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An Adaptive Joint Operating Parameters Optimization Approach for Active Direct Methanol Fuel Cells

Author

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  • Zhengang Zhao

    (Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
    Yunnan Key Laboratory of Green Energy, Electric Power Measurement Digitalization, Control and Protection, Kunming 650500, China)

  • Dongjie Li

    (Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China)

  • Xiaoping Xu

    (Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China)

  • Dacheng Zhang

    (Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
    Yunnan Key Laboratory of Computer Technology, Kunming 650500, China)

Abstract

The operating parameters of the active direct methanol fuel cell (DMFC) are essential factors that affect cell performance. However, it is challenging to maintain the optimal maximum output power density due to the system’s complexity, the operating conditions variation, and the correlations between those parameters. This paper proposes an adaptive joint optimization method for fuel cell operating parameters. The methods include the adaptive numerical simulation of the operation parameters and the optimization for fuel cell performance. Based on orthogonal tests, a BP neural network is used to build a performance evaluation model that can quantify the influence of the operating parameters on fuel cell performance. The optimal combination of operating parameters for the fuel cell is obtained by a whale optimization algorithm (WOA) through the evaluation model. The experimental results show that the evaluation model could respond accurately and adaptively to the cell operating conditions under different operating conditions. The optimization algorithm improves the maximum power density of the fuel cell by 8.71%.

Suggested Citation

  • Zhengang Zhao & Dongjie Li & Xiaoping Xu & Dacheng Zhang, 2023. "An Adaptive Joint Operating Parameters Optimization Approach for Active Direct Methanol Fuel Cells," Energies, MDPI, vol. 16(5), pages 1-14, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2167-:d:1078529
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    References listed on IDEAS

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    2. Tafaoli-Masoule, M. & Bahrami, A. & Elsayed, E.M., 2014. "Optimum design parameters and operating condition for maximum power of a direct methanol fuel cell using analytical model and genetic algorithm," Energy, Elsevier, vol. 70(C), pages 643-652.
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    4. Taymaz, Imdat & Akgun, Fehmi & Benli, Merthan, 2011. "Application of response surface methodology to optimize and investigate the effects of operating conditions on the performance of DMFC," Energy, Elsevier, vol. 36(2), pages 1155-1160.
    5. Yuan, Wei & Wang, Aoyu & Yan, Zhiguo & Tan, Zhenhao & Tang, Yong & Xia, Hongrong, 2016. "Visualization of two-phase flow and temperature characteristics of an active liquid-feed direct methanol fuel cell with diverse flow fields," Applied Energy, Elsevier, vol. 179(C), pages 85-98.
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