Optimal Parameter Matching of Hybrid Energy Storage System Based on NSGA-Ⅱ Algorithm for Energy Storage Type Tram

doi:10.3901/JME.2020.24.181

Abstract

Abstract: In order to study the parameter matching problems of a tram powered by hybrid energy storage system which consists of a battery pack and an ultracapacitor pack, a parameter matching approach of hybrid energy storage system is proposed based on a multi-objective optimization algorithm. According to the dynamic performance requirement of the tram, a design of hybrid energy storage system' parameters is presented based on equivalent calculation approach. The multi-objective cost function is established by using the daily operating cost of the tram and performance degradation rate of battery as performance indicators. The optimization process of hybrid energy storage system with system simulation model in loop is designed by using NSGA-Ⅱalgorithm. Taking a round trip as operation requirement of the tram, the simulation results of different parameter matching of Pareto solution set and equivalent calculation approach are compared and analyzed in two different drive cycles. The simulation results indicate that the optimized result reduces the performance degradation rate of battery by at least 31.1%, compared with the parameter matching result of the hybrid energy storage system based on the equivalent calculation approach. Moreover, the reasonable configuration of hybrid energy storage system can effectively guarantee the high recovery rate of regenerative braking energy and the efficiency of the tram, and the longer distance between stations increases the configuration demand of the hybrid energy storage system.

Key words: tram, hybrid energy storage system, parameter matching, multi-objective optimization, NSGA-Ⅱ

CLC Number:

U482

YANG Jibin, XU Xiaohui, PENG Yiqiang, ZHANG Jiye, SONG Pengyun. Optimal Parameter Matching of Hybrid Energy Storage System Based on NSGA-Ⅱ Algorithm for Energy Storage Type Tram[J]. Journal of Mechanical Engineering, 2020, 56(24): 181-189.

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