Sensitivity Analysis and Optimization of Operating Conditions of Proton Exchange Membrane Fuel Cell

Sensitivity Analysis and Optimization of Operating Conditions of Proton Exchange Membrane Fuel Cell | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sensitivity Analysis and Optimization of Operating Conditions of Proton Exchange Membrane Fuel Cell Liao Xiangrong, Chonlatee Photong, Jianbin Su This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3903405/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Power characteristics are important indicators of fuel cell performance. In the actual operation of fuel cells, changes in operating conditions lead to variations in their power characteristics. Therefore, it is imperative to explore the impact of operating conditions on power characteristics. This paper analyzes the factors influencing fuel cell power and uses sensitivity analysis to investigate how different factors affect fuel cell performance. The operating parameters are optimized using a Bayesian-optimized Gaussian process regression model. The research results indicate that temperature has the greatest impact on fuel cell power, followed by stoichiometry and backpressure. The Bayesian-optimized Gaussian process regression model performs the best, reducing its RSME from 0.1 to 0.0556. Residual analysis and regression characteristic analysis verify the optimized model's improved fitting and regression characteristics. Based on the Bayesian-Gaussian process regression model, the optimized operating parameters are obtained for maximum power: a temperature of 80°C, stoichiometry of 4, and backpressure of 1.7 bar. This paper provides theoretical support for improving fuel cell performance.。 Fuel cells operating conditions power characteristics sensitivity analysis Gaussian process regression model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 06 Apr, 2024 Reviews received at journal 05 Apr, 2024 Reviews received at journal 16 Mar, 2024 Reviewers agreed at journal 03 Mar, 2024 Reviewers agreed at journal 29 Feb, 2024 Reviewers agreed at journal 28 Feb, 2024 Reviewers invited by journal 26 Feb, 2024 Editor assigned by journal 02 Feb, 2024 Submission checks completed at journal 28 Jan, 2024 First submitted to journal 27 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3903405","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":269790965,"identity":"0a2b3e17-5e2c-45fe-863c-677f459416af","order_by":0,"name":"Liao Xiangrong","email":"","orcid":"","institution":"Fujian Polytechnic of Information Technology","correspondingAuthor":false,"prefix":"","firstName":"Liao","middleName":"","lastName":"Xiangrong","suffix":""},{"id":269790966,"identity":"e4b6b926-bbd6-4945-aa2f-dfed66471f35","order_by":1,"name":"Chonlatee Photong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACNv7mAwc+/pGob2NvbHyQUFFDWAufxLHEhzMbLBj7eA4fNnhw5hhhLXIMOcrGvA0VjPMk3NIkH7YwE+EwhjNs0rw7JJjZJHjMKhIb2Bj427sT8Gth7j0mOfeMBBubdI/ZjcQdMgwSZ85uIGDLuTSJN0Ar2GTOALWcYWMwkMglpCXHDKheQoJNIsesILGNmSgtxoa8bRIGbBJpaQzEaQEF8owzEglswECWSDhzjIegX+T7gVH5oaIuQb69sfHjj4oaOf72XvxaMAAPacpHwSgYBaNgFGAFAJ7wSLy1MKllAAAAAElFTkSuQmCC","orcid":"","institution":"Mahasarakham University","correspondingAuthor":true,"prefix":"","firstName":"Chonlatee","middleName":"","lastName":"Photong","suffix":""},{"id":269790967,"identity":"9bd34688-afa5-4585-b8a1-f56a64fab876","order_by":2,"name":"Jianbin Su","email":"","orcid":"","institution":"Mahasarakham University","correspondingAuthor":false,"prefix":"","firstName":"Jianbin","middleName":"","lastName":"Su","suffix":""}],"badges":[],"createdAt":"2024-01-27 15:29:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3903405/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3903405/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50453485,"identity":"43faede8-f9e4-4e4b-972c-6afbc74edbd2","added_by":"auto","created_at":"2024-01-31 18:01:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":456123,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3903405/v1_covered_81a10850-558b-4d47-b595-249d7c70b363.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sensitivity Analysis and Optimization of Operating Conditions of Proton Exchange Membrane Fuel Cell","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-applied-electrochemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jach","sideBox":"Learn more about [Journal of Applied Electrochemistry](http://link.springer.com/journal/10800)","snPcode":"10800","submissionUrl":"https://submission.nature.com/new-submission/10800/3","title":"Journal of Applied Electrochemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Fuel cells, operating conditions, power characteristics, sensitivity analysis, Gaussian process regression model","lastPublishedDoi":"10.21203/rs.3.rs-3903405/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3903405/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePower characteristics are important indicators of fuel cell performance. 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