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Emerging Technologies for Electric and Hybrid Vehicles
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Energies 2016,9, 997 minf 0t = minf f< Yes No 1t t= + maxt t= Yes S φ= No S S Yes No End Figure 18. Optimization procedure of key parameters for HEV energy management using DIRECTalgorithm. 5.3.OptimizationResult andAnalysis Figure19showstheoptimizationmodel for theHEVenergymanagementkeyparameters,which includes thepreviouslyestablishedHEVclosed-loopsimulationmodel, target tominimize the fuel consumptionper100km,andcodeof theDIRECTalgorithm.Theoptimizationmodel isestablished inMATLAB/Simulink. Besides, theconstraintofvehicle’sdynamicperformanceshouldalsobe taken intoaccount. The0to60 timefor theall-wheeldrive full-HEVstudiedshouldnotbemore than10s. ThedrivingcycleofNEDCisselected,andthe initialSOC is set to55%. Thekeyparametersof the DIRECTalgorithmaresetasshowninTable11. 300
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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