Multi-Objective Genetic Algorithm for Hybrid Electric Vehicle Parameter Optimization

As a typical multi-objective optimization problem, parameter optimization of HEV power control strategy must deal with the conflict between objectives, as fuel consumption and emissions. Classical methods define the HEV parameter optimization as a single objective problem to minimize the fuel consumption. In this paper, the multi-objective genetic algorithm (MOGA) is generalized for parameter optimization of power control strategy of series hybrid electric vehicle. Using a single unified formulation, a number of design objectives can be simultaneously optimized through searching in the parameter space. Compared with two main strategies, as Thermostatic and single-objective genetic algorithm (SOGA), the computation procedures of MOGA are discussed. Simulation results based on the model of series hybrid electric vehicle illustrate the optimization validity of MOGA

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