Multi-objective Optimization of Hybrid Electrical Vehicle Based on Pareto Optimality

Abstract

Abstract: Some basic theories about hybrid electric vehicle (HEV) were introduced. The multiobjective optimal model for minimizing the fuel consumption, the sum emission of HC and NOx, and the CO emission was established. A multiobjective evolutionary algorithm for hybrid electrical vehicle based on Pareto optimality (HEVMOEA) was proposed. HEVMOEA uses real coding method to represent gene, and employs ADVISOR to simulate HEV to obtain the value of each objective of candidate solutions, and adopts the Pareto dominance principle to evaluate each solution. A method was put forward to specify the significant digits of variables to guarantee the realizability. A series of simulation results show that HEVMOEA is capable of solving the multiobjective optimization design of HEV, and is promising to provide a set of alternative Pareto optimal solutions characterized with better fuel economy and emission performance for designer.

Key words: hybrid electrical vehicle, constrained multiobjective optimization, Pareto optimality, evolutionary algorithm

CLC Number:

YANG Guan-Ci-1, 2 , LI Shao-Bo-1, 2 , QU Jing-Lei-1, GUO Guan-Qi-3, ZHONG Yong-2. Multi-objective Optimization of Hybrid Electrical Vehicle Based on Pareto Optimality[J]. Journal of Shanghai Jiaotong University, 2012, 46(08): 1297-1303.

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