Abstract：To analyze the impact of the power system parameter matching design and energy management scheme on the vehicle performance, taking a fuel cell vehicle as research object, the parameters of main power system components were matched. The power-following energy management strategy and the fuzzy control-based energy management strategy were proposed to improve the economic performance of the vehicle, and the sliding average filtering algorithm was used to optimize the output of the fuzzy control strategy. To model the vehicle and energy management system, the joint simulation platform was established based on AVL-Cruise and Simulink to verify the power performance of the vehicle, and the economic performance of the vehicle under three control strategies was comparatively analyzed. The results show that the fuel cell output power curve of the optimized energy management strategy is smoother and is always within the high-efficiency output interval. Based on the principle of fuel cell priority protection, the optimized energy management strategy has the best performance.
SONG K, DING Y H, HU X, et al. Degradation adaptive energy management strategy using fuel cell state-of-health for fuel economy improvement of hybrid electric vehicle [J]. Applied Energy, DOI: 10.1016/j.apenergy.2020.116413.
［2］
LI W G, FENG G S, JIA S M, et al. Research on multi-energy management system of fuel cell vehicle based on fuzzy control [J]. Journal of Intelligent & Fuzzy Systems, 2021,40(4):6205-6217.
［3］
KANDIDAYENI M, MACIAS A, BOULON L. Efficiency upgrade of hybrid fuel cell vehicles′ energy management strategies by online systemic management of fuel cell [J]. IEEE Transactions on Industrial Electronics,2021,68(6):4941-4953.
LIU S C, SUN H W, WANG R X, et al. Matching design of power system for high power hydrogen fuel cell heavy-duty truck [J]. Automotive Engineering, 2021,43(2):196-203.(in Chinese)
YANG K, WANG J, XIAO J S, et al. Study on the matching and design of a B-class fuel cell electric vehicle [J]. Chinese Journal of Automotive Engineering, 2018,8(6):399-406.(in Chinese).
［6］
HU X, LIU S K, SONG K, et al. Novel fuzzy control energy management strategy for fuel cell hybrid electric vehicles considering state of health [J]. Energies, DOI:10.3390/en14206481.
［7］
GAO J W, LI M, HU Y F, et al. Challenges and deve-lopments of automotive fuel cell hybrid power system and control [J]. Science China(Information Sciences), 2019,62(5):50-74.
DENG K, LIU Y X, HAI D, et al. Deep reinforcement learning based energy management strategy of fuel cell hybrid railway vehicles considering fuel cell aging [J]. Energy Conversion and Management, DOI:10.1016/j.enconman.2021.115030.
［12］
SHEN D, LIM C C, SHI P. Fuzzy model based control for energy management and optimization in fuel cell vehicles [J].IEEE Transactions on Vehicular Technology, 2020, 69(12): 14674-14688.
［13］
ZHAO Z, WANG T, LI M,et al. Optimization of fuzzy control energy management strategy for fuel cell vehicle power system using a multi-islandgenetic algorithm [J]. Energy Science & Engineering, 2021,9(4):548-564.
ZHAO Y, XIE J F, SHI J W,et al. Energy management strategy of FCHV considering fuel cell durability [J]. Modern Manufacturing Engineering, 2020(4):70-76，158.(in Chinese)
2024, Vol. 45 
