Intelligence Based Full Car with Driver Active Suspension System for Refinement of Ride Comfort

Intelligence Based Full Car with Driver Active Suspension System for Refinement of Ride Comfort | 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 Intelligence Based Full Car with Driver Active Suspension System for Refinement of Ride Comfort Fahira Haseen S, Lakshmi P, Aathirai S P This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3271871/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 A suspension system plays an active role in balancing the conflicting requirements of stability and ride comfort in an automobile. The health of the driver is an important aspect since continuous exposure to vehicle vibrations may lead to severe health hazards in long run. In this study, full car with driver model of 13 Degrees of Freedom (DOF) is considered. The vehicle is tested under bump, pulse, half-sine and different classes of random road profiles (ISO 8608) for analysis in Matlab/Simulink environment. Initially the vehicle suspension is tested for a Proportional Integral and Derivative (PID) controller. To deal with higher complexity of the vehicle design, intelligent controllers are implemented. Fuzzy Logic Controller (FLC) is designed for the vehicle which plays a role in vibration suppression and ride comfort (ISO 2631-1 standard) improvement. This design is further enhanced by Adaptive Neuro-Fuzzy Inference System (ANFIS) controller which incorporates the advantages of both fuzzy and neural control system. The time domain analysis and ride comfort analysis show that ANFIS controller gives better control over linear PID controller, FLC and Passive Suspension System (PSS). To evaluate the effectiveness of the controller, it is tested for various classes of random road profile for varying speed condition. Simulation results show that ANFIS controller fed system gives better ride comfort and passenger safety by reducing the Root Mean Square (RMS) values of Head Acceleration (HA), Frequency Weighted RMS (FWRMS) values of HA, Vibration Dose Value (VDV) at the driver head and Power Spectrum Density (PSD) analysis of HA. Also, the proposed ANFIS controller is experimentally verified on laboratory Quarter car setup. It is tested on two road inputs namely pulse input and half-sine input. This analysis also proves that the ANFIS controller performs better than FLC and PSS. Fuzzy Logic Controller Adaptive Neuro-Fuzzy Inference System (ANFIS) controller Active Suspension System 13 DOF vehicle model Full Text 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-3271871","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":228513970,"identity":"13487ae1-acde-4769-a30c-ad51db8186d7","order_by":0,"name":"Fahira Haseen S","email":"","orcid":"","institution":"Anna University College of Engineering Guindy","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fahira","middleName":"Haseen","lastName":"S","suffix":""},{"id":228513971,"identity":"5c5a09e8-3a7d-4e78-aef2-23ead7904f80","order_by":1,"name":"Lakshmi P","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYFAC5gbGBoYDDGzsDRA+G4jgwauFEaqF5wCpWhgkEpAE8WkxZ2Bs/Djjz51oPsnHzx4X1BzO45NIYHzwtg23FssGxmbJjW3Pctuk08yNZxw7XMwmkcBsOBePFoMDjA2SDxsOA7UkmEnzsB1ObOM5wCbNi19L888Hf4BaJI9/k+b5B9bC/puAljbJDWxALRI8ZkDDgVrYG9iY8WkB+qXNcmYbUAtPTpk0b186UEtjs+Scc7i1mDMwH77ZA3TY/Pbj26R5vlknzm9mPvjhTRkeh8k/wBADxhM+YIBXdhSMglEwCkYBCAAAZvBTmED8EOwAAAAASUVORK5CYII=","orcid":"","institution":"Anna University Chennai","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Lakshmi","middleName":"","lastName":"P","suffix":""},{"id":228513972,"identity":"345819dc-5d52-4239-9ebf-cff6c1b37582","order_by":2,"name":"Aathirai S P","email":"","orcid":"","institution":"College of Engineering Guindy, Anna University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Aathirai","middleName":"S","lastName":"P","suffix":""}],"badges":[],"createdAt":"2023-08-17 10:43:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3271871/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3271871/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":44539832,"identity":"aab402a7-5e3b-474f-9f22-ca6f13f0d920","added_by":"auto","created_at":"2023-10-12 21:30:21","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":788794,"visible":true,"origin":"","legend":"","description":"","filename":"MANUSCRIPT.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3271871/v1_covered_2b20a67f-0a89-47e8-977b-2af54daae763.pdf"}],"financialInterests":"","formattedTitle":"Intelligence Based Full Car with Driver Active Suspension System for Refinement of Ride Comfort","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":"Fuzzy Logic Controller, Adaptive Neuro-Fuzzy Inference System (ANFIS) controller, Active Suspension System, 13 DOF vehicle model","lastPublishedDoi":"10.21203/rs.3.rs-3271871/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3271871/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA suspension system plays an active role in balancing the conflicting requirements of stability and ride comfort in an automobile. The health of the driver is an important aspect since continuous exposure to vehicle vibrations may lead to severe health hazards in long run. In this study, full car with driver model of 13 Degrees of Freedom (DOF) is considered. The vehicle is tested under bump, pulse, half-sine and different classes of random road profiles (ISO 8608) for analysis in Matlab/Simulink environment. Initially the vehicle suspension is tested for a Proportional Integral and Derivative (PID) controller. To deal with higher complexity of the vehicle design, intelligent controllers are implemented. Fuzzy Logic Controller (FLC) is designed for the vehicle which plays a role in vibration suppression and ride comfort (ISO 2631-1 standard) improvement. This design is further enhanced by Adaptive Neuro-Fuzzy Inference System (ANFIS) controller which incorporates the advantages of both fuzzy and neural control system. The time domain analysis and ride comfort analysis show that ANFIS controller gives better control over linear PID controller, FLC and Passive Suspension System (PSS). To evaluate the effectiveness of the controller, it is tested for various classes of random road profile for varying speed condition. Simulation results show that ANFIS controller fed system gives better ride comfort and passenger safety by reducing the Root Mean Square (RMS) values of Head Acceleration (HA), Frequency Weighted RMS (FWRMS) values of HA, Vibration Dose Value (VDV) at the driver head and Power Spectrum Density (PSD) analysis of HA. Also, the proposed ANFIS controller is experimentally verified on laboratory Quarter car setup. It is tested on two road inputs namely pulse input and half-sine input. 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