Solar-Assisted Emergency Portable Battery Charger for Electric Vehicles: A Model-Free Nonlinear Integral Backstepping Controller Optimised by Deep Deterministic Policy Gradient

Solar-Assisted Emergency Portable Battery Charger for Electric Vehicles: A Model-Free Nonlinear Integral Backstepping Controller Optimised by Deep Deterministic Policy Gradient | 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 Solar-Assisted Emergency Portable Battery Charger for Electric Vehicles: A Model-Free Nonlinear Integral Backstepping Controller Optimised by Deep Deterministic Policy Gradient Santhoshkumar¹ R, Suresh² S This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9195214/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 The design, stability analysis and real-time validation of a Solar-Assisted Emergency Portable Battery Charger (SA-EPBC) for use with Electric Vehicles (EVs) is presented in this research. This system uses solar photovoltaic (PV) energy, harvested using a perturb-and-observe MPPT algorithm and a unidirectional dual-active-bridge (DAB) DC-DC converter to provide regulated electricity to charge an EV that has become stranded and is unable to be charged. The output of the converter is controlled by a model-free nonlinear integral backstepping controller (MF-NIBC) which is designed to operate without requiring an explicit model of the dynamic characteristics of the plant, and will therefore remain inherently robust to changes in battery parameters and load transients. The MF-NIBC adapts three scalar controller gains online using a deep deterministic policy gradient (DDPG) reinforcement learning agent, and the critic aspect of this architecture is treated as a continuous-action Markov decision process. A composite Lyapunov function has been used to establish the asymptotic solidity of this closed-loop controller mathematically. Testing of this MF-NIBC controller was completed using hardware-in-the-loop (HIL) experiments on the OPAL-RT OP4510 hardware platform under conditions simulating three different types of EV battery operating voltages (400/400V, 400/300V and 400/500V), and showed that the proposed controller resulted in a voltage settling time of less than 18 ms, maximum overshoot of less than 3.2%, and steady-state error of better than +/-0.5V, each of these variables improved by 62% and 44%, respectively, compared to the baseline proportional-integral controller and model predictive controller. In addition, all test cases resulted in an end-to-end conversion efficiency exceeding 93.1%. Dual-Active-Bridge converter Model-free backstepping control deep deterministic policy gradient electric vehicle emergency charging solar photovoltaic Hardware-in-the-loop simulation 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-9195214","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":613999122,"identity":"0daf78ab-d05d-4f35-a539-024951dbe782","order_by":0,"name":"Santhoshkumar¹ R","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYJACZiBOkIBy5ODCbLh1MDYjazEmXUtiAyFHybefPf64oKIuT3JGduLnCoZ76fNnHz74gaHGjoFPGrtugzN5ic0zzhwulpbI3Sx5hqE4d8O5tGQJhmPJDGwyB7BrYcgxbOZtO5A4TyJ3g2QDQ0LuBh4eM6BHDjCwSSRgd1j/G5CWOpCWzT+BWtLle/i/MTD8w62F4QbYFubE2RK520C2JDCc4WFjYGzDrcXgxhvD2TxnDifO7Hm7zbLBIMFwwxk2Y4nEvmQe3A7LMfjMU1GXOON47uabDRUJ8vI9zA8/fPhmJyc/A4fD0EMDAoCKeYhRPwpGwSgYBaMAOwAAC55W10NBW84AAAAASUVORK5CYII=","orcid":"","institution":"Sri Ramakrishna Engineering College","correspondingAuthor":true,"prefix":"","firstName":"Santhoshkumar¹","middleName":"","lastName":"R","suffix":""},{"id":613999123,"identity":"c2361995-5de0-4812-b060-d3de165c4e6b","order_by":1,"name":"Suresh² S","email":"","orcid":"","institution":"Sri Eshwar College of Engineering","correspondingAuthor":false,"prefix":"","firstName":"Suresh²","middleName":"","lastName":"S","suffix":""}],"badges":[],"createdAt":"2026-03-23 03:53:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9195214/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9195214/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108688688,"identity":"b1ad0650-ae79-4664-ac2b-42546e2c36ed","added_by":"auto","created_at":"2026-05-07 10:28:11","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":444362,"visible":true,"origin":"","legend":"","description":"","filename":"SolarAssistedEmergencyPortableBatteryChargerforElectricVehicles.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9195214/v1_covered_b8b28376-4f0d-4636-9339-555437b8b164.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Solar-Assisted Emergency Portable Battery Charger for Electric Vehicles: A Model-Free Nonlinear Integral Backstepping Controller Optimised by Deep Deterministic Policy Gradient","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":"Dual-Active-Bridge converter, Model-free backstepping control, deep deterministic policy gradient, electric vehicle emergency charging, solar photovoltaic, Hardware-in-the-loop simulation","lastPublishedDoi":"10.21203/rs.3.rs-9195214/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9195214/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe design, stability analysis and real-time validation of a Solar-Assisted Emergency Portable Battery Charger (SA-EPBC) for use with Electric Vehicles (EVs) is presented in this research. This system uses solar photovoltaic (PV) energy, harvested using a perturb-and-observe MPPT algorithm and a unidirectional dual-active-bridge (DAB) DC-DC converter to provide regulated electricity to charge an EV that has become stranded and is unable to be charged. The output of the converter is controlled by a model-free nonlinear integral backstepping controller (MF-NIBC) which is designed to operate without requiring an explicit model of the dynamic characteristics of the plant, and will therefore remain inherently robust to changes in battery parameters and load transients. The MF-NIBC adapts three scalar controller gains online using a deep deterministic policy gradient (DDPG) reinforcement learning agent, and the critic aspect of this architecture is treated as a continuous-action Markov decision process. A composite Lyapunov function has been used to establish the asymptotic solidity of this closed-loop controller mathematically. 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