Harmonizing Aerodynamic Efficiency, Stability, and Acoustic Excellence: Multi-Objective Optimization for Electric Vehicle Rear-End Design

Harmonizing Aerodynamic Efficiency, Stability, and Acoustic Excellence: Multi-Objective Optimization for Electric Vehicle Rear-End Design | 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 Harmonizing Aerodynamic Efficiency, Stability, and Acoustic Excellence: Multi-Objective Optimization for Electric Vehicle Rear-End Design Sajjad Beigmoradi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4515048/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Nov, 2024 Read the published version in Multiscale and Multidisciplinary Modeling, Experiments and Design → Version 1 posted 11 You are reading this latest preprint version Abstract In recent years, the automotive field has exposed a significant surge in electrification, presenting a pivotal solution to environmental concerns. However, addressing the challenge of driving mileage remains a critical aspect in the realm of electric vehicles (EVs). Among the various factors influencing battery energy consumption during operation, aerodynamic force emerges as a primary contributor. Mitigating this force holds the key to substantial improvements in driving mileage, making it a focal point of exploration in this research. The impact of aerodynamic force extends beyond mere energy consumption; it intricately influences battery size, vehicle mileage, performance, stability, and passenger comfort. Navigating this multifaceted terrain poses a formidable challenge for automotive engineers engaged in the development of electric vehicles. This study undertakes the optimization of rear-end design factors for a hatchback electric vehicle, specifically addressing drag, lift, and aerodynamic noise objectives. Five critical geometric factors of the rear end – Rear Spoiler Length, Rear Spoiler Angle, Rear Diffuser Angle, Boat Tail Angle, and 5th Door Height – are identified as key design parameters. The interplay of these factors and their impact on objectives is systematically investigated through a Design of Experiment (DoE) approach. To enhance the efficiency of the investigation, a fractional factorial design method is utilized, effectively reducing the number of individual case studies. The formulation of regression equations, capturing the essence of significant terms for each objective, lays the groundwork for a subsequent multi-objective optimization process. This optimization, driven by the maximization of a composite desirability function, identifies optimal levels for each design factor. The research culminates in the selection of a model with optimum rear-end factors based on a comprehensive evaluation of drag, lift, and aerodynamic noise objectives. The aerodynamic performance surrounding this optimal model is intricately described, offering valuable insights into the holistic impact of the chosen design parameters on the electric vehicle's aerodynamics. Electric Vehicle Drag Reduction Vehicle Stability Aerodynamic Noise Multi-Objective Optimization Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Nov, 2024 Read the published version in Multiscale and Multidisciplinary Modeling, Experiments and Design → Version 1 posted Editorial decision: Revision requested 31 Jul, 2024 Reviews received at journal 31 Jul, 2024 Reviews received at journal 21 Jul, 2024 Reviewers agreed at journal 05 Jul, 2024 Reviewers agreed at journal 03 Jul, 2024 Reviewers agreed at journal 03 Jul, 2024 Reviewers agreed at journal 04 Jun, 2024 Reviewers invited by journal 03 Jun, 2024 Submission checks completed at journal 03 Jun, 2024 Editor assigned by journal 03 Jun, 2024 First submitted to journal 01 Jun, 2024 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-4515048","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":310415631,"identity":"229469ad-d8a2-4ddd-81e6-791c7b6915a0","order_by":0,"name":"Sajjad Beigmoradi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIiWNgGAWjYHCCBAMGNoYEBmYIj7GNvYGB4QFpWngOAMUIWsSGUMPYIJGAX4t8+4EHBT/KGPL42dmvbvi4x062T/LxM6AuOzndBuxaDM4kJBj2nGMolmzmKbs541mycZt0mhlQS7Kx2QEcWhgSEgx42xgSNxzmSbvNc4A5sU06wdgggeFA4jYcWuT7HyQY/gVq2Q/RUp/YJnn8M14tDDcSEozBtjCzHwNqOZzYJsFj+ACfFoMbDxKMZc5JFEsc5mG7OePAceM2npzCBwkGuP0i35+TZvimzCaPv//4sxsfDlTLzm8/vuHAhwo7OVxaGBh40gwYGCRADAOUYMED2A8/gDIe4FM2CkbBKBgFIxgAAMwwYggddIdmAAAAAElFTkSuQmCC","orcid":"","institution":"AVL Powertrain UK","correspondingAuthor":true,"prefix":"","firstName":"Sajjad","middleName":"","lastName":"Beigmoradi","suffix":""}],"badges":[],"createdAt":"2024-06-01 22:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4515048/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4515048/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s41939-024-00633-x","type":"published","date":"2024-11-14T15:57:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":69274951,"identity":"0aad50bc-d8e3-4dd1-81e3-73da7944d554","added_by":"auto","created_at":"2024-11-18 16:40:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":724406,"visible":true,"origin":"","legend":"","description":"","filename":"MMMEDBeigmoradiDraft.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4515048/v1_covered_981febfc-9b95-4f70-83c7-561cf618cb24.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Harmonizing Aerodynamic Efficiency, Stability, and Acoustic Excellence: Multi-Objective Optimization for Electric Vehicle Rear-End Design","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"multiscale-and-multidisciplinary-modeling-experiments-and-design","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mmed","sideBox":"Learn more about [Multiscale and Multidisciplinary Modeling, Experiments and Design](https://link.springer.com/journal/41939)","snPcode":"41939","submissionUrl":"https://submission.nature.com/new-submission/41939/3","title":"Multiscale and Multidisciplinary Modeling, Experiments and Design","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Electric Vehicle, Drag Reduction, Vehicle Stability, Aerodynamic Noise, Multi-Objective Optimization","lastPublishedDoi":"10.21203/rs.3.rs-4515048/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4515048/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn recent years, the automotive field has exposed a significant surge in electrification, presenting a pivotal solution to environmental concerns. However, addressing the challenge of driving mileage remains a critical aspect in the realm of electric vehicles (EVs). Among the various factors influencing battery energy consumption during operation, aerodynamic force emerges as a primary contributor. Mitigating this force holds the key to substantial improvements in driving mileage, making it a focal point of exploration in this research. The impact of aerodynamic force extends beyond mere energy consumption; it intricately influences battery size, vehicle mileage, performance, stability, and passenger comfort. Navigating this multifaceted terrain poses a formidable challenge for automotive engineers engaged in the development of electric vehicles. This study undertakes the optimization of rear-end design factors for a hatchback electric vehicle, specifically addressing drag, lift, and aerodynamic noise objectives.\u003c/p\u003e \u003cp\u003eFive critical geometric factors of the rear end \u0026ndash; Rear Spoiler Length, Rear Spoiler Angle, Rear Diffuser Angle, Boat Tail Angle, and 5th Door Height \u0026ndash; are identified as key design parameters. The interplay of these factors and their impact on objectives is systematically investigated through a Design of Experiment (DoE) approach. To enhance the efficiency of the investigation, a fractional factorial design method is utilized, effectively reducing the number of individual case studies.\u003c/p\u003e \u003cp\u003eThe formulation of regression equations, capturing the essence of significant terms for each objective, lays the groundwork for a subsequent multi-objective optimization process. This optimization, driven by the maximization of a composite desirability function, identifies optimal levels for each design factor. The research culminates in the selection of a model with optimum rear-end factors based on a comprehensive evaluation of drag, lift, and aerodynamic noise objectives. The aerodynamic performance surrounding this optimal model is intricately described, offering valuable insights into the holistic impact of the chosen design parameters on the electric vehicle's aerodynamics.\u003c/p\u003e","manuscriptTitle":"Harmonizing Aerodynamic Efficiency, Stability, and Acoustic Excellence: Multi-Objective Optimization for Electric Vehicle Rear-End Design","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-14 09:13:04","doi":"10.21203/rs.3.rs-4515048/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-31T22:44:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-31T21:50:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-21T16:12:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"194393863847376918132442931614987087688","date":"2024-07-05T08:28:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"113913198635715367798723893272181019175","date":"2024-07-03T16:56:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122559076568613395082330509105771362358","date":"2024-07-03T09:07:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"314008745760379744053379409757873302741","date":"2024-06-04T04:20:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-03T16:39:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-03T06:31:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-03T06:31:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Multiscale and Multidisciplinary Modeling, Experiments and Design","date":"2024-06-01T22:16:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"multiscale-and-multidisciplinary-modeling-experiments-and-design","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mmed","sideBox":"Learn more about [Multiscale and Multidisciplinary Modeling, Experiments and Design](https://link.springer.com/journal/41939)","snPcode":"41939","submissionUrl":"https://submission.nature.com/new-submission/41939/3","title":"Multiscale and Multidisciplinary Modeling, Experiments and Design","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"48a24851-4322-4caf-b619-3ebb29c173ee","owner":[],"postedDate":"June 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-18T16:00:55+00:00","versionOfRecord":{"articleIdentity":"rs-4515048","link":"https://doi.org/10.1007/s41939-024-00633-x","journal":{"identity":"multiscale-and-multidisciplinary-modeling-experiments-and-design","isVorOnly":false,"title":"Multiscale and Multidisciplinary Modeling, Experiments and Design"},"publishedOn":"2024-11-14 15:57:17","publishedOnDateReadable":"November 14th, 2024"},"versionCreatedAt":"2024-06-14 09:13:04","video":"","vorDoi":"10.1007/s41939-024-00633-x","vorDoiUrl":"https://doi.org/10.1007/s41939-024-00633-x","workflowStages":[]},"version":"v1","identity":"rs-4515048","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4515048","identity":"rs-4515048","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}