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Proton Exchange Membrane (PEM) fuel cell is found to be one of the efficient cells that converts chemical energy of fuel cell into electricity. Often, it is designed either using operating parameters or modeling parameters for maximizing its power. In this paper, both operating and modeling parameters are considered as decision variables and a multiobjective modeling is proposed. The modeling includes maximization of power and minimizing the number of fuel cells and box constraints on all variables. The proposed modeling is solved using NSGA-II. The obtained non-dominated solutions and relationship among the sensitive variables of the modeling show useful insight of PEM fuel cell modeling.

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Multiobjective Modeling and Optimization of Proton Exchange Membrane Fuel Cell Using Genetic Algorithm

  • 会议论文

  • 发表日期：

    2025年

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  • Dharmik Patel,
  • Deepak Sharma

摘要

Proton Exchange Membrane (PEM) fuel cell is found to be one of the efficient cells that converts chemical energy of fuel cell into electricity. Often, it is designed either using operating parameters or modeling parameters for maximizing its power. In this paper, both operating and modeling parameters are considered as decision variables and a multiobjective modeling is proposed. The modeling includes maximization of power and minimizing the number of fuel cells and box constraints on all variables. The proposed modeling is solved using NSGA-II. The obtained non-dominated solutions and relationship among the sensitive variables of the modeling show useful insight of PEM fuel cell modeling.