Energy management strategy optimization for hybrid energy storage system of tram based on competitive particle swarm algorithms

Abstract

Trams with energy storage are popular for their energy efficiency and reduced operational risk. An effective energy management strategy is optimized to enable a reasonable distribution of demand power among the storage elements, efficient use of energy as well as enhance the service life of the hybrid energy storage system (HESS). Thus, an energy management strategy optimization method of HESS based on a fixed power threshold is developed. Firstly, the energy management strategy optimization models based on single thresholds and multiple thresholds are developed. Then, the improved particle swarm optimization (PSO) algorithm with competing variable weights is proposed to solve optimization models. Finally, Guangzhou Haizhu tram is used to illustrate the performance of the developed method, the minimum charge state of the power battery under multiple thresholds is improved by 23.36 % over that of single threshold, and the total energy consumption of the power battery pack is reduced by 58.10 %, which shows that the energy management strategy based on multiple thresholds has better effects in giving full play to the power supply capacity of supercapacitor and reducing the energy consumption of power battery. Compared with other two methods, the improved PSO method has more reliable in utilizing more energy from supercapacitor.