Study on the influence of segmented fuel cell by grooving method and its application in oxygen starvation diagnosis

2021 ◽  
Author(s):  
Huicui Chen ◽  
Wanchao Shan ◽  
Tong Zhang ◽  
Pucheng Pei ◽  
Chenghao Deng ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Oxygen Starvation

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

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1140
Author(s):  
Xiao Tang ◽  
Chunsheng Wang ◽  
Yukun Hu ◽  
Zijian Liu ◽  
Feiliang Li
Keyword(s):  
Fuel Cell ◽  
Control Strategy ◽  
Proton Exchange Membrane ◽  
Proton Exchange ◽  
Auxiliary System ◽  
Fuzzy Pid ◽  
Oxygen Starvation ◽  
Oxygen Excess ◽  
Exchange Membrane ◽  
Oxygen Excess Ratio

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.

Load governor based on constrained extremum seeking for PEM fuel cell oxygen starvation and compressor surge protection

2013 ◽  
Vol 38 (33) ◽  
pp. 14314-14322 ◽  
Author(s):  
Salah Laghrouche ◽  
Imad Matraji ◽  
Fayez Shakil Ahmed ◽  
Samir Jemei ◽  
Maxime Wack
Keyword(s):  
Fuel Cell ◽  
Pem Fuel Cell ◽  
Extremum Seeking ◽  
Compressor Surge ◽  
Oxygen Starvation ◽  
Surge Protection

scholarly journals Design of Genetic Programming Control Algorithm for Low-Temperature PEM Fuel Cell

2021 ◽  
Vol 8 ◽  
Author(s):  
Abdel Gafoor Haddad ◽  
Ahmed Al-Durra ◽  
Igor Boiko
Keyword(s):  
Fuel Cell ◽  
Genetic Programming ◽  
Design Method ◽  
Effective Control ◽  
Response Analysis ◽  
Adaptive Controllers ◽  
Air Supply ◽  
Oxygen Starvation ◽  
Complex Nonlinear Systems ◽  
Time Required

An effective control system for the air supply in fuel cell systems (FCS) is required to prevent oxygen starvation and to maximize the net power. For this purpose, conventional feedback and adaptive controllers are designed using genetic programming (GP). To minimize the time required for the GP convergence, FCS models of different complexity are studied and a comparison between them is carried out. Guidelines on applying the GP approach based on data obtained from simulations are developed along with a specially designed cost function that promotes closed-loop linearization. The advantage of this design method lies in its applicability to complex nonlinear systems for which nonlinear control methods may not be applicable. Adaptation is added to the oxygen excess ratio (OER) regulation problem by training a neural network that provides the optimal OER reference based on the stack current and temperature. The performance of both the regulation and adaptive controllers is tested under noise in the compressor flow and the stack current measurements. The robustness of the GP controllers is observed through the frequency response analysis.

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