New integrated chassis control systems for vehicle ... · New integrated chassis control systems 363 Fig. 1 Schematic of nonlinear vehicle model Fig. 2 Full vehicle model synopsis

Int. J. Dynam. Control (2013) 1:360–384DOI 10.1007/s40435-013-0026-9

New integrated chassis control systems for vehicle handlingperformance enhancement

Ahmed Elmarakbi · Chandrasekaran Rengaraj ·Alan Wheately · Mustafa Elkady

Received: 11 June 2013 / Revised: 19 August 2013 / Accepted: 23 August 2013 / Published online: 6 September 2013© Springer-Verlag Berlin Heidelberg 2013

Abstract This paper investigates the principle of integra-tion of vehicle dynamics control systems by proposing anew control architecture to integrate the following four majorfunctional domains of a vehicle; braking, steering, suspen-sion and driveline. The active control systems include brake-based electronic stability control, active front steering, nor-mal suspension force control and variable torque distribu-tion. Based on the analysis of these four standalone con-trollers, a novel rule based integration strategy is proposedto improve the vehicle handling. A nonlinear vehicle han-dling model is developed for this study in Matlab/Simulink.This model contains a sprung mass of six degrees of free-dom that includes, longitudinal, lateral, yaw, roll, pitch andbounce and un-sprung masses with wheels at each corner ofthe vehicle. The simulation results show that this integrationstrategy enhances the vehicle handling stability in terms ofreduction in vehicle yaw rate and side-slip angle that wouldnot be attained in standalone manner.

Keywords Integrated control system · Vehicle dynamics ·Performance · Handling · Numerical simulations

List of symbols

a Longitudinal distance of CG from front axleax Longitudinal acceleration at CGay Lateral acceleration at CGb Longitudinal distance of CG from rear axlec Tyre cornering stiffness

A. Elmarakbi (B)· C. Rengaraj · A. Wheately · M. ElkadyDepartment of Computing, Engineering and Technology, Faculty ofApplied Sciences, University of Sunderland, Sunderland SR6 0DD, UKe-mail: [email protected]

B,C, D, E Pacejka tyre parametersFn Tyre normal forceFsi j Suspension forceFs Suspension vertical forceFt Tyre vertical forceFxi j Longitudinal tyre forceFxss Longitudinal steady state tyre forceFyi j Lateral tyre forceFyss Lateral steady state tyre forceg Gravitational constanthcg Height of centre of gravity from groundi Stands for front/rear ( f, r )Iw Wheel rotational inertiaIxx Sprung mass roll moment of inertia at CG of

vehicleIyy Sprung mass pitch moment of inertia at CG of

vehicleIzz Sprung mass yaw moment of inertia at CG of

vehiclej Stands for left/right (l, r )Kb Brake gain of the brake systemKus Under steering gradientL Wheel basel f Distance of vehicle CG from front axleL Fx Longitudinal tyre force lagL Fy Lateral tyre force laglr Distance of vehicle CG from rear axleMs Sprung-mass of vehiclemusi j Vehicle unsprung massMv Mass of total vehicleMzc Desired corrective yaw momentPbi j Brake pressureRw Dynamic tyre radiust Track width of vehicleT Drive torque on wheels

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New integrated chassis control systems 361

t f Vehicle front track widthtr Vehicle rear track widthVch Characteristic speedVx Sprung mass longitudinal velocity at CGVx Derivative of longitudinal velocityVy Sprung mass lateral velocity at CGVy Derivative of lateral velocityVz Sprung mass vertical velocity at CGVz Derivative of vertical velocityZs Sprung mass vertical displacementZs Sprung mass vertical velocityZus Unsprung mass vertical displacementZus Unsprung mass vertical velocityα Tyre lateral slip angleβ Side-slip angleδ Steering angle at the front wheelsθ Vehicle pitch angle at CGθ Vehicle pitch rate at CGθ Derivative of vehicle pitch velocityλ Tyre longitudinal slip ratioμ Coefficient of frictionφ Vehicle roll angle at CGφ Vehicle roll rate at CGφ Derivative of vehicle roll velocityψ Vehicle yaw angle at CGψ Vehicle yaw rate at CGψre f Reference yaw rateψ Derivative of vehicle yaw velocityω Angular wheel velocity

1 Introduction

Today’s modern vehicles include more than 40 actively con-trolled systems that play a major role in vehicle directionalstability, ride comfort and safety. Several significant con-trol systems, such as anti-lock braking systems (ABS) [1–3], active suspension systems [4], traction control systems,Active yaw control and so forth, are being popularly usedin automobile industries. Many theories and design meth-ods for active yaw control, anti-lock braking systems andactive suspension systems have been proposed individuallyby several literatures for decades. Various researchers haveconsidered a slip-ratio control of anti-lock braking systemsin the use of sliding mode control schemes [3]. As to thedesign of active suspensions, the improvement of ride com-fort is the major objective to be emphasized. A novel non-linear back-stepping design [4,5] has been developed for aquarter-car active suspension system which aims to improvethe trade-off between the ride quality of passenger comfortand the utilization of suspension travel. For further improv-ing vehicle handling and stability, yaw moment control hasbeen studied and developed by controlling braking force

distribution of four wheels as a strategy for driver supportsystems.

At present these systems generally work independentlybut it is widely accepted that integration of these stand-alone systems will lead to improved vehicle dynamic per-formance [6]. Additional benefits include cost and weightreductions and reduced sensor requirements. Both the auto-motive industry and the end users will benefit directly fromthis research. However, successful integration of such con-trol systems is still largely in the research phase. Previousstudies have identified that these systems were originallydeveloped independently to perform specific tasks and somesystems do co-exist, Junjie et al. [7], Karbalei et al. [8], andKazuya and Peng [9]. Researchers have succeeded in thesuccessful integration of several systems, March and Shim[10]; however, potential conflicts are still a problem. Com-plete integration of many sub-systems is still a real technicalchallenge.

The overall aim of this paper is to develop new controlstrategies/algorithms to enable a successful integration ofa subset of vehicle control systems. However, this paperfocuses primarily on the methods of improving vehicle sta-bility and emergency handling through the integration of fourspecific vehicle control systems: active front steering (AFS),normal suspension force control (NFC), brake-based elec-tronic stability control (ESC) and driveline based variabletorque distribution (VTD) system.

There are many ways to compare the performanceimprovement obtained by an integrated chassis controlleragainst its standalone counterpart. Few of the techniquesinclude comparing the reduction in energy consumption,reduced cost, less/modular parts, improvement in perfor-mance variable etc. In this paper, the improved perfor-mance objectives established from using the integrated chas-sis control approach are defined as a reduction in yawrate and vehicle side-slip angle that lead to better handlingcapabilities.

The rest of the paper is organized as follows. In the vehi-cle modelling section, a detailed passive vehicle dynamicsmodel with nonlinear tyres suitable for combined slip andtransient conditions is developed in Matlab/Simulink envi-ronment along with the dynamics of steering, braking, sus-pension and driveline systems. In the standalone control sys-tems section, the development of standalone control systemmodels of AFS, active suspension, a brake based ESC anda VTD system are discussed. Various possible integratedcontrol strategies amongst those systems in considerationare analyzed and investigated in the integrated control sys-tem section. This section also explains a new integratedchassis control (ICC) strategy developed from the resultsof the analysis and implemented in MATLAB/Simulink.Finally the conclusions based on the new ICC strategy areillustrated.

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362 A. Elmarakbi et al.

2 Vehicle modelling

The body of the vehicle model used in this paper is assumedto be rigid and has six degrees of freedom (DoF, three trans-lational and three rotational). The vehicle axis co-ordinatesystem used is assumed to be fixed at the CG of the vehiclebody. The vehicle’s equations of motion are derived with ref-erence to both the vehicle and inertial co-ordinate systems.It is assumed that a suspension unit is attached at each cor-ner of the vehicle with linear spring and damper elements.The dynamics of un-sprung mass and tyre at each corner arealso included in this model. As full vehicle modelling is nota simple task and it involves many subsystems and couplednonlinear system dynamics, certain modelling assumptionsare made and the same are explained here.

• The self-aligning moments of the tyre is neglected as theydo not disturb the vehicle dynamics by bringing back thesteering wheel to the initial position.

• The kinematics effects due to suspension geometry areneglected. So the suspensions only provide vertical forceto the chassis.

• The gyroscopic effects of the sprung mass are neglected.The only external forces acting on the vehicle is assumedto the longitudinal, lateral and vertical forces generatedby the tyres.

• The tyre cambering is considered in tyre modelling.• The vehicle chassis plane is considered parallel to the

ground.• The aero dynamical and wheel friction effects are

neglected as in this work study of those effects is notof great interest.

• The effects due to the toe-in and toe-out of the tyres areneglected.

A schematic view of the nonlinear vehicle model used isshown in Fig. 1.

The kinematics equations are mainly due to the vehiclegeometry. Each corner of the vehicle is identified with i, jindex where i = { f, r} stands for front/rear and j = {l, r}stands for left/right. The displacements of the sprung masson chassis corners are described by

Zs f j = Zs − l f sin(θ)± t f sin(φ)

Zsr j = Zs + l f sin(θ)± tr sin(φ), (1)

where Zs is the sprung mass vertical displacement, φ andθ are the roll and pitch angle of the chassis respectively,l f , lr , t f , tr stands for the vehicle geometry. where l f andlr are the distances of vehicle CG from front and rear axle,respectively, and t f and tr are the vehicle front and rear trackwidth, respectively.

The full vehicle model is defined by the following non-linear dynamical equations.

Vx ={∑

Fxi j

Mv

}− Vyψ + Vz θ , (2)

where∑Fxi j = (Fx f r + Fx f l) cos(δ)+ Fxrr

+Fxrl − (Fy f r + Fy f l) sin(δ) (3)

Vy ={∑

Fyi j

Mv

}+ Vx ψ − Vzφ, (4)

where∑Fyi j = (Fy f r + Fy f l) cos(δ)+ Fyrr

+Fyrl + (Fx f r + Fx f l) sin(δ) (5)

Zs ={∑

Fsi j

Ms

}+ Vx θ − Vy φ, (6)

where

∑Fsi j = Fs f l + Fs f r + Fsrl + Fsrr (7)

Zusi j =(−Fszi j + Ftzi j

)Musi j

(8)

θ ={(Fsrl + Fsrr ) lr − (

Fs f l + Fs f r)

l f − Mshcgax + (Izz − Ixx )ψφ}

Iyy(9)

φ ={(

Fs f l + Fsrl)

t f − (Fs f r + Fsrr

)t f − Mshcgay + (Iyy − Izz)ψ θ

}Ixx

(10)

ψ ={∑

Fmz + (Ixx − Iyy)φθ}

Izz, (11)

where∑Fmz =

∑Fy f j cos(δ)l f −

∑Fyr j lr

+∑

Fx f j cos(δ)t f −∑

Fxr j tr . (12)

The forces are given by the following equations,Tyres [6]:⎧⎨

⎩Ftxi j = Ftx

(μi j , λi j , Fni j

)Ftyi j = Fty

(μi j , αi j , Fni j

)Ftzi j = Ftz (Zus − Zr )

. (13)

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Fig. 1 Schematic of nonlinearvehicle model

Fig. 2 Full vehicle modelsynopsis

Suspensions:

Fszi j = Fsz(Zsi j − Zusi j

). (14)

The normal force on each tyre is calculated based on thefollowing equation

Fnzi j = Fns_i j + Ftzi j , (15)

where Fns_i j is the static load acting on the i j th tyre.A synopsis of data flow takes place amongst various

vehicle subsystems in this model is given in Fig. 2. Thevehicle model is divided into sub-models that describethe wheel, brake, suspension and steering dynamics.

The dynamics of the tyre–road interaction are depen-dent on the lateral and longitudinal tyre slips. The lat-eral tyre slip angles for each wheel can be calculatedas follows:

αi = tan−1

(Vy + aψ

Vx ∓ t2 ψ

)−δ; α j = tan−1

(Vy − bψ

Vx ∓ t2 ψ

).

(16)

The component of the vehicle velocity of the wheel cen-ter that is parallel to the wheel vertical plane is givenas

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Vi = cos(αi )

√(Vx ∓ t

2ψ

)2

+ (Vy + aψ

)2

Vj = cos(α j )

√(Vx ∓ t

2ψ

)2

+ (Vy − bψ

)2. (17)

The longitudinal wheel slip is defined as

λi j ={

Rwωi −VxiRwωi

(driving)Vxi −Rwωi

Vxi(braking)

. (18)

Capturing the tyre behavior is probably the most difficultand important problem to tackle while building a vehiclemodel as realistically as possible. In the past, a lot of dif-ferent models have been created to solve this problem. Themost realistic models are the most complicated but probablythey are not useful in every kind of research. On account ofour objectives, a too simple model is not applicable becauseit can provide correct results only if the slip angles are verysmall, but it cannot represent for example the forces the tyrestransfer during an emergency handling maneuver. For thisreason a semi-empirical model usually called “Magic for-mula” suggested by Pacejka [11] is chosen. For simplifica-tion, the camber has been set to zero in the current vehiclemodel. The general equation of the tyre model is as follows:

y(x)= D sin[C tan−1

(Bx−E

(Bx−tan−1(Bx)

))], (19)

where y(x) is Fx and Fy , respectively, if x is λor α.The tyre forces generated using the above equations in lon-

gitudinal and lateral directions are a function of pure slips intheir respective directions. But in reality, these tyre forcesare generated as a function of combined slip that exists dur-ing typical combined braking and cornering situations suchas braking before entering a corner and accelerating beforeexiting it. Weighting functions G as described in [12] areintroduced which when multiplied with the original pure slipfunctions produce the interactive effects of longitudinal slipon Fy and lateral slip on Fx . The cosine version of the magicformula is used to represent the hill shaped weighting func-tion G:

G = D cos[C tan−1(Bx)

]. (20)

The combined side force is described by the following for-mulae:

Fy = G yk · Fyo + SV yk, (21)

where SV yk, the effect due to ply-steer is assumed in thispaper to be zero to reduce the complexity. The function G yk

is used as described in [13]. The combined side force isdescribed by the following formulae:

Fx = Gxα · Fxo, (22)

where G yk and Gxα are described as follows

G yk = cos[Cyk tan−1(BykkS)

]cos

[Cyk tan−1(Byk SH yk)

] and

G yk = cos[Cxα tan−1(Bxα(α + SH xα)

]cos

[Cxα tan−1(BxαSH xα)

] . (23)

A detailed description of these weighing functions can befound in [14]. Figure 3 shows the longitudinal and lateral tyreforces in combined braking and cornering conditions used inthis paper obtained using the above mentioned equations.The effect of tyre force lag [13] is also taken into accountaccording to the following equations.

L FxVx

d(Fx )dt + Fx = Fxss

L FyVy

d(Fy)

dt + Fy = Fyss

}. (24)

The equation of motion for each wheel in the wheel dynamicsmodel is defined as

Iwωi j = Ti j − Fxi j Rw. (25)

The steering system modelled in this work has a hydraulicpower steering mechanism. The input for the steering systemis the angle of the steering wheel and steering column, whilethe output is the position of the rack, which determines theangle of the front wheels. There is a mechanical connectionbetween the rack and the steering column with a pinion gear,which converts the rotational motion of the steering columnto translational motion of the rack to turn the wheels.

The power assistance is provided by a hydraulic pistonattached to the rack. A torsion valve determines which sideof the piston receives pressurized hydraulic fluid. This tor-sion valve is attached to the steering column. The differencebetween the angular position of the steering wheel and theangular position of the pinion determines the fractional open-ing of the torsion valve. If the angular difference is positive,the pressure is applied to one side of the piston, and if theangular difference is negative, the pressure is applied to theother side of the piston. The power assistance continues untilthe difference between the steering wheel position and pin-ion position is approximately zero. The steering power assistcurve is shown in Fig. 4.

The hydraulic brake system considered in this study isbuilt upon a standard braking model. The standard passivebrake system considered for this study consists of a mechan-ical brake pedal, a servo brake booster, a master cylinder,a hydraulic brake caliper and the friction pad. The brakemechanics considered here are explained as follows. Themechanical brake input is amplified by the servo booster.This is further amplified and converted to a hydraulic pressurecalled line pressure/supply pressure, which is fed through the

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Fig. 3 Tyre forces in combinedslip-friction ellipse

brake lines. The line pressure is further amplified and con-verted to mechanical actuation at the brake calipers. Thisforce moves the friction pads against the rotating wheel disc.The effect of pipe friction is taken into account in line with thereal world brake dynamics. The resulting brake system model

assumes non-laminar flow through restriction as described inthe following equation by Fletcher et al. [14]

Q = Cd A

√2(P1 − P2)

ρ. (26)

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Fig. 4 Hydraulic steering power assist curve

Figure 5 shows a schematic [6] of the hydraulic braking sys-tem used in the simulation.

3 Development of control systems

3.1 Electronic stability control (ESC)

ESC is used to stabilize a vehicle by generating an externalyaw moment. The three strategies to perform this are differ-

ential braking, active steering and differential drive torquedistribution. In this section of the paper, the differential brak-ing, a brake (ABS) based ESC strategy is used. First a fuzzylogic ABS controller is developed and simulated for its per-formance. Then the ABS controller is extended to developan ESC controller by additional sensor inputs, like steeringangle, yaw rate and sideslip angle and supplemented withan ESC controller algorithm that is capable of enhancing thevehicle stability.

The control architecture as shown in Fig. 6, is designed tobe a hierarchical, two layer control [15]. The upper controllerhas the desired objective of ensuring yaw stability controland assumes that it can command any desired value of yawtorque. The lower controller ensures that the desired valueof yaw torque commanded by the upper controller is indeedobtained from the differential braking system based on ABS.The lower controller utilizes the wheel rotational dynamicsand controls the braking pressure at each of the four wheelsto provide the desired yaw torque for the vehicle. Figure 7shows one of the control surfaces used to develop the fuzzylogic ESC controller.

The ESC controller used in this paper is developed basedon the model reference control technique where the desiredvehicle states are generated from a linear 2 DoF referencemodel (a standard 2 DoF bicycle model with linear tyres).As a function of the vehicle parameters, vehicle longitudi-nal speed and the steering input, the reference model gen-

Fig. 5 Schematic of thehydraulic brake system Restriction Braking

Torque, Tb

Average DiskRadius, Rd

Displacement, x1

Force, F

QPressureP1

PressureP2

Displacement, x2

Wheel Axle CL

Fig. 6 Schematic of ESC

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Fig. 7 Control surface of ESC fuzzy controller

erates the desired vehicle state trajectories to be tracked bythe actual vehicle. The desired yaw rate can be expressed asshown in the following equation:

ψre f = Vx

L

(1 + V 2

xV 2

ch

)δ f , (27)

where ψre f is the reference yaw rate, Vch is the characteris-tic speed, L is the wheel base, δ f is the front wheel steeringangle, and Vx is the longitudinal speed. The characteristicspeed Vch in the previous equation can be calculated as fol-lows:

Vch =√

gL

Kus, (28)

where Kus is the under steering gradient which is a functionof the vehicle parameters

Kus = mg

L

(l f

cr− lr

c f

), (29)

where c f and cr are the tyre cornering stiffness of the lineartyre model. The calculated desired yaw rate from the aboveequation is valid only on dry roads with high surface coeffi-cient of friction. The maximum desired yaw rate developedis limited by the surface coefficient of friction. As the sur-face coefficient decreases the desired yaw rate also decreases.The lateral acceleration is a function yaw rate and the vehiclelongitudinal velocity

ay = ψxVx . (30)

The maximum lateral acceleration developed by a vehiclecannot exceed the surface coefficient of friction

∣∣ay∣∣ ≤ μg.

Taking this into consideration extends the validity of thedesired yaw rate calculation. So the maximum desired yawrate is limited by the following condition:

ψlimit ≤ ±μ g

Vx. (31)

The same logic is implemented in the desired yaw rate cal-culation block as follows:

ψdes ={ψdes, if |ψdes | < μg

VxμgVx

sign(ψdes), if |ψdes | ≥ μgVx

. (32)

The calculation of desired side-slip βdes angle is madesimpler by assuming it to be zero, i.e. βdes = 0, as driving thevehicle side-slip angle to the minimum increases the vehiclestability. Next, the calculation of the actual vehicle states iscarried out. In order to do that, the same steering input δ f

used to calculate the desired state values is also given to thenonlinear vehicle model which generates the actual vehiclestates. Then the desired and the actual values of yaw rateand side-slip angle are compared and the errors are used togenerate the desired corrective yaw moment.

The fuzzy ESC controller has two inputs, the yaw rateerror and side slip angle error and one output the normaliseddesired corrective yaw moment. This fuzzy controller has anoutput scaling block which converts ESC controller outputto the desired corrective yaw moment. Then the longitudinalbrake force required to develop the desired corrective yawmoment is calculated from the kinematics of the brake–tyreforce transmission system.

Fxi j = 2Mzc

ti, (33)

where, ti is the track width of the vehicle, Mzc is the desiredcorrective yaw moment. Then the brake pressure required togenerate this brake force is calculated as a function of thebrake system parameter.

Pbi j = Fxi j rwKb

, (34)

where rw is the radius of the wheel, Kb is the brake gain ofthe brake system and Pbi j is the brake pressure. Finally, theallocation of this desired brake pressure on a particular wheelis determined at the lower layer of the ESC controller. Thiscontrol pressure allocation strategy is based on the directionof steering input (left or right) and the sign of the yaw rateerror (under-steer or over-steer).

3.2 Active front steering (AFS)

The AFS improves the vehicle dynamics in the lateral direc-tion by extending the linear handling region experienced bythe driver in a passive vehicle. In a typical vehicle activesteering system, the steering angle at the tyre is set in part bythe driver through the vehicle classical steering mechanismwhile an additional steering angle can be set by the AFS con-troller using hydraulic or DC motor actuators combined witha differential mechanical device.

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Fig. 8 Schematic of AFS

Fig. 9 Control surface of AFS fuzzy controller

The AFS controller used in this paper is a yaw rate errorand side slip angle error based fuzzy logic steering controller.The schematic of the AFS control strategy followed in thisstudy described in Fig. 8. The aim of the AFS controller isto minimise the yaw rate and side slip error by modulatingthe front wheel steer angle, using model reference controltechnique. The AFS controller receives two inputs the yawrate and side slip angle errors and provides one output thenormalised corrective steering angle. Then an output scalingoperation is carried out to convert the normalised steeringangle to the required corrective steering angle.

Two commonly used control strategies, PID and fuzzylogic, are used in the development of standalone steering con-troller in this paper. The vehicle yaw rate and side-slip angleerrors (which are the functions of their nominal and actualvalues respectively) and their time derivatives are fed to theAFS controller to determine the controlled steer addition.Figure 9 shows one of the control surfaces used to developthe fuzzy logic steering controller. Results of earlier researchliterature in this field are validated here and confirm that per-formance of AFS is limited within the linear vehicle handlingregion, i.e., low to medium lateral acceleration range.

3.3 Variable drive torque (VTD)

Another important way to stabilize a vehicle is active drivetorque control. One of the recent and widely applied activedriveline control techniques is variable drive torque distribu-tion [16]. The objective of this control strategy is to increasevehicle stability and handling capability by suitably distrib-uting the drive torque between wheels. Different drive torqueon left and right wheels yield a yaw moment about the vehi-cle’s vertical axis and can be used to stabilize the yaw motion.

The control architecture of the VTD system is hierarchicalas used in the ESC controller development in this paper. Theupper controller has the objective of ensuring yaw stabilitycontrol and assumes that it can command any desired valueof yaw moment within the capability of the driveline sys-tem. The measurement from the wheel speed sensors, yawrate sensor, an estimation of the vehicle side-slip angle and asteering angle sensor are used. A fuzzy logic control strategyuses these measurements and computes the desired value ofthe corrective yaw moment. The lower controller ensures thatthe desired value of yaw torque commanded by the upper con-troller is indeed obtained from the torque management sys-tem. The lower controller uses the driveline dynamics andcontrols the biasing of the drive torque management sys-tem to provide the desired yaw torque for the vehicle. A PIcontroller strategy is followed in this case and developed inMatlab/Simulink. The PI controller takes the yaw rate andside-slip angle errors as inputs and returns a control valuebetween 0 and 1 giving the ratio of the drive torque transmit-ted to the left and right wheels. The control architecture ofVTD used in this paper is shown in Fig. 10.

3.4 Active suspension normal force control (NFC)

Active suspension in this paper is another active vehicle con-trol system that minimizes the longitudinal and lateral loadtransfer between the wheels. The NFC model used in thisresearch has hydraulic actuators at each wheel as shown inFig. 11 that either add or subtract an extra force on each

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Fig. 10 Schematic of VTDcontrol

ksbs

Fa

Xs

Xu

Xrkt

mus

Fig. 11 Quarter car suspension model

wheels and designed to optimize the normal forces on wheelsbased on signals from the active suspension controller as afunction of various vehicle dynamic states. It ensures thetracking of the desired suspension force using PID and fuzzylogic control strategies. Considerable literature can be foundon the dynamics and control of hydraulic actuators for activeautomotive suspensions.

The hydraulic actuator dynamics used in this paperincludes the dynamics of a spool valve controlled hydraulicactuator model explained by Rajamani and Hedrick [13]. Theschematic of the active suspension control strategy followedis described in Fig. 12 and few of the control surfaces usedto develop the fuzzy logic suspension controller are shownin Fig. 13.

For the purpose of this paper, the suspension control strat-egy used has the following objectives:

• To add the required amount of active suspension forcesat the individual wheel corners to reduce the vehicle yawrate and side-slip angle.

• To reduce or maintain roll angle compared to a passivevehicle.

The NFC controller strategy used in this paper is a yawrate and side slip angle errors based fuzzy logic normal forcecontroller. The main aim of the NFC controller is to min-imise the yaw rate and side slip angle error by modulatingthe front tyre normal forces, using fuzzy feedback controlstrategy. The NFC controller receives two inputs the yawrate and side slip angle errors and provides two outputs thenormalised active suspension control force. Then an outputscaling operation is carried out to convert the normalisedactive suspension control forces to the required correctivesuspension normal forces.

4 Analysis of standalone systems

The active chassis control systems can be classified as stand-alone systems if each system has its own sensor(s), con-troller and actuator(s) modules. The standalone systems do

Fig. 12 Schematic of activesuspension (NFC) system

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Fig. 13 Control surface of NFC fuzzy controller

not interact with each other in terms of resources and infor-mation sharing. And they also individually try to achieve theirown control objective(s) without taking into account whetherit affects the control objective(s) of other active systems ornot.

The section to analyse the standalone control systems isdivided into four subsections one for each active chassis sys-tem in consideration. The overall aim of all these systems isto improve the vehicle stability by reducing the yaw rate andside slip angle, but they achieve it through different meth-ods, such as controlling the distribution of braking, driving,steering and suspension forces. Studying and analysing theability of each of these four systems in developing their con-trol outputs will highlight their individual control authorityin improving vehicle handling.

4.1 Electronic stability control

Results of the earlier research show that the brake based ESCare more effective in a wide lateral acceleration (latac) rangeis validated through simulations. The control authority ofelectronic stability control system are analysed by runningthe vehicle model on dry, wet and icy road conditions at 0.2gand 0.3g for the low latac, 0.4g, 0.5g and 0.6g for the mediumlatac and at 0.7g and 0.8g for the high latac operating ranges,respectively. The control authority of ESC at the handlinglimits is also investigated. From the simulation results, asshown in Figs. 14 and 15, it can be seen that ESC improvesthe vehicle handling by reducing the peak yaw rate by 12 %at 0.2g and by 9 % at 0.3g latac on a dry road. Similarly, a23 % reduction in the peak slip angle is obtained at 0.2g and a

Fig. 14 Intrusive nature ofESC on longitudinal dynamicsin low latac

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Fig. 15 Control authority ofESC during low latac

20 % reduction at 0.3g. One important observation due to theactivation of ESC controller is that it reduced the longitudinalvehicle speed by 1.4 % at 0.2g and by 2.0 % at 0.3g latac. Thishighlights the intrusive nature of this control system in thelongitudinal dynamics of the vehicle. This is generally not apreferable characteristic from a vehicle in driver’s point ofview, especially in the low lateral acceleration range whichis not a safety critical operating range.

In the medium latac range, the ESC improves the vehiclehandling by reducing the peak yaw rate by 12 % at 0.4g, by10 % at 0.5g and by 6 % at 0.6g latac on a dry road. Similarlya 22 % reduction in the peak slip angle is obtained at 0.4g,21 % at 0.5g and a 20 % reduction at 0.6g. And it is observedthat the activation of ESC controller reduces the longitudinalvehicle speed by 2.5 % at 0.4g, 2.95 % at 0.5g and by 3.2 %at 0.6g latac. This is again not a preferable characteristicfrom a vehicle in driver’s point of view in the medium lateralacceleration range which is not a safety critical operatingrange.

In the high latac range ESC improves the vehicle han-dling by reducing the peak yaw rate by 12 % at 0.7g and by9.6 % at 0.8g latac on a dry road. Similarly a 23 % reductionin the peak slip angle is obtained at 0.7g and a 27 % reduc-tion at 0.8g. One important observation due to the activationof ESC controller is that it reduced the longitudinal vehi-cle speed by 1.4 % at 0.7g and by 2.9 % at 0.8g latac. Thishighlights the intrusive nature of this control system in thelongitudinal dynamics of the vehicle. This is generally not a

preferable characteristic from a vehicle in driver’s point ofview, especially in the low lateral acceleration range whichis not a safety critical operating range.

4.2 Active front steering

The control authority of AFS system are analysed by runningthe vehicle model on dry, wet and icy roads at 0.2g and 0.3gfor the low lateral acceleration (latac), 0.4g, 0.5g and 0.6gfor the medium latac and at 0.7g and 0.8g for the high latacoperating ranges respectively. The control authority of AFS atthe handling limits is also investigated. From the simulationresults, as shown in Figs. 16 and 17, it can be seen that AFSimproves the vehicle handling by reducing the peak yaw rateby 14 % at 0.2g and by 8 % at 0.3g latac on a dry road.

Similarly, a 17 % reduction in the peak slip angle isobtained at 0.2g and a 15 % reduction at 0.3g. Similarly, inthe medium latac range, the AFS improves the vehicle han-dling by reducing the peak yaw rate by 17 % at 0.4g, by 10 %at 0.5g and by 7 % at 0.6g latac on a dry road. Similarly a17 % reduction in the peak slip angle is obtained at 0.4g,20 % at 0.5g and a 20 % reduction at 0.6g. Again the AFSdoes not affect the longitudinal vehicle speed at the end of themanoeuvre and the longitudinal vehicle speed is at par withthe passive vehicle at 0.4g and better by 0.5 % at 0.5g. Thishighlights the non-intrusive nature of this control system inthe longitudinal dynamics of the vehicle in the medium latacrange as well.

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Fig. 16 Control authority ofAFS at 0.2g on dry roadconditions

Fig. 17 Influence of AFS onlongitudinal dynamics at 0.2g

In the high latac range AFS improves the vehicle handlingby reducing the peak yaw rate by 4 % at 0.7g and by 4 % at0.8g latac on a dry road. Similarly an 18 % reduction in thepeak slip angle is obtained at 0.7g and a 25 % reduction at0.8g. Again the AFS does not affect the longitudinal vehi-

cle speed at the end of the manoeuvre and the longitudinalvehicle speed is better by 0.8 % at 0.7g and by 1.8 % at 0.8g.This highlights the non-intrusive nature of this control sys-tem in the longitudinal dynamics of the vehicle in the highlatac range.

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4.3 Variable drive torque distribution

The control authority of VTD system are analysed by run-ning the vehicle model on dry, wet and icy roads at the low,medium and the high latac operating ranges respectively. Thecontrol authority of VTD at the handling limits is also inves-tigated. From the simulation results, as shown in Figs. 18, 19and 20, it can be seen that VTD improves the vehicle han-dling by reducing the peak yaw rate by 12 % and the peakslip angle by 28 % in the low latac region on a dry road. In themedium latac range, the VTD improves the vehicle stabilityby reducing the peak yaw rate by 11 % and the peak slip angleby 20 %. A 6 % peak yaw rate improvement and 37 % peakside slip angle improvement is obtained with VTD against apassive vehicle.

One important observation due to the activation of VTDcontroller is that, due to addition of driving torque at thewheels to improve yaw rate tracking and stability the reduc-tion in the exit speed is less compared to the ESC and AFSvehicles. And the reduction in the exit speed at high latacregion is much more pronounced than at the low and mediumlatac region, but still much better than the passive vehicle.Unlike the brake based ESC system, VTD does not intrudewith the vehicle’s longitudinal dynamics. This is a much morepreferable characteristic from a driver’s point of view, espe-cially in the low lateral acceleration range which is not asafety critical operating range.

4.4 Active suspension

The control authority of suspension NFC system on vehi-cle handling are analysed by running the vehicle model ondry, wet and icy roads at the low, medium and the high latacoperating ranges respectively. From the simulation results,as shown in Figs. 21, 22 and 23, it can be seen that whenNFC is activated in the low latac region it does improve thevehicle handling by reducing the peak yaw rate and the peakslip angle but the improvement is negligible. This is becausethe lateral load transfer between the outer and inner wheelsis not very large during low latac. And also the control strat-egy optimises the addition of suspension normal force as afunction of the vehicle roll angle which is reduced by thecontroller. But we can observe an improvement in this trendwith more reduction in the peak yaw rate and the peak sideslip angle as the vehicle moves into the medium latac zone.

The superiority of the active system continues in the highlatac range as well but with a diminishing effect on the con-trol authority. In all the three latac regions a good roll controlis obtained except at the limits. The main reason for thisbehaviour of the NFC system is that, at low latac, the tyreis operating at its linear region and hence producing lateralforce as a function of the slip angle and the normal wheel load.Being operated at the same slip angle, between passive andactive vehicles with little effect on lateral load transfer reduc-tion by NFC system, the output lateral tyre force produced

Fig. 18 Control authority ofVTD at low latac

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Fig. 19 Control authority ofVTD at medium latac

Fig. 20 Control authority ofVTD at high latac

by the active system provides a negligible improvement inthe reduction of yaw rate and slip angle. But at the mediumlatac zone, supported with a more reduction in lateral loadtransfer the NFC system produces better handling comparedto a passive vehicle.

Again, at the high latac, the trend continues but with areduced efficiency due to the addition of more active sus-pension normal force results in a tyre normal load instabilitythat affects the effective generation lateral and longitudinalforces. This limits the extent / capacity of the normal suspen-

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Fig. 21 Control authority ofNFC at low latac

Fig. 22 Control authority ofNFC at medium latac

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Fig. 23 Control authority ofNFC at high latac

Fig. 24 Schematic of AFS +ESC standalone controller

sion force actuator. So it is evident that the NFC does havethe capability to improve the vehicle stability at the mediumlatac but its control authority is limited and diminished at lowand high latacs respectively. At the limits, the NFC ceases todisplay any ability to improve the vehicle handling than thepassive vehicle.

5 Integrated control systems

5.1 Rule based integrated control strategy

Hence, in order to avoid undesirable interactions betweencontrol subsystems and reduce performance trade-offs in

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Fig. 25 Low latac performanceof AFS + ESC in standalonemode

Fig. 26 Schematic of AFS +ESC integrated controller (ICC)

vehicle handling, a new rule based integration scheme is pro-posed to coordinate the control actions of the stand-alonecontrollers. In light of the previous analysis of stand-aloneactive subsystems, the proposed integrated control systemwill be designed to achieve the following objectives:

• To improve vehicle steerability at low to mid-range lateralaccelerations.

• To maintain vehicle stability close to and at the limit ofhandling.

• To minimize the influence of brake intervention on thelongitudinal vehicle dynamics.

This strategy needs to determine the activation sequencesand active regions of the stand-alone controllers in terms ofthe current vehicle operating point to avoid conflicts and toenhance the coexistence. It is therefore necessary to measurethe vehicle operating point. The operating point of the vehi-cle ranges from normal driving to limit handling. A quantita-tive measure of this is the lateral acceleration of the vehicle.

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Fig. 27 Performance of ICC(AFS + ESC) at medium latac

Fig. 28 Performance of ICC(AFS + ESC) at high latac

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Fig. 29 Schematic of AFS +ESC + VTD standalonecontroller

Fig. 30 Schematic of AFS +ESC + VTD integratedcontroller (ICC)

The relationship between the operating point and the lateralacceleration is a function of the road surface coefficient offriction. It is assumed that the road surface coefficient of fric-tion can be measured or estimated. Hence lateral accelerationcan be used as a measure of the operating vehicle point in theintegration strategy.

5.2 Integration of ESC and AFS

Having investigated the individual behaviour and the controlauthorities of each of the four chassis control systems, thedevelopment of integrated control strategy is carried out asfollows. First the ESC and the active front steering systemsare activated individually and the vehicle yaw rate, sideslipangle, lateral acceleration and the longitudinal vehicle speedare recorded. Then both of these control systems are activatedin standalone mode and the results are compared against thatof the individual controllers.

From Fig. 24, when AFS and ESC are activated in a stand-alone manner, they reduce the yaw rate and the sideslip anglebetter than when they are activated individually. This showsthat both the AFS and the ESC controllers complement eachother in improving the vehicle handling performance. Com-pared to the ESC only activated scenario, the AFS and ESCstandalone controller performs less intrusive in reducing thelongitudinal vehicle speed. But AFS still dominates in pro-viding the less safety critical low latac region of vehicle oper-ation as shown in Fig. 25. Again, both in the medium and highlatac regions the AFS + ESC standalone controller performedbetter than the individual ones.

Following the above analysis of the AFS and ESC in stand-alone manner on low, medium and high latac regions, a rulebased ICC strategy is developed (Fig. 26). The developedintegrated controller has one input and two outputs. The vehi-cle lateral acceleration is fed back to the integrated controlleras the input and is used to determine the vehicle operating

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Fig. 31 Performance of ICC(AFS + ESC + VTD) at mediumlatac

Fig. 32 Performance of ICC(AFS + ESC + VTD) at highlatac

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Fig. 33 Schematic of AFS +ESC + VTD + NFC standalonecontroller

Fig. 34 Schematic of AFS +ESC + VTD + NFC integratedcontroller (ICC)

region. Having determined the vehicle operating region, theintegrated controller allocates the vehicle dynamics controlauthority between the AFS and the ESC.

The rule based integrated controller activates the AFS inthe low latac range until 0.3g and then handover the controlauthority to ESC. As the low latac range is within 0.3g, theICC utilises the ability of the AFS to reduce the vehicle yawrate and sideslip angle. At the same time, since the ESC is notactivated, the ICC does not intrude in the vehicle longitudinaldynamics.

From the Figs. 27 and 28, when the vehicle is operated inthe medium and high latac regions, the integrated controller

performs better than the standalone controller in improvingthe vehicle handling. Due to the deactivation of AFS and theintervention of ESC beyond the 0.3g latac, the exit speed ofthe manoeuvre is less than the standalone controller, betterthan ESC only system.

So in summary, the integrated controller (AFS + ESC)performs at par with the standalone system in the low latacand performs better than standalone controller by reducingthe vehicle yaw rate and sideslip angle at the medium andthe high latac regions. The exit speed of the manoeuvre withICC is less than the standalone controller, but, better than theESC only system.

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Fig. 35 Performance of ICC(AFS + ESC + VTD + NFC) atmedium latac

5.3 Integration of ESC, AFS with VTD

Having integrated the AFS and the ESC systems, this sec-tion investigates the integration of VTD with the integratedcontroller developed in the previous section. From the stand-alone controller analysis in the earlier sections, the controlauthority of the AFS diminishes at the medium and the highlatac regions and also less intrusive at the less critical, lowlatac region. So the further integration strategy deactivatesthe AFS at the limits of low latac and considers the next twokey stability control systems, VTD and ESC. Both VTD andESC are effective in improving lateral handling of the vehicleat the medium latac zone, but the VTD limits the reductionin vehicle longitudinal speed compare to the more intrusiveESC.

So, the integrated control strategy activates only the AFSat the low latac and the VTD at medium latac. For the highand limit latac the ESC is activated. This integration strategyoptimises the use of these three active chassis systems at thesame time improves the vehicle handling without reducingthe current vehicle performance, such as maintain or negligi-ble effects of longitudinal vehicle speed. Figures 29 and 30shows the schematics of AFS, VTD and ESC controllers instandalone and integrated modes.

The rule based integrated controller is enhanced to accom-modate the necessary extra rules to integrate the VTD system

to the existing integrated controller. From the Figs. 31 and32, when the vehicle is operated in the medium and highlatac regions, the integrated controller performs better thanthe standalone controller in improving the vehicle handling.Due to the activation of VTD and the deactivation of ESCin the medium latac zone of 0.3–0.6g, the exit speed of themanoeuvre is better than the AFS + ESC ONLY integratedcontroller system.

In summary, the integrated controller (AFS + VTD + ESC)performs at par with the (AFS + ESC) integrated control sys-tem in the low, medium and high latacs and performs betterthan the standalone controller across the all latac regions.The exit speed of the manoeuvre with ICC is better in themedium latac range due to the activation of VTD.

5.4 Integration of ESC, AFS, VTD with NFC

From the individual chassis controller analysis the NFC con-troller has little or no effect at the low latac and a moderateeffect on improving the vehicle handling in the medium latacregion. Its ability to generate the extra tyre forces dependsmainly on the amount of lateral and longitudinal load trans-fer. When NFC is activated, only the steering input is given tothe vehicle. Hence the additional normal force on the wheelsinfluenced only the lateral tyre forces.

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Fig. 36 Performance of ICC(AFS + ESC + VTD + NFC) athigh latac

The effect of NFC on the longitudinal forces will addmore influence on generating the corrective yaw moment. Aschematic diagram of the AFS, ESC, VTD andNFC controllers in standalone manner is given onFig. 33.

A further enhancement is made to the rule based inte-grated to accommodate the necessary rules to integratethe NFC system to the existing integrated controller. Thisfully integrated chassis controller (ICC), integrates the ESC,AFS, VTD and suspension NFC. This rule based ICC strat-egy provides the control authority to AFS at the low latacrange, to VTD at medium latac range, to ESC at highand at limits and activates the NFC from medium lataconwards to optimise the generation of lateral and longitu-dinal tyre forces and to use the four active chassis systemseffectively.

A schematic of the novel four systems ICC control strat-egy is given in Fig. 34. From the Figs. 35 and 36, when thevehicle is operated in the medium and high latac regions,the integrated controller performs better than the standalonecontroller in improving the vehicle handling. In summary, theintegrated controller (AFS + VTD + ESC + NFC) performs atpar with the (AFS + ESC + VTD) integrated control systemin the low latac region and performs better in the medium tohigh latac and at the limits.

6 Conclusions

A detailed non-linear vehicle dynamics model is developedand four standalone vehicle control systems AFS, ESC, VTDand NFC are modelled and simulated in MATLAB/Simulink.In some cases, researcher used standard commercially avail-able softwares such as CarSim and MSc. ADAMS as theirbase vehicle models. Most of the studies reviewed, consid-ered only two standalone chassis systems that represent anytwo of the four key vehicle functional domains for the pur-pose of integration. Those approaches either provide little orno interaction between various key DoF of a vehicle and theireffects of each other. In this paper, various possible combina-tions of integrated strategies between these four systems areinvestigated through simulations. Based on these investiga-tions a new integrated control strategy is proposed to makethese four systems cohabit to improve the present vehiclehandling performance. Simulations with the integrated con-troller demonstrated a significant improvement in the per-formance objectives. The vehicle motion during an emer-gency maneuver is much improved, showing better handlingand characteristics during sudden, high speed maneuverstogether with a corresponding reduction in yaw rate and side-slip angle. The significant conclusions here is that the AFS,ESC, VTD and NFC individually have a significant positive

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influence on vehicle handling and integrating these four sys-tems showed that they can be a part of future global chassiscontrol strategies.

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New integrated chassis control systems for vehicle ... · New integrated chassis control systems 363 Fig. 1 Schematic of nonlinear vehicle model Fig. 2 Full vehicle model synopsis