Adaptive Fuzzy PID Based on Granular Function for Proton Exchange Membrane Fuel Cell Oxygen Excess Ratio Control

• Published in: Energies (Basel) Vol. 14; no. 4; p. 1140
• Main Authors: Tang, Xiao, Wang, Chunsheng, Hu, Yukun, Liu, Zijian, Li, Feiliang
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2021
• Subjects: adaptive fuzzy PID (AFPID); Dynamic models; Fuel cells; Fuel technology; granular function fuzzy PID (GFPID); Humidity; Hydration; oxygen excess ratio; oxygen starvation; proton exchange membrane fuel cell (PEMFC); Proton exchange membrane fuel cells; Response functions
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en14041140

An effective oxygen excess ratio control strategy for a proton exchange membrane fuel cell (PEMFC) can avoid oxygen starvation and optimize system performance. In this paper, a fuzzy PID control strategy based on granular function (GFPID) was proposed. Meanwhile, a proton exchange membrane fuel cell dynamic model was established on the MATLAB/Simulink platform, including the stack model system and the auxiliary system. In order to avoid oxygen starvation due to the transient variation of load current and optimize the parasitic power of the auxiliary system and the stack voltage, the purpose of optimizing the overall operating condition of the system was finally achieved. Adaptive fuzzy PID (AFPID) control has the technical bottleneck limitation of fuzzy rules explosion. GFPID eliminates fuzzification and defuzzification to solve this phenomenon. The number of fuzzy rules does not affect the precision of GFPID control, which is only related to the fuzzy granular points in the fitted granular response function. The granular function replaces the conventional fuzzy controller to realize the online adjustment of PID parameters. Compared with the conventional PID and AFPID control, the feasibility and superiority of the algorithm based on particle function are verified.