Active Damping Wheel-Torque Control System to Reduce ...hying/images/getPDF.pdf · Active Damping...

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 58, NO. 9, NOVEMBER 2009 4769

Active Damping Wheel-Torque Control System toReduce Driveline Oscillations in a Power-Split

Hybrid Electric VehicleFazal U. Syed, Ming L. Kuang, and Hao Ying, Senior Member, IEEE

AbstractPower-split hybrid electric vehicles (HEVs) providea great opportunity to improve fuel economy and emissions. Thispower-split hybrid system has inherent low damping in drivelinesince it uses planetary gear sets to directly connect the engine,the generator, and the motor to the driveline for improved vehicleefficiency, thus lacking a clutch or a torque converter that providesthe conventional vehicles with driveline damping. When they aresubjected to acceleration or disturbances, the low damping in thedriveline may cause torsional vibrations. Since the power-splitcontrol system is closed loop in nature, these torsional vibrationscan result in sustained driveline oscillations. These oscillations canbe very objectionable to the driver as they affect the vehiclesdrivability. In this paper, we present the design of an activedamping wheel-torque control system to suppress such oscilla-tions to improve the drivability of a power-split HEV. To thebest of our knowledge, this is the first reported use of an activedamping wheel-torque control system to suppress the drivelineoscillations in a power-split HEV. Simulations in a power-splitHEV environment and experimental tests in the field using aFord Escape Hybrid demonstrate the effectiveness of the proposedsystem in suppressing the oscillations. The driveline disturbancesare suppressed to below the perceptible level of wheel torque(< 100 N m). Additional simulations are performed to validatethe system to other key factors that can affect its performance.Even with increased motor/generator disturbances by a factorof 2 and change in driveline stiffness of 50%, the proposedcontrol system can still effectively suppress driveline oscillationsand thereby improve drivability.

Index TermsActive damping, driveline oscillations, hybridelectric vehicle (HEV), power split, wheel-torque control.

I. INTRODUCTION

IN recent years, concerns regarding environment pollutionhave shifted the focus of research and development to-ward developing hybrid electric vehicles (HEVs) to achieveautomotive technology improvements without compromisingour lifestyle or the environment [1], [2]. HEVs are mainlycategorized into three types: 1) the series hybrid system [3],

Manuscript received December 15, 2007; revised June 9, 2008, January 26,2009, and April 19, 2009. First published June 23, 2009; current versionpublished November 11, 2009. The review of this paper was coordinatedby Prof. A. Khaligh.

F. U. Syed and M. L. Kuang are with the Hybrid Electric Vehicle Program,Sustainable Mobility Technologies Laboratory II, Ford Motor Company,Dearborn, MI 48120 USA (e-mail: [email protected]; [email protected]).

H. Ying is with the Department of Electrical and Computer Engineer-ing, Wayne State University, Detroit, MI 48202 USA (e-mail: [email protected]).

Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TVT.2009.2025953

[4]; 2) the parallel hybrid system [3], [4]; and 3) a more recenttype called the complex HEV [1]. Complex HEVs, such aspower-split hybrid powertrain systems [1], [5][7], combine thebenefits of both parallel and series types of hybrid systems. Atypical power-split HEV powertrain is shown in Fig. 1, whichconsists of two power sources: 1) a combination of engine,generator, and planetary gear set and 2) a combination of motorand high-voltage (HV) battery [5][7]. The planetary gear setprovides interconnection between engine, generator, and motor,where the carrier gear is connected to the engine, the sun gearis connected to the generator, and the ring gear is connected tothe motor. The motor is also connected to the wheel throughgear reductions. The HV battery acts as an energy storagedevice [27]. The power-split powertrain configuration providesthe ability to have electric-only or hybrid drive modes [1][6],[10][12], [16], [27]. This powertrain system also has an elec-trohydraulic braking system, which provides seamless integra-tion of the friction and regenerative braking functionality. Themain advantage of the power-split powertrain system is that itfunctions like an electronic continuous variable transmission(CVT) [11], [16], which provides a great potential to achievebetter engine efficiency and lower emissions by controlling theengine speed, independent of the vehicle speed. In addition,a highly coordinated vehicle system controller (VSC) is usedfor controlling torque, speed, and power among these multiplesubsystems to meet the vehicle attributes [5][15].

The driveline system in a conventional (nonhybrid) vehiclemainly consists of engine, torque converter or clutch, transmis-sion system, driveshaft, differential, half-shafts, and wheels.Since these components in a conventional vehicle are elasticin nature, mechanical resonance may occur [22]. When sucha vehicle is subjected to disturbances, the elasticity of thesecomponents can result in driveline vibrations or disturbances,which can also result in driveline or vehicle speed oscillations.These driveline oscillations, which are also known as shufflemode, are low-frequency oscillations corresponding to the firstresonance frequency of the driveline [22], [23]. Generally,the presence of the torque converter or clutch together withthe driveline systems elastic nature in a conventional vehicleprovides a passive way of damping the vibrations and oscil-lations. In a power-split HEV, there are no clutches or torqueconverter. In addition, the driveline system in a power-splitconfiguration is more rigid (i.e., less elastic) in nature due tothe direct mechanical coupling between the engine, generator,and motor to the driveline through a set of planetary gears.

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4770 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 58, NO. 9, NOVEMBER 2009

Fig. 1. Power-split-type HEV configuration.

Therefore, this powertrain has no passive damping mechanismthat can dampen disturbances [31], [33], [34]. Therefore, owingto the low damping in a power-split HEV and the absence ofpassive damping mechanisms (hardware) as compared witha conventional vehicle, an active damping control systemis desirable to reduce the driveline oscillations in a power-split HEV.

Various researches have been done on understanding anddamping the driveline oscillations or the shuffle mode of aconventional vehicle [28], [29]. There exist literatures on theuse of a control system to actively damping the drivelineoscillations in nonhybrid vehicles [23][26]. Other literatureabout damping driveline oscillations in parallel HEVs alsoexists [31], [33]. In all of this literature, the driveline oscil-lations mostly occur during transmission shift events or dur-ing engine start or stop, whereas in complex hybrid vehicles,such as power-split HEV, the driveline oscillations can occuranytime under any conditions due to its low damping in thedriveline.

Passive damping approaches can be used, but such ap-proaches require additional hardware, such as clutches or damp-eners, to dampen the driveline disturbances and oscillations,leading to increased system cost. Therefore, an active dampingapproach utilizing a control system that can be implementedas software is more desirable. The objective of this paperis to develop an active-damping-capable wheel-torque controlsystem to suppress the driveline oscillations in a power-splitHEV. To the best of our knowledge, this is the first reporteduse of the proposed active damping control system to suppressthe driveline oscillations for a power-split HEV in the appliedautomotive field. In this paper, we compare this proposedactive damping wheel-torque control system with a base wheeltorque control system without active damping to demonstratethe effectiveness of our proposed approach. In addition, customtests are devised for the evaluation of the effectiveness and

validation of this proposed control system under various con-ditions. First, the simulation environment is used to verify theeffectiveness of this approach. Next, the controller is validatedthrough experimental tests by implementing it in a Ford EscapeHybrid vehicle. Finally, the proposed approachs performanceis validated through simulations by varying key parameters inthe vehicle plant model describing the worst-case conditions.The results clearly demonstrate that the developed approachis capable of suppressing the driveline oscillations in a power-split HEV.

II. VEHICLE SYSTEM WHEEL-TORQUE CONTROL SYSTEMFOR REDUCING OSCILLATIONS IN A POWER-SPLIT HEV

As mentioned in Section I, the VSC is responsible fordetermining and managing torque, speed, and power amongvarious subsystems. As such, the VSC uses the vehicle wheeltorque control system for delivering driver demand torque atthe wheels. It also uses the fuzzy engine power control systemto determine the desired engine speed and the desired enginetorque to provide driver demand power and HV battery stateof charge maintenance power [30]. Fig. 2 shows this vehiclecontrol system architecture. Fig. 2 also shows the proposedactive-damping-capable vehicle wheel-torque control systemarchitecture responsible for delivering the desired wheel torquein a power-split HEV. To deliver the desired wheel torque, theVSC requests a desired engine speed and wheel torque to thetransaxle control module (TCM). The TCM uses the desiredengine speed from the engine power control block to determinethe generator torque and the desired wheel torque from thedesired drivetrain wheel-torque determination control block todetermine the motor torque. The generator and the motor torquetogether are primarily responsible for delivering the driverdemand or the desired wheel torque. The active-damping-capable vehicle wheel-torque control system, as shown in


SYED et al.: WHEEL-TORQUE CONTROL SYSTEM TO REDUCE DRIVELINE OSCILLATION IN A POWER-SPLIT HEV 4771

Fig. 2. Vehicle control system architecture.

Fig. 2, consists of the following: 1) the active-damping-capable transaxle control system and 2) the active-damping-capable desired drivetrain wheel-torque determination controlsystem.

A. Active Damping Capable Transaxle Control System in aPower-Split HEV

The two major objectives of this active-damping-capabletransaxle control system are primarily to control the enginespeed to a desired engine speed command and to deliver therequested or desired wheel torque while providing active damp-ing of the driveline disturbances. The desired wheel torque andengine speed are the primary inputs to the TCM. Based onthese inputs, the TCM determines the motor torque commandto achieve or delivers the desired wheel and generator torquesto control the engine to the desired engine speed.

The generator control portion in the transaxle controller usesthe desired engine speed (eng_des) input from the enginepower control block, which is shown in Fig. 2, to calculatethe desired generator speed (gen_des) based on the gear ratiobetween engine and generator (ke2g), the motor speed (mot),and the gear ratio between motor and generator (kg2m). Thefollowing equation describes the computation of the desiredgenerator speed:

gen_des = (eng_deske2g + mot/kg2m) (1)

where ke2g = (/1 + ), wherein is the planetary gear ratio,which is the ratio between sun and ring gears represented by = Ns/Nr (Ns is the sun gear, and Nr is the ring gear);and kg2m = (1 + /R1R2), wherein R1 is the gear ratio fromcounter shaft to ring gear shaft, which is the ratio between gears2 and 3 represented by R1 = N2/N3, and R2 is the gear ratiofrom motor shaft to counter shaft, which is the ratio betweengears 1 and 2 represented by R2 = N1/N2.

Once the desired generator speed (gen_des) is determined, aproportionalintegral (PI) controller is used, which comparesthe actual generator speed with the desired generator speedto compute the generator torque command. Equations (2)(4),shown at the bottom of the page, describe the PI controller forcontrolling the generator speed to a desired generator speed,where (4) represents the PI controller for controlling the de-sired engine speed. It calculates the generator torque commandTgen_des, which is equal to the sum of the generator torqueproportional term (Tg_pterm) and the generator torque integralterm (Tg_iterm). Kp and Ki are proportional and integral gainsof the PI controller, respectively. Note that the generator torqueintegral term (Tg_iterm) is determined in a manner to ensurethat the sum of the generator torque integral term and theproportional term is between the minimum generator torque(Tgen_min) and the maximum generator torque (Tgen_max). Inaddition, note that Tgen_min 0 and that Tgen_max 0.

Next, an unconstrained desired motor torque command(Tmotdes_unlm) is determined in the motor control portion of

Tg_pterm = (gen_des gen)Kp (2)

Tg_iterm =

Tgen_max, if (Tg_iterm + Tg_pterm) > Tgen_max(gen_des gen)Kidt, if Tgen_min (Tg_iterm + Tg_pterm) Tgen_max

Tgen_min, if (Tg_iterm + Tg_pterm) < Tgen_min(3)

Tgen_des = Tg_pterm + Tg_iterm (4)



Fig. 3. Active-damping-capable transaxle controller with feedforward active compensator.

the transaxle controller using the planetary gear set fundamentalequations [27] through the desired wheel torque and the gearratio between motor and wheel as follows:

Tmotdes_unlm =Twh_deskm2w

(

Tgen_desJg dgendt

)kg2m (5)

where Jg is the effective generator moment of inertia, andTwh_des is the desired wheel torque from the desired drivetrainwheel-torque determination controller shown in Fig. 2.

Observer-based acceleration compensation is an effectivemethod of reducing the drive sensitivity to mechanical reso-nance [32]. Therefore, a feedforward active compensator usingan active compensator in the feedforward path is used. Thecompensator uses the motors moment of inertia (Jm) and thederivative of the motor speed (dm/dt) with specific active mo-tor damping logical multiplier (Lamd) and the maximum andminimum damping torque limits (Tmdamp_max, Tmdamp_min)to compute the feedforward inertial torque that is compen-sated/subtracted from the unlimited desired motor torque todetermine the desired motor torque, as in (6)(8), shown at thebottom of the page.

Notice that, to calculate the desired motor torque com-mand (Tmot_des), first, an unlimited motor torque command(Tmotdes_unlm) is determined. Next, the motor damping torque(Tmot_damp) is determined, which is used under specific con-dition through the use of an active motor damping logicalmultiplier (Lamd). Lamd is determined through the logicalfunction of the actual pedal position (App) versus a pedalposition threshold (App_th), motor speed (mot) versus motorspeed threshold (mot_th), and desired wheel torque (Twh_des)versus desired wheel-torque threshold (Twh_des_th). The sumof Tmotdes_unlm and LamdTmot_damp is finally bounded be-tween the motor minimum torque (Tmot_min) and the motormaximum torque (Tmot_max). Note that Tmot_min 0 andthat Tmot_max 0.

This proposed active-damping-capable transaxle controlleris shown in Fig. 3, and the feedforward active compensatoris shown by active motor damping and logic for activatingactive motor damping blocks in Fig. 3. The transaxle controllerwith feedforward active compensator, in contrast with the com-pensator control systems in the literature [33], should be morerobust since no estimation is used in the system. Unlike someactive damping controllers in the literature that use wheel speedinput to perform the active damping functionality [31] that can

Tmot_damp =

Tmdamp_max, if Jmdmot

dt > Tmdamp_maxJm

dmotdt , if Tmdamp_min Jm dmotdt Tmdamp_max

Tmdamp_min, if Jmdmot

dt < Tmdamp_min

(6)

Tmot_des =

Tmot_max, if (Tmot_des_unlim LamdTmot_damp) > Tmot_maxTmot_des_unlim LamdTmot_damp, if Tmot_min (Tmot_des_unlim LamdTmot_damp) Tmot_maxTmot_min, if (Tmot_des_unlim LamdTmot_damp) < Tmot_min

(7)

Lamd ={

1, if ((App > App_th) (mot < mot_th) (Twh_des > Twh_des_th))0, Otherwise

(8)



Fig. 4. Comparison of base transaxle controller versus proposed transaxle controller with feedforward active compensator. Plot [A] shows the wheel-torqueresponse using a base transaxle controller. Plot [B] shows the wheel-torque response using feedforward active compensator-based transaxle controller.

result in incorrect damping under wheel slip events, our con-troller uses motor speed that is not affected by such events. Inaddition, our proposed transaxle control system requires no ad-ditional sensor since the motor speed sensor is already requiredby the motor control and can be used to calculate the derivativeof the motor speed. Clearly, if the motors moment of inertia,the minimum/maximum damping torque limits, and the activemotor damping logical gain of this compensator are properlydesigned, then a desired frequency response on the driveshaftcan be achieved, and an attenuation to the disturbance at theresonant frequency can be attained. Therefore, the driveline os-cillations will be minimized. The control system design utilizedby our proposed active damping capable transaxle controllerfor power-split HEV is different from a typical existing activedamping control system design [33] for nonhybrid vehiclesor parallel HEVs. In the currently existing active dampingcontrol designs, the controlled output of the system is usedas a feedback signal to complete a closed-loop control [33];therefore, the open-loop frequency response of a system is usedin its compensator design process. However, in our proposedactive-damping-capable control system design, the frequencyresponse has to actively be used through the motor speed ratherthan the controlled output motor shaft torque [33] that is usedas feedback in the existing active damping control methods.

At this point, it is important to emphasize that, if only abase transaxle controller without active damping for power-splitHEV was used, then the feedforward active compensator blocksof the proposed transaxle controller in Fig. 3 will be deleted,and the equations governing the determination of desired motortorque will be written as follows:

Tmot_des =

Tmot_max, if Tmotdes_unlm > Tmot_maxTmotdes_unlm, if Tmot_min Tmotdes_unlm

Tmot_maxTmot_min, if Tmotdes_unlm < Tmot_min.

(9)

Fig. 4 illustrates the frequency responses on the wheel torqueat the motor shaft to a step change in desired wheel torquewith the base transaxle controller and the proposed active-damping-capable transaxle controller with a feedforward activecompensator. These results are obtained under the simulation

environment for the Ford Escape Hybrid. The vehicle charac-teristics and the simulation environment are described later inSections III-A and B, respectively. These frequency responsesare based on Lamd = 1 and damping torque limits of 200 and200 N m. It is clear from Fig. 4 that the feedforward activelycompensated driveline system can reject driveline disturbances,particularly at the natural frequency of the driveline system,and therefore has a much higher damping as compared with theuncompensated driveline system. In other words, a disturbancesuch as torque ripple and backlash will result in minimalexcitation of the compensated driveline system (wheel torque)through the motor shaft. In this proposed feedforward activecompensator transaxle control system, the use of logical gain toactivate this compensator gives the flexibility to minimize theeffect on the drive shaft from this compensator controller underconditions where the desired wheel torque (or the effectivedrive shaft torque) is low or the motor speed is low. Undersuch conditions, noise on motor speed or torque may result inunwanted damping; therefore, such a logical gain to minimizethe effect from this controller can avoid unnecessary dampingor wheel-torque ripples. Hence, this feedforward active com-pensation is only used under desired conditions where drivelineresonance may occur. These conditions include high driverdemand cases, such as full pedal acceleration conditions, higherengine power demand, and/or higher HV battery power demandconditions.

B. Active Damping Capable Desired Drivetrain Wheel-TorqueDetermination Control System in a Power-Split HEV

As described in Fig. 2, the VSC determines a desired enginespeed and a desired engine torque. It also determines a desiredwheel torque that is used by the TCM. The desired enginespeed is calculated through the engine power control block,and the desired wheel torque is calculated through the desireddrivetrain wheel torque control block. In addition, the enginepower control block determines the desired engine torque. Theengine power control block is responsible for determining theengine operating point based on the overall system efficiency[8], [9], [30]. The actual engine power available to the wheelsneeds to be estimated to afford the driver the maximum power



Fig. 5. Desired drivetrain wheel-torque determination control.

train system capability under any engine and HV battery con-ditions without violating battery power or system limits. Thisengine power estimation is used to determine an affordablemaximum wheel power command and is then used to determinean affordable maximum wheel-torque command for the givenconditions. Fig. 5 shows the details of the desired drivetrainwheel-torque determination control block. It can be seen fromFig. 5 that the driver power request (Pdrv) is calculated basedon accelerator pedal, vehicle speed, etc. This driver powerrequest is then clipped or constrained between the minimumsystem power capability Psys_min and the maximum systempower capability Psys_max in the limit driver demand block,resulting in the system limited driver power request (Pmod).The determine actual engine power block is responsible forestimating the actual engine power (Peng_act). The desiredelectrical power (Pelec_des) can be calculated from the ac-tual engine power and the system limited driver power. Thedetermine wheel-torque block uses the actual engine powerand the system limited driver power to calculate the finalwheel power request such that the electrical system limitsare not violated. In addition, to ensure that electrical limitsare not violated, it uses the desired electrical power togetherwith the actual HV battery power in a feedback manner. It isthe responsibility of this block to calculate the desired wheel

torque in a manner such that the resultant wheel power willnot exceed the sum of the actual engine power and the HVbattery discharge and charge limits. For example, when theHV battery discharge and charge limits are zero, the desiredwheel torque or corresponding desired wheel power should beequal to the estimated (actual) engine power to ensure no HVbattery power usage. In addition, due to the nature of the power-split HEV powertrain configuration, the motor torque must becoordinated (i.e., closed-loop control) with the generator torqueand compensate the inertial effects of the generator/sun gearassembly in the transaxle controller to ensure that the drivetrainwheel-torque control blocks desired wheel-torque request isfulfilled. The desired wheel torque Twh_des from the desireddrivetrain wheel-torque determination controller, as describedin Fig. 5, can be represented by the simplified equations in(10)(14), shown at the bottom of the page, where wheel is thewheel speed, Ploss is the system power losses, Pelec_chg_lim isthe electrical charge power limit, Pelec_dch_lim is the electricaldischarge power limit, Peng_min is the minimum engine power,Peng_max is the maximum engine power, and Pelec_des is thedesired electrical power bounded between the electrical chargepower limit (Pelec_chg_lim) and the electrical discharge powerlimit (Pelec_dch_lim). Note that Pelec_chg_lim 0, Peng_min 0, Pelec_dch_lim 0, and Peng_max 0.

Psys_min = Pelec_chg_lim + Peng_min (10)

Psys_max = Pelec_dch_lim + Peng_max (11)

Pmod =

Psys_max, if Pdrv > Psys_maxPdrv, if Psys_min Pdrv Psys_maxPsys_min, if Pdrv < Psys_min

(12)

Pelec_des =

Pelec_dch_lim, if f(Pmod, Peng_act) > Pelec_dch_limf(Pmod, Peng_act), if Pelec_chg_lim f(Pmod, Peng_act) Pelec_dch_limPelec_chg_lim, if f(Pmod, Peng_act) < Pelec_chg_lim

(13)

Twh_des =Pelec_des Ploss + Peng_act

wheel(14)



Fig. 6. Feedback weighted narrow-band notch filter approach for engine power estimation.

As described in Section I, in a power-split HEV configura-tion, the driveline can also get excited through the generatorpath because the generator and motor together are responsiblefor delivering a desired wheel torque. Since the engine powerestimate is used for the determination of the desired wheeltorque, which uses both the generator and the motor feedbackto compute the desired wheel torque, the lack of couplingof the engine power estimate between VSC and TCM canamplify the driveline resonance and result in sustained drivelineoscillations. One of the well-established techniques to attenuatethe effect of the resonant poles is to introduce a notch filter witha transfer function consisting of a set of complex zeros that, atleast in theory, cancel the resonant poles of the plant to producea set of well-damped poles that are located in a more stable(well-damped) position in the left half s-plane [32]. Hence,our approach uses a feedback-based weighted narrow-bandnotch filter in the desired drivetrain wheel-torque controller inaddition to the active-damping-capable transaxle controller.

The weighted narrow-band notch (bandstop) filter in thefeedback path filters the unwanted frequency components ofthe engine power estimate. A weight mechanism is used todetermine the final weighted engine power estimate by takingthe weighed contribution from the actual engine power estimateand the filtered engine power estimate. This engine powerestimate (Peng_act) is then used to determine the desired wheeltorque that is sent to the TCM. The fundamental equations ofthis controller are (15) and (16), shown at the bottom of thepage, where wheel is the wheel speed, Twh_des is the desiredwheel torque, Ploss is the system power loss, Pelec_des is thedesired electrical power, Tmot is the motor torque, Tgen is thegenerator torque, mot is the actual motor speed, gen is the ac-

tual generator speed, km2w is the gear ratio between the motorand the wheel (driveshaft) defined as km2w = (Rg/R2), R2 isthe gear ratio from motor shaft to counter shaft, which is theratio between gears 1 and 2 represented by R2 = N1/N2, Rg isthe gear ratio from drive shaft to counter shaft, which is the ratiobetween gears 5 and 4 represented by Rg = N5/N4, and W isthe notch filtering weight for deciding the contribution of notch(bandstop) filtering, with b1, . . . , b6 and a1, . . . , a6 representingthe coefficients for poles and zeros of the sixth-order narrow-band notch filter, respectively. The actual delivered wheeltorque estimate T wh_des is the result of the desired wheel torque(Twh_des) command from VSC to TCM. The actual deliveredwheel-torque estimate is described as T wh_des = z

kTwh_des,with k representing the time step delay, which is the timethat TCM takes to deliver the requested desired wheel-torquecommand from the VSC.

Fig. 6 shows the weighted narrow-band notch-filter-basedengine power estimation controller for determining the enginepower estimate. As mentioned, the implementation to achievedecoupling between VSC and TCM is achieved by using thenarrow-band notch filter together with a weight determinationprocess. For the Ford Escape Hybrid vehicle, these coefficientsare determined such that the narrow reject band is between2.5 and 8 Hz as the driveline resonance for this vehicle is around6 Hz. The weight determination process determines the value ofthe weight W (between 0 and 1) and is calibrated or tuned as afunction of vehicle speed (motor speed) to minimize the phasedelays or essentially the effect on HV battery power control.Since we know that the driveline is less prone to oscillationsat a higher speed, a smaller weight can be used at higherspeeds.

Peng_act =(

T wh_deskm2w

mot + Tmotmot + Tgengen

)((1 W ) + W b1 + b2z

1 + b3z2 + b4z3 + b5z4 + b6z5

a1 + a2z1 + a3z2 + a4z3 + a5z4 + a6z5

)(15)

W =

1, if f(mot) > 1f(mot), if 0 f(mot) 10, if f(mot) < 0

(16)



TABLE ISPECIFICATIONS OF THE FORD ESCAPE HYBRID

VEHICLE AND ITS SUBSYSTEMS

At this point, it is important to emphasize that, if a basedesired driveline wheel-torque determination controller forpower-split HEV without active damping was used, then theweighted narrow-band notch-filter-based engine power estima-tion controller in Fig. 6 will be replaced with a simple enginepower estimation controller, and the equation governing thedetermination of the engine power estimate using a simpleengine power estimation controller is as follows:

Peng_act =T wh_deskm2w

mot Tmotmot Tgengen. (17)

We point out that most of the existing approaches for damp-ing disturbances use either acceleration compensation or notchfilters [32] but not both at the same time. However, in apower-split HEV, due to the planetary gear-set rigid and directinterconnection between engine, generator, and motor, suchsolutions cannot effectively damp the driveline disturbances.Hence, our proposed vehicle system wheel-torque controllerutilizes a two-step active damping driveline oscillation sup-pression control system, which is novel in power-split HEVapplication. It consists of 1) a feedforward active compensatorin transaxle control system and 2) a feedback-weighted narrow-band notch-filter-based engine power estimation controller inthe desired driveline wheel-torque control system. It is im-portant to emphasize that a base vehicle system wheel-torquecontroller consists of a base transaxle controller and a basedesired driveline wheel-torque determination controller, whichcannot perform active damping of driveline disturbances orshuffle mode.

With the proposed active-damping-capable vehicle systemwheel-torque control system described in this section, the nextstep is to perform experimental tests and simulations to verifythe systems effectiveness and robustness.

III. EVALUATION OF PROPOSED CONTROLLER INACHIEVING DRIVELINE OSCILLATION SUPPRESSION

To evaluate the proposed active-damping-capable vehiclewheel-torque control system, a Ford Escape Hybrid (a power-split HEV) is selected. The characteristics and specifications forthis vehicle are shown in Table I. The evaluation is performedusing both simulation environment and experimental testing inthe field.

Fig. 7. HEV simulation model (top level).

A. Power-Split HEV Simulation Environment

Simulation modeling [16][22], [27] has become very com-mon in the study of the behavior of controllers and plants. Toevaluate and verify the designed vehicle system wheel-torquecontroller, a validated simulation environment [27] is used toincorporate the vehicle system wheel-torque controller with avalidated power-split powertrain HEV dynamics plant model[27] and a driverenvironmental input model [27]. The power-split HEV plant model for simulation, shown in Fig. 7, wasdeveloped by integrating the developed subsystems mathemat-ical representations and models in a hierarchical architectureusing MATLAB SIMULINK [27]. The power-split HEV plantmodel consists of a driver and environmental input model andthe VSC. The driver and environmental inputs block in Fig. 7contains the driver model that generates driver inputs (e.g.,accelerator and brake pedal commands) and the environmentalconditions, such as road coefficient of friction, road grade,ambient temperature, etc. The driver portion of the driverand environment inputs block can be configured to follow awide selection of standard drive cycle traces representing urban,highway, or even a custom drive cycle. The VSC block con-tains VSC, TCM, engine controller, battery control module, andbrake system module [27]. The power-split powertrain HEVdynamic plant model block contains the powerplant dynamicmodel, the brake system dynamic model, the driveline dynam-ics, and the vehicle dynamic model, as shown in Fig. 8 [27].The driveline and vehicle dynamic blocks are shown in Fig. 9.The mathematical representation of the driveline dynamics isexpressed by the following equations [27]:

d

dt= (2drive_shwheel_rightwheel_left) (18)

dwheel_rightdt

=1

Jw(Thalf_sh Tbrake_right Ftire_rightrw)

(19)

dwheel_leftdt

=1

Jw(Thalf_sh Tbrake_left Ftire_leftrw)

(20)

dV

dt=

1M

(Ftire_right Ftire_left Fresist) (21)Thalf_sh = Ks + Rsh(2drive_sh wheel_right

wheel_left) (22)

where is the effective displacement of the half shaft (inradians), drive_sh is the drive shaft speed (in radians per



Fig. 8. Complete power-split powertrain HEV dynamics plant model.

Fig. 9. Block diagram for the driveline and vehicle dynamics model.

second), wheel_right and wheel_left are, respectively, the rightand left wheel speeds (in radians per second), V is the vehiclespeed (in meters per second), Thalf_sh is the half shaft torque (innewton meters), Ks is the driveline stiffness, Rsh is the damp-ing ratio for the drive shaft, and Ftire_right and Ftire_left are,respectively, the right and left tire forces (in newtons). Theseparameters are calibrated under a simulation environment tomatch the experimental data. The design and experimental datafor the driveline of the Escape Hybrid detail that the resonancefrequency of the driveline is around 6 Hz; hence, the term Ks(driveline stiffness) in (22) is determined such that the resultingresonance frequency of the driveline will be around 6 Hz.

This simulation environment can be used for the develop-ment and evaluation of the control system to actively damp thedriveline oscillations.

B. Vehicle Test Conditions

The Ford Escape Hybrid vehicle is used to study and eval-uate the active-damping-capable vehicle system wheel-torquecontroller.

To study the performance of the controllers, a custom testthat could emphasize on the vehicle and controllers behavior isdevised. Therefore, during this test, the vehicle either is at lowvehicle speed (0 km/h) or initially cruises at a constant highervehicle speed of above 30 mi/h, and then, the accelerator pedalis fully depressed to achieve full pedal vehicle acceleration. To

emphasize the driveline oscillation behavior, the HV batterypower discharge and charge limits are set to zero, therebyrequiring the control system to ensure that, during this test, theactual HV battery power is controlled to be around 0 kW.

C. Performance Evaluation of Proposed Wheel-TorqueControl System in Simulation Environment

After careful analysis of (1)(5), (9)(14), and (17)(19),it can be observed that the disturbances with the frequencycomponent matching the driveline resonance frequency (6 Hzin this case), which appears in motor speed (which can beinduced by driveline mode or abrupt change in motor torque)and generator speed (which can be induced by powertrain blockshake, motor speed noise, or abrupt change of engine torque),can result in driveline oscillations.

To test the effectiveness of the proposed control systemagainst the driveline oscillations, the custom test described inSection III-B that could emphasize the vehicle and controllersbehavior is used.

The driveline oscillations may occur as a result of noiseon the motor speed, due to motor torque or speed distur-bances, with the driveline resonance frequency component[34]. Various simulations with the test conditions described inSection III-B are performed at low vehicle speed (0 km/h) toreproduce driveline oscillation with different disturbances. Inthe simulation environment, burst peak sine wave noise withdifferent amplitudes is used to reflect these disturbances or thedriveline frequency component noise at motor and generator.The driveline resonance frequency for the Ford Hybrid Escapeis around 6 Hz, and hence, a 6-Hz burst sine wave is used. Inthese tests, the vehicle is either at low speed (0 km/h) or athigh vehicle speed (30 km/h), and the accelerator pedal is de-pressed to 100%, whereas the HV battery power discharge andcharge limits are maintained at 0, and key vehicle parameters(accelerator pedal position, vehicle speed, motor or generatorspeed noise, engine power estimate, and desired wheel torque)are captured at a rate of 100 samples/s. The burst peak sine wavemotor or generator noise with driveline resonance frequency(6 Hz) is used, which reflects the driveline frequency compo-nent noise on the motor speed or the generator speed.



Fig. 10. Simulation results for driveline oscillation using base controller at low speed and 10-rad/s peak motor speed noise burst. Plot [A] shows the key vehicleand drivetrain parameters. Plot [B] shows the frequency analysis of wheel torque for every second of data.

Fig. 11. Simulation results for driveline oscillation using the base controller at higher speed and 50-rad/s peak motor speed noise burst. Plot [A] shows the keyvehicle and drivetrain parameters. Plot [B] shows the frequency analysis for every second of data.

Plots [A] and [B] in Figs. 10 and 11 show the results fromsuch a test using a base wheel-torque controller, where mini-mum amplitudes of 10-rad/s peak sine wave motor noise burstat low vehicle speed and 50-rad/s peak sine wave motor noiseburst at high vehicle speed result in driveline oscillations. Theaccelerator pedal position, the motor speed noise, the resultingvehicle speed, the commanded wheel torque to TCM, and theengine power estimate are shown in plot [A] of Figs. 10 and 11.In all these tests, with the key vehicle parameter of the desiredwheel torque being captured at a rate of 100 samples/s, fre-quency analysis using discrete fast Fourier transform (FFT) isperformed for every second of data (e.g., the FFT is performedfrom 3 to 11 s for the test data shown in Fig. 10) for thewheel torque. Plot [B] in Figs. 10 and 11 give the peak-to-peakwheel-torque amplitude frequency, which clearly shows that10- and 50-rad/s peak sine wave motor noise bursts result indriveline oscillations at 6 Hz with peak-to-peak amplitude ofabout 1400 and 1000 N m at low and high vehicle speeds,respectively. These results clearly show that the noise withdriveline resonance frequency component appearing on motorresults in driveline oscillations at both low and high vehiclespeeds when the base wheel-torque controller is used. Notethat the motor noise level of 10-rad/s peak sine wave results

in driveline oscillations, which is relatively small (equivalent to1.24-km/h noise in vehicle speed). An even higher amplitudeof motor noise level (50 rad/s equivalent to 6.25-km/h noisein vehicle speed) is needed to induce driver line oscillations athigh vehicle speeds. In all these tests, it can be noticed thatthe oscillations grew in magnitude and sustained because theoscillations appear in the engine power estimate, as the enginepower estimate is dependent on motor torque and speed. Hence,the engine power estimate amplifies these oscillations andresults in sustained driveline oscillations when the base wheeltorque controller is used. Since a relatively higher magnitudeof noise is needed to induce driveline oscillations at highervehicle speeds, there will be higher occurrences of drivelineoscillations at lower vehicle speeds than higher vehicle speeds.Therefore, throughout the rest of this paper, we will study theperformances of the controllers at low vehicle speeds.

As mentioned earlier, noise (which is induced by powertrainblock shake, motor speed noise, or abrupt change of enginetorque) with a driveline resonance frequency component ap-pearing on the generator speed may also result in drivelineoscillations. Hence, simulation tests at low vehicle speed arealso performed to reproduce driveline oscillation using variousamplitudes of peak sine wave generator noise burst. Plots [A]



Fig. 12. Simulation results for driveline oscillation using the base controller at low speed and 8-rad/s peak generator speed noise burst. Plot [A] shows the keyvehicle and drivetrain parameters. Plot [B] shows the frequency analysis for every second of data.

and [B] in Fig. 12 show the results from such a test. In thistest, a minimum of 8-rad/s peak sine wave generator noise burstresults in driveline oscillations. Again, the accelerator pedalposition, the generator speed noise, the resulting vehicle speed,the commanded wheel torque to TCM, and the engine powerestimate are shown in plot [A] of Fig. 12. From the frequencyresponse for wheel-torque peak-to-peak amplitude shown inplot [B] of Fig. 12, it is clear that the oscillation frequencyis at 6 Hz with peak-to-peak amplitude of above 1000 N m.Note that the generator noise level of 8-rad/s peak sine wave isvery small, i.e., equivalent to 20-r/min noise on engine speed atzero vehicle speed. It can also be noticed that the oscillationsgrew in magnitude and are sustained because they appear in theengine power estimate. Hence, once again, the engine powerestimate (which is also dependent on the generator torqueand speed) amplifies these oscillations and results in sustaineddriveline oscillations. Note that noise in the generator torquewill also result in noise on the generator speed. These resultsclearly show that the base wheel-torque control system is morevulnerable to generator noise as compared with motor noise.

To summarize, these results clearly show that the wheeltorque or driveline oscillation amplitudes are higher than1000 N m at low vehicle speeds. Since the creep torque, whichis the wheel torque required to slowly move the vehicle fromvehicle speed of 0 km/h for the Ford Escape Hybrid, is around400 N m, the perceptible level of the wheel torque for thisvehicle is around 100 N m at low vehicle speeds. The wheel-torque or driveline oscillation of higher than 1000 N m canbe very objectionable to the driver as they are 2.5 times higherthan the creep torque. Hence, these driveline oscillations willseverely impact the drivability of the vehicle under such condi-tions. In addition, these results show that, regardless of the vehi-cle speeds, the power-split HEV powertrain is more vulnerableto generator noise than motor noise. In addition, the power-splitHEV power train is more vulnerable to driveline oscillations atlow vehicle speed, in comparison with the driveline oscillationsat higher vehicle speeds.

It is clear that the power-split HEV power train is verysusceptible to driveline oscillations and that the base wheeltorque controller does not reduce the driveline oscillations orshuffle mode. For the rest of this paper, we will study the

performances of the controllers at low vehicle speeds using gen-erator noise only, as this system is more vulnerable to generatornoise disturbances at low vehicle speeds, and therefore, if theproposed controller is effective under these conditions, thenit will also be effective under all the other conditions. Now,the proposed active damping wheel-torque control system fordriveline oscillation suppression designed in Section II is testedunder the simulation environment.

The simulations are again performed with this proposedactive-damping-capable vehicle system wheel-torque controllerunder low vehicle speed condition with varying amplitudesof generator noise, as described in Section III-B. The resultsclearly show that the driveline oscillations are suppressed withthe proposed controller. Fig. 13 shows the results of such a sim-ulation test using the proposed active-damping-capable vehiclesystem wheel-torque controller, where a 10-rad/s peak sinewave generator noise burst (with driveline resonant frequencyof 6 Hz) is used at low vehicle speed to induce drivelineoscillations. The results in plot [A] of Fig. 13 clearly show thatthe driveline oscillations are suppressed with the proposed con-troller. The frequency response of peak-to-peak wheel torqueamplitude for every second of data from 3 to 11 s in plot [B]of Fig. 13 shows that the driveline oscillation frequencycomponent at around 6 Hz is suppressed to below 50 N mof the wheel torque. Since the resonance component of thewheel torque amplitude is eight times below the creep torque,therefore, it is well below the perceptible level of torque(100 N m) by the driver and, hence, will improve the drivabil-ity of the vehicle.

D. Performance Evaluation of the Proposed Wheel-TorqueController in an Experimental Vehicle Testing

The proposed controller consists of two parts: 1) The active-damping-capable transaxle control system is implemented inthe TCM, and 2) the active-damping-capable desired drive-train wheel torque determination control system is imple-mented in the VSC of the Ford Escape Hybrid experimentaltest vehicle. The performance of this proposed controller is thenverified by performing the custom test described earlier duringthe experimental vehicle field testing on Ford Motor Companys



Fig. 13. Simulation results for the effectiveness of the proposed controller in suppressing driveline oscillations at low speed with 10-rad/s peak generator speednoise burst. Plot [A] shows the key vehicle and drivetrain parameters. Plot [B] shows the frequency analysis for every second of data.

Fig. 14. Experimental test results for driveline oscillations using base controller at lower vehicle speed. Plot [A] shows the key vehicle and drivetrain parameters.Plot [B] shows the frequency analysis for every second of data.

Fig. 15. Experimental test results for the effectiveness of the proposed controller in suppressing driveline oscillations at lower vehicle speed. Plot [A] shows thekey vehicle and drivetrain parameters. Plot [B] shows the frequency analysis for every second of data.

test track using this experimental Ford Hybrid Escape testvehicle setup. These tests are performed at various road con-ditions to ensure that the solution is effective under low vehiclespeeds. This is achieved by comparing the performances of thebase and active-damping-capable vehicle system wheel-torquecontrollers. The results of this experimental vehicle test at lowvehicle speed are shown in Figs. 14 and 15. It is clear from

Fig. 14 that the commanded wheel torque results in sustaineddriveline oscillations at low vehicle speeds (full accelerationfrom zero speed) after 2 s when the base wheel torque controlleris used. The peak-to-peak wheel-torque amplitude frequencyresponse in plot [B] of Fig. 14 clearly shows that there isa sustained driveline oscillation at around 6 Hz with peak-to-peak oscillation amplitudes of more than 1500 N m after



Fig. 16. Simulation results for the robustness of the proposed controller in suppressing driveline oscillations at low speed with multiple 20-rad/s peak generatorspeed noise burst. Plot [A] shows the key vehicle and drivetrain parameters. Plot [B] shows the frequency analysis for every second of data.

2 s of the test. Such amplitudes of oscillations can be veryobjectionable, as wheel-torque magnitude changes of above100 N m can be perceived or felt by the driver, and hence,they affect the drivability of the vehicle. Plot [A] of Fig. 15shows that the driveline oscillation is suppressed using theproposed active-damping-capable vehicle system wheel-torquecontroller. Plot [B] of Fig. 15 clearly shows that the peak-to-peak wheel-torque oscillatory frequency component at 6 Hzis much below the perceptible level of 100 N m. These experi-mental tests provide the verification that the proposed controlleris effective in suppressing driveline oscillations and, thereby,can improve the drivability of this hybrid vehicle.

E. Validation of Proposed Control System Performance toKey Factors

The two key factors that can affect the performance of thecontroller are customer usage and external environment.The customer usage effect is mainly described through dif-ferent road conditions (such as pot holes or severely degradedroads that can result in higher amplitude of disturbances), andthe External Environment effect is mainly described as thevehicles driveline characteristic change over the life of thevehicle. We need to validate the performance of this proposedcontroller to these factors. Since it is very difficult to test thevehicle under such conditions in a real-world environment,simulation tests are again used to validate the performance ofthe proposed solution to these factors.

1) Validation of Proposed Control System Performance toDegraded Road Conditions: The simulations are performedwith the same driving maneuvers or custom test as describedin Section III-B at low vehicle speeds with varying amplitudesof generator noise. Since we already know that the system ismore vulnerable to driveline oscillation due to generator noiseat low vehicle speeds, simulations are performed to verify theeffectiveness and robustness of the solution at low speed by in-jecting a generator noise burst of 20-rad/s peak sine wave (overtwice higher than the level required to induce oscillations). Inaddition to increasing the amplitude of noise by a factor ofover 2, multiple noise bursts are also used. Fig. 16 shows the

result from such a test, where multiple 20-rad/s peak sine wavegenerator noise bursts with amplitudes of over twice higher thanthe level required to induce oscillations (when compared withthe base wheel-torque controller) under normal conditions areused. It is clear from the results that the resonance componentof the driveline at 6 Hz stayed below the perceptible level of100 N m. It is also clear from the results that the engine powerestimate stayed very clean (without disturbances), even withmultiple generator noise with amplitudes of 20-rad/s peak burstsine wave. Hence, it can be concluded that the proposed active-damping-capable controller can suppress driveline oscillationsresulting from higher amplitude of motor or generator noise ordisturbances at low or high vehicle speeds due to degraded roadconditions.

2) Validation of Proposed Control System Performance toVarying Driveline Characteristics: As the vehicles drivelinecharacteristics can change over the life of the vehicle, thisvarying driveline characteristic can be characterized by varyingthe stiffness of the driveline in the simulation environmentthrough the driveline and the vehicle dynamics plant model,whose mathematical representation is described in (22).

Based on the experimental vehicle characteristic data, thestiffness of the vehicles driveline can change by no more than25% over the life of the vehicle, resulting in shifting of thedriveline resonance frequency. We need to ensure that the pro-posed control system is also robust to such affects. To achievecomplete robustness, simulation studies are done for drivelinestiffness changes of 50%, which is two times higher than whatis expected over the life of the vehicle. We again chose to usea generator noise signal at low speeds for these studies, sincewe know that low-speed driveline oscillation can occur withvery small generator noise amplitudes. Simulations with thebase wheel-torque control system described in Section II arefirst performed with the changed driveline stiffness that resultedin driveline oscillations. These results are then compared withthe proposed active-damping-capable vehicle wheel-torquecontrol system.

First, the driveline stiffness is reduced by 50%, and sim-ulations are used to compare the performances of the con-trollers. Plot [A] of Fig. 17 shows that the base wheel-torque



Fig. 17. Simulation results with the base controller at low speed with 20-rad/s peak generator speed noise burst, where the driveline stiffness is reduced by50%, resulting in suppression of driveline oscillations. Plot [A] shows the key vehicle and drivetrain parameters. Plot [B] shows the frequency analysis for everysecond of data.

Fig. 18. Simulation results for the robustness of the proposed controller at low speed with 20-rad/s peak generator speed noise burst, where the driveline stiffnessis reduced by 50%. Plot [A] shows the key vehicle and drivetrain parameters. Plot [B] shows the frequency analysis for every second of data.

control system with the reduced stiffness results in wheel-torque oscillations. Plot [B] of Fig. 17 shows that reductionin the stiffness by 50% resulted in a lower driveline oscilla-tion frequency of around 4 Hz. In addition, the amplitude ofpeak-to-peak oscillations with the base wheel-torque controllerand reduced driveline stiffness are greater than 2000 N m.Again, simulations using the proposed active-damping-capablevehicle wheel-torque control system with the driveline stiffnessreduced by 50% are again performed to validate the solutionsperformance. Fig. 18 shows the results of the simulation. It isclear that, with the peak generator noise amplitude of 20 rad/s(over twice higher than the level required to induce oscillationsunder normal road conditions), there are no sustained oscilla-tions in the wheel torque. Plot [B] of Fig. 18 shows that theresonance frequency component of the driveline stayed below100 N m. Again, a peak-to-peak amplitude of 100 N m of thewheel torque at low vehicle speed is below the perceptible level.It is also clear from the results that the actual engine power re-mained acceptable and became clean (without disturbances) af-ter 5 s with the reduced driveline shaft stiffness. Hence, we canconclude that the solution is effective in suppressing drivelineoscillation when the driveline stiffness is reduced by up to 50%.

Next, the driveline stiffness is increased by 50%, and simu-lations are used to compare the performances of the controllers.Fig. 19 shows the results of the simulation results using thebase wheel-torque control system, where the driveline stiffnessis increased by 50%. Note that, initially, a generator peak-noise burst signal of 20 rad/s (over twice higher than the levelrequired to induce oscillations under normal road conditions)was used to induce oscillations, but such an amplitude was notenough to result in driveline oscillations. This suggested thatan even higher magnitude of generator noise burst is requiredfor sustained driveline oscillations if the driveline stiffness isto increase over time. Therefore, an even higher amplitude of30-rad/s peak generator noise burst is used. Plot [A] of Fig. 19shows that the increased amplitude of 30-rad/s peak generatornoise burst (over three times higher than the level requiredto induce oscillations under normal road conditions) resultsin sustained driveline oscillations. Plot [B] of Fig. 19 showsthat the increase in the stiffness resulted in a higher drivelineoscillations frequency of 7 Hz with peak amplitudes of above500 N m. This clearly suggests that a very high magnitudeof generator noise is required for sustained driveline oscilla-tions when the driveline stiffness increases by 50%. Hence,



Fig. 19. Simulation results with the base controller at low speed with 30-rad/s peak generator speed noise burst, where the driveline stiffness is increased by50%, resulting in driveline oscillations. Plot [A] shows the key vehicle and drivetrain parameters. Plot [B] shows the frequency analysis for every second of data.

Fig. 20. Simulation results with the base controller at low speed with 30-rad/s peak generator speed noise burst, where the driveline stiffness is increased by50%, resulting in driveline oscillations. Plot [A] shows the key vehicle and drivetrain parameters. Plot [B] shows the frequency analysis for every second of data.

it is very likely that the increase in driveline stiffness willresult in the reduction of driveline oscillation occurrences andamplitudes. To still validate the performance of the proposedactive-damping-capable vehicle system wheel-torque controlsystem, simulations using the proposed active damping controlsystem with the driveline stiffness increased by 50% are againperformed. Fig. 20 shows the results from the simulation. It isclear from plot [A] of Fig. 20 that the induction of generatornoise burst with a peak amplitude of 30 rad/s (over three timeshigher than the level required to induce oscillations) did notresult in sustained oscillations in the wheel torque with the pro-posed controller. In addition, plot [B] of Fig. 20 shows that theresonance frequency component of the driveline stayed below50 N m, which is again far below the perceptible level. It isalso clear from the results that the engine power estimate stayedvery clean (without disturbances) with the increased drivelineshaft stiffness. Hence, we can conclude that the proposed activedamping controller is effective in suppressing the drivelineoscillations with increase in driveline stiffness of up to 50%.

As we have noticed from the simulations using a higher levelof disturbance (reflecting the degraded road conditions) andincreased/reduced driveline stiffness (reflecting the drivelinecharacteristics changes over the life of the vehicle), the engine

power estimate or the wheel torque did not have sustaineddriveline oscillations; hence, it can be concluded that the per-formance of the proposed solution is capable of suppressingdriveline oscillations with driveline characteristic changes anddegraded road conditions.

IV. CONCLUSION

A vehicle system wheel-torque controller without activedamping capability in a power-split HEV can result in sustaineddriveline oscillations due to the shuffle mode of the vehicle,which can severely impact the drivability of the vehicle. Thispaper has presented an innovative approach to actively dampingthe sustained driveline oscillations, thereby improving drivabil-ity in a power-split HEV.

The design of the active damping controller was presentedalong with the simulation and experimental results. The sim-ulations quantitatively demonstrated that the proposed activedamping control system can improve the drivability by reducingthe driveline resonance component of the wheel torque to below100 N m versus using the conventional method, which is proneto driveline oscillations. Further, the test vehicle results throughexperiments clearly demonstrate that the proposed controller



is effective in significantly improving the drivability behaviorsby suppressing the driveline resonance. In addition, the controlsystem is validated against customer usage and environmentalchanges. Finally, this controller provides a significant reductionor suppression in the shuffle mode, thereby improving drivabil-ity and customer satisfaction.

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Fazal U. Syed studied electrical engineering withAlfateh University, Tripoli, Libya, and received theB.S. degree in electrical engineering from the Tech-nical University of Budapest, Budapest, Hungary, in1992 and the M.S. and Ph.D. degrees in electricalengineering from Wayne State University, Detroit,MI, in 1995 and 2008, respectively.

In 1995, he was with Servotech Engineering,where he worked on various vehicle, engine,electrical, and electronic control projects. SinceSeptember 2002, he has been a Lead Design Engi-

neer with the Hybrid Electric Vehicle Program, Sustainable Mobility Technolo-gies Laboratory II, Ford Motor Company, Dearborn, MI. He has published morethan 12 technical papers in various conference proceedings and journals. Hiswork regarding hybrid electric vehicle modeling and fuzzy controls has beenpublished in the IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY. He isthe holder of various U.S. and international patents in the area of diesel andhybrid electric vehicle controls.

Mr. Syed received the 2005 Henry Ford Technology Award, which is thehighest technical achievement recognition and most prestigious award at theFord Motor Company, for his work related to the development of the hybridelectric vehicle control systems.



Ming L. Kuang received the B.S. degree in me-chanical engineering from South China Universityof Technology, Guangzhou, China, in 1982 and theM.S. degree in mechanical engineering from theUniversity of California, Davis, in 1991.

Since 1991, he has held various engineering posi-tions with Ford Motor Company, Dearborn, MI. Hewas a Control System Engineer working on electricand series hybrid electric vehicles from 1991 to1995. He worked in the areas of vehicle dynamicsand controls as a Research Engineer from 1995 to

2000. He became a Technical Expert in 2000 for the Escape Hybrid vehicleprogram and played a critical role in vehicle/powertrain control system de-velopment and implementation, delivering the first Ford Escape Hybrid andMercury Mariner Hybrid vehicles to production. He is currently a TechnicalLeader in vehicle controls with Research and Advanced Engineering. He hasauthored/coauthored 20 technical papers in various engineering journals andconference proceedings and is currently the holder of 36 U.S. and internationalpatents. His primary research interests include vehicle control architecture,vehicle control system development, and implementation methodologies, aswell as advanced vehicle control algorithm development for hybrid and fuel-cell vehicles.

Mr. Kuang is a member of the Society of Automotive Engineers. He wasrecognized and honored with the 2005 Henry Ford Technology Award for histechnical leadership and contributions to the success of the Escape Hybridand was the recipient of SAE 2007 Henry Ford II Distinguished Award forExcellence in Automotive Engineering.

Hao Ying (S88M90SM97) received theB.S. and M.S. degrees in electrical engineeringfrom Donghua University (formerly China TextileUniversity), Shanghai, China, in 1982 and 1984,respectively, and the Ph.D. degree in biomedicalengineering from The University of Alabama atBirmingham in 1990.

Between 1992 and 2000, he was with the faculty ofThe University of Texas Medical Branch, Galveston.Between 1998 and 2000, he was an Adjunct As-sociate Professor with the Biomedical Engineering

Program, University of Texas at Austin. He is currently a Professor with theDepartment of Electrical and Computer Engineering and a Full Member of theBarbara Ann Karmanos Cancer Institute, Wayne State University, Detroit, MI.He has published one research monograph/advanced textbook entitled FuzzyControl and Modeling: Analytical Foundations and Applications (IEEE Press,2000), 90 peer-reviewed journal papers, and more than 120 conference papers.He is an Associate Editor of four international journals (the InternationalJournal of Fuzzy Systems, the International Journal of Approximate Reasoning,the Journal of Intelligent and Fuzzy Systems, and Dynamics of Continuous,Discrete and Impulsive SystemsSeries B: Applications and Algorithms). Heis also an Editorial Member for the journal Advances in Fuzzy Sets and Systems.He was a Guest Editor for four journal issues.

Dr. Ying is serving as Associate Editor and member of the editorial boardfor nine international journals. He is a member of the Fuzzy Systems TechnicalCommittee of the IEEE Computational Intelligence Society and chairs its TaskForce on Competitions. He is an elected board member of the North AmericanFuzzy Information Processing Society (NAFIPS). He served as Program Chairfor the 2005 NAFIPS Conference and the International Joint Conference ofthe NAFIPS Conference, the Industrial Fuzzy Control and Intelligent SystemConference, and the NASA Joint Technology Workshop on Neural Networksand Fuzzy Logic held in 1994. He served as the Publication Chair for the 2000IEEE International Conference on Fuzzy Systems and as a Program CommitteeMember for more than 35 international conferences. He has been invited toserve as a reviewer for more than 60 international journals.


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