燃料电池汽车能量管理策略多目标优化研究

Research on a multi-objective optimization energy management strategy for fuel cell electric vehicles

为了优化燃料电池汽车氢耗并减缓燃料电池衰退,提出一种基于粒子群优化算法的分层多目标能量管理策略。首先构建燃料电池汽车动力系统简化模型,建立等效氢耗和燃料电池衰退数学模型;然后设计能量管理策略的规则层和优化层,规则层利用特定规则来缩小优化算法搜索空间,提高搜索速度,使其能够应用于实时控制;优化层将等效氢耗和燃料电池衰退量化为相应成本,构成瞬时成本函数,并采用粒子群优化算法对该成本函数进行优化,从而得到最优功率分配方案;最后利用Advisor和MATLAB联合仿真平台对所提出的能量管理策略进行仿真分析。结果表明,与功率跟随控制策略相比,总氢耗降低了46.8%,总成本减少了13.4%,其中燃料电池衰退等效成本下降了11.5%,初步验证了所提出的能量管理策略能有效降低氢耗并减缓燃料电池衰退。

In order to optimize the hydrogen consumption of fuel cell electric vehicles and slow down the degradation of fuel cells,proposes a stratified multi-objective energy management strategy based on particle swarm optimization algorithm.Firstly,build a simplified model of powertrain system,the mathematical models of equivalent hydrogen consumption and fuel cell decline are established,then the rule layer and optimization layer of the energy management strategy are designed.The rule layer uses specific rules to narrow the search space and improve the search speed of the optimization algorithm,so that it can be applied to real-time control,the optimization layer quantifies the equivalent hydrogen consumption and fuel cell degradation into corresponding costs,forming a instantaneous cost function,and using particle swarm optimization algorithm to optimize it for obtaining the optimal power distribution scheme.Finally,use the Advisor and MATLAB joint simulation platform to simulate and analyze the presented energy management strategy.The results show that compared with the power following control strategy,the total hydrogen consumption is reduced by 46.8%and the total cost is decreased by 13.4%,of which the equivalent cost of fuel cell recession is reduced by 11.5%.It is preliminary verified that the proposed energy management strategy can effectively reduce hydrogen consumption and slow down the decline of fuel cells.