基于粒子群的有轨电车混合储能参数匹配研究

目前，混合储能式有轨电车作为一种高性价比的交通工具已得到广泛应用。混合储能系统承担着有轨电车供能任务，合理配置储能元件对于保障有轨电车正常运行具有重要的现实意义。以混合储能式有轨电车作为研究对象，在多目标、多约束条件下，利用粒子群优化算法，求解混合储能系统最优参数匹配方案；以广州海珠有轨电车THZ1线作为实例进行仿真验证，结果表明:最优配置混合储能系统在降低储能系统的体积、重量及成本、发挥储能元件充放电能力方面具有明显的优越性。

Research on parameter matching of hybrid energy storage system for tram based on particle swarm optimization

At present, hybrid energy storage trams have been widely used as cost-effective vehicles. The hybrid energy storage system acts as energy supply for the trams and appropriate configuration of energy storage components is of practical significance for ensuring the normal operation of the trams. This paper focuses the research on hybrid energy storage trams and the particle swarm optimization algorithm is used to achieve optimal parameter matching of the hybrid energy storage system under multi-objective and multi-constraint conditions. A simulation test was made on the Haizhu tram line, or THZ1, in Guangzhou Metro and the simulation results showed that the hybrid energy storage system with optimal configuration had obvious advantages in reducing the size, weight and cost of the system and giving play to the charge and discharge capacity of energy storage elements.