Active Attenuation of Electromagnetic Noise in an Inverter Fed Automotive Sys

8/11/2019 Active Attenuation of Electromagnetic Noise in an Inverter Fed Automotive Sys

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IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 21, NO. 3, MAY 2006 693

Active Attenuation of Electromagnetic Noise in anInverter-Fed Automotive Electric Drive System

Andrzej M. Trzynadlowski, Fellow, IEEE

AbstractElectromagnetic noise, typical for systems withswitching power converters, is especially troublesome in automo-tive electric drive systems because of the multitude of sensitiveelectronic equipment onboard of modern cars. To satisfy therelevant engineering norms, passive radio-frequency (RF) filtersmust be installed in the power electronic part of a drive. The RFfilters add to the cost and size of the drive, which car designersstrive to minimize to increase the passenger space. In this paper,active attenuation of the electromagnetic noise by means of theso-called random-delay pulse width modulation is described inapplication to an inverter-fed automotive ac drive. Based oncomputer simulations and experimental investigation, this simpleand inexpensive method is shown to be highly effective.

Index TermsAutomotive drives, electromagnetic noise, filters,pulse width modulation (PWM).

I. INTRODUCTION

ELECTROMAGNETIC noise is generated in electric drive

systems as a result of switching operation of the power

electronic converter feeding the motor. Considering the level of

saturation of modern cars with various control and communi-

cation devices, the noise poses a serious threat to undisturbed

operation of the car. In an electric or hybrid automobile, the cur-

rent noise in cables connecting the battery and the converter isespecially troublesome, because the cables act as antennas and

radiate the resultant electromagnetic noise throughout the small

and enclosed space of the vehicle. Relevant engineering stan-

dards limit the allowable maximum levels of the conducted and

radiated noise within specified frequency ranges. A given stan-

dard also specifies the type of the noise considered, that is, de-

pending on the type of a detector employed, the average, peak,

or quasipeak values of the noise are subjected to the limitations.

Radio-frequency (RF) filters are most commonly used for re-

duction of the electromagnetic interference (EMI). The filters,

which are simple inductive-capacitive networks, constitute pas-

sive means of noise attenuation. In the context of continuous ef-forts to cut down the volume and cost of automotive drives, elim-

ination or size reduction of the filters is a worthy engineering

objective.

In this paper, an active approach to electromagnetic noise mit-

igation is described. It is based on the addition of a random

factor to the switching pattern of the power electronic converter.

In this way, most of the harmonic power in the frequency spectra

Manuscript received February 21, 2005; revised October 26, 2005. Recom-mended by Associate Editor J. Shen.

The author is with the Electrical Engineering Department, University ofNevada, Reno, NV 89557-0153 USA (e-mail: [email protected]).

Digital Object Identifier 10.1109/TPEL.2006.872368

of voltage and current is transferred to the continuous power

density. As a result, the spectra are flattened, significantly re-

ducing the required degree of attenuation of the noise by the RF

filters, which can thus be greatly reduced too. Computer simu-

lations and the results of an experimental investigation illustrate

advantages of the proposed method.

II. BACKGROUND

There exist many national and international engineering

standards on electromagnetic compatibility (EMC). The Inter-

national Electrotechnical Commission (IEC) standards, most ofwhich became European Norms (EN), are the most influential.

U.S. organizations involved in EMC product standards include

the Federal Communication Commission (FCC), The IEEE,

Inc., and the American National Standards Institute (ANSI)

[1]. EMC testing of novel electric and electronic products is

required in order to ensure the immunity of individual devices,

as well as the safety of other equipment within the reach of

electromagnetic effects of the tested product. Electromagnetic

disturbances causing the EMI can be classified as noise, im-

pulses, and transients. They travel mostly by conduction on

wiring and by radiation in space, and can get into closely spaced

circuits via inductive and capacitive coupling. In the frequency

range of 0.15 to 30 MHz it is the conducted EMI that is ofmain concern and, in that range, most EMC standards address

conducted disturbances only[2].

Noise components in the range of 0.15 to 30 MHz, and

eventually down to 10 kHz, are measured by EMI receivers.

The peak, average, effective (rms), or quasipeak measurements

of the electromagnetic noise are taken and compared with

relevant standards[3]. The quasipeak detection developed by

CISPR (IECs International Committee for Radio Interference)

is most common in practice, yielding the best correlation be-

tween the EMI receiver readings and the broadcast disturbances

heard by human ear[2]. Still, many engineering norms, among

them those of automobile manufacturers, define limits on themaximum peak and average values of the noise. For example,

in the GM Worldwide Engineering Standard GMW3097, the

limits for the radiated EMI for artificial networks (AN) within

the 0.531.71 MHz frequency range are 42 dB V, peak, for

nonspark noise sources (and 50 dB V, quasipeak, for spark

sources)[4].

In the same standard, the automobile equipment tested for

immunity to the radiated and conducted emissions is classified

into the following categories:

A components/modules containing active electronic

devices, such as op-amp circuits, switching power

supplies, microprocessors, and displays;

0885-8993/$20.00 2006 IEEE


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694 IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 21, NO. 3, MAY 2006

Fig. 1. EMIfilter for an automotive ac drive.

AS electronic components/modules operated from a

regulated power source in another module, typically

sensors;

AM electronic components/modules containing magnetically

sensitive elements;

AX electronic modules containing inductive devices, e.g.,

motors and solenoids;

BM brush-commutated electric motors;

EM electronically controlled or commutated electric motors.

Categories A, AS, and AM must meet the nonspark limits,

Categories AX and EM must meet both the nonspark and

spark limits, and Category BM must meet the sparklimits

[4].

So far, RFfilters are the only means employed for EMI miti-

gation in automobile electric drives. An examplefilter arrange-

ment, which screens the supply cables from noise to preventthem from radiating the EMI throughout the vehicle, is shown in

Fig. 1. The filter contributes to the cost and bulk of the drive. It is

worth mentioning that active EMIfilters for inverter-fed indus-

trial ac drives have recently gained attention of researchers [5].

Their application in automobile drives remains yet to be consid-

ered.

The magnitude of peaks in frequency spectra of the electro-

magnetic noise is the major factor affecting the size of RF filters.

As an example, consider a simple low-pass filter shown in

Fig. 2. In the attenuation frequency range (well above the reso-

nance frequency), its voltage attenuation, , is given, with

good approximation, by

(1)

where and denotefilters inductance and capacitance, re-

spectively, and is the frequency. Thus, the bigger the mag-

nitude of the spectral peaks, the larger inductor and capacitor

are required. Consequently, if the peaks were reduced, thefilter

components could be reduced too, both parametrically (lower

inductance and capacitance) and physically (lower volume and

weight).

The dependence of voltage attenuation on the square of fre-

quency implies that the high-frequency electromagnetic noise,resulting mostly from the high rates accompanying state

Fig. 2. Simple low-pass filter.

transitions of inverter switches, can be mitigated with relatively

low inductances and capacitances of the filters. However, the

current ripple associated with the low-frequency train of voltage

pulses of the inverter causes EMI that is more difficult tofight.

In the frequency spectrum, the current ripple appears in the form

of harmonic clusters centered about multiples of the switching

frequency.

Flattening a frequency spectrum, without reducing its total

power content, is tantamount to transferring the discrete har-

monic power (watts) to the continuous power spectral density(watts/hertz). This can be accomplished by random pulse width

modulation (RPWM) of gate pulses of the inverter switches [6].

Many RPWM methods have proposed in the literature, e.g.,

[7][10]. Those with a randomized switching frequency or,

more precisely, with a randomized length of switching periods,

turned out to be most effective[11].

Almost all the existing RPWM techniques with randomized

switching periods are characterized by a random sampling rate

of the digital modulator, because individual sampling periods

are synchronized with corresponding switching periods. This,

in most practical cases, is highly inconvenient. In a complex

digital system, the sampling frequency should be a constant,representing the best tradeoff between various bandwidth re-

quirements of multiple tasks of the system. The modulation is

only one of those tasks. The sampling and switching frequencies

can be made constant by employing a random sequence of in-

verter states[12].However, this approach detrimentally affects

the quality of both the switching patterns and frequency spectra

[13]. As a result, RPWM, despite its undeniable advantages, still

has not gained much popularity in practice. The novel random

modulation method described in the subsequent sections of this

paper combines the features of spectral continuity and of quality

of a space-vector PWM. In addition, the method, further called

a random-delay PWM (RDPWM) technique, is characterized

by exceptional algorithmic simplicity and minimum computa-tional overhead.

It is worth mentioning that a similar approach to EMI reduc-

tion has been proposed with respect to high-speed digital sys-

tems, such as computers. A randomly varied clock rate has been

shown to be an effective means of mitigation of EMI[14][16].

III. RANDOM-DELAYPWM TECHNIQUE

Although the classic space-vector PWM method is very well

known, its basics are invoked here because of certain twists in

realization of that method, described in this paper. The space-

vector technique with afixed switching frequency is illustrated

inFigs. 3and4. As shown inFig. 3,the reference space vector,, of output voltage of the inverter is synthesized


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TRZYNADLOWSKI: ACTIVE ATTENUATION OF ELECTROMAGNETIC NOISE 695

Fig. 3. Illustration of the space-vector PWM method.

Fig. 4. Single switching cycle in the space-vector PWM method.

TABLE IINVERTER STATES ANDTHEIRFRACTIONALTIMES

by time averaging of stationary space vectors , , and

of the inverter. Non-zero vectors and , framing the ref-

erence vector , are generated when the inverter is in State

and State , respectively. A state is defined here as , where

, , and are switching variables associated with phases A,

B, and C of the inverter. The active states and , resulting in

nonzero voltages of the inverter, are 1, 2, , 6. The zero vector,, can be produced by either State 0 or State 7.

Fig. 5. Sampling and switching cycles: (a) DPWM, (b) RPWM, and (c)

VDPWM.

Fig. 6. Frequency spectra of the input current noise at the low-speed, high-torque operating point and frequency range of 0.0130 MHz: (a) DPWM, (b)RPWM, and (c) RDPWM.

Fig. 4illustrates division of a switching cycle into five timeintervals, whose lengths are 2, 2, , 2, and 2.


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Fig. 7. Frequency spectra of the input current noise at the low-speed, high-

torque operating point and frequency range of 10150 kHz: (a) DPWM, (b)RPWM, and (c) RDPWM.

This is the so-called minimum-loss switching strategy, which

within switching cycles produce as few as 3 1 pulses

of each switching variable[17]. Times and are expressed

by simple formulas involving cosine functions of the angular

position, , of the reference vector with respect to vector

. Specifically

(2)

(3)

where denotes the modulation index, defined here as the ratio

of magnitude of the reference vector to the highest available

value of that magnitude. Time is given by

(4)

Thus, subdivision of a switching cycle involves the following

computations: (a) determination of the sextant of the vector

plane in which the reference voltage vector is located, (b)

calculation of angle based on the known components of

vector , and (c) calculation of times , , and using

trigonometric equations(2) and (3)and an arithmetic equation(4).

Fig. 8. Frequency spectra of the input current noise at the medium-speed,medium-torque operating point and frequency range of 0.0130 MHz: (a)DPWM, (b) RPWM, and (c) RDPWM.

A fullyarithmeticapproach to the space-vector PWM, em-

ployed in simulations and experiments described in this paper,

lowers the computational overhead. It is assumed that the refer-

ence voltage vector is expressed in the per-unit format using

the maximum available vector as the base. In thefirst step, three

auxiliary variables, , , and , are calculated as

(5)

(6)

(7)

Next, based on the signs of , , and ,Table Iis used for de-

termination of times , , and .

It can be seen that simple arithmetic formulas are employed

only. The table-driven algorithm lends itself to simple imple-

mentation in a digital modulator. For minimization of switching

activity, only State 7 is used as the zero state.

As already mentioned, for active attenuation of the electro-

magnetic noise, the switching period, , must be randomly

varied from one switching cycle to another. That can be accom-

plished, while maintaining a constant sampling period, ,

by random variation of the delay, , between the beginning ofa sampling cycle and that of the corresponding switching cycle.


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Fig. 9. Frequency spectra of the input current noise at the medium-speed,medium-torque operating point and frequency range of 10150 kHz: (a)

DPWM, (b) RPWM, and (c) RDPWM.

This is illustrated inFig. 5,which, for comparison, also shows

the relation between sampling and switching cycles for the de-

terministic PWM (DPWM) and the classic RPWM with simul-

taneous variations of the sampling and switching periods.

In the classic RPWM method, consecutive switching (and

sampling) periods are randomly drawn from a uniform-proba-

bility pool of values ranging from to , where

denotes the desired average switching period and the co-

efficient determines the shortest period as a fraction of the

average period. In the novel RD-PWM technique, the randomdelay is calculated as , where is a random number

from the 0 to 1 range. When in two consecutive switching cy-

cles, the and , is close to 1 and is close

to 0, the second, , switching cycle may be too short,

that is, its length, , may be lower than the minimum al-

lowable length, . Therefore, in case of such occurrence,

, is set to or another value of is drawn. As a

result, lengths of switching cycles vary from to .

Comparing RPWM with RD-PWM by assuming ,

and it can be seen that the difference be-

tween the longest switching period and the shortest one equals

for the RPWM method and for the

RD-PWM technique. Thus, RD-PWM offers a larger variety ofswitching periods than does RPWM.

Fig. 10. Frequency spectra of the input current noise at the maximum-speed,maximum-power operating point and frequency range of 0.0130 MHz: (a)DPWM, (b) RPWM, and (c) RD-PWM.

IV. COMPUTERSIMULATIONS

Computer simulations of an electric ac drive for an electric

car developed by a major automobile manufacturer were per-

formed using the SABER software package. Comparative eval-

uation of the impact of PWM technique employed in control of

the drives inverter on various characteristics of the drive was the

object of the simulations. The characteristics in question were:

a) frequency spectra of the current noise in supply cables, b) ef-

ficiency of the drive, c) torque ripple, and d) controllability of

the drive, in particular, response to torque andflux commands.Example frequency spectra of the input current noise in the

ranges of 10 kHz to 30 MHz and 10 kHz to 150 kHz are shown

in Figs. 611, each figure showing the spectra when the DPWM,

RPWM, and RD-PWM are used. The 10150 kHz spectra were

computed with the same number of samples as the 10 kHz to

30 MHz spectra, thus the former spectra can be considered more

accurate. Three operating points of the drive are represented: (a)

low speed and high torque (Figs. 6and 7), (b) medium speed

and medium torque (Figs. 8 and 9), and (c) maximum speed

and maximum power (Figs. 10and11). The average switching

period, , equal to the sampling period, , was 83.3 s,

which represents the sampling frequency of 12 kHz. The min-

imum switching period, was set to 40 s (a reciprocalof 25 kHz), so that the switching periods varied from 40 s to


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Fig. 11. Frequency spectra of the input current noise at the maximum-speed,maximum-power operating point and frequency range of 10150 kHz: (a)DPWM, (b) RPWM, and (c) RDPWM.

166.6 s, that is, with an approximately one to four shortest-to-

longest ratio.

A significant difference of 1020 dB V between the spectra

with deterministic and random PWM techniques can be ob-

served for all spectra. As seen in Figs. 6,8, and10, the choice

of modulation strategy ceases to affect the frequency spectra

above some 3 MHz. However, as indicated by (1), it is the

low-frequency region in which the current harmonics are mostdifficult to attenuate. Also, in the 0.531.71-MHz frequency

range specified in the GMW3097 standard (seeSection II), the

random modulation yields distinctly flatter spectra than does

the DPWM.

Additional simulations, although of limited scope due to ex-

cessive computation times, have been performed using a high-

frequency model of the motor described in[18]. The model in-

troduces distributed stray capacitances. Apart from minor am-

plitude differences in the high frequency range, the obtained fre-

quency spectra were very similar to those for the low-frequency

model of the motor.

Efficiency of the drive is unaffected by the type of modula-

tion, while the torque ripple increases by an order of 30% whenDPWM is replaced with RPWM or RD-PWM. However, the

Fig. 12. Rapid changes of the reference torque-producing current: DPWM.

fundamental frequency of the ripple, which well exceeds the av-erage switching frequency, is so high that its effects on speed of

the car would be imperceptible.

When the average orfixed sampling frequency is sufficiently

high to provide the required control bandwidth, there is no

significant impact of the modulation strategy on the quality of

torque andflux control. This is illustrated inFigs. 1214,which

compare the reference and actual waveforms of the torque-pro-

ducing current, and , and those of theflux-producing

current, and , following an up-and-down step com-

mand signal, , while remains unchanged. Although

the waveforms of and with RPWM (see Fig. 13) and

RD-PWM (seeFig. 14) are less regular than those with DPWM(see Fig. 12), both the overshoot and settling time are similar for

all the three modulation methods. However, it must be pointed

out that when the average switching frequency decreases, the

quality of current control deteriorates faster when random

modulation, instead of DPWM, is employed. That is mostly the

result of nonuniform current sampling, as opposed to the at

peak or at valley patterns typical for DPWM. In effect, the

measurement errors of the locally-averaged current are more

pronounced.

V. EXPERIMENTAL INVESTIGATION

For confirmation of theoretical expectations and simulationresults, a 40-hp laboratory drive system with an induction


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Fig. 13. Rapid changes of the reference torque-producing current: RPWM.

motor driving a loaded dc generator was set up and investi-

gated. The motor was fed from a commercial inverter from

Danfoss, with the original control system replaced with a

digital modulator based on the TMS320F243 DSP controller

from Texas Instruments. The modulator generated switching

signals in accordance with the DPWM, RPWM, and RDPWM

algorithms. The drive was operated in the constant volts/hertz

mode, with the average (for RPWM and RD-PWM) or fixed (for

DPWM) switching period of 0.5 ms, representing a switching

frequency of 2 kHz. In the steady state, the drive run with

the fundamental frequency of 9 Hz (the value of fundamentalfrequency does not affect the electromagnetic noise). The goal

of the investigation was to assess qualitative features of the

PWM techniques compared, rather than to perform precise

measurements of the noise. Therefore, the noise was sensed

directly in the wires connecting the inverter to the power line,

without a line impedance stabilization network (LISN).

Frequency spectra of the input current noise with the drive op-

erating on full load are shown inFigs. 1517. Due to equipment

limitations on the number of collected samples, the frequency

range is narrower than that in computer simulations, specifi-

cally, 0 to 20 kHz. Also, in contrast to the simulated system,

the dc supply voltage in the experimental setup was obtained

not from a battery but from a diode rectifier, which contributedcurrent harmonics at the lower end of frequency range. Still,

Fig. 14. Rapid changes of the reference torque-producing current: RDPWM.

Fig. 15. Experimental frequency spectrum of the input current noise: DPWM.

the mitigating effect of random PWM techniques on the elec-

tromagnetic noise in the low end of the spectrum, which is most

difficult forfiltration, is clearly observable.

VI. CONCLUSION

Electromagnetic noise, a highly undesirable side effect ofswitching operation of power electronic converters in adjustable


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Fig. 16. Experimental frequency spectrum of the input current noise: RPWM.

Fig. 17. Experimental frequency spectrum of the input current noise:RDPWM.

speed ac drives, especially those used in automobiles, can be at-

tenuated by random PWM employed in the power inverter. Flat-

tering the frequency spectrum of noise allows for size reduction

of EMI filters, contributing to compactness and cost reduction of

the drive. Conveniently, the novel random-delay PWM methodis characterized by a constant sampling frequency of the dig-

ital modulator. Implementation of the RDPWM technique is

a simplesoftwarefix,requiring no modifications of the drive

system.

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[4] GM Worldwide Engineering, Std. GMW3097, Feb. 2004.

[5] Y.-C. Son and S.-K. Sul, A new active common-mode EMI filterfor PWM inverter, IEEE Trans. Power Electron., vol. 18, no. 6, pp.13091314, Nov. 2003.

[6] A. M. Stankovic and H. Lev-Ari,Randomized modulation in powerelectronic converters, Proc. IEEE, vol. 90, no. 5, pp. 782799, May2002.

[7] A. M. Trzynadlowski, F. Blaabjerg, J. K. Pedersen, R. L. Kirlin, andS. Legowski, Random pulse width modulation techniques for con-

verter-fed drive systemsa review, IEEE Trans. Ind. Appl., vol. 30,no. 5, pp. 11661175, Sep./Oct. 1994.[8] A. M. Stankovic, G. C. Verghese, and D. J. Perrault, Randomized

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Andrzej M. Trzynadlowski (M83SM86F99)received the M.S. degree in electrical engineering,the M.S. degree in electronics, and the Ph.D. degreein electrical engineering from the Technical Univer-sity of Wroclaw (TUW), Wroclaw, Poland, in 1964,1969, and 1974, respectively.

From 1966 to 1979, he was a faculty member

with TUW. Later, he worked at the University ofSalahuddin, Iraq, the University of Texas, Arlington,and the University of Wyoming, Laramie. Since

1987, he has been with the University of Nevada,Reno, where he is a Professor of electrical engineering. In 1997, he spent sevenmonths at Aalborg University, Aalborg, Denmark, as the Danfoss VisitingProfessor. In 1998, he was a Summer Faculty Research Fellow at the NavalSurface Warfare Center, Annapolis, MD. He has authored or co-authored over150 publications on power electronics and electric drive systems and holds12 patents. He is the author of The Field Orientation Principle in Controlof Induction Motors (Norwell, MA: Kluwer, 1994), Introduction to ModernPower Electronics (New York: Wiley, 1998), andControl of Induction Motors

(New York: Academic, 2001). He wrote chapters for Modern Electrical Drives(Norwell, MA: Kluwer, 2000) and Control in Power Electronics (New York:

Academic, 2002).Dr. Trzynadlowski received the 1992 IAS Myron Zucker Grant and has

been listed in Whos Who in the World, Whos Who in America, and WhosWho in Science and Engineering. He is an Associate Editor of the IEEETRANSACTIONS ON POWER ELECTRONICS and the IEEE TRANSACTIONS ON

INDUSTRIAL ELECTRONICS, and a member of the Industrial Drivesand IndustrialPower Converters Committees, IEEE Industry Applications Society (IAS).

Active Attenuation of Electromagnetic Noise in an Inverter Fed Automotive Sys

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