Abstract：Maximum power point tracking (MPPT) is an effective means to improve the efficiency of fuel cell energy conversion. Based on the analysis of fuel cell output characteristics and the characteristics of DC-DC converter circuit of fuel cell power generation system, this paper presents a maximum power intelligent tracking method for fuel cell based on cloud model theory. The changes of output power and voltage in the fuel cell are used as the front part of the cloud model generator, DC-DC Boost chopper duty cycle as the latter part of the cloud model generator. An intelligent cloud model controller for maximum power tracking of fuel cells is established. This method can effectively solve the misjudgment problem of the perturb observe method when the external condition is drastic as well as the design difficulty of the precision membership in fuzzy control. The simulation model of fuel cell power generation system is built by Matlab/Simulink. The maximum power tracking strategy proposed in this paper is simulated by the start of fuel flow, steep increase, steep drop of three typical perturbation modes. The results show that this strategy can quickly and accurately track the maximum power point (MPP), with the advantages of fast convergence and good stability.
杨德友, 崔冬晓, 蔡国伟. 基于云智能控制器的燃料电池最大功率跟踪策略[J]. 电工技术学报, 2018, 33(14): 3362-3370.
Yang Deyou, Cui Dongxiao, Cai Guowei. A Maximum Power Point Tracking Technology for Fuel Cells Using Cloud Model Based Intelligent Controller. Transactions of China Electrotechnical Society, 2018, 33(14): 3362-3370.
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