Open AccessSimulation study on genetic algorithm control of hydrogen fuel cell gas supply system
Author(s) -
Rong Cheng,
Jing Chen,
Nanding Cheng,
Chun Xiao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1983/1/012049
Subject(s) - pid controller , matlab , genetic algorithm , fuel cells , computer science , algorithm , noise (video) , control theory (sociology) , control (management) , automotive engineering , control engineering , engineering , temperature control , chemical engineering , machine learning , artificial intelligence , image (mathematics) , operating system
Fuel cell as a new clean energy, its advantages of high efficiency, low emission and low noise have attracted the attention of domestic and foreign governments and scholars. To this end, based on the requirement analysis of the hydrogen fuel cell gas supply system, this paper focuses on the genetic algorithm optimization PID control strategy of the hydrogen fuel cell gas supply system. The simulation model is built on the Matlab/Simulink platform and compared with the conventional PID algorithm in the model. The simulation results show that the comprehensive index of PID control algorithm optimized by genetic algorithm is better than that of conventional PID algorithm, which proves the improvement effect of the proposed control strategy on the dynamic response of the gas supply system.