hybrid electric vehicle power train

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Vehicle

Dynamics

Brake

Torque

Vehicle

Driver

Longitudinal

Dynamics

Tire/Roadccelerator

Command

Brake

Command

Vehicle Velocity

Controller

Brake

Torque

Brake

Hardware

Longitudinal

Dynamics

Tire/Road

Brake Hydraulic

Command Brake System

.

nterface

Load Forces

InverteriMotor

Controller

InverteriMotor

Control

-

Braking Control

Motor Torque

Vehicle Velocity

Interface

LoadForces

Traction Motor

Motor

Torque

Delivered

Motor Nonlinearities

1q

ommandI

Driveline

Dynamics

Dynamic

Weight

Transfer

-----+I I

Battery

Motorhverter

Efficiency

Battery Dynamics

Battery Nonlinearities

Battery Efficiencies

Energy Recovered

Inverter Load

Current

Fig.

I .

Electric vehicle dynamic model.

The driveline efficiency of the conventional powertrain portion

of the HEV system can be improved by the inclusion of an auto-

matic manual transmissioddry clutch driveline combination. Au-

tomation of a manual transmission alleviates driver interaction

with the clutch and gear shift lever required in a standard manual

bansmissiodclutch combination, while providing near automatic

transmission performance.

This

type of driveline, combined with

the proper choice of “shift points,” and elimination of the torque

converter (prevalent in automatic transmissions) can enhance fuel

economy while mitigating emission effects.

Such combinations of components, with an array of energy

and power levels (as well as perhaps dissimilar dynamic proper-

ties), yields

a

potentially difficult ensemble dynamic control

problem. A powertrain dynamic model of such a complex pro-

cess enables the development of a measure of performance and

allows insight into the dominant dynamic effects in control law

synthesis. Additionally, a powertrain model can be used to help

determine optimum powerplantldriveline combinations, elimi-

nating unnecessary vehicle builds. This article contains a de-

scription of HEV dynamic models; many of the important

dynamic control related issues are highlighted. The primary

components presented include a vehicle driver, coordinated con-

troller, a phenomenological model of a Spark Ignited

(SI)

Inter-

nal Combustion Engine

(ICE),

variable field altemator, dynamic

lead acid battery,

dry

clutch, automated manual layshaft trans-

mission, brake system, complete vehicle longitudinal dynamics

with tire-road interface characterization, and an ac induction mo-

tor electric drive system.

Also discussed in this article are automated manual layshaft

conventional powertrain test results and simulations that demon-

strate dynamic interactive effects and aid

in

the formulation of

dynamic control laws for powertrain control. Presented also are

simulations of the

PHEV

dynamic model, which demonstrate the

added complexity

of

the electric powertrain dynamic interactive

effects, the understanding of which is a precursor to dynamic

control law synthesis.

EV Powertrain System

Vehicle Driver and Coordinated Control

Generally, for all the vehicle configurations discussed herein,

the driver model includes an implicit vehicle velocity controller,

with driver velocity error and

Propohonal-Integral-Denvatrve

(PID)capability, and a collection of drive cycles to provide a ve-

hicle input command. The vehicle driver model uses vehicle ve-

locity feedback from the vehicle dynamics and a commanded

vehicle velocity to generate braking to the brakes, and for an EV,

a coordinated vehicle controller then provides motoring and re-

generative commands to the motor controller for corresponding

positive and negative motor torque. Perhaps command informa-

tion is also provided to a clutch and transmission system when a

manual or automatic manual transmssion

is

employed. A sche-

matic representation of an EV dynamic powertrain without a

gear changing transmission is shown in Fig.

1.

Inverter/Motor Controller

The traction motor and controller

[lo],

[11] extract power

from the battery, or alternative energy storage device, and pro-

vide torque to the driveline

[

121, [

131,

which in turn provides the

EV motive power. Additionally, the traction motor and controller

18 IE E E Control Systems



may be operated as a starter/alternator combination [14] or as a

generator used to recover the vehicle kinetic energy dissipated

during braking [1.51, [161. The traction motor and controller then

provide power to the battery or altemative power source, and

negative torque to the driveline, which in turn brakes the vehicle.

The coordination of electric and hydraulic blending, during

braking, is performed by the traction motor controller to meet the

driver brake torque command. Compression braking torque,

electric braking torque used to emulate the feel of engine drag

present on an IC engine vehicle, is also determined by the trac-

tion motor controller.

All

negative motor torque is reduced lin-

early at low vehicle speeds where no energy can be recovered.

Clompression braking torque allows braking to occur while re-

covering the maximum energy, due to all braking being per-

folrmed electrically.

Traction Motor Dynamics

The traction motor dynamic model [lo] represents the dy-

namics of a specific field oriented controlled ac induction motor

as described by the following equations:

h,, = L .iqs L , .iqr

h,, =

L,T

id +L ,

.id

A = L m . i q a L;iq,

h ,

= L , . L , i

The inverter load current is a function of traction motor speed,

torque delivered, and terminal voltage of the battery during mo-

toring and during regeneration as:

where

elb

is battery terminal voltage, V; Tmposdels positive motor

torque delivered during motoring, Nm.;

q

is motor and inverter

combined efficiency.

Battery

The battery model is a lumped parameter dynamic character-

ization of a lead acid battery [8], [14]. The open circuit voltage is

a function of traction battery state of charge and empirical pa-

rameters for lead acid batteries. The dynamic relationships be-

tween battery voltage and current are modeled, including the

polarization capacitive effect, incipient capacitance of the bat-

tery, internal battery resistance, and terminal ohmic resistance.

For example,

V,, = 338.8.[0.94246

+

0.0.05754.(

S O C ) ]

R~ .

elb = zCh

R ~

lh

dt

where C, is capacitive impedance, F; C, is polarization capaci-

tance, F;Zlbisvoltage drop due to_polarization capacitance, V; ilb

is battery discharge current,

A; R

is battery intemal resistance,

ohms;

Rb

is battery terminal resistance, ohms; SOC is battery

state of charge, percent; V,, is battery open circuit voltage, V.

wlherei,,, iqr are d q axis rotor current respectively, A; i d s i q s are

d ,

q

axis primary current respectively, A ; L are mutual induc-

tance, H; r ,LJ are resolved rotor, stator inductance respec-

tively, H; P is poles; Rr,

Rs

re resolved rotor, stator resistance

reispectively, ohms;

V,,

Vqsare d

q

axis primary voltage respec-

tively, V; h,,,h

qr

are d q axis rotor equivalent flux respectively,

V-sec; h,, h , are

d q

axis stator equivalent flux respectively,

V-sec;

o s synchronous frequency,rps ;ors rotor frequency,

rps;

&,is

rotor acceleration,

rps*;

T,is electric motor torque, Nm.

The traction motor torque delivered is modeled as a function

of the motor dynamics, motor nonlinearities, and losses in both

the motor and inverter as a function of motor speed. The traction

motor torque limit is characterized by functions of the form:

Brake Controller

The dissipation of kinetic energy during braking, by an electric

or hybrid vehicle, can be recovered advantageouslyby controlling

power electronics such that the electric traction motor behaves as a

generator [121. The energy recovered during this process can be

returned to the energy storage device for future use.

A parallel braking system applies regenerative braking torque

(to the driven wheels), in addition to hydraulic braking torque

provided by the foundation braking system. Hydraulic brake

torque is determined in the brake controller, based on HEV coor-

dinated control commands

[

1.51,

[

161. Regenerative brake com-

mands are predetermined as a function of master cylinder

pressure in the traction motor controller and are based on PHEV

coordinated control commands. In a series braking system, not

illustrated here, integrated control exists between the brake con-

troller and the traction motor controller [16], [17].

T,

= a r e d

a <a

Vehicle Dynamics

The vehicle dynamic model in this instance includes four

wheel longitudinal vehicle dynamics for

a

front wheel drive ve-

hicle. The inputs to the vehicle drivetrain are the motor torque or

output

from a gearbox (transmission) with motor torque

as

gear

where

0

s motor base speed, Tm ;

0

is m~ ha ni ca l otor

W e d q m ;

rated motor

torque, Nm.;

T,

is mechanical motor torque, Nm.

rated

motor

power, hp; Trared

October 1998 19



box input. In addition, the vehicle drivetrain receives hydraulic

brakmg torque or other driveline loads, and vehicle velocity is

determined via integration of the longitudinal equations of mo-

tion. Rotational dynamics for each wheel, and halfshafts, and

a

representation of the forces acting on the vehicle, are modeled.

Rotational wheel dynamics include wheel slip (skid), tireiroad

surface adhesion coefficient, wheel tractive force as a function of

dynamic weight transfer, road load torque for each wheel, and

rotational wheel speed.

Wheel slip (skid) is used to determine the tireiroad surface ad-

hesion coefficient with a nonlinear analytic tireiroad surface inter-

face model

[l], [ 3 ] , [17].

The tire model used for this study

assumed a high road surface adhesion coefficient for dry pave-

ment, because these are conventional driving conditions. The

wheel tractive force as a function of dynamic weight transfer is

the product of the road surface adhesion coefficient and the nor-

mal force acting on the wheel:

In calculating the normal forces acting on each wheel, the dy-

namic weight transfer is modeled for each of both front and rear

wheels in terms of the vehicle pitch and lever arms (wheel base)

to the vehicle center of mass. The road load torque for each wheel

is then determined from the wheel diameter and tractive force:

The torques acting on the wheels include the halfshaft torque,

Ts,

road load torque,

Tb,

bearing friction torque, and the braking

torque. Rotational wheel acceleration is obtained by the sum of

the torque acting on the wheel divided by the wheel inertia.

Wheel speed is obtained by integrating rotational wheel acceler-

ation:

The halfshaft model accounts for the torsional compliance be-

tween the differential and wheel. The resulting halfshaft torque is

applied to the wheel. The relations for shaft torque, and shaft com-

pliance in terms of physical parameters are shown below:

The four wheel tractive forces, aerodynamic drag, grade

forces, and rolling resistance, describe the forces acting on the

vehicle and are depicted below:

Ft”,= Ft,, + lr Ft + Fdf - Fa,, Fry

grada

The aerodynamic drag on the vehicle is a function of vehicle

velocity squared, air density, vehicle frontal area, and coefficient

of drag, where the vehicle velocity is determined by solving €or

vehicle acceleration and integrating over time:

The rolling resistance force is a function

of

vehicle weight, roll-

ing resistance coefficient, and vehicle speed:

F,, = f, .

W ,

.1.3558(1+

k ,

. V k, .

V’)

The grade forces acting on the vehicle are a function of vehi-

cle weight and grade angle:

FgrOd, W,

.1.3558

sin0

.

The total forces on the vehicle equal the vehicle mass multi-

plied by the vehicle acceleration.

In these equations,4 s frontal area of vehicle,m2;Cd s aero-

dynamic drag coefficient; Fa,, is aerodynamic drag force on ve-

hicle,

N ;

Fgrad,s grade force on vehicle, N; Frr is rolling

resistance force on vehicle, N;

f , s

rolling resistance coefficient;

ev

s tractive force on left front wheel, N;

c,rs

tractive force on

left rear wheel, N;

e,,

s total forces acting on vehicle, N; F, is

tractive force on right front wheel, N ; Jdq

is

differential inertia,

kg.m2 ; Jfd dg

s final drive inertia on differential side,

k g , m 2 ;

J ,

is

wheel inertia,

kg

.m2

K ,

is halfshaft stiffness, “/rad;

K ,

is

empirical constant;

K 2

is empirical constant; R,, is loss in shaft

bearings, k g . m 2 sec.rad

;

R, s wheel radius, ft; Tb is brake

torque, Nm; T is final drive output torque, Nm; TIoads road

torque, Nm

Tsis

halfshaft torque, Nm; V is vehicle velocity,

m i

sec2 ;

W,is vehicle weight, lbf; y is air density, kg i m ;8 is

grade angle, rad;

0 ,

is halfshaft displacement, rad;

p ( 7 r , l r , r f , y )

s

coefficient of friction on right rear, left rear, right front, and left

front wheels respectively; 03 is wheel speed, radfsec;

ofd

is final

drive speed on differential side, radfsec;ol s left wheel speed,

radisec; w is right wheel speed, radisec.

fd.

Series

HEV

Powertrain System

Vehicle

Driver

and

Coordinated Control

A Series HEV (SHEV) powertrain may be achieved with the

addition of an auxiliary power plant to the electric vehicle in

power series connection with the traction battery and traction

motor. In a “senes” configuration, the power unit interacts with

the vehicle system controller and the rest of the vehicle electrical

system, which includes the vehicle traction motor and other an-

cillary loads such as power steering or air conditioning. The ve-

hicle system controller provides a desired power command and a

desired engine speed command to the SHEV system. Two or

more control variables may be used to attempt to achieve the de-

sired altemator power at a desired engine speed. In addition, the

coordinated vehicle controller provides motoring and regenera-

tive commands to the motor controller. A schmatic representa-

tion of a series HEV is given in Fig.

2.

Engine Dynamic Model

The key exogenous control variable to the

SI

ICE engine sys-

tem

[9]

is the throttle angle (or mechanical equivalent). For a die-

sel engine it might be the fuel control system command. Control

variables such as spark advance, Exhaust Gas Recirculation

(EGR), and Air-to-Fuel ratio AF),nd variable geometry

turbocharger on a supercharged power plant, are for this current

representation considered

to

be precalibrated emission control

20

I E E E Control Systems



ATR Brake System

-

Vehicle Dynamics

Fixed Field

aximum Power Command SI Engines Speed

Meet Emission

Turbine *Variable Field

tilization

Constraints Diesel

10

to

60

kW

Accel and Brake

ICommands -

Follow Specified

13rive Cycle

-

Brake Torque

High Fidelity Modelof

Brake Components

IMC and Motor

Fixed Field

aximum Power Command SI Engines Speed

Meet Emission

Turbine Variable Field

Utilization

Constraints Diesel

10

to

60

kW

High Fidelity Induction Motor Provides

Motoring Torque

Regen Braking Torque

No

Pedal Torque

Inverter Load

Strateav

&

t Energy Storage

otational Dynamics

*Tire/Road lntetface

Longitudinal Dynamics

Driveline Dynamics

Device

Batteries

Powerplant

Fig. 2.

Series HEV dynam ic model.

variables. The throttle control law includes

a

variable gain PI

(proportional plus integral) controller to provide

a

limited throt-

tle command to the engine, based on commands from the vehicle

driver controller. Included also in the throttle command control

law are the Wide Open Throttle (WOT) operating logic and an

engine Idle Speed Control (ISC) law.

The throttle body is considered as a variable nozzle for air

flow modeling. By considering one dimensional, steady, com-

pressible, isentropic flow of

an

deal gas, the equation represent-

ing mass flow across

a

valve opening or orifice results in

a

quasi-steady relation. In terms of the throttle valve or cross sec-

tional area, Ae, and pressure ratio, the mass flow rate through the

valve is given by

temperature,

KO;

y is ratio of constant pressure to constant vol-

ume specific heats.

The changing flow area, Ae, is

a

function of the obstructing

geometry presented to the flow field. For example, employing

experimentally obtained engine pumping flow rate data for a cir-

cular bore of approximately

34

mm the flow rate (kgh r) may be

given in terms of throttle angle (theta) in degrees

as

F ( e )= c , ( e ) A ( e ) = 3.765-0.1058e 0.05479e*

The manifold dynamic equations that result from using en-

ergy balance and thermodynamic principles

[8]

are

P

=

- Th,,,

Y

- T h o ) + Qm-1

‘

V V

where

where

P, is downstream pressure, kPa;P, is upstream pressure, kPa; R is

specific gas constant, atm

.liter I

gm .mole .

K ; Tu

is upstream

where

C,, C

is constant pressure, volume specific heats; m is

sum

of

manifold intake mass flow rates, kghr;

iz

is sum of all

outflow mass rates, kghr ;

Q,

is rate of heat flow into the mani-

fold, Jouleslsec;

Tt

is temperature of intake masses, deg;

V

is

manifold volume, cm3.

Mass and momentum balance are achieved by assuming uni-

form temperature, pressure and density in each open thermody-

namic volume

as

well as assuming

a

conservation

of

mass

constituents where

no

chemical reactions ake place. In some in-

stances, a further simplified model is justified by assuming in-

variant manifold temperature without loss of the dominant

manifold filling effect. However, temperature effects should not

be neglected when “cold” engine conditions, cold dense air

October

1998

21



charge, or evaporating and condensing fuel are important dy-

namic issues.

An estimation of mass flow rates out of the manifold is given

approximately by a product of the engine speed, engine displace-

ment, and volumetric efficiency, which in turn is resolved in

terms of engine speed, intake temperature, manifold pressure,

and exhaust gas pressure. Manifold mass flow rate egress is

given in terms of manifold pressure and engine speed by an ap-

proximate polynomial functional form

. N

N

M

= ---(OS22 O.OS553(-))(0.17P+ 0 .0 0 0 9 8 P 2 ) ,

1000

1000

where M is speed density mass flow rate, kg/hr and

N

is engine

speed, rpm.

The engine torque developed at any time is a function of the

mass rates (mass charge) or ratios of rates (mass constituents)

that were sampled one engine induction event earlier. This

breathing event is a crank angle synchronized relationship that is

primarily dependent 011engine speed. For a zero order extrapola-

tion, the minimum delay in torque generation that results from

ingestion of the manifold constituents is

180

crankangle degrees.

For a four cylinder engine with a speed of N

RPM,

this is repre-

sented by a propagation lag relationship with idealized delay T is

30/N

seconds.

A similar lag exists for the mixed A/F from the end

of

com-

bustion to exhaust valve closure. In addition,

a

nonspeed depend-

ent propagation lag, and some gaseous diffusion, is assumed to

persist in the exhaust pipe before the A/F sensor location [18].

Representation of the A/F delays in an SI ICE is extremely im-

portant as the torque response is highly sensitive to A/F tran-

sients, including throttle input and fuel control system transients.

The nonlinear structure for the A/F (Air/Fuel) system con-

sists of an EGO (exhaust gas oxygen) A/F sensor in the exhaust

pipe, with a time constant of the order of

70

ms, followed

by

a

nonlinear (Nernst) rich/lean Signum function and

a

PI fuel com-

mand control law

[18].

An intake runner port fuel injector is as-

sumed with a fuel rate output, and with fuel condensation and

evaporation dynamics

[

191. The resulting system equations are

dm

.

,

T - ‘=rp~~-m~,

” dt

m = (1

l)rifi

mi,

m is manifold fuel flow rate, kglhr; m t~ is injector fuel rate com-

mand, kg/hr;nifLs injected fuel flow rate, kglhr;m is fuel evapo-

ration rate, kg hr ;q is fuel accumulation parameter, = 0.25sec;

T~

is injector time constant,

=

50 ms; 7 is condensation and evapo-

ration time, = 0.5 sec.

The fuel mass flow rate is combined with the throttle mass air

flow rate to form the manifold A/F. This A/F is delayed by the in-

duction breathing lag, preparatory to combustion torque genera-

tion, followed by a combustion torque delay, a power-stroke to

exhaust delay, and a plug stroke exhaust system delay that is de-

pendent on the location of the EGO sensor.

Torque generated from the combustion process is dependent

on the ignition of a cylinder charge o f air, fuel, and residual gas,

as well as other variables and parameters that influence combus-

tion efficiency. Assuming a spark advance, EGR (exhaust gas

recirculation), and fuel emission calibrated 1.8 liter engine, an

approximate brake torque relationship is of the form

T

= q A l F , A /F ) 2 , M ,

M 2 , N

...,N 4 , E G R ) .

The rotational motion of the engine crankshaft is given in

terms of the engine polar moment of inertia, angular accelera-

tion, and the difference between the net torque generated by the

engine and the load torque on the driveshaft. Thus,

J , N = (30 / E) T ,

where the load torque may be the starter-alternator (S/A) load,

clutch torque, air conditioning, power steering, or any driveshaft

load and J , is

engine flywhee l inertia, kg .m ’.

StartedAlternator

The alternator model is empirically derived from data taken at

several voltage, field current, and speed operating points. Using

voltage, field current, and speed as inputs, the alternator current

output is determined by functional relationships. This model rep-

resents a three phase synchronous machine generating full wave

rectified DC current [

161.

The starter portion of the StartedAlter-

nator (S/A) is also empirically derived from data and dynamic

simulation results

[7]

t is depicted by a 1.4 kW ac motor directly

connected to the voltage

bus

and geared to the ICE crank. The

S/A

system is controlled via on/off logic and field current com-

mands to control the S/A torque input (or output) of the device.

For an HEV application, the alternator may be assumet to out-

put 70 amps over a voltage operating range from 200 to 380

Volts. The alternator output current can be represented as a func-

tion of field current, speed, voltage and temperature where the al-

ternator field current is a separate dynamic control component.

The alternator output current approximation at a certain speed

and varying output voltage

is

The field current can be represented as follows:

The inductance and resistance vary with speed, load and interior

alternator temperature.

Here,

I l

is alternator output current, A;

I ,

is alternator field

current, A; Lfld s alternator field inductance, H; R , is alternator

filed resistance, ohms; V is al ternator field voltage,V; V,,, is al-

ternator output voltage,V

mail

s alternator rotational speed, krpm.

Series

HEV

Control

A large ICE powerplant (approximately 60kW or more),

could be employed to directly supply the demand power while

using a scaled down battery for partial load leveling or

as

a direct

power source during high power demand. In such a power source

tradeoff the nature of the performance requirements, limitations

on sensor and control mechanisms, and dynamic control law

structure will likely change. The control objectives with

a

more

powerful ICE/alternator and reduced traction battery system

22 IE E E

Control Systems



34

338

336

334

332

33

328

326

324

1000 \

1

5 I

0

0

5

10 15

Fig. 3. Series pow er

unit

control.

might yield a load leveling or load following strategy [20]. In this

instance, the combined powerplanthattery system would be the

prime vehicle power source used to follow the desired vehicle pro-

file while the battery power supply would be used to mitigate the

traction motor transient demands to the ICE/altemator system.

Simulation results for such a combination are shown in Fig.

3 .

In this simulation, the vehicle driver would like to follow the

the first few active (non-idle) seconds

of

the Federal Urban

Driving Cycle (FUDS). In the transient behavior depicted in

Fig. 3 , the driver’s input goes directly to the Induction Motor

Control IMC) of the traction motor and simultaneously to the

thirottle command of the ICE. Until the ICE/alternator can

achieve alternator “cut-in’’ (i.e., that speed at which there is a

power output from the alternator), the traction motor draws

power from the energy storage device which in this case i s a low

storage (small) battery pack. The combination of components

thus illustrated would require a smaller battery pack and re-

duced ICE by proper sizing and proration of power between the

ICE and energy storage device.

Simulations that include engine, alternator, battery, and trac-

tion motor/driveline sizing and dynamic interactions, could be

used to examine energy tradeoffs and transient tradeoffs by vary-

ing control and sizing (kW output) between an alternator and bat-

tery system as series power sources. For instance, for a small

ICE-alternator-battery power source (about

25

kW), a system

operating strategy could be such that the “Range Extender” RE)

is to be activated during estimated low battery State-of-Charge

(SOC)

and simply operates until a desired SOC [8], [20]has been

achieved. There exists dynamic interaction among the

ICE,

alter-

nator, battery and vehicle traction motor (drivetrain) such that en-

Olctober 1998

23



ified operating strategy. speed and alternator kW errors must be simultaneously con-

trolled by the throttle and alternator field current, with

an

inter-

active control law [21].

Engine speed is the pnma q variable to be controlled by the throt-

tle using

a

modified

Proportional-Integral-Differentd

(PID) type

control.

As

mentioned earlier,conditions for wide open throttle (con-

trol variable saturation) and throttle damping (throttle dashpot) must

beaccommodated. Control nteractionof the kW set point is provided

by a modulation of the throttle voltage command.

A

desireable control objective for

a RE

HEV is to control to

a

commanded engine speed (RPM)-alternator kW trajectory with

minimum speed and A/F transients, to provide idle stability at the

lowest possible engine idle speed, to yield a smooth transition to

and from idle speed set point, and to yield a speed profile that is

impervious to exogenous disturbances suchas changes in electric

vehicle driver demand. This objective may be accomplished with

feedback control

on

the engine throttle and alternator field current.

24 IEEE Control Systems



+

Starter/ Energy

Control Device

Alternator b Starter/ 4 Storage

Alternator

t

Vehicle

Driver

and

Coordinated

Control

Clutch Clutch

Control Mechanism

-

Transmission

Layshaft

Differentiall

Control

Transmission 4 Driveline

Hydraulic

Brake System

Vehicle

Dynamics

and

Tire Road

Interface

Fig.

5.

Automated layshaji transmission vehicle dynamic model.

When altemator field current

is a

control variable, kW error

may be the primary variable to be controlled using perhaps a

modulated

PID

control. The use

of

altemator field current allows

a

rapid variation in alternator kW output at a given altemator

speed with,

of

course, corresponding rapid loading and unload-

ing of the power source (the ICE). Modulation

of

the kW control

can eliminate engine speed transients during altemator loading

and unloading from bus load variations resulting from rapid

changes in vehicle driver demand.

A

simulation result for assumed

RPM

and kW command pro-

files (RPMcom and kWcom) with engine speed

(RPM)

and alterna-

tor kW

as

feedback variables, s shown in Fig.4.Throttle command

to Ihe engine is relatively well behaved resulting in

a

minimization

of A/F

transients, where the extemal

RE

input disturmance is the

traction motor kW demand. In the simulation he battery is initially

at

40

percent State-of-Charge (SOC). Any increase in battery volt-

age:

is due to alternator activation and is especially evident during

motor inactivity (vehicle idle). In

this

instance, the simulation did

not include a regenerative braking system.

An Autom atic Manual Transm ission

Powertrain System


The automated manual layshaft transmission and dry clutch

combination dynamic model, depicted in Fig.

5,

consists of a

driver, ICE engine and controller, starter-alternator and control-

ler, dry clutch and controller, automated manual layshaft trans-

mission and controller, hydraulic brakes, vehicle dynamics, and

tirehoad surface interfaces. In the case of n automatic transmis-

sion powertrain system, the vehicle controller provides the en-

gine throttle commands to the engine controller, and to the

clutch, transmission, and brake system. In particular, the control-

ler provides engine, clutch and transmission control during shift-

ing, or braking. Throttle blade commands from the controller to

the engine may be based on transmission gear, driver accelerator

pedal position, engine speed, shift status, and clutch status.

Engine Controller

The key exogenous control variable to the SI ICE engine sys-

tem is the throttle angle (or mechanical equivalent). Control vari-

ables such

as

spark advance, Exhaust Gas Recirculation

(EGR),

and Air-to-Fuel ratio

( A / F ) ,are

for this current representationcon-

sidered to be precalibrated emission control variables. However,

the engine dynamic model does have provision

for

independent

control of these variables if desired. The throttle control law in-

cludes a variable gain

PI

(proportional plus integral) controller to

provide

a

limited throttle command to the engine, based on com-

mands from the vehicle driver controller. Included

also

in the

throttle

command

control

law

are the

Wide Open

Throttle

W m )

operating logic and an engine Idle Speed Control (ISC) law. The

throttle command is received by a throttle dynamic control mecha-

nism which may contain representations

for

throttle springs, link-

ages, deadband, and throttle motor characteristics if desired.

October

1998

25



Clutch Controller

The description of the clutch dynamic model is contained in

the Driveline Dynamics section. The clutch will be commanded

to disengage if upshifting or downshifting is requested, braking

is commanded, engine speed falls below idle, or no engage clutch

command is present and the clutch is not presently engaged.

Clutch engagement will be commanded when engine speed is

sufficient, the brakes are not commanded,

no

upshift and no

downshift requests exist, the transmission is in gear, and

no

dis-

engage clutch command is present.

The clutch uses friction to transmit torque to the manual

transmission. The clutch plate friction allows the plates to slide

before becoming fully engaged preventing jerking. The condi-

tions for slipping are a function of engine speed, transmission

speed, clutch pressure, clutch wear, clutch temperature, and

drive shaft resonance. When the engine speed is much greater

than the transmission input speed, then slipping is necessary to

allow the clutch friction to load the engine, thus reducing the en-

gine speed to the transmission input speed level so that smooth

engagement can take place. When the engine speed is much

slower than the transmission input speed, clutch slippage allows

engine speed to be increased, via the throttle, while exposing the

engine to a very small load, thus avoiding engine stall. During

engagement, essential negative damping causing “clutch shud-

der”

as

well as halfshaft resonance may be present in a magni-

tude that can be felt by the driver, in which case the modulation of

the clutch pressure

in

a variable slipping state is desirable in or-

der to damp such oscillations. Furthermore, it is possible to mod-

ulate clutch pressure to affect torque transmission during

engagement, as well.

Transmission Controller

The dynamic model of the transmission is described in the

Driveline Dynamics section. The transmission controller deter-

mines when a shift event shall occur and selects the appropriate

transmission gear based on transmission output speed, throttle

angle, current gear and clutch state. The occurrence of a shift

event depends

on

piecewise linear functions, called shift sched-

ules. Separate shift schedules exist for upshifting and downskift-

ing. During braking the clutch is disengaged, the engine is

ramped to idle speed, and the transmission continues to shift al-

lowing the transmission to be in the proper gear when an engage-

ment is requested.

A

shift command and gear change are

not

initiated until the clutch controller initiates a clutch disengage

command and the clutch fully disengages. The transmission gear

shift is emulated by modeling a delay, which represents fork

movement and gear engagement time, based

on

experimental

data. Forces

are

not transmitted to the

drivetrain

when the clutch

is disengaged, thus a delay is a sufficient representation. Once

the shift is complete, the clutch is engaged. The transmission will

then remain in gear

as

long as the shift schedule dictates and the

clutch remains engaged.

Brakes

Hydraulic brake pressure commands are received directly

from the vehicle driver. These brake pressure commands are ap-

plied to the brake hardware and then the resultant braking torque

is applied to the vehicle wheels.

Transmisslor

Engine

Fig. 6 utomated Layshaft Transmission Powertrain.

Driveline Dynamics

The driveline dynamic model includes the rotational dynamics

for an automated manual layshaft transmission and

dry

clutch com-

bination, which accepts engine torque, and delivers orque to the ve-

hicle wheels through the differential and halfshafts. The engine is

connected directly to the differential through the clutch, transmis-

sion,

and a final drive, as a conventionalpowertrain. Rotational dy-

namics and nonlinearities for the engine, clutch, transmission, final

drive and differential are modeled.A simplified diagram, represent-

ing

this

nonlinear dynamic powertrain, is given in Fig.

6.

When engine torque is transmitted, the engine inertia coupled

to the clutch inertia on the engine side is accelerated. The altema-

tor is an additional engine load, and torque from the starter aids

the engine during starting.Three states of the clutch are modeled:

fully engaged, slipping, and disengaged. Constitutive relation-

ships allow seamless transition between differential equations

that represent each of the three clutch states. If the speeds

of

both

clutch plates are not equivalent, then the clutch plate may be slip-

ping or disengaged. The acceleration equation for the engine

crankshaft is:

In

this

constitutive relationship for slipping during clutch en-

gagement, the fi st multiplicative relation characterizes the drive-

shaft stiffness and is a function of the integral of the speed

26

IEE E Control Systems



difference between the two clutch plates. The second bracketed

term characterizes the percentage of torque transmitted through

the clutch due to the speed difference between the plates. The neg-

ative damping imposed by this term can be felt by the driver, when

sufficient slip is not present and the clutch is nearing lockup. The

driveline stiffness and the percentage of torque transmitted

through the clutch are also a function of the clutch friction material

temperature and the clutch wear. The third multiplicative term

f o ,

-

oce, l

s the normalized clutch capacity and shows that

the clutch can be modulated as a function of the halfshaft reso-

naince to enhance stability and driver feel. When the clutch is en-

gaged, the fully engaged conditions areo

o c a :

The constitutive relationship characterization of the clutch in the

fully engaged state includes the driveshaft stiffness and damping

due to the speed difference between the two clutch plates.

Included in the driveline

is

a layshaft transmission which lies

between the clutch and the differential. The synchromesh pre-

vents gears inside the transmission from engaging at different

speeds. Before any forward gear is selected, gear wheels driven

by the engine free-wheel on the transmission shaft. Before gear

engagement the gear and the shaft must be brought to the same

speed and locked together. The synchromesh uses friction to ac-

complish this. The selector fork pushes a collar along the trans-

mission shaft, the collar rotating with the shaft. The collar fits

over a cone on the gear wheel, allowing the gear wheel to speed

up

or slow down until both gear wheel and shaft are moving at the

sarne speed. An outer toothed ring on the collar engages dog

teeth on the cone, locking the collar to the gear wheel. When the

synchromesh is disengaged, the collar and gear wheel are not

connected. The gear wheel rotates with the transmission shaft.

When the synchromesh is engaged the collar makes contact with

the cone and friction between them brings them to the same

speed. The teeth mesh together to lock the gear to the transmis-

sion shaft and allow torque through from the engine.

When the transmission is in gear, assuming 100 mechan-

ical efficiency, rigid gears, and no gearlash or dead band, then

ace,a,g,. Engine torque is transmitted through the trans-

mission:

When the transmission is in gear, but gearlash and or dead band is

present in the transmission:

When the transmission is in gear and no gear lash or dead band is

present:

where

When the transmission is not in gear

Assuming 100 mechanical efficiency, rigid gears, and no

gearlash or dead band, then ag =0 .hen torque is trans-

mitted to the differential:

m

When gearlash and or dead band is present in the final drive

Assuming 100 mechanical efficiency, rigid gears, and no

gearlash and or dead band, then torque is transmitted to the

halfshafts:

October

1998

27



140

7

120:

100:

2 801

> :

60

1

L

i

o ~ ' ' ' ' ' ' ' ' ' ' '

0

10

20

30 40

50

60

0

0 10

20

30

40 50 60

Time sec)

Fig. 7. Wide open throttle data.

1000~

7

6

e

500

400

300

200

1004

~ ' ' ' ' ~

0 10 20 30 40 50

60

Time sec)

,000 l

04

' I

0 10 20 30 40 50 60

Time sec)

Fig.

8.

Wide-open throttle simulation.

28

Test Data and Simulation

Results

An automatic manual layshaft

transmission/dry clutch vehicle

was built. Test data was taken for

model validation for an array of ve-

hicle operating conditions, includ-

ing medium acceleration and Wide

Open Throttle (WOT) on various

grades and road surfaces. For ex-

ample, Figs.

7

and

8

show WOT

test data

and

simulation results on

flat terrain. In this context, WOT

implies maximum driver demand

on

the powertrain system. The test

data plotted is vehicle velocity in

kph, throttle position in counts,

gear, and engine speed in

rpm.

Comparing the test data versus

the simulation, six seconds after

the vehicle begins acceleration it

has attained a speed

of

45

kph with

the test data and

40

kph with the

simulation. Shifting takes place at

about six seconds,

10

seconds,

20

seconds, etc., in both the simula-

tion and the vehicle. The vehicle

speed and gear shifting relation-

ships show close correlation. Gen-

erally, the automatic layshaft

I E E E

Control Systems



--c

Diesel Turbocharged

Fuel Diesel

Control

Driveline

Dynamics

Vehicle

Driver

and

Coordinated

Fig

9. Pre-transmission (motor ahead of transmission) coupled PHEV dynamic model.

*

Clutch Clutch

Control Mechanism

Rotational

Dynamics

Induction Differential Tire/Road

Generator

I

nverter

Motorl

-

Motorl - Transmission

+

Generator

Control

Driveline -+ Interface

*

3-

Transmission

Control

c Energy Storage

Battery

Flywheel

Ultracap

I

Parallel

transmission vehicle test data and simulation results correlate

quite closely. When comparing the test data and simulation,

model parameters are adjusted for one operating condition until

very close correlation exists. The resulting parameter set is fixed

and remains the same for all other simulation and test vehicle op-

erating conditions. The tests were conducted over several differ-

ent road conditions and grades for all comparison studies. The

primary objective of the comparison was to establish a reason-

able dynamic powertrain model upon which hybridization of the

vehicle could take place.

1

PHEV

Component Models

and

Controllers

The model for a PHEV powertrain contains many of the com-

ponents of a conventional thermomechanical system. It also in-

cludes electric vehicle components such as a traction motor and

traction motor controller, as well as a traction energy storage

source suitable for electric only or hybrid vehicle operation. The

PHEV

dynamic model, depicted in Figs. 9 and 10,consists of a

drker, startedalternator, startedaltemator controller, engine, en-

gine controller, a traction motor controller, a traction motor, hy-

draulic and regenerative braking system, a battery, engine clutch

cointroller, engine clutch, motor clutch controller, motor clutch,

transmission controller, transmission, vehicle dynamics, PHEV

coordinated controller, and tire/road surface interfaces. The

coimponents of such a hybrid are discussed subsequently.

Regenerative

Brake System


Power, energy, or torque partitioning between two power

sources is dependent on vehicle objectives and may be based on

bal.tery State Of Charge (SOC), motor speed versus torque limits,

transmission gear, driver accelerator pedal position, engine

speed, average drive wheel power, shift status, engine clutch sta-

tus, estimated engine torque, and estimated engine torque avail-

able. Torque may be partitioned to operate in an engine only

mode, a motor only mode, or a two traction device mode. Addi-

tionally, the motor provides torque during shifting so that torque

disruption to the powertrain is eliminated

[

171. The powertrain

will provide negative torque via the motor during braking for en-

ergy recovery. During periods of low battery SOC, the engine

may be loaded with the alternator to charge the battery.

StartedAlternator Controller

The starter portion of the Starter/Alternator S/A) is empirically

derived from data and dynamic simulation results [141.An ac motor

is directly connected to the voltage bus and geared to the SI ICE

crank. The S/A system is controlled via on/off logic and field current

commands to control the S/A torque input (output) of the device.

Engine, Clutch and Transmission Controllers

The throttle control law includes a variable gain Proportional

plus Integral (PI) controller to provide a limited throttle com-

mand to the engine, based on commands from the

PHEV

coordi-

nated controller. Included in the throttle command control law

are many of the functions discussed earlier such as the Wide

Open Throttle (WOT) operating logic and an engine idle speed

control law.

The coordinated control of the engine, engine clutch, and

transmission for an HEV could be conducted in a manner similar

to the Automatic Layshaft Powertrain

ALP),

especially for the

post transmission configuration shown in Fig. 10. However, the

added complexity of regenerative brake capability could greatly

increase control complexity [

161,

[ 221. For the post transmission

configuration, one relatively simple addition to the autolayshaft

0,ctober

1998 29



Started

Alternator Alternator

Control

Differential/

Layshaft + Driveline

ransmission

Control Transmission

ehicle

Driver

and

Coordinated

t--

Control

1

+

Engine IC Engine

Control

Motor

Clutch

Inverter Induction Motor

Generator Generator Control

Motor1 Motor/ t lutch 4 F

-

ontrol

Engine Engine

Clutch Clutch

Control

I

i

Storage

Regenerative

Brake System

Vehicle

Dynamil

and

Tire

Ro;

lnterfac

Fig.

10.

Post-transmission coupled

PHEV

dynamic model.

control might be to simply open the engine clutch and idle or shut

down the ICE during electric regenerative braking.

InvertedMotor Controller

The traction motor and controller extract power from the bat-

tery, or alternative power source, and provide torque to the

driveline, which in turn provides the EV motive power. Addi-

tionally, the traction motor and controller may be operated

as

a

generator and recover kinetic energy dissipated during braking.

The traction motor and controller then provide power to the en-

ergy storage device, and negative torque to the driveline, which

in turn brakes the vehicle. The coordination of electric and hy-

draulic blending, during braking, is performed by the traction

motor controller to meet the driver brake torque command. The

motor torque command

is

input

to

a torque loop compensator

that controls drivetrain stability.

Brake System Dynamic Model and Control

Dissipation of kinetic energy during braking, by an EV or

HEV, can be recovered by controlling power electronics such

that the electric traction motor behaves as a generator, and re-

turned to the energy storage device for future use

[13],

[14].

A

parallel braking system applies regenerative braking torque to

the driven wheels, in addition to hydraulic braking torque pro-

vided by the foundation braking system. The amount of electric

brake torque that can be added to the hydraulic brake torque is

derived from static brake force relationships, motor torque char-

acteristics, driver feel, and the tire/road surface interface.

The brake hardware model includes dynamics of the hydrau-

lic brake system. Brake pressure commands are received directly

from the PHEV coordinated controller and applied to brake hard-

ware. The resultant brake torque is applied to the wheels.

Driveline Dynamics

The driveline dynamic model includes rotational dynamics

for a PHEV, which accepts engine and motor torque (in a regen-

erative or motoring mode), and delivers torque to the wheels

through a differential and halfshafts. Motor torque is delivered,

via a transaxle, to the differential through

a 4 x 4

coupler con-

nected to

a

halfshaft, and summed with engine torque at the dif-

ferential. The engine is connected directly to the differential

through the clutch, transmission and final drive, as in a conven-

tional powertrain. Rotational dynamics and nonlinearities for the

engine, engine clutch, transmission, final drive, differential,

4

x

4

coupler, motor clutch, motor transaxle, and motor are mod-

eled in

a

manner similar to that discussed earlier. See Fig. 11for

a

simplified diagram representing this nonlinear dynamic PHEV

powertrain.

When motor torque is transmitted, the motor inertia, coupled

to the transaxle inertia, is accelerated. Assuming

100

mechani-

30

I EEE

Control Systems



Motor Transaxle

Assembly

Fig.

11.

Parallel

hybrid

powertrain.

cal efficiency, rigid gears, and

no

gearlash or dead band, then

toirque is transmitted to the motor clutch and

om

wale .

gale:

( J m + Ju/e m m

=

T , a / e g a i e .

When gearlash and or dead band exist in the transaxle then:

Three states of the motor clutch are modeled: disengaged, fully

engaged, and slipping. The motor will be commanded to engage

when the PHEV coordinated controller initiates motor opera-

tion. When the motor clutch is disengaged:

( J a i e c c m

+ J c m ) C i ) a i e = Tale

When torque is applied to the transaxle, torque is transmitted to

the

motor clutch during engagement or slipping:

( J a r 1 e - m + J c m N a i e = L i e

- T m l .

When the motor clutch is slipping or engaged:

f(wa,

- w c m l ) j k w a l e

wcm1 dt

=

L I .

When torque is transmitted through the motor clutch to the 4x4

coupler, assuming

100

mechanical efficiency, rigid gears, and

no gearlash and or dead band:

When gearlash and or dead band is present in the 4x4 coupler:

Assuming

100

mechanical efficiency, rigid gears, and no

gearlash and or dead band, then torque is transmitted to the

hailfshafts and

w f d

= o :

Simulation Results

Typical PHEV simulation results (see Fig.

12) show vehicle velocity (mph), throttle angle

(degrees), engine speed (rpm), gear, drive wheel

average power (kWatts), halfshaft torque (Nm),

engine and motor torque (Nm). The PHEV simu-

lation shows the vehicle accelerating and decel-

erating, highlighting regenerative braking.

When

the

vehicle accelerates from rest in first

gear, the motor provides the necessary torque. As

the vehicle begins to accelerate the throttle angle

and engine speed are at idle. The vehicle operates

in motor only mode until third gear. The motor

also provides torque to the drive wheels during

shifting. During third gear the vehicle

runs

in en-

gine only mode. Application of motor torque can

be seen, in third

ge ,

just after

5

seconds, in or-

der to meet the driver acceleration command,

when the engine is already delivering full torque.

This occurs again in fourth gear just before 10 seconds.

As

the

vehicle decelerates there is

a

downshift, while the clutch is disen-

gaged, and the engine

is

ramped to idle. The motor provides neg-

ative brake torque to the drive wheels slowing the vehicle, while

recovering energy.

Conclusions

This paper describes the mathematical modeling, analysis,

and simulation of

a

dynamic automatic manual layshaft trans-

mission and dry clutch combination powertrain model, and cor-

responding coordinated control laws synthesized using a

conventional SI ICE powerplant-alternator combination, a dry

clutch and manual transmissioddifferential,variable field alter-

nator, brakes, and complete vehicle longitudinal dynamics with

tire-road interface characterization. The conventional power-

train model is validated using experimental test data confirming

accurate emulation of dynamic components of the pre-hybrid-

ized vehicle. In addition, the development of dynamic series and

parallel HEV powertrain models and corresponding coordinated

control laws are described. The HEV models are developed by

modeling the additional traction motor transaxle and gearing. A

discussion of the key issues associated with coordinated control

law development is provided

Simulations of the dynamic behavior of two types of series

HEV's vehicle are shown. Also, simulations depicting the dy-

namic behavior of vehicle test data for an automatic manual

transmission vehicle and simulations of

a

PHEV are shown. The

simulation environment consists of the modular code of Xmath/

Systembuild (ISI) and Matlab/Simulink (Mathworks) with mod-

ifications to the code in order to implant real time stiff integration

methods into the ICE, battery system, traction motor system, and

driveline dynamics. The nominal integration time step (frame-

time) for simulation is on the order of two to ten msec, depending

on

the model version and custom developed real time integration

method employed.

The dynamic model is currently being used to provide the

framework

for

hybrid vehicle control law development, and

for

the

DI

dieseVautomatic manual layshaft transmission vehicles al-

ready being developed in the

U.S.

and Europe. Versions of the

model, including on board computer emulation and communica-

tion

network latencies and delays, are being employed for control

October 1998

31



100

80

60

40

20

ouu

400

200

0

-200

t iear3 I

-400 ’

120

~ _ _ _ _ _ _ _ _ _ _ , - _ _ _ _ _ _ _ _

60

- - - - - - - - - ,

- r - - - - - - - - -

0 5

10 15 20 25 30

Fig.

12.

P ar a l le l hybrid ve h ic le

simulation

and con t r o l .

algorithm code processor implementation and as a foundation for

Hardware-in-the-Loop simulation.

[Z] R.G. Delosh, et al, “Dynamic Computer Simulation of

a

Vehicle with

Electronic Engine Control,” SAE Paper 8 10447, Detroit, Michigan, Febru-

ary 1981.

Acknowledgements

The authors would like to acknowledge technical contribu-

tions to the automated manual layshaft transmission dynamic

model of D. B. Bell, W. J. Weber, Miroslava Jankovic, and N.

Sureshbabu, as well as the technical discussions with our Euro-

pean collegues R. Busch and

C.

Krauss. The authors also ac-

knowledge the efforts of

D.

B. Bell,

J.

R.

Blankenship, and

R. D.

Gilland in test data collection as well as hybrid vehicle consult-

ing from

M.A.

Tamor, W. Buschhaus,

L.

R. Brandenburg,

R.I.

Sims. and B. Bates.

References

[

11K.E. Bailey, and B.K. Powell, “A Hybrid Electric Vehicle Powertrain Dy-

namic M odel,” Proc. America n ContuoZ C onference, Seattle, Washington,

June 1995.

[3]

T.D.

Gillespie, “Fundamentals of Vehicle Dynamics,” SAE Publcatious,

1992.

[4] B. Bates ed ., “Electric and Hybrid Vehicle Technology,” SAE Piihlication

SP-915, February 1992.

[5] B. Bates, “Getting

a

Ford HEV on the Road,”

IEEE Spectrum,

p.22-25,

July 1995.

[6]A.F. Burke, “HybridE lectric Vehicle Design Options and Evaluations,”

Electric

and

Hybrid Vehicle Technology,

B. Bates ed., SAE Publication

SP-915, February 1992.

[7] A. Kalberlah, “Electric Hybrid Drive Systems for Passenger Cars and

Taxis,”

EZectric Vehicle Design

and

Development,

SAE Publication SP-862,

February 1991.

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I E E E

Control

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[SI B.K. Powell, andT.E. Pilutti, “A Range Extend er Hybrid Electric Vehicle

Dynamic Model,”

Proc. 33rd IEEE Con Decision and Control,

Lake Buena

Vista, Fla., December 1994.

[9] B.K. Powell and J.A. Cook, “Nonlinear Low Frequency Phenomen-

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1987

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Con f, vol.

I . .

[

101 T. Matsuo, and T.A. Lipo, “Hyb rid Compu ter Simulatio n of a Field Ori-

ented Induction M otor Drive,” University of Wiscon sin, Madison, WI, July

15,1993;Lipo, T. A., “A Cartisian Vector Approach to Referen ce Frame The-

ory of AC M achines,” Int. Con Electric Mac hines, Lausanne, Switzerland,

Sept. 18, 1984.

[

1

I] P. Kachroo, and M. Tomizuka, “V ehicle Traction Control,” ASME W in-

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[121

K. Asano,

S.

Okada, and

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wam a, “Vibration Suppression of Induction

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tric Vehicles,”Int. J.

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Technological Advances in Vehicle De-

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[

161 K.E. Bailey, and S.R. Cikanek, “Com parison of Energy Recovery C apa-

bility of Electric Vehicle Braking Systems,”

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vanced Vehicle Control, Aachen, Germany, June 1996.

[

171 K.E. Bailey, S.R. Cikanek, and B.K. Powell, “Dyna mic Mode l and Co-

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(EVS-14), Orlando , Fla., Decem ber 16, 1997.

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tral Fuel Injection Engine,” SAE 810494, Detroit Michigan, February 1 981.

[20]

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Barry Powell

received degrees from the University of Michigan in Applied

Mathe matics, Aeronautica l and Astronautical Engine ering, Instrume ntation

Engineering, and Information and C ontrol Theory. He has been a Research

Engine er at Ford Resea rch Laboratory, since October, 1976. Prior to that time

he worked in Ford Automotive Safety Research, Bendix Research Labora-

tories, and Excel lo Corporation Resea rch. His responsibilities have included

mathematical modeling, analysis, simulation and control development of

high performance aircraft, space vehicles, and automotive powerplant and

powertra in systems. He has had responsibility for the technical direction of

real-time simulation and hardware-in-the-loopdevelop ment of advanced en-

gine con trol systems. Mr. Powell is currently involved in the ana lysis, devel-

opme nt and impleme ntation of hybrid electric vehicle dynamic systems.

Kathleen Bailey received

a

BS degree in M athematics from Lawrence Tech-

nologica l University in 1978 and a MSE in Comp uter, Informa tion and Con-

trol Engineerin g from the University of Michigan in 1979. She joined the

Ford Mo tor Company R esearch Laboratory in 1993 and is currently partici-

pating in the development of hybrid vehicle subsystem mathematical mod-

els, synthesis of system dynamic models for various hybrid vehicle

configurations, and dynamic analysis and control system development for

selected hybrid power source vehicles. Prior to that time she worked at

Hughes M issile Systems Group, and General Dynam ics Land Systems Divi-

sion. Her responsibilitie s have includ ed electronic control system optimiza-

tion for missile seeke r systems, senior project engineer on arobotic machine

vision testbed program, and an alysis and development of a model reference

adaptive electronic fuel metering system for automob iles.

Susan Cikanek is employed with Ford Motor Company on the Hybrid Elec-

tric Vehicle program, as a Research Engineer. He r current responsibilities in-

clude dynamic system modeling, control law development, simulation and

testing of conv entional, hybrid, and electric vehicles, as well a s establish-

ment of system and subsystem design requirements a nd architectures. After

receiving a B.S. and M .S. in Electrical Engineering from Wayne State Univer-

sity, Detroit, Michigan, she worked at Eaton Corporation. She modeled, de-

signed, implemented, and tested real-time closed loop control algorithms for

automotive, truck and motor applications applying robust, optimal, adaptive,

digital, classical, and m odern control techniques. In addition, she worked on

electric vehicle induction motor and driveline control applications. She holds

patents on regenerative braking control, and induction motor control for elec-

tric and hybrid vehicle applications.

October

1998

33

hybrid electric vehicle power train

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