Predictive Modeling and Comparative Performance Analysis of PMSM Designs in EV and Industrial Drives

Predictive Modeling and Comparative Performance Analysis of PMSM Designs in EV and Industrial Drives | 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 Predictive Modeling and Comparative Performance Analysis of PMSM Designs in EV and Industrial Drives Rajesh G, Sebasthirani K, Maruthupandi P, Remyasree R This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7715956/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) are increasingly adopted in electric vehicles (EVs) and industrial drives due to their high efficiency and torque density. However, performance varies with motor topology, operating conditions, and thermal management. This study presents a comparative evaluation of three PMSM types—Axial Flux, Interior Permanent Magnet (IPM), and Surface Permanent Magnet (SPM)—using a subset of 1,000 records from the PMSM Smart Control Dataset (Kaggle), containing 15 electrical and thermal parameters. Statistical analysis and comparative plots were used to examine efficiency, torque–speed characteristics, current and voltage demand, and temperature rise under different load conditions, cooling methods, and application modes. Results show that SPM motors achieve the highest efficiency (75.9%) and superior thermal stability, making them suitable for sustained EV traction, while IPM motors provide strong torque density and wide-speed performance. Axial Flux motors, with compact geometry and steady torque, are most advantageous in constant-torque industrial drives. In addition, predictive modeling was employed to estimate efficiency from electrical, thermal, and categorical descriptors. A linear regression model achieved R² ≈ 0.62 on the test dataset, with stator/rotor temperatures, current, and operating mode identified as the most influential predictors. These findings demonstrate that combining comparative evaluation with predictive modeling supports optimal PMSM selection and enables lightweight, real-time efficiency estimation, contributing to intelligent control strategies for sustainable mobility Permanent Magnet Synchronous Motor (PMSM) Axial Flux Interior Permanent Magnet (IPM) Surface Permanent Magnet (SPM) Electric Vehicles (EVs) Industrial Drives Predictive Modeling Efficiency Estimationnd industrial automation 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-7715956","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":523057033,"identity":"4f9b26bc-3620-45af-a651-bfa8647070f8","order_by":0,"name":"Rajesh G","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYHCCBAbGBgYehjPMB4AcCRlStLAlgLTwEGcPUAsDwxkeAxCbsBbz9gMPH/7cUSvDd+bM51c3aix4GNgPH92AT4vMmYRkY94zx3kkz/Zus845BnQYT1raDXxaJBgS0qQZ247xGJzn3WacwwbUIsFjhl8L/4P0nz/BWnieGef8I0aLREIaA29bDY/B2R7mx7ltRGl5kCzN23aAR/LMMTPm3D4JHjaCfuHPSfz4s63Onu9M8uPPOd/q5PjZDx/DqwUYEQlA4jCIxSYBJvErBwH2A0CiDsRi/kBY9SgYBaNgFIxEAAAj7kmviIZJfAAAAABJRU5ErkJggg==","orcid":"","institution":"\u0026Research Scholar at Anna university","correspondingAuthor":true,"prefix":"","firstName":"Rajesh","middleName":"","lastName":"G","suffix":""},{"id":523057034,"identity":"eb391fbe-fcda-4030-bc93-7c12411b9345","order_by":1,"name":"Sebasthirani K","email":"","orcid":"","institution":"Sri Ramakrishna Engineering College","correspondingAuthor":false,"prefix":"","firstName":"Sebasthirani","middleName":"","lastName":"K","suffix":""},{"id":523057035,"identity":"4ff6ddcd-d9e8-480b-ab60-44cbc504d9b9","order_by":2,"name":"Maruthupandi P","email":"","orcid":"","institution":"Government College of Technology","correspondingAuthor":false,"prefix":"","firstName":"Maruthupandi","middleName":"","lastName":"P","suffix":""},{"id":523057036,"identity":"6b455f99-3741-4c8f-b48e-112d24779cd1","order_by":3,"name":"Remyasree R","email":"","orcid":"","institution":"IDK Institutions","correspondingAuthor":false,"prefix":"","firstName":"Remyasree","middleName":"","lastName":"R","suffix":""}],"badges":[],"createdAt":"2025-09-25 20:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7715956/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7715956/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":99798028,"identity":"ca12d141-7b28-4756-9e5d-27e5ca2736d6","added_by":"auto","created_at":"2026-01-08 13:47:08","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":852703,"visible":true,"origin":"","legend":"","description":"","filename":"PredictiveModelingandComparativePerformanceAnalysisofPMSMDesignsinEVandIndustrialDrives.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7715956/v1_covered_c5d4265c-ac0c-4d1c-8266-a359b80d5740.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictive Modeling and Comparative Performance Analysis of PMSM Designs in EV and Industrial Drives","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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 (PMSM), Axial Flux, Interior Permanent Magnet (IPM), Surface Permanent Magnet (SPM), Electric Vehicles (EVs), Industrial Drives, Predictive Modeling, Efficiency Estimationnd industrial automation","lastPublishedDoi":"10.21203/rs.3.rs-7715956/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7715956/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Permanent Magnet Synchronous Motors (PMSMs) are increasingly adopted in electric vehicles (EVs) and industrial drives due to their high efficiency and torque density. However, performance varies with motor topology, operating conditions, and thermal management. This study presents a comparative evaluation of three PMSM types—Axial Flux, Interior Permanent Magnet (IPM), and Surface Permanent Magnet (SPM)—using a subset of 1,000 records from the PMSM Smart Control Dataset (Kaggle), containing 15 electrical and thermal parameters. Statistical analysis and comparative plots were used to examine efficiency, torque–speed characteristics, current and voltage demand, and temperature rise under different load conditions, cooling methods, and application modes.\nResults show that SPM motors achieve the highest efficiency (75.9%) and superior thermal stability, making them suitable for sustained EV traction, while IPM motors provide strong torque density and wide-speed performance. Axial Flux motors, with compact geometry and steady torque, are most advantageous in constant-torque industrial drives.\nIn addition, predictive modeling was employed to estimate efficiency from electrical, thermal, and categorical descriptors. A linear regression model achieved R² ≈ 0.62 on the test dataset, with stator/rotor temperatures, current, and operating mode identified as the most influential predictors. 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