile of an EV. It is observed that a

comprehensive evaluation of the multilevel converters in real

EV application scenarios is still not yet available. A

well-rounded comparison to the conventional six-pack IGBT

inverters and SiC inverters is also absent.

In this paper a multilevel inverter is modelled and compared

to a conventional IGBT inverter and a pure SiC inverter in

different application scenarios of EVs. A longitudinal vehicle

model is constructed and verified for the comparison. Aspects

including efficiency improvement and cost reduction are

considered in the evaluation. The general suitability of using

multilevel topologies in different vehicles and different

scenarios is also discussed.

The following chapters are organized as follows: The second

chapter contains the modelling of the three types of inverters as

mentioned above, and verifications of the models using

ANSYS Simplorer software. The third chapter and the fourth

chapter compare the three inverters in a reference vehicle

(BMW i3), respectively in terms of efficiency improvement

and cost reduction. A sensitivity analysis is also conducted in


chapter four to evaluate the multilevel inverters in different

vehicle concepts and different scenarios. The following fifth

chapter shortly discusses other EV-relevant benefits of the

multilevel inverters.

II. LOSS MODELS AND VERIFICATIONS

The circuits of the three inverters to be modelled are shown

in Fig. 1. As the models will be used for driving cycle

simulations, the loss models should consider average values

rather than detailed transient behavior to provide acceptable

simulation speed. In this paper, all the losses are evaluated

based on the average values over a base frequency period of the

AC output.

Additionally, to simplify the modelling of multilevel

inverters, the topology Cascaded H-Bridges (CHB) is selected

in this paper as a representative of multilevel inverters and

carrier phase shifted PWM (PS-PWM) is selected as the

modulation algorithm.

A. Modelling of Cascaded H-Bridges

For the CHB with n modules in each phase as in Fig. 1(c), the

conduction loss is modelled first. Considering the bidirectional

conducting ability of MOSFETs, when the phase current is not

high enough to turn on the anti-paralleled diodes, the

conduction loss is just caused by the phase current passing

through the inner resistance 2n MOSFETs in each phase, as

shown in (1).

2

C_CHB P_RMS on P_RMS on F06 for ( 2 )P ni R I R u (1)

When the diodes are conducting current, the calculation is

more complicated. Considering that the PS-PWM is used in the

CHB, the working pattern of each half bridge in the CHB

circuit resembles the half-bridges in a common MOSFET

six-pack inverter driving an AC electric machine. Therefore,

the conduction loss of each MOSFET in the CHB can be

obtained as in (2) [54]. Detailed derivation steps are in

Appendix I.

2

C_MOS on P_RMS

C_Diode F0 _

2

d P_RMS

C_CHB C_MOS C_Diode

P_RMS on F0

cos12 ( )

8 3cos1

2 ( )2 8

cos12 ( )

8 312 ( + )

( 2 )

a

a

P RMS

a

mP R I

mP u I

mR I

P n P P

i R u

(2)

However, the situation that the diode is conducting the

current can seldom happen, because most low voltage

automotive Si MOSFETs have a rather low inner resistance and

the diode cannot be triggered in the rated current range.

Additionally, even for Si MOSFETs with a higher inner

resistance, as an BEV mostly works at partial load, a load

current high enough to trigger the diode can be rarely seen in

practical usages.

For the switching loss of the CHB, a linear approximation of

the switching transient is implemented in (3), as suggested in

[54], to calculate the energy loss of turn-on and turn-off

processes. The parameters determining the rising/falling time

of current and voltage can be found in the datasheet or the

specification of the driving circuit. The worst-case recovery

loss of diodes is considered as the switching loss of diode.

S_MOS DS ri fu fi ru

S_Diode rr DC

( ) / 2DCE u i t t t t

E Q u

(3)

Replacing the instantaneous drain to source current by the

average phase current, and multiplying the energy loss with the

carrier frequency and the total number of switches, the average

switching loss of a CHB over a base frequency period is

obtained as in (4).

c P_RMS

S_MOS ri fu fi ru

S_Diode c rr DC

12 2( )

12

DCn f u IP t t t t

P nf Q u

(4)

Thus, when the phase current is not high enough to trigger

the conduction of diodes, i.e., P_RMS on F02I R u , the average

loss of the CHB over a base period is calculated in (5), where fs

is the switching frequency observed in the output voltage

waveform. When PS-PWM is used in the CHB, the wanted

output switching frequency fs equals 2nfc.

When the diodes in the CHB are conducting current, i.e.,

P_RMS on F02I R u , which seldom happens, (6) should be adopted

instead.

s P_RMS2

CHB_Loss P_RMS on ri fu fi ru s rr DC

6 26 + ( ) 6

DCf u IP ni R t t t t f Q u

(5)

MA B C

MA B C

(a) (b)

ua ub uc

SM1C

SM2C

SMnC

(c)

Fig. 1. The three different inverters to be modelled. (a) Six-pack IGBT inverter;(b) Six-pack SiC MOSFET Inverter;(c) Cascaded H-Bridge with n

submodules in each phase.


2

C_MOS on P_RMS

2

C_Diode F0 _ d P_RMS

s P_RMS

CHB_Loss C_MOS C_Diode ri fu fi ru s rr DC

cos12 ( )

8 3cos cos1 1

2 ( ) 2 ( )2 8 8 3

6 26( + ) ( ) 6

a

a a

P RMS

DC

mP R I

m mP u I R I

f u IP P P t t t t f Q u

(6)

Although (5) is obtained based on the PS-PWM algorithm,

without significant error, this model can also be used to

describe the loss of a CHB controlled by other PWM methods,

as long as the condition of no conduction by diodes still holds.

No matter which PWM method is used, when the

anti-paralleled diodes in a CHB are not conducting current, in a

2n+1 level CHB (referring to phase voltage, so throughout the

paper) there are always 2n MOSFET channels per phase

conducting the current, which means the conduction loss item

in (5) still applies. And regardless of the choice of PWM

algorithm, when the output voltage has a switching frequency

of fs, the total times of switching in one second in the CHB

should always be 6fs, Thus the switching loss should be always

6fs(ES_MOS + ES_Diode), the same as switching loss items in (5).

Only when considering the thermal dependence of the switch

parameters, errors could be introduced by the different heat

distributions of different PWM methods.

One step further, if the condition of no diode conduction still

applies, due to the same resemblance of switching and

conducting behaviors, this loss model can also be used for other

MOSFET multilevel inverter topologies besides the CHB, such

as ANPC or the classic multilevel modular converters (MMC)

(ignoring the circular current as in [51]). The conclusions

obtained based on the CHB are therefore generally applicable

for different types of multilevel MOSFET inverters.

B. Modelling of a Six-Pack IGBT Inverter and a Six-Pack SiC

MOSFET Inverter

The loss model of the IGBT inverter is in (7), which is also

used and verified by measurement results in [55]. The

switching loss is a linear approximation of datasheet values

based on DC bus voltage and load current.

For the six-pack SiC MOSFET inverter, due to the similarity

of the conduction behavior, a conduction loss model of a

six-pack Si MOSFET inverter in [54] can be used. According to

datasheets and the measurement results of [56], the total

switching loss of the SiC MOSFETs is approximately linearly

dependent on the DC bus voltage and the load current.

Recovery loss of the diode is neglected due to the low recovery

charge of SiC diodes [56]. Therefore, when the current is not

high enough to trigger the anti-paralleled diode, the loss of a

SiC MOSFET six-pack inverter is modelled by (8).

If the current is high enough to trigger the conduction of the

anti-paralleled diode, (9) should be used to calculate the total

loss.

2a a

C_IGBT CE0 P_RMS C P_RMS

2a a

C_Diode F0 P_RMS D P_RMS

P_RMS P_RMS

S s IGBT IGBT s Diode Diode

IGBT_Loss C_IGTB C_Diode

cos cos1 12 ( ) 2 ( )

2 8 8 3cos cos1 1

2 ) 2 ( )2 8 8 3

2 2 2 2( ) ( )

6( +

DC DC

m mP u I R I

m mP u I R I

I IP f u a b f u a b

P P P

S+ )P

(7)

2

C_SiC on P_RMS

C_Diode

P_RMS

S_SiC s DC SiC SiC

SiC_Loss C_SiC C_Diode S

3

0

2 2( )

6( + + )

P R I

P

IP f u a b

P P P P

(8)

2

C_SiC on P_RMS

2a a

C_Diode F0 P_RMS D P_RMS

P_RMS

S s DC SiC SiC

SiC_Loss C_SiC C_Diode S

cos12 ( )

8 3cos cos1 1

2 ( ) 2 ( )2 8 8 3

2 2( )

6( + + )

amP R I

m mP u I R I

IP f u a b

P P P P

(9)

C. Thermal Model of the Inverters

Since most parameters of the three loss models have thermal

dependence, to improve the accuracy of the models, a thermal

model based on equivalent circuit is implemented in this paper

to estimate the junction temperature as illustrated in Fig. 2.

The values of the thermal resistance thermal capacitance can

be found in the datasheets. The heatsink temperature is set to be

constantly 50 to simplify the simulation. The losses of the

transistor and the diode switch in Fig. 2 are the average value

over one base period. The thermal circuit can thus be used to

calculate the average junction temperature, based on which the


values of the thermal dependent parameters can be determined

in the next time step of simulation.

D. Verification of the Models

For verification, the results of the three models are compared

to the results collected in ANSYS Simplorer, which

implements detailed semiconductor models and thermal models

and is able to calculate the losses with an error less than 5%

compared to experimental results [57] [58]. Although this

simulation platform has a confirmed high accuracy, it is not

appropriate to directly verify the loss models in driving cycles,

because the simulation speed is largely limited by the detailed

semiconductor models. Therefore, the accurate models and the

average models are compared at operational points that are

frequently seen in electric powertrains. In this research, the

output voltage, output current and power factor (cosθ) of the

selected operational points are respectively in the range of 50 V

to 160 V (phase peak value), 50 A to 250 A (phase peak value),

and 0.6 to 1.0.

In the verification, the configurations of the three inverters

are listed in Table I. These values are selected to match the

specifications of the BMW i3 powertrain, the reference vehicle

in this research for benchmarking. This vehicle is selected

mainly due to the availability of the parameters. The maximum

continuous currents of the three inverters are all 400 A (RMS

value, rated at 75 ambient temperature). For the IGBT

inverter, the HybridPAC2 module FS800R07A2E3 is selected,

which is exactly the IGBT module used in the reference vehicle

of this paper according to the report of Oak Ridge National

Laboratory (ORNL) [59]. Thus this switch is able to benchmark

the IGBT modules used in current electric vehicles.

C2M0025120D is selected for SiC MOSFET inverter, as this

switch has the lowest on-state resistance among all the choices

of Wolfspeed (excluding bare dies) and represents the

state-of-art performance of SiC MOSFETs. The Si MOSFET

IPP100N10S3-05 is not specifically chosen. This switch is just

selected from the automotive standard MOSFETs of Infineon

to test and demonstrate the general performance of the CHB

inverter. The intention of such a selection of switch would be to

compare a generally configured CHB with the state-of-art SiC

MOSFET inverter, and the benchmarked IGBT inverter, which

is practically used in the reference vehicle, and demonstrate the

potential of the proposal in the paper. This is not an indication

of optimal choice, or a recommendation for real

implementations. Further optimization of the switch selection

and the circuit configuration (number of levels, number of

parallel etc.) is still possible.

The gate resistors of all the solutions are configured to be 2.2

Ω, as this is also the value used in the reference vehicle [59].

The switching frequencies of three solutions in the verification

are different. The switching frequency of the IGBT inverter in

the reference vehicle is unknown, but it is selected to be 10

kHz, as this is the median in the switching frequency range

recommended in [60], and this switching frequency also

matches the best with the experimental results in [59] and [61]

at different operational points. The SiC MOSFET and CHB are

verified at 20 kHz to demonstrate the ability to work at a higher

switching frequency, which is also the frequency typically used

to reduce acoustic noises of switching.

The detailed comparison results of the three inverters are

listed in Appendix II. It is observed that the CHB loss model

and the SiC inverter loss model have an accuracy of 1 %

compared with the ANSYS Simplorer results at all points. The

accuracy of the IGBT model is slightly lower. The maximum

efficiency error is 2.45 %, but the error is still mostly in the

same level as the other two inverters and stays within 1 % at

most operational points.

To further verify the loss model of the IGBT and make sure

this research is correctly benchmarked, the simulated efficiency

map, Fig. 3(a), and the efficiency map measured by ORNL

[59], Fig. 3(b), of the IGBT inverter in the reference vehicle are

Rth(c-s)

RDth(j-c)

CDth(j-c)CTth(j-c)

RTth(j-c)

PTransistor PDiode

50

Tj

Fig. 2. Equivalent circuit thermal model.

TABLE I

CONFIGURATIONS OF THE THREE INVERTERS

Si IGBT SiC MOSFET CHB

Output voltage (phase-peak value) 180 V 180 V 180 V

Rated current (75 RMS value) 400 A 400 A 400 A

Selected switch FS800R07A2E3 C2M0025120D IPP100N10S3-05

Gate resistance 2.2 Ω 2.2 Ω 2.2 Ω

DC voltage 360 V 360 V 60 V

per module

Number of submodules 1 1 3×3=9

Number of parallel 1 6 6

Total number of switches 1×6=6 6×6=36 6×4×9=216

Output switching frequency 10 kHz 20 kHz 20 kHz


compared. It can be observed that firstly the shapes of the

efficiency contours in two maps match each other accurately.

The correspondences of the speeds to the contour curves are

rather close. Selecting any specific point of speed and torque

combination, the absolute efficiency error is within 1 %. The

IGBT loss model is hence proved to be accurate when

compared to experimental results. This comparison to

measured results also further proves that verifying the proposed

models with the results generated in ANSYS Simplorer is

reliable. Therefore, the three average models are proved to be

accurate and can be used in driving cycle simulations to

generate reliable results.

III. EFFICIENCY EVALUATION WITH DRIVING CYCLES

A. Longitudinal Model of the Reference Vehicle

To evaluate the efficiency of different inverters with

different driving cycles, the longitudinal model of the reference

vehicle, including the electric motor model, is built as in the

block diagram in Fig. 4. Relevant parameters are listed in

TABLE II. Since the inverter model of the reference vehicle is

already verified in the previous chapter, using the reference

vehicle in driving cycle simulations can better manifest the

advantages and disadvantages of alternative solutions in real

life.

The vehicle model is verified by a comparison with the

experimental results obtained by the Argonne National

Laboratory (ANL) in a consumption test using the FTP72

driving cycle. The measured energy consumption of the

reference vehicle over a FTP72 driving cycle is 1248 Wh [61],

whilst the model gives a driving consumption of 1265 Wh. The

error is 1.42 %. The comparison of the simulated and measured

battery pack current in Fig. 4 further proves the accuracy of the

model. The average of the absolute error of the simulated

waveform is 0.88 A. Therefore, this vehicle model can also be

reliably used in driving cycle simulations to compare different

inverter solutions.

B. Simulation Results and Discussion

Firstly, besides the efficiency map of the IGBT inverter in

Fig. 3(a), the efficiency maps of the SiC MOSFET inverter and

the CHB inverter in speed-torque coordinate are further

generated in Fig. 6 for comparison. In Fig. 3(a), it is seen that

the efficiency of the IGBT inverter is constantly higher than

97% in high speed range (6,000-12,000 rpm), but deteriorates

significantly at lower speed. In the low speed range

(1,000-4,000 rpm), the efficiency of the IGBT inverter varies

from 70 % - 95 %. The low partial load efficiency problem is

again confirmed by the efficiency map.

In comparison, as observed in Fig. 6(a) and (b), the SiC

inverter and the CHB inverter achieve a higher efficiency in

9898

98

98 98

97

97

96

96

9695

95

94

9 494

93

929

190

9090

93

92

87

84

81787 0

70

9795

50

100

150

200

250

Torq

ue

in N

·m

2000 4000 6000 8000 10000 120000

Motor rotation speed in RPM

20

30

40

50

60

70

80

90

100

Eff

icie

ncy

in %

97

95

99

99

(a)

250

200

150

100

50

Torq

ue

in N

m

1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000

95

90

85

80

75

Eff

icie

ncy

in %

125 kW

9992

98

98

98

98

98

99

99

99

99

99

99

99

9999

99

97

97

97

96

96

95

9394

95

94

96

95

88

93

91

91

90

84

(b)

Fig. 3. Comparison of the simulated and the measured efficiency maps of the

IGBT inverter. (a) Simulated efficiency map of the IGBT inverter in the reference vehicle; (b) Measured efficiency map of the IGBT inverter in the

reference vehicle [59].

Driving Cycle

Vehicle

Longitudinal

Model

Electric Motor

Model

Inverter

Model

v

a

nM T

u

i

cosθ

Pbattery

Ploss

Fig. 4. Block diagram of the longitudinal vehicle model.

TABLE II

VEHICLE PARAMETER OF A BMW I3 [61]

Parameter Symbol Value

Mass M 1443.3 kg

Rolling resistance fR 0.0075

Air resistance cw 0.33 Cross section AA 2.04 m2

Motor type - HSM

Gear ratio iG 9.7 Transmission efficiency η 98 %

Radius of tyre R 0.350 m

Rotation mass coefficient ∂ 1.0696 Maximum power Pmax 125 kW

0 200 400 600 800 1000 1200 1400-60

-40

-20

0

20

40

60

80

100Simulation ResultMeasurement Result

Time in s

Bat

tery

Pac

k C

urr

ent

in A

Fig. 5. Comparison of battery pack current waveforms in simulation and experiment [61].


both low-speed and high-speed range. In the high-speed range,

the efficiency is improved from 97-99 % to almost constantly

99 %. An improvement of around 2-3 % is observed. In the

low-speed range, the efficiency improvement of both CHB and

the SiC inverter is more significant. The efficiency of these two

solutions varies from 96-99 % in the speed range of

2,000-4,000 rpm, and stays higher than 92 % even when the

speed decreases to 1,000 rpm. The efficiency improvement

compared to the IGBT inverter is in the range of 3-10 %.

Therefore, it can be concluded that both the CHB and the SiC

inverter are able to conspicuously improve the partial load

efficiency compared to the IGBT inverter. The major reason of

this improvement is the usage of unipolar switches (MOSFETs

in this paper) in both solutions [20], [45], which is the first

essential method summarized in the introduction. At partial

load, since a MOSFET conducts the current like a resistor, the

conduction loss is in comparison much lower than that of an

IGBT, which conducts like a diode and causes constant voltage

drop. The switching loss of the MOSFET is also much lower

because of its intrinsically high switching speed.

The variation of efficiency improvement in different load

scenarios is also manifested correspondingly in the overall

energy consumptions. Based on the vehicle model and the

inverter loss models, the energy consumptions of the reference

vehicle using the three inverters are simulated in different

driving cycles. The results of the three inverter solutions are

listed in Table III, Table IV and Table V respectively. All the

energy values are converted to kWh/100km to form a

comparison basis.

(a) (b)

Fig. 6. Efficiency maps of the two inverters in speed-torque coordinate. (a) SiC inverter; (b) CHB inverter.

TABLE III SIMULATION RESULTS OF THE IGBT INVERTER,

ENERGY VALUES CONVERTED TO KWH/100 KM

Driving Cycles BEV Consumption Inverter Efficiency Inverter Loss Conduction Loss Switching Loss

Urban

Cycles

USA NECC 10.3 kWh 86.2 % 4.18 kWh 0.72 kWh 3.45 kWh

Europe City 8.4 kWh 86.8 % 2.31 kWh 0.33 kWh 1.98 kWh USA City II 8.5 kWh 88.8 % 2.09 kWh 0.32 kWh 1.76 kWh

Synthesis

Cycles

FTP 72 9.7 kWh 90.8 % 1.72 kWh 0.27 kWh 1.45 kWh

NEDC 11.1 kWh 91.9 % 1.39 kWh 0.19 kWh 1.20 kWh WLTP C3 12.8 kWh 93.7 % 1.20 kWh 0.18 kWh 1.02 kWh

Highway

Cycles

Artemis 150 19.10 kWh 96.6 % 0.85 kWh 0.14 kWh 0.61 kWh

Artemis 130 18.10 kWh 96.5 % 0.72 kWh 0.12 kWh 0.60 kWh

TABLE IV

SIMULATION RESULTS OF THE SIC INVERTER, ENERGY VALUES CONVERTED TO KWH/100 KM


Urban

Cycles


Europe City 6.4 kWh 97.8 % 0.34 kWh 0.14 kWh 0.20 kWh

USA City II 6.8 kWh 97.8 % 0.38 kWh 0.19 kWh 0.19 kWh

Synthesis

Cycles


NEDC 9.9 kWh 98.8 % 0.20 kWh 0.09 kWh 0.11 kWh

WLTP C3 11.8 kWh 98.9 % 0.20 kWh 0.09 kWh 0.11 kWh

Highway

Cycles

Artemis 150 18.5 kWh 99.2 % 0.16 kWh 0.08 kWh 0.08 kWh Artemis 130 17.5 kWh 99.3 % 0.14 kWh 0.07 kWh 0.07 kWh


The efficiency benefits of the SiC and CHB inverters depend

on the driving scenarios. For the typical highway driving cycle,

Fig. 7(a), more than 75 % of the operating points have a speed

higher than 6000 rpm. The lower improvement in this area

limits the efficiency improvement of the SiC and CHB inverters

to only 2-3 %. In contrast, for the comprehensive or urban

driving cycles, since the range of 1000-4000 rpm covers more

than 50 % of the non-zero operating points, Fig. 7 (b) and (c),

the overall efficiency improvement is correspondingly in the

range of 5-10 %.

The energy consumption results correspond well to the

efficiency maps and show that the improvement of partial load

efficiency is more important in terms of urban and

comprehensive scenarios.

Secondly, comparing the results of the SiC inverter and the

CHB inverter, it can be observed that the efficiencies of these

two inverters are similar, but the loss distribution is different.

The total switching losses of the CHB is 50 % lower than that of

the SiC inverter despite the usage of Si switches, because the

CHB is switching at a much lower DC voltage. The total

conduction loss of the CHB is not lower than that of the SiC

inverter, although the Si MOSFET switches have lower

on-state resistance, because the load current passes through

more switches in the CHB than in the six-pack SiC inverter.

That indicates for further optimization of the CHB in real

implementations, the number of submodules should be limited

to achieve a better efficiency. A better selection of switches or

modules could also further improve the efficiency.

Therefore, based on the simulation results and analysis, it can

be concluded that the both SiC inverter and the CHB are able to

improve the overall efficiency significantly, especially in urban

or comprehensive driving scenarios due to the usage of unipolar

switches. Their performances in terms of efficiency are similar,

but the distribution of the losses is different due to the topology

difference.

IV. COST ANALYSIS

As the major motivation of this research is to reduce the

purchase cost of EVs through a higher efficiency, it is necessary

to calculate and compare the cost of each concept. And since it

is almost impossible to calculate the cost influence of different

inverters based on the bill of materials (BOM) of a whole

vehicle, the cost comparison in this paper is limited to the cost

difference of the inverter in and the battery, which can be

changed by the different efficiencies of different solutions. The

other parts are assumed not to be influenced and have a constant

total cost.

A. Material Cost Calculation of Inverter Solutions

In this paper, the material cost of each inverter solution is

calculated based on the cost models in [62] and [63],

considering the costs of switches, capacitors, cooling system,

gate drivers, controlling circuits and also other overhead costs.

As the models in [62] and [63] are constructed based on mass

production costs, the estimated costs can manifest the OEM

purchasing price and, therefore, demonstrate the realistic costs

of the three solutions when used in a mass-produced vehicle.

The block diagram of the cost calculation model is shown in

Fig. 8.

In the model in Fig. 8, the switch cost is firstly calculated

based on the model published in [63], in which the switch type,

packaging type and the die size are required. These parameters

are available on the website of manufacturers when searching

for the specific name of the switch. The cost of SiC MOSFET

per 1mm2 of die size in the model is recalibrated based on the

current price of the market, as a major decline of SiC switch

TABLE V

SIMULATION RESULTS OF THE CHB INVERTER, ENERGY VALUES CONVERTED TO KWH/100 KM


Urban

Cycles


Europe City 6.4 kWh 98.1 % 0.30 kWh 0.15 kWh 0.15 kWh

USA City II 6.8 kWh 98.1 % 0.32 kWh 0.19 kWh 0.13 kWh

Synthesis

Cycles


NEDC 9.9 kWh 98.9 % 0.17 kWh 0.08 kWh 0.09 kWh

WLTP C3 11.8 kWh 99.1 % 0.17 kWh 0.09 kWh 0.08 kWh

Highway

Cycles

Artemis 150 18.5 kWh 99.4 % 0.13 kWh 0.08 kWh 0.04 kWh Artemis 130 17.5 kWh 99.4 % 0.11 kWh 0.07 kWh 0.04 kWh

0 2000 4000 6000 8000 100000

0.05

0.1

0.15

0.2

0.25

Rotation speed of electric motor in rpm

Rate

of

dis

trib

uti

on

0 2000 4000 6000 8000 100000

0.02

0.04

0.06

0.08

0.1

0.12


Rat

e o

f d

istr

ibu

tio

n

0 2000 4000 6000 8000 100000

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18


Rate

of

dis

trib

uti

on

(a) (b) (c)

Fig. 7. Speed distributions of a comprehensive driving cycle and an urban driving cycle. (a) Artemis 130 driving cycle ; (b) WLTP C3 driving cycle; (c) USA City II driving cycle.


price has been observed since the publication of [63].

Then the driver cost, or the driving circuit cost, is estimated

based on the material of the switch. For the IGBT and Si

MOSFET, the driving circuit is assumed to have one isolated

±15V DC power supply MEA1D0515DC and one isolated

circuit driver 1ED020I12-F2. The costs of other components

are negligible. The unit price of the driving circuit of the IGBT

and Si MOSFET is thus estimated to be USD 6.5, based on the

large bundle prices of the two components. The driving circuit

of the SiC is special, because the gate voltage output is required

to be +20/-5 V. According to the reference design

CGD15FB45P1 of Wolfspeed, the cheapest solution results in a

cost of USD 11, using the large volume prices of the relevant

components.

For the cost of capacitor, the IGBT inverter and the SiC

inverter are assumed to have a 475 uF, 450 V capacitor, the

same as in the reference vehicle’s inverter [59]. The CHB needs

no capacitors on the DC link of submodules, because filtering is

meaningless when the current of the submodules is always AC.

The cost of the cooling system is estimated based on the cost

of the liquid cooled heatsinks in [63], [64], in which both the

material costs and the manufacturing costs are considered. The

heat dissipaters in the liquid cooling systems of the three

solutions are assumed to have the same specifications. As the

CHB requires a heatsink in each submodule, the cost of each

heatsink is calculated based on the maximum loss per

submodule, and then summed together to manifest the

manufacturing cost of each small heatsinks. However, in real

implementations, a better approach might be to let the CHB

share the heatsinks with the battery module, because batteries

always require strong cooling for safety reasons and the

maximum additional heating load of one H-Bridge module can

be neglected compared to that of batteries.

Besides the costs of power components, the cost of the

controlling circuit, i.e., the central controller of the inverter and

submodules, necessary communication ICs and wires, is

estimated based on the topology type. All the three inverters are

assumed to be controlled by a DSP (Digital Signal Processor)

board, which in total costs USD 150 according to the large

volume prices of relevant components on online purchasing

platforms [65]. The cost of the controlling circuit of the two

six-pack inverters is thus USD 150. For the CHB, each

submodule additionally needs one CPLD EPM7064AETC44

(USD 5.25) chip and one set of fiber optic receiver/transceiver

HFBR-2522/1521Z (respectively USD 5.72 and 5.24 for the

received and transceiver) to implement rapid communication

and control. Therefore, an additional 9×(5.25 + 5.72 + 5.24) ≈

150 USD is assumed to apply for the CHB inverter and

resulting in a total cost of USD 300 for the controlling circuits

of the CHB.

In the end, the total cost of the inverter is calculated by

multiplying the component costs with an overhead cost factor

of 1.25 for Si switch inverters, 1.1 for SiC switch inverters, to

count in the cost of manufacturing and assembly [62], [63]. The

cost estimations of the three inverter solutions using the model

in Fig. 8 are listed in TABLE VI, in which U/P and Qty mean

respectively the unit price and quantity. The cost model shows

that although the SiC inverter and CHB inverter are more

efficient, their cost is also relatively high. The SiC inverter cost

is about 100 % higher than the cost of the IGBT inverter

because of a higher switch price, whilst the higher cost of the

CHB is caused by a higher number of utilized components.

That also indicates for real implementations of the CHB, the

number of submodules is not the larger the better. An optimal

configuration needs to be further explored.

It is also worth noting that, although this paper seems to use

discrete devices for cost analysis, it does not indicate that the

Number of

Drivers

Maximum

Loss

Topology

Type

450V Capacitor

Cost model [63]

Cost per Driver

SiC: 11 USD

Si: 6.5 USD

- Capacitance

CHB: -

IGBT: 470uF [59]

SiC: 470uF [59]

Submodules

CHB: 9

Six-Pack: 1

×

×

×÷

Single Heatsink

Cost model [63]

××

SUM

Driver Cost Capacitor Cost Cooling Cost

Controlling Circuit Cost

CHB: 300 USD

Six-Pack: 150USD

××

Number of

Switches

Switch

Name

Switch Price

Model in [63]

Switch Type

Die Size

Package Type

Cost per Switch

××

Switch Cost

Overhead factor for housing, assembly, etc.

Si: 1.25 [62]

SiC: 1.1 [62][63]

Total Cost of the Inverter

+++

+ +

Fig. 8. Cost calculation model for the cost comparison of SiC, IGBT and CHB inverters.


paper recommends using discrete devices in real

implementations. In fact, a number of switch modules and

driving circuit module are available. The intention of using

discrete devices is only to simplify the cost modelling and make

the analysis clearer.

B. Cost Comparison Considering the Influence on Battery

As the battery pack counts for about 30-50 % in the total cost

of an EV, to evaluate the overall cost of different inverter

solutions, the influence of the efficiency on the battery cost

should be considered. A higher efficiency requires a lower

battery pack capacity for the same nominal driving range and

thus reduces the purchase cost of an EV. In this section, taking

the reference vehicle as a benchmark, the overall costs (battery

and inverter) of three solutions are compared. In the

comparison, the battery pack capacity is sized according to the

300 km nominal range requirement of the reference vehicle in

WLPT driving cycle test, as the WLPT cycle will soon be the

standard testing cycle internationally to quantify the nominal

range of electric cars [66]. The battery cost is obtained by

multiplying the per kWh price 150 USD/kW [8]. Adding the

material cost of the inverter solution to the corresponding

battery cost, the overall cost of the solution can be calculated as

in VII. Additionally the cost of contactors in the battery pack is

also considered in VII. For the IGBT inverter and SiC inverter,

two high voltage contactors are required at both positive and

negative of the battery pack. For the CHB, since the voltage of

each module is below 60 V and considered to be in low voltage

range, it is not necessarily required to have contactors on the

batteries [67]. However, to demonstrate the worst case of the

CHB in the paper, each module of the CHB is assumed to have

one 48V contactor on the positive side of the battery to ensure

full stop of high voltage during vehicle shutdown.

It is observed that the SiC inverter solution has the highest

total cost, because the price of the SiC switches is right now

still too high to be counterbalanced by the saved battery cost.

Using the cost model in this paper, the unit price of one SiC

switch should be lower than USD 18.98, i.e., a per-current price

of 0.22 USD/A, to break even with the IGBT inverter solution.

The lowest cost among the three solutions is achieved by the

CHB inverter. Although the CHB inverter price is slightly

higher than that of the IGBT inverter, due to its high efficiency,

the additional cost is easily paid off. The CHB solution is in the

end USD 67.2 cheaper than the IGBT solution in the reference

vehicle.

The CHB solution also has the potential to further reduce the

cost by optimizing the topology design, switch selection, usage

of contactors and controlling circuit. As a conclusion, it is

proven by the cost comparison based on the WLTP C3 cycle

that the CHB inverter outperforms the SiC inverter and the

IGBT inverter also in terms of purchasing cost. SiC switch

price needs to decline to 0.22 USD/A to break even with the

IGBT inverter, and to 0.19 USD/A to break even with the CHB

solution, under the assumption that the Si based inverters will

not be cheaper in the future.

C. Sensitivity Analysis

So far, the CHB has been proved to be a better choice than

the SiC and the IGBT inverter using the current price values

and in the reference vehicle. To demonstrate the general

applicability of the CHB, a sensitivity analysis is conducted in

this section to demonstrate the advantages of the CHB in

different vehicles and different scenarios. Four parameters: the

nominal range, battery price, vehicle weight and driving cycle

are varied to define a range of vehicle concepts in which the

CHB inverter solution will bring benefit.

Firstly, the nominal range rated by the WLTP C3 cycle is

swept from 100 km to 800 km as in Fig. 9. It is seen that as the

nominal range increases, the advantages of the two solutions

with higher efficiency will be more significant, because a larger

battery capacity can be saved.

However, as the SiC inverter has a much higher purchasing

price, compared to the IGBT solution, only when the nominal

range is higher than 540 km, the saved battery cost can

counterbalance the additional cost of power electronics. The

CHB solution sees the break-even point at the nominal range of

255 km. That means as long as the nominal range of the vehicle

TABLE VI

COST COMPARISON OF THE THREE INVERTERS IN USD

Costs IGBT inverter SiC inverter CHB inverter

U/P Qty Sum U/P Qty Sum U/P Qty Sum

Switch cost 296.6 1 296.6 28.1 36 1011.6 0.94 216 203.4

Driver cost 6.5 6 39 11 6 66 6.5 36 234

Capacitor cost 30.3 1 30.3 30.3 1 30.3 - 0 0 Heatsink cost 17.3 1 17.3 14.9 1 14.9 1.8 9 16.2

Controlling cost 150 1 150 150 1 150 300 1 300

Overhead cost 133.3 127.3 188.6 Inverter total sum 666.5 1400 943.3

TABLE VII

COST COMPARISON INCLUDING BATTERY

Driving cycle: WLTP IGBT inverter SiC inverter CHB inverter

U/P Qty Sum U/P Qty Sum U/P Qty Sum

Inverter cost 666.5 1 666.5 1400 1 1400 943.3 1 943.3

Battery cost 150 38.4 5760 150 35.7 5355 150 35.4 5310 Contactor cost 37 2 74 37 2 74 20 9 180

Total sum of inverter and

battery pack costs

6500.5 6829 6433.3


is higher than 255 km, the CHB will result in a lower cost than

the IGBT inverter in the reference vehicle.

Secondly, as a steady trend of battery price reduction has

been observed in the recent 7-10 years, it is also necessary to

discuss the situation when the battery is cheaper. A sweep of

battery price from 70 to 200 USD/kWh is conducted and

plotted in Fig. 10.

In the whole interval of battery price, the SiC inverter is

constantly the least preferred among the three solutions. Even

when the battery price is 200 USD/kWh, the saved battery cost

by the SiC inverter is still not higher than the added cost of the

switches. As for the CHB inverter, when the battery price is

higher than 127 USD/kWh, the CHB is still able to realize a

lower overall cost for the vehicle with a rated range of 300 km.

However, as in this paper the worst case cost of the CHB is used

in the comparison, in reality the CHB solution is suitable in an

even wider range of battery price. Therefore, even when the

battery price is lower in the future, the CHB solution is still in

favor.

Thirdly, the cost sensitivity to the vehicle mass is also

analyzed, as the reference vehicle discussed in this paper has a

rather low weight and the power demand of the powertrain is

relatively smooth compared to heavier vehicles and the partial

load problem is relatively not severe. In the sweep of vehicle

mass, the power rating of the inverters and the motor changes

proportionally with the mass to keep the longitudinal dynamic

performance constant. The cost of the switches in the inverters

thus also changes in proportion. WTLP C3 cycle is still used to

rate the required range at 300 km. Therefore, the overall

efficiency of the three inverters stay unchanged due to the

proportional changes of relevant parameters and the unchanged

driving cycle. The result of the mass sweep from 1000 kg to

3500 kg, which covers the mass of light private vehicles until

minibuses, is illustrated in Fig. 11.

As the weight increases, the difference between the overall

costs of three solutions enlarges, because the load of the

powertrain distributes in an even larger range and prefers more

efficient solutions. As long as the vehicle mass is higher than

1440 kg, the cost of the CHB is lower than the IGBT solution.

For heavier vehicles, the CHB inverter solution is even more

advantageous. However, it is worth noting that the total cost

difference of the three inverter solutions is unclear in term of

percentage in this sensitivity analysis, because the cost of the

whole vehicles is not known nor the research focus of this

paper. The SiC inverter solution becomes even more expensive

as weight increases. The reason is that the rated power of the

inverters increases proportionally with the mass, and the SiC

switch cost grows fasters than the saved battery cost, resulting

in an even higher cost compared to the IGBT inverter solution.

As the last part of the sensitivity analysis, the driving cycle is

also varied. In general, the range of the vehicles is rated by

OEMs currently using the NEDC cycle, and in the future the

WLTP cycle. Other driving cycles are used not as often as these

two comprehensive cycles. However, to observe the advantage

of the CHB solution in different driving scenarios, a sweep of

driving cycles is still conducted in the cost analysis. The

calculations of the total battery capacity required by each

solution still use 300 km as the rated range. The total costs of

different solutions in different driving cycles are in Fig. 12.

When the range of the vehicle is rated by the two highway

driving cycles, the energy can be saved by the SiC inverter or

the CHB inverter is relatively less, because the powertrain

operates mostly in nominal load area. Therefore, the CHB

IGBT

SiC

CHB

100 200 300 400 500 600 700 800Rated range in WLTP C3 cycle in km

0

2000

4000

6000

8000

10000

12000

14000

16000

18000C

ost

of

bat

tery

and i

nver

ter

in d

iffe

rent

solu

tions

in U

SD

255 km, CHB

break even

540 km, SiC

break even

Fig. 9. The sensitivity of the inverter solution cost to the nominal range.

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

60 80 100 120 140 160 180 200

Battery price in USD/kWh

IGBT

SiC

CHB

Co

st o

f b

atte

ry a

nd

in

ver

ter

in d

iffe

ren

t

solu

tio

ns

in U

SD

127 USD/kWh,

CHB break even

Fig. 10. The sensitivity of the inverter solution cost to the battery price.

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

1000 1500 2000 2500 3000 3500Vehicle mass in kg

IGBT

SiC

CHB

Cost

of

bat

tery

and i

nver

ter

in d

iffe

rent

solu

tions

in U

SD

1440 kg, CHB

break even

Fig. 11. The sensitivity of the inverter solution cost to the mass of the vehicle.

IGBT

SiC

CHB

USANECC

EuropeCity

USACity II

FTP 72 NEDCWLTP

C3Artemis

150Artemis

130

Driving Cycles

0

2000

4000

6000

8000

10000

12000

Cost

of

veh

icle

s w

ith d

iffe

rent

inver

ter

solu

tions

in U

SD

Fig. 12. The sensitivity of the inverter solution cost to driving cycles.


solution and the SiC solution both have a higher cost than the

IGBT solution in this case. When evaluated by the

comprehensive or urban driving cycle, the benefit of the high

partial load efficiency starts to emerge. The CHB solution

realizes a lower cost than the IGBT solution in all the urban and

comprehensive driving cycles, while the SiC solution is only

cheaper than the IGBT solution when evaluated by urban

driving cycles.

Based on the cost comparison and the sensitivity analysis in

this chapter, it can be concluded that the CHB inverter solution

is able to bring benefit in terms of cost for a wide range of

vehicles over different driving scenarios. Considering the

worst-case CHB cost scenario is adopted in the comparisons

and analysis, the suitability of the CHB inverter solution

applies in fact for even more vehicles and in more scenarios.

Therefore, the concept of using MOSFET multilevel inverters

in EVs is in general beneficial.

V. DISCUSSION

Other than the efficiency and cost, a number of other factors

are also relevant for the implementation in electric vehicles, in

which the CHB solution has both pros and cons. From the point

of view of electric engineers, the weight, volume, reliability,

EMI and complexity of control of different solutions should be

discussed. For automotive engineers, the inverter solution also

has a major influence on the overall design of electric

powertrains. The further advantages and disadvantages in these

aspects should be qualitatively discussed.

A. Discussion on Electrical Performances

In this section, the weight, volume, reliability, EMI and the

complexity of control of the three solutions are discussed.

Firstly, the weight and volume, i.e., the power density of the

inverters are important of automotive applications, because the

energy consumption and cost are directly influenced by them.

Compared to the SiC and IGBT inverters using six-pack

topology, the CHB has inevitably a higher weight, as more

components are used. However, as the additional components

are only ICs, switches or driving circuits, the added weight is

limited within several kilograms. Additionally, considering the

saved weight of the batteries, even this few kilograms can be

compensated.

The CHB also has a larger volume which may result in

difficulty of vehicle packaging. Therefore, the optimal method

to implement CHB inverter is to integrate the H-Bridge

modules into the battery pack, in which the H-Bridge board can

be put horizontally on top of battery modules. Thus the larger

volume of the CHB inverter just results in a minor increase of

the height of the battery pack and the H-Bridges share the

heatsink with batteries. A demonstration of this method using a

battery pack, which will be used in full scale prototyping in the

following years, is shown in Fig. 13. The PCBs on the battery

module heatsinks now are the battery management systems

(BMS) and will be replaced by H-Bridge boards. The H-Bridge

boards can be mounted onto the battery module heatsinks

similarly. This only makes the battery pack 1-2 cm higher than

before. Therefore, although CHB inverter does have a higher

weight and larger volume, the caused influence is rather minor

for electric vehicles.

Secondly, reliability is also important of the selection of

inverter solutions. Previous studies proved that due to the

higher number of switches, the reliability of multilevel

topologies is significantly lower compared to six-pack

topologies in industrial applications [67]–[70]. For automotive

applications, the reliability of the switches is not the only

source of failure anymore, the solder joints and connecting

quality have a more conspicuous influence, due to vibration,

humidity etc. to be expected [71]–[73]. Therefore, as the CHB

inverter requires more connecting and soldering in the final

assembly, the full power reliability of the CHB could be lower

than the six-pack inverters, despite a lower thermal stress on the

switches. Nonetheless, the availability, i.e., the percentage of

fully or partially functional time, CHB is expected to be higher

than the six-pack inverters, due to the possibility of fault

tolerance operation [68], [70].

Thirdly, EMI should be considered in the inverter selection.

As the CHB is switching at a much lower DC voltage, the dv/dt

is naturally lower. EMI filtering of the CHB inverter could be

easier. The implementation of SiC MOSFETs on the contrary

causes much worse EMI problems as reported in different

studies [74]–[77], since SiC MOSFET is switching a high

voltage at a rather high speed. To replace the IGBTs with SiC

MOSFET, correspondingly improved EMI filters are also

required. Therefore, in terms of EMI, the CHB or multilevel

topologies will be preferred.

Another obstacle to widely implement CHB or any other

multilevel topologies is their high complexity of control [50],

[78], as PWM of multilevel topologies is not as easy as 2-level

inverters and requires inevitably more computation and

communication resources. This complexity is naturally not

preferred by engineers, who are not familiar with multilevel

topologies. Additionally, as a main research topic regarding

multilevel converters, different algorithms to further utilize the

advantages of such topologies, such as harmonic reduction

[79], SOC balancing [48], [50], fault-tolerance operation [70],

[80], etc., have also been explored intensively by previous

researchers, which demands even more computational

resources. That is also the reason this papers estimates the

controlling circuit of the CHB is much more expensive than the

other two inverters.

Heatsink of

battery modules

BMS, to be replaced by

H-Bridges

Fig. 13. Demonstration of CHB integration into the battery pack.


Based on the previous discussions, it can be summarized that

the CHB has the advantage of lower EMI, but disadvantage in

terms of weight, volume, reliability and control complexity,

among which the increase of weight and volume are not

significant for automotive applications.

B. Influences on Powertrain Design

Beside the factors commonly concerning the power

electronic engineers, the influence of different solutions on the

overall powertrain structure design should also be discussed.

Firstly, using the cascaded type of multilevel topologies, e.g.,

the CHB discussed in this paper, it is not simple anymore to use

multiple motors in the powertrain, because the shared DC bus

to supply multiple inverters does not exist and each additional

CHB means more battery modules. Nonetheless, powertrains

using multiple motors are found in a number of vehicles

available on the market, such as Tesla Model S, to enhance the

vehicle performance. That forms a main drawback of the CHB

solution.

Secondly, while discharging, the battery modules in the CHB

is experiencing an AC current instead of DC current, as in Fig.

14, the measured battery current waveform in a single low

power H-Bridge. Whether this large ripple is harmful or not for

the batteries is still unclear. Researchers concluded differently

in previous studies [81]–[86]. The influence of such a ripple

current on batteries will also be the next step of the research.

The main advantage of the CHB solution for powertrain

design is its easier expandability from 400 V to 800 V (due to

its modularity), which is a trend in the automotive industry and

already implemented in Porsche Mission E to reduce the

charging current density [46]. For the IGBT inverters, 1200 V

automotive standard IGBTs are required to handle 800 V and

resulting in a much higher switch cost, while for SiC inverters,

a higher DC voltage further deteriorate the EMI problem.

Therefore, the trend to have a higher voltage powertrain is more

in favor of the CHB solution.

Another point to be noted is that the price of SiC switches is

gradually declining and may meet the breakeven point

eventually. As stated in section 4.2, the break-even point of SiC

switch price with regard to IGBT is 0.22 USD/A, 0.19 USD/A

to the worst case CHB solution. If the contactors in the CHB are

removed, the break-even point further will decline to 0.15

USD/A. However, considering the current price of SiC

MOSFET is still above 0.30 USD/A [87], breaking-even with

the other two solutions will still take some time. Furthermore,

even when the price of SiC MOSFETs is comparable with Si

switches, the concept of using multilevel inverters in BEVs

might still be reasonable by turning to use SiC switches in the

topology for some vehicles. On the one hand, the pros and cons

of multilevel inverters are still applicable in this case. On the

other hand, the price of switches is not linear with their voltage.

Using SiC MOSFETs rated at lower voltage in a multilevel

inverter may in the end result in a lower total cost. To fully

utilize the high switching speed of SiC MOSFETs without

generating a high EMI, a multilevel inverter is also a good

choice.

VI. CONCLUSION

Motivated by the cost reduction effect of a higher efficiency,

this paper firstly summarizes the two essential features of the

previous methods to improve the partial load efficiency, i.e., the

utilization of unipolar switches and the enhancement of the

controlling flexibility. Then by combining the two features

together, this paper proposes to use the Si MOSFET based

multilevel inverters in EVs to improve the overall efficiency

and reduce the powertrain cost.

Only as a representative of this proposal, a cascaded

H-Bridge inverter is compared to a conventional IGBT inverter,

which is used in the reference vehicle in real life, and a SiC

MOSFET inverter, which demonstrates the state-of-art

performance, using the reference vehicle model. The advantage

of the CHB in terms of efficiency is proven in simulations

based on carefully built and verified models. A cost analysis is

also conducted based on the available cost models, and the

results show that the Si MOSFET based multilevel inverters

can generally realize a lower cost for different EV concepts in

different scenarios, due to the low switch price and the

improved overall efficiency. It should be also noted that the

IGBT inverter in this paper demonstrates the tier-one

performance among current automotive inverters. The

reference vehicle also has a light weight and a rather efficient, a

relative low switching frequency, and a compact electric motor

to further enhance the efficiency. When compared to other

being-used IGBT inverters, the improvement is expected to be

more significant. Therefore, it can be concluded that Si

MOSFET based multilevel inverters have a great potential to

improve the efficiency and reduce the cost of electric

powertrain systems.

Beside the efficiency and cost, in the aspects of volume,

weight, reliability, complexity of control and the influences on

powertrain design, the CHB is also qualitatively compared to

the IGBT and SiC inverter based on previous studies. The

proposal to use CHB is proved to have both disadvantages and

advantages when the view of comparison is broadened.

Fig. 14. A measured current waveform of one battery module in an H-bridge

(10 mV/A).


Whether battery aging is deteriorated in the CHB is still not

clear yet, and will be the next step of the study.

This paper is primarily about the proposal and the

verification of this concept. To fully exploit its benefit, more

detailed studies regarding the optimization of the circuits still

need to be conducted. The cost of the CHB could also be further

optimized if appropriate MOSFET modules can be found to

replace the discrete switches used in this paper for

simplification. And for real life implementation, it is also

important to investigate if the CHB is fit for the desired overall

powertrain design.

APPENDIX I. DERIVATION OF THE CHB CONDUCTION LOSS

MODEL

When using PS-PWM to modulate CHB module, the total

conduction loss in one H-Bridge module could be described by

the following formula, (11), in which N is half of the carrier

ratio. Assuming the switching frequency is much higher than

the base frequency, i.e., N goes to infinity, the sums in the

formula can be written as integrals as in (12). And the average

per switch conduction loss in (2) can be obtained by dividing

the final results of the previous integrals by 4.

APPENDIX II. RESULTS COMPARISON WITH ANSYS SIMPLORER

To verify the proposed loss models with the results collected

in ANSYS Simplorer, the efficiency values are compared at the

commonly seen operational points. Efficiency error is defined

in (10):

Model Simplorer

Simplorer

e _fficiency error

(10)

The efficiency errors of the IGBT inverter model, the SiC

inverter model and the CHB inverter model are listed in

TABLE VIII, TABLE IX and TABLE X respectively. The

efficiency errors of all three models are within 2 % at all points.

The IGBT model tends to overestimate the efficiency while the

other two models have an underestimation of the efficiency.

Therefore, the energy consumption estimations based on the

three models are reliable.

2

P_RMS on 2

C_MOS

2

P_RMS on 2

1

P_RMS F

C_Diode

2

P_RMS D 2

sin( ) 12sin ( )sin( )

2

1 sin( )2sin ( )sin( )

2

1 sin( )2sin( )sin( )

2

2sin ( )

N a

k N

Na

k

N aa

k N

a

kmI R k k NP

N N N

kmI R k k N

N N Nk

mm I u k k NPN N N

m I r k

N

P_RMS F

1

2

P_RMS D 2

1

1 sin( )

sin( )2

1 sin( )2sin( )sin( )

2

1 sin( )2sin ( )sin( )

2

N a

k N

Na

a

k

Na

a

k

km

k N

N N

kmm I u k k N

N N Nk

mm I r k k N

N N N

(11)

2

P_RMS on 2

C_MOS

2

P_RMS on 2

0

P_RMS F

C_Diode

2

P_RMS D 2

2 sin( ) 1sin ( )sin( )

22 1 sin( )

sin ( )sin( )2

2 1 sin( )sin( )sin( )

22 1 sin(

sin ( )sin( )

a

a

a a

a a

I R m tP t t d t

I R m tt t d t

m I u m tP t t d t

m I r mt t

P_RMS F

0

2

P_RMS D 2

0

)

22 1 sin( )

sin( )sin( )2

2 1 sin( )sin ( )sin( )

2

a a

a a

td t

m I u m tt t d t

m I r m tt t d t

(12)


CONTRIBUTIONS

Mr. Fengqi Chang initiated the research topic, developed the

average models and obtained the results in the paper. Dr. Olga

Ilina and Dr. Leon Voss verified the accuracy of the models

using the ANSYS Simplorer Software, and also helped to

optimize the structure and the language of the paper. Mr.

Professor Markus Lienkamp made an essential contribution to

the conception of the research project. He revised the paper

critically for important intellectual content. Professor Markus

Lienkamp gave final approval of the version to be published

and agrees to all aspects of the work. As a guarantor, he accepts

responsibility for the overall integrity of the paper.

REFERENCES

[1] A. Beltramo, A. Julea, N. Refa, Y. Drossinos, C. Thiel, and S. Quoilin,

“Using electric vehicles as flexible resource in power systems: A case

study in the Netherlands,” 14th Int. Conf. Eur. Energy Mark. EEM, 2017. [2] J. R. Serrano, “Imagining the future of the internal combustion engine for

ground transport in the current context,” Appl. Sci., vol. 7, no. 10, 2017.

[3] E. Chemali, M. Peindl, P. Malysz, and A. Emadi, “Electrochemical and Electrostatic Energy Storage and Management Systems for Electric Drive

Vehicles: State-of-the-Art Review and Future Trends,” IEEE J. Emerg.

Sel. Top. Power Electron., vol. 4, no. 3, pp. 1117–1134, 2016.

[4] E. Shafiei, J. Leaver, and B. Davidsdottir, “Cost-effectiveness analysis of

inducing green vehicles to achieve deep reductions in greenhouse gas

emissions in New Zealand,” J. Clean. Prod., vol. 150, pp. 339–351, 2017. [5] S. G. Wirasingha and A. Emadi, “Classification and review of control

strategies for plug-in hybrid electric vehicles,” IEEE Trans. Veh.

Technol., vol. 60, no. 1, pp. 111–122, 2011. [6] M. Yilmaz and P. T. Krein, “Review of charging power levels and

infrastructure for plug-in electric and hybrid vehicles,” 2012 IEEE Int.

Electr. Veh. Conf. IEVC 2012, vol. 28, no. 5, pp. 2151–2169, 2012. [7] ADAC, “Wie rentabel sind Elektroautos?,” p. 35, 2016.

[8] F. Michael, K. Mathias, S. Rohr, S. Schickrama, M. Sinninga, and M.

Lienkamp, “An Overview of Costs for Vehicle Components, Fuels, Greenhouse Gas Emissions and Total Cost of Ownership Update 2017,”

2017.

[9] B. Propfe, M. Redelbach, D. J. Santini, and H. Friedrich, “Cost analysis of plug-in hybrid electric vehicles including maintenance & repair costs and

resale values,” World Electr. Veh. J., vol. 5, no. 4, pp. 886–895, 2012.

[10] M. Wiestschel, P. Plotz, A. Kuhn, and T. Gnann, “Market Evolution

Scenarios for Electric Vehicles,” p. 36, 2013.

[11] E. A. Grunditz and T. Thiringer, “Characterizing BEV powertrain energy

consumption, efficiency, and range during official and drive cycles from Gothenburg, Sweden,” IEEE Trans. Veh. Technol., vol. 65, no. 6, pp.

3964–3980, 2016.

[12] S. S. Williamson, A. Emadi, and K. Rajashekara, “Comprehensive efficiency modeling of electric traction motor drives for hybrid electric

vehicle propulsion applications,” IEEE Trans. Veh. Technol., vol. 56, no.

4 I, pp. 1561–1572, 2007. [13] S. S. Williamson, S. M. Lukic, and A. Emadi, “Comprehensive drive train

efficiency analysis of hybrid electric and fuel cell vehicles based on

motor-controller efficiency modeling,” IEEE Trans. Power Electron., vol. 21, no. 3, pp. 730–740, 2006.

[14] H. Tanabe, T. Kojima, A. Imakiire, K. Fuji, M. Kozako, and M. Hikita,

“Comparison performance of Si-IGBT and SiC-MOSFET used for high efficiency inverter of contactless power transfer system,” Proc. Int. Conf.

Power Electron. Drive Syst., vol. 2015–Augus, no. June, pp. 707–710,

2015.

[15] E. Knischourek and D. Gerling, “Analysis of Electric Vehicle Driving

Cycles for Inverter Efficiency Improvement at Partial Load,” Power

Electron. Drive Syst., no. June, pp. 503–508, 2015. [16] K. Muehlbauer and D. Gerling, “Improvement of energy efficiency in

power electronics at partial load,” IECON 2011 - 37th Annu. Conf. IEEE Ind. Electron. Soc., pp. 2775–2779, 2011.

[17] E. Knischourek, K. Muehlbauer, and D. Gerling, “Power losses reduction

in an electric traction drive at partial load operation,” in 2012 IEEE International Electric Vehicle Conference, 2012, pp. 1–6.

[18] A. Reger, M. Hamacher, J. Böhner, T. Kestler, and R. Steinhilper,

“Analyzing the active power of variable frequency drives in manufacturing plants,” 2014 4th Int. Electr. Drives Prod. Conf. EDPC

2014 - Proc., 2014.

[19] Y. Okazaki et al., “Experimental Comparisons Between Modular Multilevel DSCC Inverters and TSBC Converters for Medium-Voltage

Motor Drives,” IEEE Trans. Power Electron., vol. 32, no. 3, pp. 1802–

1817, 2017.

TABLE VIII

EFFICIENCY ERRORS OF THE IGBT INVERTER MODEL COMPARED TO THE SIMPLORER RESULTS

Voltage

Current 50 V 100 V 150 V 160 V Power

Factor

50 A -1.64 % -0.90 % -0.61 % -0.57 %

0.6

100 A -2.45 % -1.34 % -0.90 % -0.84 %

150 A -2.24 % -1.19 % -0.80 % -0.75 %

200 A -2.04 % -1.07 % -0.71 % -0.66 %

250 A -1.90 % -0.99 % -0.65 % -0.60 %

50 A -1.30 % -0.69 % -0.45 % -0.42 %

0.8

100 A -1.92 % -1.01 % -0.67 % -0.62 %

150 A -1.74 % -0.89 % -0.58 % -0.54 %

200 A -1.57 % -0.80 % -0.51 % -0.48 %

250 A -1.47 % -0.73 % -0.47 % -0.43 %

50 A -1.07 % -0.55 % -0.35 % -0.33 %

1.0

100 A -1.57 % -0.80 % -0.52 % -0.48 %

150 A -1.42 % -0.71 % -0.45 % -0.42 %

200 A -1.28 % -0.63 % -0.39 % -0.36 %

250 A -1.18 % -0.57 % -0.35 % -0.33 %

TABLE IX EFFICIENCY ERRORS OF THE SIC INVERTER MODEL

COMPARED TO THE SIMPLORER RESULTS

Voltage

Current 50 V 100 V 150 V 160 V

Power

Factor

50 A -1.19 % -0.65 % -0.44 % -0.41 %

0.6

100 A -0.77 % -0.44 % -0.30 % -0.29 %

150 A -0.36 % -0.28 % -0.17 % -0.19 %

200 A -0.16 % -0.13 % -0.01 % -0.09 %

250 A 0.09 % 0.01 % -0.01 % -0.01 %

50 A -1.13 % -0.61 % -0.41 % -0.39 %

0.8

100 A -0.81 % -0.45 % -0.31 % -0.29 %

150 A -0.54 % -0.32 % -0.22 % -0.21 %

200 A -0.31 % -0.20 % -0.14 % -0.14 %

250 A -0.09 % -0.09 % -0.07 % -0.07 %

50 A -1.13 % -0.61 % -0.40 % -0.38 %

1.0

100 A -0.86 % -0.47 % -0.32 % -0.31 %

150 A -0.63 % -0.36 % -0.25 % -0.24 %

200 A -0.43 % -0.26 % -0.18 % -0.17 %

250 A -0.24 % -0.16 % -0.11 % -0.11 %

TABLE X EFFICIENCY ERRORS OF THE CHB INVERTER MODEL

COMPARED TO THE SIMPLORER RESULTS

Voltage

Current 50 V 100 V 150 V 160 V Power

Factor

50 A -0.98% -0.68% -0.49% -0.46%

0.6

100 A -0.87% -0.55% -0.39% -0.37%

150 A -0.23% -0.21% -0.19% -0.18%

200 A 0.03% -0.08% -0.11% -0.11%

250 A 0.16% -0.01% -0.07% -0.07%

50 A -0.89% -0.56% -0.42% -0.40%

0.8

100 A -0.45% -0.34% -0.29% -0.28%

150 A -0.30% -0.27% -0.25% -0.25%

200 A -0.23% -0.24% -0.24% -0.23%

250 A -0.21% -0.04% -0.23% -0.23%

50 A -0.80% -0.54% -0.42% -0.41%

1.0

100 A -0.47% -0.38% -0.33% -0.32%

150 A -0.37% -0.33% -0.31% -0.30%

200 A -0.33% -0.31% -0.30% -0.30%

250 A -0.32% -0.31% -0.31% -0.31%


[20] F. Chang, O. Ilina, O. Hegazi, L. Voss, and M. Lienkamp, “Adopting

MOSFET Multilevel Inverters to Improve the Partial Load Efficiency of Electric Vehicles,” in proceedings EPE 2017, 2017, pp. 1–13.

[21] J. O. Estima and A. J. Marques Cardoso, “Efficiency analysis of drive

train topologies applied to electric/hybrid vehicles,” IEEE Trans. Veh. Technol., vol. 61, no. 3, pp. 1021–1031, 2012.

[22] R. Karimi, D. Kaczorowski, A. Zlotnik, and A. Mertens, “Loss

optimizing control of a multiphase interleaving DC-DC converter for use in a hybrid electric vehicle drivetrain,” ECCE 2016 - IEEE Energy

Convers. Congr. Expo. Proc., 2016.

[23] W. Deng, Y. Zhao, and J. Wu, “Energy efficiency improvement via bus voltage control of inverter for electric vehicles,” IEEE Trans. Veh.

Technol., vol. 66, no. 2, pp. 1063–1073, 2017.

[24] M. Roche, W. Shabbir, and S. Evangelou, “Voltage Control for Enhanced Power Electronic Efficiency in Series Hybrid Electric Vehicles,” IEEE

Trans. Veh. Technol., vol. 66, no. 5, pp. 1–1, 2016.

[25] H. Chen, H. Kim, R. Erickson, and D. Maksimovic, “Electrified Automotive Powertrain Architecture Using Composite DC-DC

Converters,” IEEE Trans. Power Electron., vol. 8993, no. c, pp. 1–1,

2016. [26] J. Fu, Z. Zhang, Y. F. Liu, and P. C. Sen, “MOSFET switching loss model

and optimal design of a current source driver considering the current

diversion problem,” IEEE Trans. Power Electron., vol. 27, no. 2, pp. 998–1012, 2012.

[27] A. Battiston, E. Miliani, S. Pierfederici, and F. Meibody-tabar,

“Efficiency Improvement of a Quasi-Z-Source Inverter-Fed Permanent-Magnet Synchronous Machine-Based Electric Vehicle,” IEEE

Trans. Transp. Electrif., vol. 2, no. 1, pp. 14–23, 2016. [28] Q. Lei, D. Cao, and F. Z. Peng, “Novel loss and harmonic minimized

vector modulation for a current-fed quasi-Z-source inverter in HEV motor

drive application,” IEEE Trans. Power Electron., vol. 29, no. 3, pp. 1344–1357, 2014.

[29] P. Liu and H. P. Liu, “Permanent-magnet synchronous motor drive

system for electric vehicles using bidirectional Z-source inverter,” IET Electr. Syst. Transp., vol. 2, no. 4, p. 178, 2012.

[30] P. Wacker, J. Adermann, B. Danquah, and M. Lienkamp, “Efficiency

determination of active battery switching technology on roller dynamometer,” 2017 12th Int. Conf. Ecol. Veh. Renew. Energies, EVER

2017, 2017.

[31] P. Wacker, L. Wheldon, M. Sperlich, J. Adermann, and M. Lienkamp, “Influence of active battery switching on the drivetrain efficiency of

electric vehicles,” 2017 IEEE Transp. Electrif. Conf. Expo, ITEC 2017,

pp. 33–38, 2017. [32] J. Azurza Anderson, C. Gammeter, L. Schrittwieser, and J. W. Kolar,

“Accurate Calorimetric Switching Loss Measurement for 900V 10mΩ

SiC MOSFETs,” IEEE Trans. Power Electron., vol. 8993, no. c, pp. 1–1, 2017.

[33] A. Merkert, T. Krone, and A. Mertens, “Characterization and scalable

modeling of power semiconductors for optimized design of traction inverters with si-and sic-devices,” IEEE Transactions on Power

Electronics, vol. 29, no. 5. pp. 2238–2245, 2014.

[34] F. Xu et al., “Development of a SiC JFET-based six-pack power module for a fully integrated inverter,” IEEE Trans. Power Electron., vol. 28, no.

3, pp. 1464–1478, 2013.

[35] X. Wen, S. Member, T. Fan, and S. Member, “Technical Approaches Towards Ultra-High Power Density SiC Inverter in Electric Vehicle

Applications,” CES Trans. Electr. Mach. Syst., vol. 1, no. 3, pp. 231–237,

2017. [36] H. Zhang, L. M. Tolbert, and B. Ozpineci, “Impact of SiC devices on

hybrid electric and plug-in hybrid electric vehicles,” IEEE Trans. Ind.

Appl., vol. 47, no. 2, pp. 912–921, 2011. [37] S. Ozdemir, F. Acar, and U. S. Selamogullari, “Comparison of silicon

carbide MOSFET and IGBT based electric vehicle traction inverters,” in

2015 International Conference on Electrical Engineering and Informatics (ICEEI), 2015, no. 113, pp. 1–4.

[38] M. Su, C. Chen, S. Sharma, and J. Kikuchi, “Performance and cost

considerations for SiC-based HEV traction inverter systems,” WiPDA 2015 - 3rd IEEE Work. Wide Bandgap Power Devices Appl., pp. 347–

350, 2015.

[39] F. Shang, A. P. Arribas, and M. Krishnamurthy, “A comprehensive evaluation of SiC devices in traction applications,” 2014 IEEE Transp.

Electrif. Conf. Expo, pp. 1–5, 2014.

[40] J. Biela, M. Schweizer, S. Waffler, B. Wrzecionko, and J. W. Kolar, “SiC vs. Si - Evaluation of Potentials for Performance Improvement of Power

Electronics Converter Systems by SiC Power Semiconductors,” IEEE

Trans. Ind. Electron., vol. 58, no. 7, pp. 2873–2882, 2011. [41] M. Su and C. Chen, “Prospects for the application of SiC power devices in

hybrid electric vehicle drive systems,” in IEEE Workshop on Wide

Bandgap Power Devices & Applications, 2016, pp. 1–22. [42] S. Sic, H. S. Power, J. He, S. Member, R. Katebi, and S. Member, “A

Current-Dependent Switching Strategy for Si/SiC Hybrid Switch-Based

Power Converters,” vol. 64, no. 10, pp. 8344–8352, 2017. [43] S. Ueno, N. Kimura, T. Morizane, and H. Omori, “Study on

characteristics of hybrid switch using Si IGBT and SiC MOSFET

depending on external parameters,” in 2017 19th European Conference on Power Electronics and Applications (EPE’17 ECCE Europe), 2017, p.

P.1-P.10.

[44] J. S. Lai et al., “A hybrid-switch-based soft-switching inverter for ultrahigh-efficiency traction motor drives,” IEEE Trans. Ind. Appl., vol.

50, no. 3, pp. 1966–1973, 2014.

[45] A. Baumgardt, F. Bachheibl, A. Patzak, and D. Gerling, “48V Traction: Innovative Drive Topology and Battery,” SAE Int. J. Altern. Powertrains,

vol. 1, no. 5, pp. 148–156, 2016.

[46] V. Reber, “e-power: New Possibilities with 800-Volt Charging,” Porsche Eng. Mag., no. 1, pp. 10–15, 2016.

[47] L. M. Tolbert, S. Member, F. Z. Peng, T. Cunnyngham, and J. N.

Chiasson, “Charge Balance Control Schemes for Cascade Multilevel Converter in Hybrid Electric Vehicles,” October, vol. 49, no. 5, pp. 1058–

1064, 2002.

[48] L. M. Tolbert, F. Z. Peng, and T. G. Habetler, “Multilevel converters for large electric drives,” IEEE Trans. Ind. Appl., vol. 35, no. 1, pp. 36–44,

1999. [49] F. Altaf and B. Egardt, “Comparative Analysis of Unipolar and Bipolar

Control of Modular Battery for Thermal and State-of-Charge Balancing,”

IEEE Trans. Veh. Technol., vol. 66, no. 4, pp. 2927–2941, 2017. [50] Z. Zheng, K. Wang, L. Xu, and Y. Li, “A hybrid cascaded multilevel

converter for battery energy management applied in electric vehicles,”

IEEE Trans. Power Electron., vol. 29, no. 7, pp. 3537–3546, 2014. [51] M. Quraan, P. Tricoli, S. D’Arco, and L. Piegari, “Efficiency Assessment

of Modular Multilevel Converters for Battery Electric Vehicles,” IEEE

Trans. Power Electron., vol. 32, no. 3, pp. 2041–2051, 2017. [52] F. H. Khan, L. M. Tolbert, and W. E. Webb, “Hybrid electric vehicle

power management solutions based on isolated and nonisolated

configurations of multilevel modular capacitor-clamped converter,” IEEE Trans. Ind. Electron., vol. 56, no. 8, pp. 3079–3095, 2009.

[53] M. Quraan, T. Yeo, P. Tricoli, and S. Korea, “Design and Control of

Modular Multilevel Converters for Battery Electric Vehicles,” IEEE Trans. Power Electron., vol. 8993, no. c, pp. 507–517, 2015.

[54] D. Graovac, M. Pürschel, and K. Andreas, “MOSFET Power Losses

Calculation Using the Data- Sheet Parameters,” Infineon Technol. AG, no. July, pp. 1–23, 2006.

[55] A. Anthon, Z. Zhang, M. A. E. Andersen, G. Holmes, B. McGrath, and C.

Teixeira, “Comparative evaluation of the loss and thermal performance of advanced three level inverter topologies,” IEEE Trans. Ind. Appl., vol. 53,

no. 2, pp. 1381–1389, 2017.

[56] R. M. Burkart and J. W. Kolar, “Comparative Life Cycle Cost Analysis of Si and SiC PV Converter Systems Based on Advanced eta-rho-sigma

Multiobjective Optimization Techniques,” IEEE Trans. Power Electron.,

vol. 32, no. 6, pp. 4344–4358, 2017. [57] F. Wang, S. Kher, T. Fichtner, and J. Aurich, “A new power MOSFET

model and an easy to use characterization tool using device datasheet,” in

2013 IEEE 14th Workshop on Control and Modeling for Power Electronics, COMPEL 2013, 2013, no. 1, pp. 1–5.

[58] J. Aurich, T. Barucki, and H. Lane, “Fast Dynamic Model Family of

Semiconductor Switches,” in Power Electronics Specialists Conference, 2001, pp. 67–74.

[59] M. Olszewski, “Oak Ridge National Laboratory Annual Progress Report

for the Power Electronics and Electric Machinery Program”, October. 2016.

[60] T. Kimura, R. Saitou, K. Kubo, K. Nakatsu, H. Ishikawa, and K. Sasaki,

“High-power-density inverter technology for hybrid and electric vehicle applications,” Hitachi Rev., vol. 63, no. 2, pp. 96–102, 2014.

[61] Advanced Powertrain Research Facility (APRF) at Argonne National

Laboratory, “Test Summary Sheet of BMW i3 BEV,” 2014 [62] G. Domingues-Olavarria, P. Fyhr, A. Reinap, M. Andersson, and M.

Alakula, “From Chip to Converter: A Complete Cost Model for Power

Electronics Converters,” IEEE Trans. Power Electron., vol. 32, no. 11, pp. 8681–8692, 2017.


[63] R. Burkart and J. W. Kolar, “Component cost models for multi-objective

optimizations of switched-mode power converters,” 2013 IEEE Energy Convers. Congr. Expo. ECCE 2013, pp. 2139–2146, 2013.

[64] U. Drofenik, A. Stupar, and J. W. Kolar, “Analysis of theoretical limits of

forced-air cooling using advanced composite materials with high thermal conductivities,” IEEE Trans. Components, Packag. Manuf. Technol., vol.

1, no. 4, pp. 528–535, 2011.

[65] “findic.com.” [Online]. Available: http://www.findic.com/.

[66] M. Tutuianu et al., “Development of a World-wide Worldwide

harmonized Light duty driving Test Cycle,” Tech. Rep., vol. 3, no. January, pp. 7–10, 2014.

[67] J. Xu, P. Zhao, and C. Zhao, “Reliability analysis and redundancy

configuration of MMC with hybrid submodule topologies,” IEEE Trans. Power Electron., vol. 31, no. 4, pp. 2720–2729, 2016.

[68] P. Tu, S. Yang, and P. Wang, “Reliability and Cost based Redundancy

Design for Modular Multilevel Converter,” IEEE Trans. Ind. Electron., vol. 46, no. c, 2018.

[69] F. Richardeau and T. T. L. Pham, “Reliability calculation of multilevel

converters: Theory and applications,” IEEE Trans. Ind. Electron., vol. 60, no. 10, pp. 4225–4233, 2013.

[70] T. Soong and P. W. Lehn, “Assessment of Fault Tolerance in Modular

Multilevel Converters with Integrated Energy Storage,” IEEE Trans. Power Electron., vol. 31, no. 6, pp. 4085–4095, 2016.

[71] R. Bayerer, T. Herrmann, T. Licht, J. Lutz, and M. Feller, “Model for Power Cycling lifetime of IGBT Modules,” Integr. Power Syst. (CIPS),

2008 5th Int. Conf., pp. 1–6, 2008.

[72] Y. Yang, V.-S. Sularea, K. Ma, and F. Blaabjerg, “Advanced design tools for the reliability of power electronics — Case studies on a photovoltaic

(PV) system,” IECON 2015 - 41st Annu. Conf. IEEE Ind. Electron. Soc.,

pp. 002828–002833, 2015. [73] B. Gadalla, E. Schaltz, and F. Blaabjerg, “A survey on the reliability of

power electronics in electro-mobility applications,” in Joint International

Conference - ACEMP 2015: Aegean Conference on Electrical Machines and Power Electronics, OPTIM 2015: Optimization of Electrical and

Electronic Equipment and ELECTROMOTION 2015: International

Symposium on Advanced Electromechanical Moti, 2016, pp. 304–310. [74] N. Oswald, P. Anthony, N. McNeill, and B. H. Stark, “An experimental

investigation of the tradeoff between switching losses and EMI

generation with hard-switched All-Si, Si-SiC, and All-SiC device

combinations,” IEEE Trans. Power Electron., vol. 29, no. 5, pp. 2393–

2407, 2014.

[75] V. Dos Santos, B. Cougo, N. Roux, B. Sareni, B. Revol, and J. P. Carayon, “Trade-off between losses and EMI issues in three-phase SiC

inverters for aircraft applications,” IEEE Int. Symp. Electromagn.

Compat., vol. 3, pp. 55–60, 2017. [76] Y. Wang, Q. Ma, and T. Cui, “Repetitive control strategy of SiC

MOSFET to reduce EMI generation,” in IECON 2017 - 43rd Annual

Conference of the IEEE Industrial Electronics Society, 2017, pp. 1464–1469.

[77] X. Yuan, S. Walder, and N. Oswald, “EMI generation characteristics of

SiC and Si Diodes: Influence of reverse-recovery characteristics,” IEEE Trans. Power Electron., vol. 30, no. 3, pp. 1131–1136, 2015.

[78] F. Z. Peng, “A generalized multilevel inverter topology with self voltage

balancing,” IEEE Trans. Ind. Appl., vol. 37, no. 2, pp. 611–618, 2001. [79] C. D. Townsend, Y. Yu, G. Konstantinou, and V. G. Agelidis, “Cascaded

H-Bridge Multilevel PV Topology for Alleviation of Per-Phase Power

Imbalances and Reduction of Second Harmonic Voltage Ripple,” IEEE

Trans. Power Electron., vol. 31, no. 8, pp. 5574–5586, 2016.

[80] M. Evzelman, M. M. Ur Rehman, K. Hathaway, R. Zane, D. Costinett,

and D. Maksimovic, “Active Balancing System for Electric Vehicles With Incorporated Low-Voltage Bus,” IEEE Trans. Power Electron., vol.

31, no. 11, pp. 7887–7895, 2016.

[81] S. D. De Breucker, K. Engelen, R. D’hulst, and J. Driesen, “Impact of current ripple on li-ion battery ageing,” World Electr. Veh. J., vol. 6, no.

3, pp. 532–540, 2013.

[82] M. Uno and K. Tanaka, “Influence of high-frequency charge-discharge cycling induced by cell voltage equalizers on the life performance of

lithium-ion cells,” IEEE Trans. Veh. Technol., vol. 60, no. 4, pp. 1505–

1515, 2011. [83] S. Y. Cho, I. O. Lee, J. Il Baek, and G. W. Moon, “Battery Impedance

Analysis Considering DC Component in Sinusoidal Ripple-Current

Charging,” IEEE Trans. Ind. Electron., vol. 63, no. 3, pp. 1561–1573, 2016.

[84] L. R. Chen, S. L. Wu, D. T. Shieh, and T. R. Chen,

“Sinusoidal-ripple-current charging strategy and optimal charging frequency study for Li-ion batteries,” IEEE Trans. Ind. Electron., vol. 60,

no. 1, pp. 88–97, 2013.

[85] S. Bala, T. Tengner, P. Rosenfeld, and F. Delince, “The effect of low frequency current ripple on the performance of a Lithium Iron Phosphate

(LFP) battery energy storage system,” Energy Convers. Congr. Expo.

(ECCE), 2012 IEEE, pp. 3485–3492, 2012. [86] K. Uddin, A. D. Moore, A. Barai, and J. Marco, “The effects of high

frequency current ripple on electric vehicle battery performance,” Appl.

Energy, vol. 178, pp. 142–154, 2016. [87] L. Schrittwieser, “99% Efficient Three-Phase Buck-Type SiC MOSFET

PFC Rectifier Minimizing Life Cycle Cost in DC Data Centers,” CPSS

Trans. Power Electron. Appl., vol. 2, no. 1, pp. 47–58, Apr. 2017.

Fengqi Chang (S’14) was born in

Xinxiang, Henan China, on May 6, 1991.

He received the Bachelor and Master

degrees in Electrical Engineering from

Tsinghua University, respectively in 2013

and 2015. He is currently pursuing his Ph.D.

degree in the Institute of Automotive

Technology, Technical University of

Munich, (TUM) Germany. Meanwhile he is

also working as a research associate of TUM CREATE,

Singapore. His research interests include the converters for

energy storage systems, high efficiency automotive power

electronic devices, implementation of artificial intelligence in

automotive engineering.

Olga Ilina received her M.S. and Ph.D.

degrees in power electronics from the

National Technical University “Kharkiv

Polytechnic Institute” (NTU KhPI) Kharkiv,

Ukraine, in 2005 and 2008, respectively.

From 2008 to 2013 she worked as a senior

lecturer in the NTU KhPI, also conducting

research in the field of active power filtering

and power conditioning in low-voltage distribution networks.

She is currently an application engineer for low frequency

electromagnetics at ANSYS, Inc. Her research interests include

modelling of power semiconductor devices and simulation of

power electronics and motor drive systems.

Markus Lienkamp, is conducting research

in the area of electro-mobility with the

objective of developing new vehicle

concepts. He is professor of the Institute of

Automotive Technology at Technical

University of Munich (TUM) and is

involved in the CREATE project in

Singapore. After studying mechanical

engineering at TU Darmstadt and Cornell

University, Prof. Lienkamp obtained his doctorate at TU

Darmstadt (1995). He worked at Volkswagen as part of an

international trainee program and took part in a joint venture

between Ford and Volkswagen in Portugal. Returning to

Germany, he led the brake testing department in the VW


commercial vehicle development section in Wolfsburg. He

later became head of the “Electronics and Vehicle” research

department in Volkswagen AG’s Group Research division. His

main priorities were advanced driver assistance systems and

vehicle concepts for electro-mobility. Prof. Lienkamp is

heading the Chair of Automotive Technology at TUM since

November 2009.

Leon Voss was born near Manchester, UK,

in 1970. He received the BA Sc. and MA Sc.

degrees in Electrical and Computer

Engineering from the University of

Waterloo, Canada in 1994 and 1996

respectively. He obtained the Dr.-Ing.

Degree from the University of Bochum,

Germany in 2002 for research in power

electronics for grid applications. From 2000

to 2007 he was R&D Engineer and Project Manager at Siemens

AG, Large Drives Business Unit, Nürnberg, Germany. In 2007

he joined ANSYS Inc. where he is currently Lead Technical

Support Engineer with focus on simulation methods for

electromagnetic components, power electronics and electric

drive systems.

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