2000-01-0288

Validation and Use of SIMULINK Integrated,High Fidelity, Engine-In-Vehicle Simulation

of the International Class VI TruckDennis Assanis1, Zoran Filipi, Steve Gravante2, Dan Grohnke2, Xinqun Gui2, Loucas Louca,

Geoff Rideout, Jeffrey Stein, Yongsheng WangAutomotive Research Center3

Copyright © 2000 Society of Automotive Engineers, Inc.

ABSTRACT

This work presents the development, validation anduse of a SIMULINK integrated vehicle system simulationcomposed of engine, driveline and vehicle dynamicsmodules. The engine model links the appropriatenumber of single-cylinder modules, featuringthermodynamic models of the in-cylinder processes withtransient capabilities to ensure high fidelity predictions.A detailed fuel injection control module is also included.The engine is coupled to the driveline, which consists ofthe torque converter, transmission, differential and propshaft and drive shafts. An enhanced version of the pointmass model is used to account for vehicle dynamics inthe longitudinal and heave directions. A vehicle speedcontroller replaces the operator and allows the feed-forward simulation to follow a prescribed vehicle speedschedule. For the particular case reported here, thesimulation is configured for the International 4700 series,Class VI, 4x2 delivery truck powered by a V8turbocharged, intercooled diesel engine. The integratedvehicle simulation is validated against transient datameasured on the proving ground. Comparisons ofpredicted and measured responses of engine andvehicle variables during vehicle acceleration from 0 to 60mph and from 30 to 50 mph show very good agreement.The simulation is also used to study trade-offs involvedin redesigning control strategies for improvedperformance of the vehicle system.

INTRODUCTION

Vehicle design is a costly process that is initiatedwith a comprehensive analysis of the vehicle system inorder to determine the desired characteristics of sub-systems, followed by detailed design of sub-systems andcomponents, and finally building and testing ofprototypes. The latter include engine, driveline, andvehicle components and sub-systems, as well as thecomplete vehicle system. Development time and costcan be significantly reduced through the use ofsimulation-based design. A predictive vehicle system

simulation can allow the creation and testing of thevirtual vehicle for a variety of conditions, and guidecomponent design prior to building prototypes. Theavailability of a comprehensive vehicle simulation withhigh-fidelity sub-system modules also enablesconcurrent design, where change in one system isreflected on the design process of related componentsand systems. Furthermore, design of powertrain andvehicle control strategies can be tested on the computerinstead of the test cell or the proving ground. Since thelatter would be necessary only for final verification, thecost of the product development process could besignificantly reduced. In addition, a predictive simulationcan assist in quantifying parameters associated withsubjective driver feel and overall driveability that aredifficult to measure and yet very important for customeracceptance.

Previous attempts to model entire vehicle systemshave been characterized by a variety of approaches,differing in the fidelity of individual models as well as themethodologies used to integrate the various modules.Early attempts were based on collections of look-uptables for engine and driveline components, andsimplified, point-mass vehicle dynamics models (Heavy-Duty Vehicle Simulation Program - HEVSIM [1], VehiclePowertrain Simulation – VPS [2], NATO ReferenceMobility Model - NRMM [3]). These simulations can bevery valuable for quick assessments of vehicle mobility,even though they lack the ability to capture true vehicletransients. Their other limitation is the fact that, for everynew component, a new look-up table needs to begenerated through hardware testing, hence it isimpossible to study non-existing designs.

Caterpillar was among the first to attempt to marry athermodynamic diesel engine cycle simulation withDYNASTY [4] - a dynamic system simulation solving intime domain for vehicle position, velocity, accelerationand jerk; however, substantial challenges were reportedin the integration of two independent codes. Significantimprovements in the integration methodology have since

1Authors are listed in alphabetical order and, except if stated otherwise, are with the University of Michigan in Ann Arbor.2International Transportation Corporation3The ARC (http://arc.engin.umich.edu) is a U.S. Army Center of Excellence for Automotive Research at the University of Michigan, currently inpartnership with the University of Alaska-Fairbanks, Clemson University, University of Iowa, Oakland University, University of Tennessee, Wayne StateUniversity, and University of Wisconsin-Madison.

emerged based on object-oriented graphicalprogramming environments, such as EASY5 [5], MatrixXSystem Build and MATLAB/SIMULINK [6, 7, 8 and 9].The utilization of this technology allows much moreflexibility and is very suitable for control type of studies[5 and 9]. A fully flexible, comprehensive and predictivetransient vehicle system simulation needs to takeadvantage of both improved models and advancedprogramming environments. The physically basedmodeling of components is the prerequisite forpredictiveness, while the application of a simulationenvironment with block-diagram interfaces facilitatesintegration within a modular, dynamic structure.

Since 1994, the University of Michigan in partnershipwith the University of Iowa, Wayne State University, andthe University of Wisconsin at Madison has establishedan Automotive Research Center (ARC) for thedevelopment and validation of advanced ground vehiclesimulations. A hierarchy of models of varying resolutionis being built into the flexible, dynamic simulation systemthat can be tailored for specific applications. The firstgeneration of the high-fidelity ARC vehicle simulationwas configured for the 6x6 heavy truck heavy truck [10].The structure in MATLAB/SIMULINK, as well as thedriveline model and the turbo-machinery modules, werebased on the work of Munns [11]. The in-cylinderphenomenological module was based on the parentdiesel engine system simulation of Assanis andHeywood [12], with dynamic extensions by Filipi andAssanis [13], and SIMULINK implementation by Zhanget. al. [14]. For the vehicle model, non-linear, detailed,3-D multi-body kinematics and dynamics models hadbeen developed based on the work of Sayers and Riley[16 and 17]. The application of the complete vehiclesimulation demonstrated the ability to predict the effectof engine system design changes on vehicleperformance, as well as the complex interaction betweenthe powertrain and the vehicle during a hill climb on wetsurface causing front wheel slippage.

The objectives of the present study are to furtherdevelop the integrated ARC vehicle simulation forenhanced fidelity and flexibility, to validate its ability topredict engine and vehicle behavior during transients,and to illustrate its use for assessing the impact ofcontrol strategy on performance. Fidelity enhancementsfocus on the incorporation of realistic engine fuel andvehicle speed controllers, as well as enhanced modelsof peripheral engine components, such as the manifoldsand turbomachinery. Structural enhancements focus onclearly identifying the engine, the driveline and thevehicle dynamics modules at the top level of theSIMULINK simulation architecture.

Validation of the integrated vehicle simulation hasbeen performed by comparing simulation predictions foran International 4x2 class VI truck against datameasured on the proving ground by the manufacturer.The modules have been tailored to the needs of theparticular study, i.e. simulation of on–road vehicleperformance. The turbocharged engine module is

configured for the V8 engine configuration with newlydeveloped external component modules (manifolds,turbine, compressor, intercooler) based on [12]. Arealistic fuel injection and timing controller is developedfrom data provided by International. The drivelinemodule is configured with the 4-speed automatictransmission coupled to the engine via a torqueconverter. The shift logic, developed from manufacturerdata, is based on vehicle speed and “throttle position”,with two sets of characteristics, one for upshifts and theother for downshifts. The vehicle dynamics module isreduced compared to [10], so as to allow more efficientcalculations of vehicle acceleration performance on thestraight and flat road where excitation does not generatesignificant pitch motion. Hence, the vehicle model iscomposed of two components that describe its dynamicbehavior in longitudinal and heave directions. The mainmodules (cylinder, transmission, vehicle dynamics) areprogrammed in FORTRAN and C, and then converted toMEX file format in order to be able to create a SIMULINKmodule suitable for integration. The integration of allvehicle modules is performed simultaneously by thesolver package built in SIMULINK. The integratedsimulation environment is referred to as Vehicle EngineSIMulation – VESIM.

The paper is arranged as follows. The description ofthe physical vehicle system and the SIMULINKsimulation structure are presented first. Next, details ofthe main modules, i.e., the engine, driveline and vehicledynamics sub-systems are highlighted. This is followedby the description of the Intelligent Vehicle Speed (IVS)controller, developed to provide a driver demand signalfor a given vehicle speed schedule. Then, themethodology for integrating the engine with the drivelineand the vehicle is described. The newly configuredsimulation is validated against data measured on theproving ground. Experimental measurements andsimulation predictions are compared during launch andacceleration from 0-60 mph and from 30 to 50 mph.Finally, the simulation is used to study the effect ofvarying certain control functions on the transientbehavior of the vehicle system.

DESCRIPTION OF THE VEHICLE SYSTEM

The typical vehicle system is comprised of engine,drivetrain and vehicle dynamics modules. The vehicle inquestion is a diesel-powered 4x2 delivery truck with a 4-speed automatic transmission. The schematic of thevehicle system is given in Figure 1. The engine isconnected to the torque converter (TC), whose outputshaft is then coupled to the transmission (Trns),propeller shaft (PS), differential (D) and two driveshafts(DS), coupling the differential with the driven wheels.The complete vehicle system simulation is structured todirectly resemble the layout of the physical system.Previous study of the integration methodology [10]indicated the key parameters that define the physicalinteraction between modules. For a vehicle system,these parameters include the “active” and “resistive”torques, as well as the angular speeds of key powertrainshafts. Hence, the system is configured in a way that

allows a natural connection between the three mainmodules.

For a high degree of flexibility, the simulationstructure is implemented in the MATLAB/SIMULINKgraphical software environment. The top-leveldescription of VESIM is shown in Figure 2. Besides themain modules and “buttons” used to manipulateinput/output data, it shows three blocks used to controlthe transient simulation run: driver demand, brake andslope block. These modules allow specification of thedriver action on the gas pedal and the brake pedal, aswell as the road profile as a function of time.Alternatively, the IVS controller that allows the feed-forward simulation to follow a prescribed vehicle speedschedule can provide the driver demand signal. Detailsabout the approach to system integration will be givenlater, in the section on integration methodology.

ENGINE MODULE

The engine module is comprised of multiple enginecylinder modules linked with external componentmodules, such as compressors and turbines, heatexchangers, air filters, and exhaust system elements.The engine cylinder model tracks the thermodynamicprocesses within the cylinder throughout a cycle as afunction of crank angle. An engine dynamics moduleprovides a link with the vehicle through the driveline.The specifications for the engine used in this work aregiven in Table 1 of the Appendix and correspond to theInternational 7.3 L V8 engine type T444E.

THERMODYNAMIC DIESEL ENGINE CYLINDERMODULE - The foundation of the diesel engine cylindermodule used in this work is the physically based,thermodynamic, zero-dimensional model developed byAssanis and Heywood [12]. In the parent model, thecyclic processes in the cylinder are represented by ablend of more fundamental and phenomenologicalmodels of turbulence, combustion, and heat transfer.The parent simulation has been validated against test

results from diesel engines of various sizes, rangingfrom highway truck engines [12 and 15] to largelocomotive engines [18]. The cylinder control volume isopen to the transfer of mass, enthalpy, and energy in theform of work and heat. The cylinder contents arerepresented as one continuous medium, uniform inpressure and temperature, characterized by an averageequivalence ratio.

Quasi-steady, adiabatic, one-dimensional flowequations are used to predict mass flows past the intakeand exhaust valves. The compression process isdefined so as to include the ignition delay period, i.e., thetime interval between the start of the injection processand the ignition point. A refined version of the Arrheniusexpression relates the length of ignition delay to the gastemperature, pressure and overall fuel/air equivalenceratio in the cylinder after injection [19]. The inclusion ofthe equivalence ratio as the additional term has provennecessary in order to achieve the desired level ofpredictiveness during transients. Combustion ismodeled as a uniformly distributed heat release process,using Watson’s correlation [20]. The latter consists ofthe sum of two algebraic functions, one for premixed andone for diffusion burning and it includes ignition delayand overall fuel to air ratio terms. Hence, the correlationis able to account for the effect of engine load and speedon heat release.

Convective heat transfer in the combustion chamberis modeled using a Nusselt number correlation based onturbulent flow in pipes and the characteristic velocityconcept [12] for evaluating the turbulent Reynoldsnumber in the cylinder. The characteristic velocity andlength scales required by these correlations are obtainedfrom an “energy cascade” zero-dimensional turbulencemodel [12 and 21]. Radiative heat transfer is addedduring combustion [12]. The combustion chambersurface temperatures of the piston, cylinder head, andliner can be either specified or calculated from aspecification of the wall structure.

A friction sub-model based on the Millington’s andHartles’ correlation [22] is used to predict the enginefriction losses and convert indicated to brake quantities.In this application the model uses the instantaneousengine speed supplied by the engine dynamics model,rather then the mean engine speed used in thetraditional approach.

The diesel engine model [13] was originally coded inFORTRAN. It essentially contains the system ofsimultaneous, non-linear, ordinary differential equationsfor the cycle processes, along with a set of “utility”routines providing values for various terms in the stateequations, e.g., thermodynamic and transport properties,flow rates through valves, etc. The prospect of using asingle-cylinder engine code to develop a higher levelmulti-cylinder engine simulation necessitatedmodification of the FORTRAN source to make it fullycompatible and “open” for communication links withinSIMULINK. The procedure involves development of the

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FORTRAN-MEX file that contains all the necessary statederivatives and gateway routines for handling input andoutput vectors. More details on the conversiontechnique can be found in [14].

ENGINE DYNAMICS MODEL – An automotiveengine application implies frequent, and often dramatic,variations of driver demand and external load. Hence,the thermodynamic engine simulation needs to beextended to include calculation of dynamics resultingfrom these varying operating conditions. The dynamicequation is derived from a two-disk system coupled witha rigid shaft. Therefore, the rate of change of crankshaftangular velocity is simply the ratio of the algebraic sumof all active and reactive torques divided by thecrankshaft system inertia. The engine brake torque,calculated as the difference between the indicated andthe friction torque represents the active torque. Itdepends on the set of instantaneous engine operatingconditions, which include the action of the driver and theresponse of the controller. The indicated torquecalculation accounts for the pressure force acting onpiston as well as the inertial forces resulting from thepiston and connecting rod movement [13]. The resistivetorque can be either the torque converter pump torque, ifthe engine is coupled to a vehicle or the dynamometertorque if the engine is tested on a “virtual test stand”.The engine dynamics equation is solved at each crank

angle to return the new value of crankshaft speed for thenext integration step.

MANIFOLDS - Intake and exhaust manifolds aretreated as open thermodynamic systems. Equations forthe conservation of mass, species, and energy areapplied for analysis of manifold state, as well as fortracking enthalpy and fuel concentration fluxes into andout of cylinders [12]. Convective heat transfer from theworking fluid to the manifold walls is included in theconservation equations. The intake manifoldcommunicates with the intercooler, upstream, and withthe cylinders, downstream. The exhaust manifoldcommunicates with the cylinders, upstream, and with theturbine, downstream. The modular SIMULINK structureof the simulation greatly facilitates these connections forany arbitrary number of cylinders and manifolds.

TURBOCHARGER AND INTERCOOLER - Theturbocharger model is based on a 2-D interpolation ofdigitized compressor and turbine performance maps. Atany integration step, the mass flow rate and efficiencyare determined from the rotor speed and the pressureratio across the machine. Mass flow rate is an essentialinput into the manifold module, while the efficiencyallows calculation of compressor and turbine power.These variables allow the turbocharger dynamicsequation to be solved [12]. Hence, the new value ofrotor speed is returned after every integration step.

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w shaft

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w wheel

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Brake

VEHICLE DYNAMICS

DRIVELINE

DIESEL ENGINE

Driver Demand

Brake

Slope

Time

Load Input Data

Load Output Variables

Double Click to Plot Vehicle

Double Click to Plot Driveline

Double Click to Plot Engine

Figure 2: Vehicle system in SIMULINK – Vehicle Engine SIMulation.

The temperature drop in the intercooler isdetermined from the inlet air temperature, specified walltemperature and cooling efficiency [12]. The pressuredrop in the intercooler is calculated using an orificemodel. The orifice effective area has been calibratedagainst the experimental measurements obtained fromInternational.

FUEL INJECTION CONTROL - The role of thediesel engine fuel injection control module is to providethe signal for the mass and timing of fuel injected percycle based on driver demand, environmental conditionsand current engine operating conditions. Specialfunctions include corrections for insufficient boostpressure, cold start, high altitude, and the governingfunction. The correction of the amount of fuel based onthe boost pressure or density in the intake manifold isespecially important during full load acceleration, whenturbo lag may cause the engine to operate with muchlower boost pressures than normally experienced undercorresponding steady-state conditions [23]. Fuelinjection timing maps are designed to provide maximumfuel efficiency and satisfy the emissions constraint. TheInternational T444E engine is equipped with theHydraulically actuated Electronically controlled UnitInjector system (HEUI) allowing a high degree offlexibility and accuracy of control.

The selected simulation software, MATLAB/SIMULINK, provides a very suitable environment forcontroller design and testing. In this work, we relied oninformation about the fuel control logic and data providedby the engine manufacturer to design a controller thatwould have all the necessary functions determiningpowertrain transient response. The controller isconfigured as a single module that accepts driverdemand (or cruise control signal), engine speed andintake manifold pressure as inputs, and provides amountof fuel injected per cycle and injection timing as outputs.Hence, if there is a need to use and evaluate aproprietary controller, the user can simply cut theexisting one and paste in a new module. Figure 3illustrates the implemented control logic for the mass offuel injected per cycle. Since the engine in questionuses a drive-by-wire system, the step change in driverdemand will be modulated by a tip-in function based onthe desired “driver feel” upon vehicle launch. The driverdemand signal varies between 0 and 1. Base calibrationdetermines the “steady-state” amount of fuel for a given

demand and engine speed. This value is checkedagainst the limiting value determined from a look-uptable, depending on current values of engine speed andboost. The smaller of the two values will be passed onto the actuator and determine the actual mass of fuelinjected. This value can be further reduced by thegovernor function if engine speed exceeds the ratedspeed.

The algorithm for injection timing starts with theinformation about the engine speed and the mass of fuelper cycle as the measure of actual engine load. The 2-Dlook-up table determines the desired value in degreescrank angle. This is then corrected for the hydraulicdelay known to exist in the International HEUI injectionsystem before the actual value is passed on as theoutput.

The controller has been tested at various steady-state points before it is used for in-vehicle studies.Comparison against experimentally obtained engine testdata confirmed its ability to respond correctly to anychange in system operating conditions. All thesubsequent in-vehicle transient simulation runs areperformed with the factory calibration except the onewhere an alternative, more aggressive fueling calibrationis contrasted to the original one.

DRIVELINE

The driveline module consists of the torqueconverter, transmission, propshafts, differential, anddrive shafts. It provides the connection between theengine and the vehicle dynamics module (see Figure 1).The torque converter input shaft, on one end, and thewheel, on the other end, are the connecting points forthe engine and the vehicle dynamics models,respectively. The state equations are generated andcompiled in a SIMULINK C-MEX function. The shift logicis also coded in another C-MEX file. The two C-MEXfunctions are combined to form the VESIM drivelinemodule. The module inputs are the engine speed andwheel rotational speed, and the outputs the torque to thewheels and load torque on the engine. The drivelinemodel, excluding the shift logic, is constructed using thebond graph modeling language [24 and 25] andimplemented in the 20SIM system-modelingenvironment [26]. The 20SIM environment is selecteddue to its capability to combine block diagram elementsand bond graph elements. The specific elements usedin the components are described below and theirparameter values are given in Table 2 of the Appendix.

TORQUE CONVERTER - The torque converter isthe fluid clutch by which the engine is coupled to thetransmission. The typical three-element converterconsists of an impeller, stator (reactor), and turbine(runner), as shown in Figure 4. The impeller isconnected rigidly to the engine output shaft, and theturbine to the transmission input shaft. The stator isconnected to the torque converter housing via a one-wayclutch. The presence and arrangement of the stator

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cause the torque converter to act as a torquemultiplication device when operating at low speed ratios,and as an approximately direct-drive fluid coupling athigher speed ratios. The speed ratio is defined as theratio of turbine speed to impeller speed.

The torque converter model is a quasi-steady modelbased on experimental data available from transmissionsupplier. Such a model [27, 28, 29 and 30] assumesthat the torque converter is not subject to engine speedinputs with high frequency content, as would occurduring the fast transients that accompany throttle steps,or fast changes in speed ratio. The torque convertermodel is thus a limiting factor at present, in the study ofengine/transmission speeds during the short periodimmediately after such transients are initiated.

The TC model is shown schematically in Figure 5 asa block diagram. The inputs to the model are the pump(engine) speed and turbine (transmission) torque. Look-up tables convert the speed ratio into a torquemultiplication ratio and a capacity factor, which is used inconjunction with engine speed to calculate load torqueon the engine. Multiplication of the engine load torquewith the torque multiplication ratio gives the outputturbine torque that is applied to accelerate the turbine.

The torque converter model will also work when thetransmission is driving the engine, i.e., when the speedratio exceeds unity. Data for load torque on the engineas a function of engine and transmission speed havebeen converted to capacity factors for speed ratiosgreater than one. Piecewise curve fits for capacity factorand torque ratio versus speed ratio have beendeveloped to match the experimental data provided bytorque converter the manufacturer.

TRANSMISSION, PROPSHAFTS, DIFFERENTIALAND DRIVE AXLE - The two primary modeling concernsfor the remaining driveline components are the speedreduction / torque multiplication ratios; and the inertial,spring and damping properties. Input and outputinertias, stiffnesses and damping rates for each of thetransmission, propshafts, and differential/axle aredetermined experimentally and referenced to the inputspeeds thereof. While the physical properties of eachindividual gear and shaft are not considered explicitly,these properties are accounted for in the experimental“effective” parameters.

The central element of the transmission is a non-power-conserving transformer that models gearinefficiency and allows it to vary among different gears.The speed reduction in each gear is assumed ideal,while the torque multiplication is reduced by theappropriate inefficiency factor. The transmission torquelosses due to fluid churning are modeled as a variableresistance. As per manufacturer’s recommendations,the charging pump is modeled as a constant torque losssource, regardless of gear number or transmissionspeed.

The two propshafts are modeled as three effectiveinertias and two springs in series, again with a smallamount of viscous damping in parallel with each spring.The differential/axle model consists of an inertia, inputstiffness, and axle cooler churning loss resistor. In amanner similar to the transmission, the differentialgearing inefficiency is modeled using a non-power-conserving transformer with ideal speed reduction, butnon-ideal torque multiplication.

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Figure 4: Torque converter schematic.

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Pump Torque

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Figure 5: Block diagram of the torque converter model.

SHIFT LOGIC - The inputs to the shift logic moduleare the transmission output shaft speed and the driver-demanded throttle position. A chart such as the oneshown in Figure 6, based on the transmissionmanufacturer shift logic, determines the current gearnumber, and whether or not an upshift or downshift is tobe initiated. The solid and dashed lines indicate upshiftand downshift thresholds, respectively.

During a gearshift, the speed reduction and torquemultiplication ratios vary from the initial to the final valueaccording to blending functions. The blending functionsmodel the torque and speed ratio variations that occurduring the shift event, as clutches and bands engageand disengage. Typical shapes of blending functionsare shown in Figure 7.

VEHICLE DYNAMICS

The vehicle subsystem includes the wheels/tires,axles, suspensions and body of the vehicle, as shown in

Figure 8. Vehicle dynamics describe the motion of theselected rigid bodies (wheels, axles and body), that areallowed to move in space subject to forces/moments andrigid constraints. The forces/moments are physicalelements, which act at a specific point of two bodies,e.g., suspension. In addition, two bodies can berestrained to move only in specific directions by a rigidconstraint, e.g., a wheel is allowed only to rotate aroundthe axis of the axle. The connection of the vehicle withthe driveline is at the driven wheels where the drive-axleis connected to the rim of the wheels.

A number of approaches can be used to modelvehicle dynamics depending on the overall simulationobjectives. A single Degree of Freedom (DOF), pointmass model, can be selected for an initial estimate ofvehicle performance as different powertrain options areexplored. The model assumes that the vehicle mass islumped at the center of gravity. Such approach can givesufficiently accurate predictions of vehicle accelerationand speed on “smooth” or flat roads. The modelcomplexity can be enhanced with more DOFs as moresevere excitations (road roughness, steering, braking,etc.) are introduced into the model. This is necessary forthe investigation of vehicle-powertrain interactions duringsuch extreme transients that induce significant pitchmotion. The complexity of the model can besystematically adjusted, as proposed by Louca et. al.[31], to accommodate the needs of a specific scenario.

The studies in this work consider only theacceleration of the vehicle on a flat and straight road,where the excitation does not generate significant pitchmotion. Therefore, for this “mild” scenario, the pointmass model adequately predicts the interactionsbetween the powertrain and vehicle dynamics. Theenhanced point mass model is shown in Figure 9. Themodel is composed of two components that describe thedynamic behavior of the vehicle in the longitudinal andheave directions. The two components are coupledthrough the road/tire interaction.

The heave direction component is a standard

quarter car model, as shown in Figure 9. The modelconsists of the sprung mass, namely the major masssupported by the suspension, and the unsprung mass,which includes the wheel and axle masses supported bythe tire. This model represents the driven (rear) axle of

Transmission Output Shaft Speed [rad/s]

Driv

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Time [sec]

Speed ratio

Torque ratio

Shift duration

Figure 7: Blending functions for the shift event

Wheels Axle Suspension

Body

Tires

Figure 8: Vehicle and its main sub-systems.

Longitudinal

Wheel Inertia

Total Vehicle Mass

Heave

Road Excitation

Tire

Sprung�Mass

Unsprung Mass

Suspension

Drive Torque

Figure 9: Schematic of vehicle dynamics.

the vehicle and the sprung mass is adjusted to accountfor the location of the center of gravity of the vehiclebody. The suspension is modeled as a spring and adamper in parallel, and acts as a constraint forcebetween the sprung and unsprung masses. The tire isalso modeled as a spring and a damper in parallel,which transfer the road force to the unsprung mass(wheel hub). The input to the system is the road profilethat prescribes a vertical velocity as a function of thelongitudinal position of the vehicle.

The model of the longitudinal dynamics includes thetotal mass of the vehicle, which is the sum of the sprungand unsprung masses, and the inertia of all four wheelsof the rear driven axle. In addition, energy dissipationelements are included that account for energy lossesdue to bearing friction, tire rolling resistance andaerodynamic drag. The torque from the driveline isapplied to the wheel hub and the available traction forceto accelerate the vehicle is calculated based on thewheel slip. The traction force increases linearly with thewheel slip and it saturates when it reaches a value thatis equal to the tire normal force multiplied by the road/tirefriction coefficient (µ). The two components (heave andlongitudinal dynamics) are coupled since informationfrom the heave dynamics is needed to calculate thelongitudinal dynamics, and vice versa. The heavedynamics are coupled to the longitudinal dynamics sincethe tire normal force is needed to calculate the tractionforce. The vehicle dynamics are modeled using thebond graph language [24 and 25] and implemented inthe 20SIM system-modeling environment.

The dynamic model is represented by ordinarydifferential equations that describe the kinematic anddynamic behavior of the real system. These equationsare generated by 20SIM [26]. They are then coded inthe C programming language and converted into C-MEXfile. Hence, the final product is an S-function suitable fordirect integration with the SIMULINK model. All thevehicle dynamics parameters correspond to theInternational 4700 series delivery truck and are given inTable 3 of the Appendix.

INTELLIGENT VEHICLE SPEED CONTROLLER

A delivery truck, like the International 4700 series,operates under a wide range of conditions during normaluse. Traffic conditions, numerous stops, and vehiclelaunches initiate frequent and often rapid transients inthe city. The effects of this driving cycle arecompounded by the varying payload mass that affectsthe vehicle dynamics, and hence the resistance load feltby the engine. An additional element of driverintelligence is needed in order to achieve certain vehiclespeed schedule. The driving schedule can range frommaintaining constant vehicle speed on varying terrain tocomplex speed/load cycles, such as the ones used foremission testing. As mentioned earlier, the simulation isconfigured as a feed-forward system, where everythingstarts with the driver action and the system respondsbased on its abilities and external conditions. Hence,

the Intelligent Vehicle Speed (IVS) controller shouldhave the ability to provide the signal representing adriver demand based on the desired driving scheduleand vehicle speed feedback loop. In principle, thestructure of the IVS controller includes the vehicle speedcontroller itself and the fuel Injection Control Module(ICM), as illustrated in Figure 10. The engine isequipped with the electronically- controlled fuel injectionsystem (HEUI), hence ICM determines the actualamount of fuel injected and injection timing based on theIVS signal and on engine operating conditions, e.g.,boost pressure, crankshaft speed and hydraulic delay inthe system. Therefore, the output of the IVS controller isa signal that varies from 0 to 1 and is provided to theICM for further processing.

The speed control algorithms used in automotivecruise controllers are often of the proportional-integral(PI) type [32 and 33]. If a closed form, mathematicalmodel of the controlled system (vehicle system) can beformulated in the form of a transfer function or a state-space equation, the controller gain (proportional) andtime constant (integral) can be readily determined frombasic control theory. However, in our case, the modelsof the diesel engine, driveline, and vehicle are in theform of complex differential and algebraic systems ofequations. This makes it infeasible to derive a simpletransfer function. The Ziegler-Nichols tuning method[32] based on an open loop is selected as an alternativeapproach to set the controller's gain and time constant.The method relies on measurements of the dynamicresponse of the system when a unitary input is imposedon the system.

In addition, the vehicle system is time varying,because the characteristics of the vehicle change withthe operating conditions (e.g., vehicle mass, road slope,etc.). Therefore, if an IVS controller is well tuned underone set of conditions it may exhibit sluggish behaviorwhen the vehicle mass or road conditions change.Providing a schedule of controller gain and time constantis a practical approach to dealing with this type of non-linearity of a fully transient simulation. The controllergain and time constant are calculated using the Ziegler-Nichols method for a range of operating conditions andtabulated as a discrete set of values that depend on thevehicle mass and road slope. Consequently, whenoperating conditions change the IVS controller gain andtime constant are modified accordingly to much theoperation conditions (see Figure 10).

Vehicle Speed Controller

-+

Desired Vehicle Speed Fuel Injection

Control ModuleEngine Vehicle

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Gain Scheduling

Vehicle mass, Road slope

Figure 10: Intelligent Vehicle Speed controller.

INTEGRATION METHODOLOGY

As illustrated in Figure 2, the vehicle systemsimulation (VESIM) consists of three main modules:engine, driveline and the vehicle structure. Interactionbetween the main modules is in the form of “active” and“resistive” torques, as well as shaft angular speeds. Theengine simulation provides as output the instantaneousvalue of engine torque and rotational speed. The enginespeed is passed on to the torque converter input shaft,i.e., torque converter pump. The torque undergoesmultiple transformations as it is transmitted through thedriveline. The final value at the wheel depends on thetorque converter operating conditions, gear ratios in thetransmission and the differential, and the flexing of thepropeller and drive shafts. The torque on the wheels isconverted into the tractive force, which in conjunctionwith other information about the vehicle and the terraindetermines vehicle dynamic behavior. Hence, thevehicle dynamics module returns the instantaneousvehicle speed and the wheel angular velocity. Thisinformation is propagated back through the system, allthe way to the TC output shaft, thus determining thetorque converter turbine speed and the speed ratio ofthe TC. The latter determines the TC pump torque,which is in turn supplied to the engine module asresistive torque. The solution of the engine dynamicsequations determines the engine speed value for thenext integration step.

The integration is performed in the SIMULINKenvironment. Its graphical programming capabilitiesallow easy coupling of the modules, as long as each oneof them has a desired set of input/output links. Howeverit was shown [35] that the flexibility of SIMULINK comeswith a certain overhead in terms of computationalefficiency, the actual magnitude being stronglydependent on the level of system decomposition and thenumber of component modules and links. Hence, inorder to enhance computational efficiency, some of themore complex modules are programmed in FORTRAN(engine cylinder) or C (driveline, vehicle dynamics), andconfigured as self-contained SIMULINK blocks throughthe use of MEX function standard. The SIMULINKsolver is used to integrate the complete vehicle system;thus the classic problem in software numericalintegration of “who is in charge” is avoided. Moredetails about the integration procedure andmodularization of the engine cycle simulation can befound in [10 and 14].

SIMULATION VALIDATION

Simulation validation is performed throughcomparisons of VESIM predictions with measurementsobtained on the real vehicle on International provinggrounds. The experimental data was limited to engineand vehicle speed histories. However, since thesevariables represent the end result of complex engine andvehicle interactions, it is felt that the agreement betweenthese two quantities would effectively validate thebehavior of the entire system.

VEHICLE LAUNCH AND ACCELERATION FROM 0TO 60 MPH – VESIM behavior is first tested under oneof the most dramatic transients – vehicle launch at fullload. The vehicle is initially at stand still, with brakesapplied and the engine idling at 700 rpm. The amount offuel injected is automatically determined based on thedesired idle speed and internal losses in the torqueconverter. At t = 1 second, the brakes are released anddriver demand is linearly ramped up to the maximumvalue in one second. Vehicle and engine parametersare tracked until the vehicle reaches 60 mph. Thecomparison of predicted and measured engine andvehicle speed results is shown in Figure 11 andFigure 12, respectively. The vehicle speed results showexcellent agreement. The engine speed responseindicates reasonable agreement across the overallprofile, with the first two gear shifts actually occurring atthe same time as predicted, and only the last oneoccurring slightly earlier on the simulated profile.Further, the predicted drop in engine speed duringgearshifts closely matches the experimental results.

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The first five seconds should be examined moreclosely, since that interval is influenced by turbochargerlag and system dynamics significantly more than the restof the test. The sharp increase and the first spike on themeasured engine speed profile is associated with theextreme dynamics in the torque converter and itsapparent inability to provide the instantaneous responseto the sudden change of engine speed. Hence, theengine overspeeds somewhat before the torqueconverter is able to provide feedback in the form of theincreased pump torque, felt by the engine as thereaction torque. This is hypothesized based on the factthat the whole event associated with that initial spiketakes place during one crankshaft revolution, and itwould take some finite time to accelerate the fluid insidethe torque converter. The quasi-steady TC model is notcapable of capturing such a dynamic process and henceresponds instantaneously, keeping the engine speeddown. The comparison of the rest of the initial fivesecond part of the profile illustrates roughly the sameslope of the lines associated with the turbo lag, i.e., thegradual build up of pressure in the intake manifold andcorresponding increase of engine torque are in verygood agreement. A more dynamic torque convertermodel, which includes the fluid inertial effects, isexpected to improve the simulation results.

VEHICLE ACCELERATION FROM 30 TO 50 MPH –In this test the driver maintains the 30 mph speed for fewseconds, then depresses the pedal all the way andaccelerates to a speed above 50 mph. This allowsaccurate measurement of the 30–50 mph passing time.To simulate the same transient test required the use ofthe Intelligent Vehicle Speed controller. The transientschedule is designed as follows: at vehicle launch, thedesired speed is set at 30 mph and the system isallowed to reach steady state conditions. At a givenpoint in time, the demanded speed is instantly changedto 60 mph, and the IVS controller adjusts the fueldelivery appropriately. The intention is to still have fullfuel delivery at 50 mph and record the passing time.After a speed of 60 mph is achieved, the controllerdecreases fueling again, and attempts to keep thevehicle at this new quasi-steady state. The comparisonbetween predicted and measured vehicle speed andengine speed responses is shown in Figure 13a andFigure 13b, respectively. The agreement is very good,thus providing additional evidence of VESIM’s predictivecapabilities. It appears that the IVS provides excellentresponsiveness and stability, since the overshoot ofvehicle speed above 60 mph is minimal.

Variations of the normalized mass of fuel injectedduring the complete schedule of events are shown inFigure 13c. Dramatic changes are evident at theinitiation of the two hard acceleration sequences, as wellas more subtle changes resulting from the fuel controllerresponse to variations of boot pressure and enginespeed. Predicted intake manifold pressures are alsogiven in Figure 13c. The effect of turbo lag is especiallyevident at the vehicle launch (t = 5 sec). It is alsointeresting to note the decrease of boost pressure just

before the gearshift during the 30-60 mph acceleration.This is the result of the governor function in the ICMbecoming active and reducing fueling at high enginespeed, despite the “full demand” by IVS. Reducedfueling leads to a decrease of exhaust enthalpy anddeceleration of the turbocharger, thus the ”dip” in themanifold pressure line. The instantaneous fuel/airequivalence ratio, shown in Figure 13d, is the result ofdynamic interactions between the fuel and intake airsystems. Two peaks of equivalence values above 0.6predicted at the beginning of full power accelerationsillustrate the ability of the simulation to identify significantdepartures from normal, steady state conditions, thusassisting in solving transient emissions problems.

SYSTEM RESPONSE STUDIES

The potential usefulness of VESIM as a design toolis explored through two parametric studies. In bothcases the intention is to assess the possible side-effectseffect associated with modifications of control strategieswith the aim to improve overall vehicle performance.The first study focuses on the effect of varying theduration of the gearshift event. The second studyinvestigates the effect of implementing a less restrictivelow-boost correction in the engine fuel injectioncontroller.

SHIFT DURATION STUDY - The duration of theshift event is varied in order to study possible effects onsystem response and driver comfort. As shown in theengine speed time series in Figure 11 and Figure 12, thenominal shift duration of 0.8 seconds gave goodagreement with experimental data. This duration isvaried by +/- 0.4 seconds and the “full-throttle”acceleration run is repeated. Changing the shift durationessentially scales the blending functions in Figure 7along the horizontal axis. A shorter shift durationrepresents quicker engagement and disengagement oftransmission clutches and bands, and higher slopes ofthe torque ratio during the speed and torque phases ofthe shift.

The effect on ride quality, as evidenced by maximumforward vehicle jerk (second derivative of vehicle speed)during the shift from the first gear to second, is shown inFigure 14. The latter shows that the maximum value offorward jerk increases as the shift duration decreases.Ride quality in this simple example may be consideredslightly improved for longer shift duration, however, sucha modification brings up questions about the clutch wearand long-term durability, as the clutch slip occurs over alonger period of time. A shorter shift duration of 0.4seconds shows that the side effect of a crispieracceleration would be a drastically increased peak valueof jerk. For a typical truck application, this wouldprobably be unacceptable from the point of view of drivercomfort. However, the ability to evaluate such a trade-off between acceleration performance and driver comfortand feel can be a valuable aid in designing a new,specialized application, e.g., commuter bus, off roadvehicle, etc.

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Figure 13: Sequence of engine and vehicle transients during the 30-50 mph passing time test: comparison ofpredicted and measured a) vehicle speeds, and b) engine speeds; predictions of c) Intake manifold pressure andMass of Fuel Injected per cycle normalized by the maximum value, d) F/A equivalence ratio.

STUDY OF THE EFFECT OF FUEL CONTROLCALIBRATION ON ENGINE AND VEHICLERESPONSE – System behavior at vehicle launch is theresult of the combination of multiple effects, i.e., fuelsystem response to the step change of demand,turbocharger lag, fuel control correction for low boost,torque converter dynamic response, etc. The enginetransient at launch can be described as rapidacceleration under load, and it is one of the most criticalones in terms of its effect on performance, particulateemissions, and powertrain vibration. In order toinvestigate the potential for improvements of enginetransient response, a test is performed with a lessrestrictive low boost/low speed fueling correction thanthe standard one. This is accomplished by modifying the2-D look up table in the low speed zone in order to limitthe amount of fuel for a given pair of speed/boost values.

Then the vehicle launch is simulated, much like forthe case described in the section on validation, andresults of the two fueling calibrations are compared.Figure 15a illustrates the engine’s ability to acceleratemore rapidly with the new fueling map, while Figure 16ashows the corresponding increase of vehicle velocityduring the first five seconds. Vehicle jerk is given inFigure 16b, and its peak values are significantly higherfor the modified engine. This directly impacts the driver'ssubjective feel, and may prove to be too harsh for theaverage driver. The modified fueling map also causesmore wheel slip (see Figure 16c), which in the long termmay result in faster tire wear.

A closer examination of engine performance trendssheds more light onto processes taking place in theengine cylinder. The change of instantaneous in-cylinder equivalence ratio (φ) during vehicle launch isshown in Figure 15b. The modified, more aggressivefueling map causes two peaks of φ around 0.62, one atthe very beginning and the other after roughly 1.7seconds. The engine with the standard mapexperiences only one peak, after about 2.7 seconds.The initial high peak of φ caries more potential foradverse effect on engine particulate emission since it is

occurring at very low engine speed, when flow andmixing in the cylinder are sluggish. Figure 15c illustratesthe character of combustion through the mass ratio of

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fuel that burns in premixed mode versus diffusioncontrolled mode. For the modified fuel map, the richermixture during the very beginning of the transient causesthe fast decline of the premixed component, leading tocomplete domination by the diffusion burning process.This in fact can be a benefit in terms of engine NVH,since premixed burning typically translates into rapidpressure gradients after ignition and rough engineoperation.

In summary, the engine and vehicle simulation witha comprehensive fuel control module allows evaluationof trade-offs associated with the fueling strategymodifications aimed at performance improvements. Thefinal decision depends on careful evaluation ofsubjective (reaction to jerk, roughness) and objectivecriteria (soot emission, engine noise) for a specificapplication, i.e., vehicle configuration.

SUMMARY AND CONCLUSIONS

This work has reported further development,validation and use of a SIMULINK integrated vehiclesystem simulation. Our approach has relied uponintegrating a transient thermodynamic engine modulewith driveline and vehicle dynamics modules of propercomplexity for the simulation objectives. Fidelityenhancements included the incorporation of realisticengine fuel and vehicle speed controllers, as well asenhanced models of peripheral engine components,such as the manifolds and turbomachinery. Thecomplete vehicle simulation structure was implementedin SIMULINK. Some of the main modules wereprogrammed as SIMULINK MEX functions in order toenhance the computational efficiency of the integratedsystem. For validation purposes, the simulation hasbeen configured to predict the dynamic behavior of anInternational 4700 4x2 truck, powered by the T444E V8,turbocharged, intercooled engine, and equipped with afour speed automatic transmission.

The following conclusions have been drawn from ourwork:

• The SIMULINK system framework allows easyintegration of the vehicle system and addition orsubstitution of modules depending on goals of thespecific study.

• The SIMULINK software environment also facilitatedimplementation of the Intelligent Vehicle Speedcontroller, which provided a replacement for theoperator in the loop and allowed a feed-forwardsimulation to follow a prescribed vehicle speedschedule.

• For studies of vehicle acceleration performance on astraight and flat road, where excitation does notgenerate significant pitch motion, an enhanced point-mass model composed of two components(longitudinal and heave direction dynamics) isadequate.

The simulation was applied to a series of transientruns with two main goals. One was to validate thecomplete engine/vehicle simulation under transient

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c)Figure 16: Comparison of vehicle parameters duringlaunch for two fueling strategies: a) Vehicle speeds, b)Vehicle jerk, and c) Wheel slip.

conditions, while the other was to study the effect ofselected control parameters on critical aspects of systemresponse under severe dynamic conditions. Validationwas performed through comparisons of predictions andmeasurements with following results:

• Vehicle launch from stand still, and subsequent fullload acceleration to 60 mph, showed very goodagreement between predictions and measurements.The vehicle speed profile was predicted with greataccuracy. The overall engine speed history showedvery good agreement, with the exception of the verybeginning of the transient. Discrepancies areattributed to the insufficient fidelity of the torqueconverter model, and its inability to handle the highlydynamic conditions, from idle to full load, within onerevolution of the rotor. The rest of the engine speedprofile during the first gear acceleration sufficientlycaptured turbo lag effects.

• Predictions of 30-50 mph passing time showed goodagreement with measurements. Step changes ofengine load, and consequent response of the torqueconverter, driveline and vehicle were somewhat lesssevere than in the case of vehicle launch. All moduleswere able to handle dynamic conditions experiencedduring this run. This and the previous test effectivelyvalidate the adequacy of predictions of engine andvehicle transient performance, as well as transmissionbehavior, including shift logic.

System response studies indicated the following:

• The duration of the shift event was shown to havesignificant effect on the vehicle performance. Ashorter shift duration causes increased vehicle jerk,which can be a measure of driver comfort. However,the shorter shift duration may improve transmissionclutch wear.

• Comparison of results obtained for the standard andmodified fueling strategy enabled quantification of theeffect of such modification on all aspects of the vehiclesystem response. More aggressive fueling strategyresulted in improved vehicle acceleration; significantlyincreased jerk felt by the driver; more wheel slip; morepronounced peaks of the in-cylinder F/A equivalenceratio; and predominance of diffusion burning processduring vehicle launch.

These studies demonstrated the potential of thesimulation to be a useful engineering tool for evaluationof vehicle design trade-offs, such as those associatedwith increasing performance, while at the same timemanaging vehicle NVH, emissions, driveability, driverfeel, comfort, and durability.

ACKNOWLEDGMENTS

The authors would like to acknowledge the technicaland financial support of the Automotive Research Center(ARC) by the National Automotive Center (NAC) located

within the US Army Tank-Automotive Research,Development and Engineering Center (TARDEC) inWarren, Michigan. The ARC is a U.S. Army Center ofExcellence for Automotive Research at the University ofMichigan, currently in partnership with University ofAlaska-Fairbanks, Clemson University, University ofIowa, Oakland University, University of Tennessee,Wayne State University, and University of Wisconsin-Madison. The authors are grateful to the governmenttechnical monitor Walt Bryzik for his continuousguidance and support. Polat Sendur, University ofMichigan, is recognized for his initial work on modelingthe torque converter and transmission. Thecontributions of Pranab Das of InternationalTransportation Corporation are also gratefullyacknowledged.

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APPENDIX

Table 1: DI Diesel Engine Specifications

Configuration V8, Turbocharged, IntercooledDisplacement [L] 7.3Bore [cm] 10.44Stroke [cm] 10.62Connecting Rod Length [cm] 18.11Compression Ratio [-] 17.4Rated Power [HP] 210 @ 2400 rpm

Table 2: Driveline Specifications

Torque converter - Turbine inertia [kg*m2] 0.068Transmission - 1st gear churning losses coeff. R11 0.0192Transmission - 2nd gear churning losses coeff. R12 0.015Transmission - 3rd gear churning losses coeff.R13 0.031Transmission - 4th gear churning losses coeff.R14 0.0367Transmission - 1st gear churning losses coeff.R21 1.361 10-5

Transmission - 2nd gear churning losses coeff.R22 5.719 10-6

Transmission - 3rd gear churning losses coeff.R23 -3.189 10-5

Transmission - 4th gear churning losses coeff.R24 -4.177 10-5

Transmission - 1st gear ratio [-] 3.45Transmission - 2nd gear ratio [-] 2.24Transmission - 3rd gear ratio [-] 1.41Transmission - 4th gear ratio [-] 1.00Transmission - Fluid charging pump loss [N*m] -6.12Transmission - 1st Gear efficiency [-] 0.9893Transmission - 2nd Gear efficiency [-] 0.966Transmission - 3rd Gear efficiency [-] 0.9957Transmission - 4th Gear efficiency [-] 1.0Propshafts/Differential - Axle churning loss coeff.R0 8.34Propshafts/Differential - Axle churning loss coeff.R1 0.04087Propshafts/Differential - Differential drive ratio [-] 3.21Propshafts/Differential - Differential efficiency [-] 0.96

Table 3: Vehicle Specifications

CG location from front axle [-] 0.61875Sprung mass [kg] 6581.6Unsprung mass rear [kg] 430.9Unsprung mass front [kg] 244.9Longitudinal - Wheel inertia [kg*m2] 18.755Longitudinal – Break viscous damping [N*m*s/rad] 100.0Longitudinal – Break coulomb damping [N*m] 0.0Longitudinal - Wheel radius [m] 0.4131Longitudinal - Tire pressure [psi] 115.0Longitudinal - Number of tires on rear axle [-] 4.0Longitudinal - Wheel bearing damping [N*m*s/rad] 3.0Longitudinal - Road/tire friction coefficient [-] 0.7Longitudinal- Aerodynamic drag = 0.5*Cd*ρ*Area 2.081

Vertical - Rear suspension compliance [m/N] 6.34461 10-7

Vertical - Rear tire compliance [m/N] 2.97403 10-7

Vertical - Rear suspension damping [N*s/m] 7000.0

Vertical - Rear tire damping [N*s/m] 2000.0