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<p>Fuel cell electric vehicles (FCEVs) present a sustainable transportation and decarbonization solution, but their complex powertrain dynamics pose challenges for optimal energy management. This research presents a comprehensive modeling framework for hydrogen proton exchange membrane (PEM)-based FCEV architecture, considering the double-layer charge effect in fuel cells—an important phenomenon in automobile applications. It also implements a fuzzy logic controller (FLC) using both Mamdani and Sugeno methods to enhance efficiency, optimize power distribution, and reduce energy losses. The proposed architecture integrates a fuel cell system, electric motor, power electronics, and energy storage system to achieve superior performance, efficiency, and reliability. Mamdani FLC manages nonlinear dynamics of fuel cell operation through intuitive control to generate a precise output, while Sugeno FLC offers computational efficiency for real-time energy management. Findings indicate that integrating advanced fuzzy control strategies within a robust powertrain architecture can enhance FCEV viability and competitiveness. The Mamdani technique yields a 6–8% performance improvement compared to the Sugeno system, improving current consumption, hydrogen consumption, and system efficiencies. This research contributes to developing efficient, intelligent control strategies for FCEVs, promoting the adoption of eco-friendly transportation solutions.</p>

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Development of mathematical plant model and implementation of fuzzy logic controller for improved performance of hydrogen fuel cell electric vehicle

  • 期刊论文

  • 发表日期：

    2025年5月28日

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  • Rakesh V. Mulik,
  • Ekambaram Porpatham,
  • Senthil Kumar Arumugam

摘要

Fuel cell electric vehicles (FCEVs) present a sustainable transportation and decarbonization solution, but their complex powertrain dynamics pose challenges for optimal energy management. This research presents a comprehensive modeling framework for hydrogen proton exchange membrane (PEM)-based FCEV architecture, considering the double-layer charge effect in fuel cells—an important phenomenon in automobile applications. It also implements a fuzzy logic controller (FLC) using both Mamdani and Sugeno methods to enhance efficiency, optimize power distribution, and reduce energy losses. The proposed architecture integrates a fuel cell system, electric motor, power electronics, and energy storage system to achieve superior performance, efficiency, and reliability. Mamdani FLC manages nonlinear dynamics of fuel cell operation through intuitive control to generate a precise output, while Sugeno FLC offers computational efficiency for real-time energy management. Findings indicate that integrating advanced fuzzy control strategies within a robust powertrain architecture can enhance FCEV viability and competitiveness. The Mamdani technique yields a 6–8% performance improvement compared to the Sugeno system, improving current consumption, hydrogen consumption, and system efficiencies. This research contributes to developing efficient, intelligent control strategies for FCEVs, promoting the adoption of eco-friendly transportation solutions.