A Multi-Objective Optimization Method for Energy Management Control of Hybrid Electric Vehicles Using NSGA-II Algorithm

A multi-objective optimization evaluation method for hybrid electric vehicle(HEV)is proposed by comprehensively considering the influences of fuel economy,emission and drivability on the energy management control for HEV.The multi-objective optimization algorithm based on NSGA-Ⅱ(non-dominated sorting genetic algorithm-II)is established by setting the parameters of the energy management control and the driveline system as the optimal parameters for the parallel hybrid electric vehicles,and the dynamic performance as the constraint condition.Then the proposed method is comparatively analyzed with the traditional control strategy that only considers the fuel economy. Simulation results show that the maximum fuel economy performance increases by 7.8% and the average value increases by 6.38%;the maximum drivability performance increases by 42.28% and the average value increases by 21.74%;the average synthetic emission performance increases by 41.51%.The proposed multi-objective optimization algorithm has good convergence and distribution.The obtained Pareto optimum solutions may provide more trade-off options for HEV energy management control strategy,which reflect the advantages of multi-objective optimization.