Multi-objective optimization analysis of hydrogen internal combustion engine performance based on game theory

Zhenzhong Yang, Ping Guo, Lijun Wang and Qingyang Hao

Applied Energy, 2024, vol. 374, issue C, No S0306261924013291

Abstract: An innovative analytical approach combining game theory and particle swarm algorithms is used for the performance optimisation problem of hydrogen engines.An innovative analysis method combining game theory and particle swarm optimization algorithm was adopted to optimize the performance of hydrogen engines. Firstly, the power performance, fuel economy and emission of hydrogen internal combustion engines are studied in detail, and a three-way game model is constructed with the three as the main players, with strategic attribution for ignition timing, hydrogen injection timing and compression ratio.The simulation process of the model is then transformed into numerical optimisation by integrating the game utility function. Finally, the particle swarm algorithm is used to determine the initial set of strategies to obtain the Nash equilibrium solution.The results of the study showed that the optimized hydrogen internal combustion engine improved its power performance by 3.6%; economic efficiency increased by 5.7%; and emissions were reduced by 2% compared to the original engine.

Keywords: Game theory; Multi-objective optimization; Variable compression ratio; Hydrogen injection timing; Ignition timing (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123946

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