Multiobjective Optimization of HEV Fuel Economy and Emissions Using the Self-Adaptive Differential Evolution Algorithm

This paper describes the application of a novel multiobjective self-adaptive differential evolution (MOSADE) algorithm for the simultaneous optimization of component sizing and control strategy in parallel hybrid electric vehicles (HEVs). Based on an electric assist control strategy, the HEV optimal...

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Veröffentlicht in:	IEEE transactions on vehicular technology Jg. 60; H. 6; S. 2458 - 2470
Hauptverfasser:	Wu, Lianghong, Wang, Yaonan, Yuan, Xiaofang, Chen, Zhenlong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.07.2011 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Applied sciences Batteries Differential evolution (DE) algorithm Driving Electrical engineering. Electrical power engineering Electrical machines emissions Engines Evolution Exact sciences and technology Fuel consumption fuel consumption (FC) Fuels Ground, air and sea transportation, marine construction Hybrid electric vehicles hybrid electric vehicles (HEVs) Hybrid vehicles multiobjective optimization Optimization Pareto optimality Regulation and control Road transportation and traffic Strategy Studies Torque Hybrid electric powered vehicles Archive Adaptive algorithm Evolutionary algorithm Differential evolution (DE) algorithm Evolutionary computation Multiobjective programming Fuel consumption Optimization Optimal design multiobjective optimization Performance requirement Fuel economy Fuzzy set theory emissions hybrid electric vehicles (HEVs) Nearest neighbour Pareto optimum Control system Nonlinear problems Electric control Dimensioning European community Optimal solution fuel consumption (FC) Comparative study
ISSN:	0018-9545, 1939-9359
Online-Zugang:	Volltext
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