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Emerging Technologies for Electric and Hybrid Vehicles
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Energies 2016,9, 997 optimization. TheDIRECTalgorithmbasedoptimizationmethodcanensure theglobaloptimized parametersofHEVenergymanagementstrategy.However, the literatureswhichoptimizedhybrid electricvehicleparametersbasedonDIRECTalgorithmmerelyoptimizedtheparametersofpowertrain configurationorpartial parameters of control strategy to improveenergyefficiency. Fewresearch workshavecomprehensivelyanalyzedandoptimizedthe influencingparametersof logic threshold control strategyforHEV,especially forall-wheel-driveHEV.The logic thresholdcontrol strategyof all-wheel-driveHEVismorecomplicated, for theall-wheel-driveHEVhasmorefreedomofpower sources.Andtheoptimizationof the logic thresholdcontrol strategyparameters forall-wheel-drive HEVcomprehensively ismorechallengingandmoremeaningful to improvethe fueleconomy. Table1.General comparisonofdifferentalgorithms. Algorithm Convergence ComputationBurden GlobalOptimization Geneticalgorithm good general bad Hybridgeneticalgorithm good general general Particleswarmoptimization good good bad Simulatedannealing bad good general Beesalgorithm good bad general DIRECTalgorithm good general good In thispaper, the logic thresholdparametersof theall-wheel-driveHEVenergymanagement strategyare comprehensivelyanalyzed, and thesevenenergyefficiency influencingparameters to beoptimizedareextracted. Then, theminimizedequivalent fuel consumptionper100kmissetas the target, andtheDIRECTalgorithmis implementedtooptimize theproposedparametersglobally. Finally, theeffectivenessof thealgorithmtosolve theproblemisanalyzedbysimulation. 2.HEVPowertrainModel Theresearchobject in this studyisanall-wheel-drive fullHEV,anditspowertrainstructure is shown inFigure1 [25]. Its front axleadopts thedrivingstructure including theengine, integrated starterandgenerator (ISG)motor,andautomatedmechanical transmission(AMT)gearbox. Its rear axle isdrivenbytwoin-wheelmotors. TheISGmotorshares thesameaxlewith theengine; therefore, it canfunction as a crankingmotor to start the engine quickly. Besides, the output torque of the in-wheelmotorcanbedirectly transmittedto thewheelandiscapableofdrivingthevehiclealoneat lowspeed.At thesametime, the ISGandin-wheelmotorscanbeusedbothasdrivingmotors for the vehicleandfunctionasgenerators toregenerate theexcesskineticenergy. Figure1showsthat thekeypartsof theHEVpowertrain include theengine, ISGmotor,AMT gearbox, in-wheelmotor, andpowerbattery. Themain technical parameters of these components areshowninTables2–7. Inconsiderationof thecomplexity foracquiringthemodelparametersand controlaccuracy, thestaticmodelwithdynamiccorrectionformainpowercomponents isadopted. Table2.Vehicleparametersof four-wheeldriveHEV. Vehicle CurbMass Tire Radius Frontal Area Correction Coefficientof RotatingMass Coefficientof AirResistance Coefficientof Rolling Resistance 1650kg 0.308m 2.095m2 1.05 0.293 0.0137 Table3.Engineparametersof four-wheeldriveHEV. EngineCapacity PeakTorque PeakPower MaximumRotationalSpeed 1.8L 250N·m 150kW 6500rpm 284
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Emerging Technologies for Electric and Hybrid Vehicles
Titel
Emerging Technologies for Electric and Hybrid Vehicles
Herausgeber
MDPI
Ort
Basel
Datum
2017
Sprache
englisch
Lizenz
CC BY-NC-ND 4.0
ISBN
978-3-03897-191-7
Abmessungen
17.0 x 24.4 cm
Seiten
376
Schlagwörter
electric vehicle, plug-in hybrid electric vehicle (PHEV), energy sources, energy management strategy, energy-storage system, charging technologies, control algorithms, battery, operating scenario, wireless power transfer (WPT)
Kategorie
Technik
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Emerging Technologies for Electric and Hybrid Vehicles