Parameter Identification of PMSM Based on Improved Secretary Bird Optimization Algorithm

Parameter Identification of PMSM Based on Improved Secretary Bird Optimization Algorithm | 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 Parameter Identification of PMSM Based on Improved Secretary Bird Optimization Algorithm Xiaoliang Yang, Zhiang Fu, Nan Jin, Zelan Li, Jihao Zhan, Tianxi Du This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6359767/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Permanent magnet synchronous motors (PMSMs) serve as the critical propulsion component in electric aircraft systems, where accurate parameter identification is essential for optimal performance. To address the limitations of conventional methods in balancing precision and computational efficiency, this study develops an improved Secretary Bird Optimization Algorithm (ISBOA) featuring multiple algorithmic enhancements. The proposed approach incorporates Tent chaotic mapping for population initialization, stochastic differential mutation for solution diversity preservation, random interaction transfer for local optima avoidance, and adaptive step-size adjustment for balanced search performance. Successfully implemented on a TMS320F28335 DSP-based control platform, ISBOA demonstrates superior experimental performance with parameter identification errors below 2.6% and significantly faster convergence compared to traditional methods. This work provides both algorithmic advances in optimization techniques and a practical solution for real-time motor control in electric aviation applications. permanent magnet synchronous motor electric aircraft parameter identification secretary bird optimization algorithm Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-6359767","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442831224,"identity":"c06aba34-00cf-4c3d-99fb-f7a1f00818bf","order_by":0,"name":"Xiaoliang Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYNCCApsEMM1DvBaDNNK1HCZBi8Hxs4df8xiczzOXSGB88LaNQd6coJYzeWmWMwxuF1vOSGA2nNvGYLizgZCWAzlmBh8MbiduuJHAJs3bxpBgcICQlvNvzAwSDM6BtLD/Jk7LjRzjBx8MDoBtYSZKi+SNN2aMMwySEzecedgsOeechOEGQlr4zucYf+apsEvccDz54Ic3ZTbyBG1ROMDAJgFhMjYACQkC6oFAvoGB+QNhZaNgFIyCUTCiAQAgYEQBI0oLrAAAAABJRU5ErkJggg==","orcid":"","institution":"Zhengzhou University of Light Industry","correspondingAuthor":true,"prefix":"","firstName":"Xiaoliang","middleName":"","lastName":"Yang","suffix":""},{"id":442831226,"identity":"703f55ad-7ed7-4cf4-8261-4330bb82d44b","order_by":1,"name":"Zhiang Fu","email":"","orcid":"","institution":"Zhengzhou University of Light Industry","correspondingAuthor":false,"prefix":"","firstName":"Zhiang","middleName":"","lastName":"Fu","suffix":""},{"id":442831228,"identity":"af876eb3-71f5-499b-8c10-d5b75f886972","order_by":2,"name":"Nan Jin","email":"","orcid":"","institution":"Zhengzhou University of Light Industry","correspondingAuthor":false,"prefix":"","firstName":"Nan","middleName":"","lastName":"Jin","suffix":""},{"id":442831231,"identity":"4ade444e-30f8-4266-a999-abb0bb8c38bf","order_by":3,"name":"Zelan Li","email":"","orcid":"","institution":"Hunan Electrical College of Technology","correspondingAuthor":false,"prefix":"","firstName":"Zelan","middleName":"","lastName":"Li","suffix":""},{"id":442831233,"identity":"f89a47e5-a9d4-4a2f-8f06-1e6219424f23","order_by":4,"name":"Jihao Zhan","email":"","orcid":"","institution":"Zhengzhou University of Light Industry","correspondingAuthor":false,"prefix":"","firstName":"Jihao","middleName":"","lastName":"Zhan","suffix":""},{"id":442831235,"identity":"2b6b4b79-cbe1-44f5-864d-3b46ff9660c0","order_by":5,"name":"Tianxi Du","email":"","orcid":"","institution":"Zhengzhou University of Light Industry","correspondingAuthor":false,"prefix":"","firstName":"Tianxi","middleName":"","lastName":"Du","suffix":""}],"badges":[],"createdAt":"2025-04-02 09:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6359767/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6359767/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89753212,"identity":"d0317581-c692-4288-90d4-d5fd75f7631d","added_by":"auto","created_at":"2025-08-24 07:31:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1182602,"visible":true,"origin":"","legend":"","description":"","filename":"SpringerNatureLaTeXTemplatenow.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6359767/v1_covered_78435c06-007a-4988-9c66-53740a02d40d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Parameter Identification of PMSM Based on Improved Secretary Bird Optimization Algorithm","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"permanent magnet synchronous motor, electric aircraft, parameter identification, secretary bird optimization algorithm","lastPublishedDoi":"10.21203/rs.3.rs-6359767/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6359767/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Permanent magnet synchronous motors (PMSMs) serve as the critical propulsion component in electric aircraft systems, where accurate parameter identification is essential for optimal performance. To address the limitations of conventional methods in balancing precision and computational efficiency, this study develops an improved Secretary Bird Optimization Algorithm (ISBOA) featuring multiple algorithmic enhancements. The proposed approach incorporates Tent chaotic mapping for population initialization, stochastic differential mutation for solution diversity preservation, random interaction transfer for local optima avoidance, and adaptive step-size adjustment for balanced search performance. Successfully implemented on a TMS320F28335 DSP-based control platform, ISBOA demonstrates superior experimental performance with parameter identification errors below 2.6\\% and significantly faster convergence compared to traditional methods. 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