Dynamic performance improvement of proton exchange membrane fuel cell system by robust loop shaping and artificial intelligence optimized fractional order PI controllers

Singh, Swati; Tayal, Vijay Kumar; Singh, Hemender Pal; Yadav, Vinod Kumar

doi:10.1080/15567036.2023.2236081

Cited by 3 publications

(1 citation statement)

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“…While the separated protons pass through the proton-conducting electrolyte called the membrane, the electric current generated by the movement of electrons is passed through the electrical circuit located outside the system. Protons passing through the elec trolyte recombine with electrons passing through the electrical circuit and combine with oxygen, producing heat along with pure water vapor [9]. Heat is important because high temperatures can cause thermal stresses that can damage the device and reduce its ex pected lifetime.…”

Section: Hmentioning

confidence: 99%

Optimization of Proportional–Integral (PI) and Fractional-Order Proportional–Integral (FOPI) Parameters Using Particle Swarm Optimization/Genetic Algorithm (PSO/GA) in a DC/DC Converter for Improving the Performance of Proton-Exchange Membrane Fuel Cells

Benteşen Yakut

2024

Energies

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In this article, the control of a DC/DC converter was carried out using the proposed methods of conventional PI, PSO-based PI, PSO-based FOPI, GA-based PI, and GA-based FOPI controllers in order to improve the performance of PEMFCs. Simulink models of a PEMFC model with two inputs—hydrogen consumption and oxygen air flow—and with controllers were developed. Then, the outputs of a system based on conventional PI were compared with the proposed methods. IAE, ISTE, and ITAE were employed as fitness functions in optimization algorithms such as PSO and GA. Fitness function value, maximum overshoot, and rising time were utilized as metrics to compare the performance of the methods. PI and FOPI parameters were optimized with the proposed methods and the results were compared with traditional PI in which the optimum parameters were determined by an empirical approach. This research study indicates that the proposed methods perform better than the conventional PI method. However, it becomes apparent that the GA-FOPI approach outperforms the others. The simulation result also shows that the PEMFC model with conventional PI and FOPI controllers in which the controller parameters are tuned using PSO and GA has an acceptable control performance.

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Section: Hmentioning

confidence: 99%