Optimisation of wireless charging system by multiverse algorithm combining adaptive compression factor and Cauchy variation

Optimisation of wireless charging system by multiverse algorithm combining adaptive compression factor and Cauchy variation | 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 Article Optimisation of wireless charging system by multiverse algorithm combining adaptive compression factor and Cauchy variation Chunming Wen, Zhen Chen, Huilin Ma, Zhiyuan Tang, Yachen Feng, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5985377/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted 6 You are reading this latest preprint version Abstract The transmission efficiency and power of the existing Magnetically-\Coupled Resonant Wireless Power Transfer (MCR WPT) system are affected by the distance, load, coil and other factors, and cannot reach the optimal state at the same time. This paper proposes a multi-objective parameter optimisation of the system, with the objective of improving its performance. By analysing the LCC-S topology, the main parameters affecting the charging efficiency and output power are studied from the perspective of equivalent circuit. The Multi Objective Multi-Verse Optimizer (MOMVO) algorithm is employed to alter the growth mode of wormhole refreshment probability from linear to logarithmic, thereby enhancing the algorithm's capacity for effective search. Furthermore, the introduction of an adaptive compression factor and Cauchy's variance serves to achieve a balance between global and local convergence, thus enhancing the overall efficacy of the algorithm, and escape from the local extremes, so as to achieve the multi-objective parameter optimisation, while analysing the optimised model. Based on the optimised parameters, a physical platform is built to carry out experiments. The results demonstrate that the long-distance transmission performance of the optimised MCR-WPT system is enhanced. The optimal transmission distance of the system is 0.25 m, and the maximum output power is 127 W. Finally, the enhanced model's efficacy is substantiated through the construction of a prototype system. Physical sciences/Mathematics and computing/Information technology Physical sciences/Engineering/Electrical and electronic engineering Physical sciences/Mathematics and computing/Computer science wireless charging multi-objective parameter optimization multiverse algorithm adaptive compression factor Cauchy variation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 15 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Accepted 07 Apr, 2025 Reviews received at journal 04 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers invited by journal 03 Apr, 2025 Submission checks completed at journal 02 Apr, 2025 First submitted to journal 31 Mar, 2025 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5985377","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":438662438,"identity":"78ad3a43-4b51-4caa-9739-76db1d49f77f","order_by":0,"name":"Chunming 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multi-objective parameter optimization, multiverse algorithm, adaptive compression factor, Cauchy variation","lastPublishedDoi":"10.21203/rs.3.rs-5985377/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5985377/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The transmission efficiency and power of the existing Magnetically-\\\\Coupled Resonant Wireless Power Transfer (MCR WPT) system are affected by the distance, load, coil and other factors, and cannot reach the optimal state at the same time. This paper proposes a multi-objective parameter optimisation of the system, with the objective of improving its performance. By analysing the LCC-S topology, the main parameters affecting the charging efficiency and output power are studied from the perspective of equivalent circuit. The Multi Objective Multi-Verse Optimizer (MOMVO) algorithm is employed to alter the growth mode of wormhole refreshment probability from linear to logarithmic, thereby enhancing the algorithm's capacity for effective search. Furthermore, the introduction of an adaptive compression factor and Cauchy's variance serves to achieve a balance between global and local convergence, thus enhancing the overall efficacy of the algorithm, and escape from the local extremes, so as to achieve the multi-objective parameter optimisation, while analysing the optimised model. Based on the optimised parameters, a physical platform is built to carry out experiments. The results demonstrate that the long-distance transmission performance of the optimised MCR-WPT system is enhanced. The optimal transmission distance of the system is 0.25 m, and the maximum output power is 127 W. Finally, the enhanced model's efficacy is substantiated through the construction of a prototype system.","manuscriptTitle":"Optimisation of wireless charging system by multiverse algorithm combining adaptive compression factor and Cauchy variation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-07 04:29:58","doi":"10.21203/rs.3.rs-5985377/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-04-07T08:23:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-04T10:37:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"46521200855225540986280588426945994818","date":"2025-04-04T10:27:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-04T03:27:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-02T08:50:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-31T13:29:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bf963986-3ade-433b-bada-9a888a9f9435","owner":[],"postedDate":"April 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46713769,"name":"Physical sciences/Mathematics and computing/Information technology"},{"id":46713770,"name":"Physical sciences/Engineering/Electrical and electronic engineering"},{"id":46713771,"name":"Physical sciences/Mathematics and computing/Computer science"}],"tags":[],"updatedAt":"2025-04-21T16:04:23+00:00","versionOfRecord":{"articleIdentity":"rs-5985377","link":"https://doi.org/10.1038/s41598-025-97745-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-04-15 15:57:47","publishedOnDateReadable":"April 15th, 2025"},"versionCreatedAt":"2025-04-07 04:29:58","video":"","vorDoi":"10.1038/s41598-025-97745-2","vorDoiUrl":"https://doi.org/10.1038/s41598-025-97745-2","workflowStages":[]},"version":"v1","identity":"rs-5985377","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5985377","identity":"rs-5985377","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}