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| Parameter Identification of Proton Exchange Membrane Fuel Cell Model Based on Modified Tso Algorithm |
| LI Shuangshuang1，ZHENG Hui2，CAO Yubo1*
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| 1.School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin City 132022, China；School of Computer Science, BeiHua University. Jilin Province jilin city, Chian |
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Abstract Based on the principles of electrochemical reactions and semi-empirical methods, an output characteristic model for proton exchange membrane fuel cell (PEMFC) stacks is constructed. A modified transient search optimization (MTSO) algorithm is proposed, which initializes the search agent group using the tent chaotic mapping strategy and enhances global optimization capability through nonlinear decreasing and global reverse learning strategies. It is utilized for identifying unknown parameters in the semi-empirical model of PEMFC. Simulation results demonstrate that, compared to the transient search optimization (TSO) algorithm, enhanced transient search optimization (ETSO) algorithm, and harris hawks optimization (HHO) algorithm, the MTSO algorithm exhibits superior performance in parameter identification of the PEMFC model. It provides valuable insights for optimizing the design and control of fuel cell systems.
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Published: 20 December 2025
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