燃料电池有轨电车能量管理Pareto多目标优化

节能环保的出行方式得到政府的大力推广, 其中燃料电池混合动力有轨电车由于可无网运行且节能环保而备受关注.为了改善燃料电池/超级电容/动力电池大功率有轨电车的燃料经济性与系统耐久性, 提出一种有轨电车能量管理策略(Energy management strategy, EMS)的多目标优化方法. 首先以氢燃料消耗量和能量源性能衰减率作为评价指标, 建立多目标成本函数. 由于两个指标很难在同一个等式中评价, 设计了基于状态机与非支配排序的能量管理Pareto多目标优化方法, 获得了有轨电车能量管理策略Pareto非劣解集, 并分析了能量管理策略的目标功率参数对性能指标的影响规律, 进而遴选出兼顾燃料经济性与系统耐久性的综合最优解. 结果表明, 与功率跟随策略和基于遗传算法优化策略相比, 该能量管理优化方法的燃料经济性分别提高了29.4 %和2.4 %.

Pareto-based Multi-objective Optimization of Energy Management for Fuel Cell Tramway

The environment-friendly transportation has been greatly promoted by governments. Because of non-polluting and being operated without nets, fuel cell hybrid tramway has attracted much attention. In order to improve the fuel economy and system durability of fuel cell/supercapacitor/power battery high-power hybrid electric vehicles, a multi-objective optimization method of energy management strategy for tramway is proposed. Firstly, the multi-objective cost function is established by using the hydrogen fuel consumption and the performance degradation rate of each energy source as performance indices. These two performance indeces are difficult to evaluate in one equation, so a Pareto multi-objective optimization method based on the state machine and non-dominated sorting is designed. The Pareto non-inferior solution set of the energy management strategy is obtained, and the influence law of the target power parameters of the energy management strategy on the performance index is revealed, and then the comprehensive optimal solution considering both fuel economy and system durability is selected. The results show that the fuel economy of the energy management optimization method is improved by 29.4 % and 2.4 % respectively, compared with the power following strategy and the genetic algorithm based optimization strategy.