Optimal sizing of battery-supercapacitor energy storage systems for trams using improved PSO algorithm

A hybrid energy storage system (HESS) of tram composed of different energy storage elements (ESEs) is gradually being adopted, leveraging the advantages of each ESE. The optimal sizing of HESS with a reasonable combination of different ESEs has become an important issue in improving energy management efficiency. Therefore, the optimal sizing method of battery-supercapacitor energy storage systems for trams is developed to investigate the optimal configuration of ESEs based on a constant power threshold. Firstly, the optimal sizing model of HESS taking size, mass, and cost of ESEs as a comprehensive objective function is established. Then, an improved particle swarm optimization (PSO) algorithm with a competition mechanism is developed for obtaining the optimal configurations of ESEs. Finally, Guangzhou Haizhu tram is taken as an example to verify the developed method. The results show that the optimal HESS with different ESEs has advantages in reducing the size, mass, and cost, and exerting the charging and discharging capacity of ESEs.

Automated summary

This study developed an optimal sizing method for battery-supercapacitor energy storage systems in trams based on a constant power threshold. The method was validated using the Guangzhou Haizhu tram, and the results demonstrated that the optimized hybrid energy storage system had advantages in reducing size, mass, cost, and utilizing the charging and discharging capacity of the energy storage elements.