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Research on multi-energy management system of fuel cell vehicle based on fuzzy control
Journal of Intelligent & Fuzzy Systems ( IF 1.7 ) Pub Date : 2020-11-03 , DOI: 10.3233/jifs-189458
Wenguang Li 1 , Guosheng Feng 1, 2 , Sumei Jia 2
Affiliation  

This paper studies a hybrid power system composed of fuel cells, super capacitors and batteries. Super capacitors are used as auxiliary energy sources to provide the required high power when the car starts and accelerate, while absorbing braking energy when the car is braking. Fuzzy control is usedto optimize its energy management strategy. The fuzzy controller of the three-energy source system takes the battery, super capacitor, and bus demand power as the input of the fuzzy controller, and the battery demand power and the fuel cell demand power as the fuzzy controller output. The system realizes the energy distribution of super capacitors, fuel cells and storage batteries according to power requirements, thereby improving the performance of the system and extending the life of components. And with hydrogen consumption as the optimization goal, the particle swarm algorithm is used to optimize the parameters of the fuzzy membership function. Compared with the fuzzy control strategy without particle swarm optimization, the optimized fuzzy energy management strategy reduces the hydrogen consumption of fuel cell vehicles. 10 L/(100 km)-1, which improves the economy of the vehicle.

中文翻译:

基于模糊控制的燃料电池汽车多能量管理系统研究

本文研究由燃料电池,超级电容器和电池组成的混合动力系统。超级电容器用作辅助能源,在汽车起步和加速时提供所需的高功率,同时在汽车制动时吸收制动能量。模糊控制用于优化其能量管理策略。三能源系统的模糊控制器将电池,超级电容器和总线需求功率作为模糊控制器的输入,并将电池需求功率和燃料电池需求功率作为模糊控制器的输出。该系统根据功率需求实现了超级电容器,燃料电池和蓄电池的能量分配,从而提高了系统性能并延长了部件的使用寿命。以氢消耗为优化目标,粒子群算法用于优化模糊隶属度函数的参数。与没有粒子群优化的模糊控制策略相比,优化的模糊能量管理策略减少了燃料电池汽车的氢消耗。10 L /(100 km)-1,提高了车辆的经济性。
更新日期:2020-11-04
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