Vibration and noise reduction of the drive motor bearings using RBMO and PPO

Vibration and noise reduction of the drive motor bearings using RBMO and PPO | 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 Vibration and noise reduction of the drive motor bearings using RBMO and PPO Jun Yu, Yanan Zhang, Xinxin Jin, Shi Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8798466/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 To improve the ride comfort of new energy vehicles, a vibration and noise reduction method for the drive motor bearings of new energy vehicles using red-billed blue magpie optimizer (RBMO) and proximal policy optimization (PPO) is proposed. Combining the Tent map with the Sine map, the Tent-Sine map is designed to initialize the positions of red-billed blue magpies, make the distribution of individuals in the population more uniform, and enhance the randomness and traversal of population initialization. The nonlinear cosine function calculation formula of the equilibrium population coefficient is introduced. Thus, the equilibrium population coefficient stays at a higher value in the early stage, enabling the algorithm to search over a larger range, explore more areas, and enhance the algorithm's global search capabilities. Moreover, in the later stage, it converges to smaller values earlier and conducts precise searches for the possible regions where the optimal solution may exist in order to improve the local convergence speed and search accuracy. PPO is introduced into RBMO, which enables RBMO to make autonomous decisions on foraging manners based on experience and rewards, which weakens the sensitivity of the initial parameter settings, solves the problem of being stuck in local optima, and accelerates the convergence speed of the algorithm. Simulation analyses demonstrate that the optimized bearings of the new energy vehicle drive motor using this method meet the requirements of high speed, low vibration, and low noise. Experimental investigations demonstrate that the proposed method effectively suppresses the vibration and noise generated by the drive-motor bearings of new-energy vehicles and reduces their peak values. The noise signal of the optimized bearing exhibits a smoother profile without noticeable whine noise. drive motor bearing new energy vehicle vibration and noise reduction red-billed blue magpie optimizer proximal policy optimization 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-8798466","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":589699489,"identity":"547823af-2ddf-427b-978b-9cb4d7198450","order_by":0,"name":"Jun Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYDACCRDBxsAjz8x88EFChQ3xWmQM29uSDR6cSSNeiw3DmTNmkg/bDhHWIT+7+djDL2V2PIwzEswqEtgOMPC3dyfg1WJw51i6scy5ZB52iYS0Gwk8dxgkzpzdgF+LRI6ZtGQbM8iWYzcSJJ4BRXLxa5Gfkf8NqKWeh+FGYltBgsFhwloYbuSwSX5sO8zDcOYwG0NCAhFaDG6kmUkznDvOAwxkZomEA2k8BP0iPyP5meSPsmp7eWb+jx9//rOR42/vJeAwIGDmQeLw4FSGDBh/EKVsFIyCUTAKRiwAAGLuSVBFq6PMAAAAAElFTkSuQmCC","orcid":"","institution":"Harbin University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Yu","suffix":""},{"id":589699490,"identity":"657b098f-4471-43b1-8066-0051344e10ec","order_by":1,"name":"Yanan Zhang","email":"","orcid":"","institution":"Henan University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Yanan","middleName":"","lastName":"Zhang","suffix":""},{"id":589699492,"identity":"5e511ca8-8326-412d-9479-99878d8e56ab","order_by":2,"name":"Xinxin Jin","email":"","orcid":"","institution":"Harbin University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Xinxin","middleName":"","lastName":"Jin","suffix":""},{"id":589699495,"identity":"da5d7433-54e6-4abe-b1f2-9d070016d274","order_by":3,"name":"Shi Wu","email":"","orcid":"","institution":"Harbin University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Shi","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2026-02-05 14:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8798466/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8798466/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108900266,"identity":"548bdb06-d72f-46f6-b737-3c1e1b81db80","added_by":"auto","created_at":"2026-05-10 08:10:55","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":846358,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8798466/v1_covered_9861110d-42ce-402e-95b6-2a2486451edd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Vibration and noise reduction of the drive motor bearings using RBMO and PPO","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":"drive motor bearing, new energy vehicle, vibration and noise reduction, red-billed blue magpie optimizer, proximal policy optimization","lastPublishedDoi":"10.21203/rs.3.rs-8798466/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8798466/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo improve the ride comfort of new energy vehicles, a vibration and noise reduction method for the drive motor bearings of new energy vehicles using red-billed blue magpie optimizer (RBMO) and proximal policy optimization (PPO) is proposed. Combining the Tent map with the Sine map, the Tent-Sine map is designed to initialize the positions of red-billed blue magpies, make the distribution of individuals in the population more uniform, and enhance the randomness and traversal of population initialization. The nonlinear cosine function calculation formula of the equilibrium population coefficient is introduced. Thus, the equilibrium population coefficient stays at a higher value in the early stage, enabling the algorithm to search over a larger range, explore more areas, and enhance the algorithm's global search capabilities. Moreover, in the later stage, it converges to smaller values earlier and conducts precise searches for the possible regions where the optimal solution may exist in order to improve the local convergence speed and search accuracy. PPO is introduced into RBMO, which enables RBMO to make autonomous decisions on foraging manners based on experience and rewards, which weakens the sensitivity of the initial parameter settings, solves the problem of being stuck in local optima, and accelerates the convergence speed of the algorithm. Simulation analyses demonstrate that the optimized bearings of the new energy vehicle drive motor using this method meet the requirements of high speed, low vibration, and low noise. Experimental investigations demonstrate that the proposed method effectively suppresses the vibration and noise generated by the drive-motor bearings of new-energy vehicles and reduces their peak values. 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