Intelligent Nonlinear Controller for Robust Power Management in PEM Fuel Cell Systems

Intelligent Nonlinear Controller for Robust Power Management in PEM Fuel Cell Systems | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 2 November 2025 V1 Latest version Share on Intelligent Nonlinear Controller for Robust Power Management in PEM Fuel Cell Systems Authors : Avinash Mahajan 0009-0003-4415-9339 [email protected] , Nischal Mungle , Rajesh Bodkhe , and Archana Mungle Authors Info & Affiliations https://doi.org/10.22541/au.176211206.65888813/v1 170 views 128 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The PEMFCs are considered to be promising clean energy technology for electric transportation and distributed generation owing to their high efficiencies and low emissions; however, their nonlinear electrochemical dynamics and their sensitivity to load variations make a challenge to delivering stable power especially under dynamic operating conditions. This research aims to solve these issues by building a detailed mathematical model of PEMFCs based on electrochemical principles, voltage loss mechanisms, hydrogen consumption, and dynamic load behavior. One of the main objectives is to come up with a nonlinear control strategy and then verify the same so that it can be utilized to regulate output voltage, improve transient response, and enhance fuel utilization efficiency. Validation of the proposed Lyapunov-based nonlinear design of the controller was tested through MATLAB/Simulink. The performance under step, ramp, and fluctuating load conditions was then compared with that of classical PID and fuzzy-PID control methods. Simulation results demonstrate that the nonlinear controller achieves about 30% faster settling time, 40% less overshoot, and up to a 12% enhancement in hydrogen utilization efficiency than conventional methods. This instance testifies the robustness and better adaptability of the controller under real-world disturbances. The incremental research presents a scalable control framework for PEMFCs, bearing immense practical relevance in electric vehicles, microgrids, and futuristic smart energy systems. Supplementary Material File (jcc_am_pemfc_research_manuscript.docx) Download 3.63 MB Information & Authors Information Version history V1 Version 1 02 November 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords adaptive control dynamic load matlab/simulink nonlinear control Authors Affiliations Avinash Mahajan 0009-0003-4415-9339 [email protected] Rashtrasant Tukadoji Maharaj Nagpur University View all articles by this author Nischal Mungle Yeshwantrao Chavan College of Engineering View all articles by this author Rajesh Bodkhe Yeshwantrao Chavan College of Engineering View all articles by this author Archana Mungle Gurunanak College of Pharmacy View all articles by this author Metrics & Citations Metrics Article Usage 170 views 128 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Avinash Mahajan, Nischal Mungle, Rajesh Bodkhe, et al. Intelligent Nonlinear Controller for Robust Power Management in PEM Fuel Cell Systems. Authorea . 02 November 2025. DOI: https://doi.org/10.22541/au.176211206.65888813/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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