建立增程式电动汽车整车仿真模型,以恒温器控制策略为例,以车辆最长续驶里程和百公里油耗为优化目标,利用自适应遗传算法对其能量管理策略进行了优化.优化结果表明,采用自适应遗传算法可使等效燃油消耗较之优化前减少10％.同时研究了蓄电池SOC上、下限值与目标续驶里程的关系以及不同蓄电池初始SOC值对燃料电池输出功率最优值的影响.研究发现,目标续驶里程与蓄电池SOC上限值关系不大,受下限值影响较大；燃料电池恒定输出功率最优值随着蓄电池初始SOC值的增大而减小.%In this paper, extended-range electric vehicle simulation model is established on the basis of thermostat control strategy, and adaptive genetic algorithm (AGA) is used to optimize energy management strategy, with the objectives of minimum fuel consumption and maximum driving range. The simulation results demonstrate that the fuel consumption is reduced by 10% with the proposed method. The relationship between the battery SOC threshold values and driving range, as well as influence of different initial battery SOC to the optimum fuel cell power are also investigated in this paper. The studies find that the battery high-threshold is little related to driving range and battery low-threshold has great impact on driving range, the optimized fuel cell power is decreased with the increase of the battery initial SOC.
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