Multi-objective Optimization for Hybrid Power System based on the Differential Evolution Algorithm - Deng Tao; Lin Chunsong; Li Ya’nan; Lu Renzhi (Jixie chuandong)
Considering the disadvantages of energy management multi- objectives optimization for hybrid electric vehicle（ HEV） which usually adopts weighted sum method,by using the Pareto optimum algorithm,based on non- dominated sorting method to deal with the fuel economy and emissions（ CO,NOxand HC） evaluation indexes,then a new adaptive differential evolution algorithm is proposed and simulated which can be applied to multi- objective optimization of HEV energy management. The simulation results show that,a Pareto optimal solution set can be obtained by the proposed multi- objectives optimization method. And the maximum fuel economy increases by 5. 30%,the largest CO emissions reduces by 3. 65%,in the biggest NOxfalls by 14.40%,the max HC drops down by 3.26%.