提出了一种并联式混合动力汽车(HEV)参数综合优化算法，以解决其能量管理与动力系统匹配经常各自独立进行的问题。该方法考虑电驱动系统成本，用改进型模糊能量管理策略，以能量管理策略参数、动力系统匹配参数为决策变量，以等效综合油耗、电机与电池组总成本为目标函数，在ADVISOR仿真环境下，用多目标遗传算法优化求解。结果表明：在保证整车动力性的前提下优化后，等效油耗降低23.0%，电机和电池组总成本降低41.9%；一氧化碳CO的100 km排放质量降低10.8%，碳氢化合物HC的排放降低22.2%，氮氧化物NOx的排放降低27.0%，改善了发动机效率与电机效率；验证了该方法的有效性。%A synthetic parameter optimization method of hybrid electric vehicle (HEV) was proposed to solve the problem that energy management and matching of power system are usualy conducted respectively. Considering the cost of electric drive system and using an improved fuzzy energy management strategy, the parameters of energy management strategy and the parameters of power system were taken as decision variables; meanwhile the equivalent synthetic fuel consumption and the cost of motor and battery pack were taken as objective functions. Then under the simulation environment of ADVISOR, a multi-objective genetic algorithm was used to ifnd the optimal solution. Simulation results show that under the constrains of vehicle dynamic quality, the equal fuel consumption per 100km is reduced by 23.0%, the cost of motor and battery pack is reduced by 41.9%, the CO emissions per kilometer is reduced by 10.8%, the HC emissions per kilometer is reduced by 22.2%, the NOx emissions per kilometer is reduced by 27.0%, as wel as the efifciency of engine and motor has been improved. These results verify the effectiveness of the method.
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