Multi-Objective Parameter Configuration Optimization of Hydrogen Fuel Cell Hybrid Power System for Locomotives

• Published in: Electronics (Basel) 2024-09, Vol.13 (18), p.3599
• Main Authors: Liu, Suyao, Xu, Chunmei, Zhang, Yifei, Pei, Haoying, Dong, Kan, Yang, Ning, Ma, Yingtao
• Format: Article
• Language: English
• Subjects: Algorithms; Analysis; Batteries; Configuration management; Costs; Economic impact; Energy consumption; Energy distribution; Energy efficiency; Energy industry; Energy management; Energy management systems; Energy requirements; Energy storage; Equipment and supplies; Fuel cell industry; Fuel cells; Hybrid systems; Hydrogen; Hydrogen as fuel; Hydrogen fuels; Lithium; Mathematical optimization; Multiple objective analysis; Optimization; Optimization models; Parameters; Particle swarm optimization; Power sources; Power supply; Railroads; Real time; Strategic planning (Business); Trains; Vehicles
• ISSN: 2079-9292; 2079-9292
• DOI: 10.3390/electronics13183599

Conventional methods of parameterizing fuel cell hybrid power systems (FCHPS) often rely on engineering experience, which leads to problems such as increased economic costs and excessive weight of the system. These shortcomings limit the performance of FCHPS in real-world applications. To address these issues, this paper proposes a novel method for optimizing the parameter configuration of FCHPS. First, the power and energy requirements of the vehicle are determined through traction calculations, and a real-time energy management strategy is used to ensure efficient power distribution. On this basis, a multi-objective parameter configuration optimization model is developed, which comprehensively considers economic cost and system weight, and uses a particle swarm optimization (PSO) algorithm to determine the optimal configuration of each power source. The optimization results show that the system economic cost is reduced by 8.76% and 18.05% and the weight is reduced by 11.47% and 9.13%, respectively, compared with the initial configuration. These results verify the effectiveness of the proposed optimization strategy and demonstrate its potential to improve the overall performance of the FCHPS.