Loading…
Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling
Due to the rise in awareness of global warming, many attempts to increase efficiency in the automotive industry are becoming prevalent. Design optimization can be used to increase the efficiency of electric vehicles by reducing aerodynamic drag and lift. The main focus of this paper is to analyse an...
Saved in:
Published in: | Entropy (Basel, Switzerland) Switzerland), 2022-11, Vol.24 (11), p.1584 |
---|---|
Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c485t-fe968b0db10373917df50c2a4fee2afbcd45e3e3d714c36c45b4b43f178747d33 |
---|---|
cites | cdi_FETCH-LOGICAL-c485t-fe968b0db10373917df50c2a4fee2afbcd45e3e3d714c36c45b4b43f178747d33 |
container_end_page | |
container_issue | 11 |
container_start_page | 1584 |
container_title | Entropy (Basel, Switzerland) |
container_volume | 24 |
creator | Afianto, Darryl Han, Yu Yan, Peiliang Yang, Yan Elbarghthi, Anas F. A. Wen, Chuang |
description | Due to the rise in awareness of global warming, many attempts to increase efficiency in the automotive industry are becoming prevalent. Design optimization can be used to increase the efficiency of electric vehicles by reducing aerodynamic drag and lift. The main focus of this paper is to analyse and optimise the aerodynamic characteristics of an electric vehicle to improve efficiency of using computational fluid dynamics modelling. Multiple part modifications were used to improve the drag and lift of the electric hatchback, testing various designs and dimensions. The numerical model of the study was validated using previous experimental results obtained from the literature. Simulation results are analysed in detail, including velocity magnitude, drag coefficient, drag force and lift coefficient. The modifications achieved in this research succeeded in reducing drag and were validated through some appropriate sources. The final model has been assembled with all modifications and is represented in this research. The results show that the base model attained an aerodynamic drag coefficient of 0.464, while the final design achieved a reasonably better overall performance by recording a 10% reduction in the drag coefficient. Moreover, within individual comparison with the final model, the second model with front spitter had an insignificant improvement, limited to 1.17%, compared with 11.18% when the rear diffuser was involved separately. In addition, the lift coefficient was significantly reduced to 73%, providing better stabilities and accounting for the safety measurements, especially at high velocity. The prediction of the airflow improvement was visualised, including the pathline contours consistent with the solutions. These research results provide a considerable transformation in the transportation field and help reduce fuel expenses and global emissions. |
doi_str_mv | 10.3390/e24111584 |
format | article |
fullrecord | <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_0f867dbf9af241f6968467cc7158db1f</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A745709572</galeid><doaj_id>oai_doaj_org_article_0f867dbf9af241f6968467cc7158db1f</doaj_id><sourcerecordid>A745709572</sourcerecordid><originalsourceid>FETCH-LOGICAL-c485t-fe968b0db10373917df50c2a4fee2afbcd45e3e3d714c36c45b4b43f178747d33</originalsourceid><addsrcrecordid>eNpdksFuGyEQhlHVqkndHvoGSL20B6ewwLJ7qRQ5TmMpVS5Nr4iFwcHahS3sRvLbF9tRlFQcBg0_38z8GoQ-U3LBWEu-Q8UppaLhb9A5JW275IyQty_uZ-hDzjtCKlbR-j06YzUTbS35OfJ34-QHn_XkY8A6WLx2zhsPwezxZhhTfIQBwoSjw-sezJS8wX_gwZseMr7PPmzxKg7jPB0JusfX_ewtvtoHPXiT8a9ooe-L7CN653Sf4dNTXKD76_Xv1c3y9u7nZnV5uzS8EdPSQVs3HbEdJUyylkrrBDGV5g6g0q4zlgtgwKyk3LDacNHxjjNHZSO5tIwt0ObEtVHv1Jj8oNNeRe3VMRHTVuk0HfpXxDW1tJ1rtSsOurpU5rU0RhYvSwOusH6cWOPcDWBNMSLp_hX09UvwD2obH1UhtZyJAvj6BEjx7wx5UsVrUwzRAeKcVSWZaMqQJS7Ql_-kuzin4uhRxeuKVvygujiptroM4IOLpa4px0KxOwZwvuQvJReStEJW5cO30weTYs4J3HP3lKjD9qjn7WH_AICPtlM</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2734621247</pqid></control><display><type>article</type><title>Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling</title><source>Publicly Available Content Database</source><source>DOAJ Directory of Open Access Journals</source><source>PubMed Central</source><creator>Afianto, Darryl ; Han, Yu ; Yan, Peiliang ; Yang, Yan ; Elbarghthi, Anas F. A. ; Wen, Chuang</creator><creatorcontrib>Afianto, Darryl ; Han, Yu ; Yan, Peiliang ; Yang, Yan ; Elbarghthi, Anas F. A. ; Wen, Chuang</creatorcontrib><description>Due to the rise in awareness of global warming, many attempts to increase efficiency in the automotive industry are becoming prevalent. Design optimization can be used to increase the efficiency of electric vehicles by reducing aerodynamic drag and lift. The main focus of this paper is to analyse and optimise the aerodynamic characteristics of an electric vehicle to improve efficiency of using computational fluid dynamics modelling. Multiple part modifications were used to improve the drag and lift of the electric hatchback, testing various designs and dimensions. The numerical model of the study was validated using previous experimental results obtained from the literature. Simulation results are analysed in detail, including velocity magnitude, drag coefficient, drag force and lift coefficient. The modifications achieved in this research succeeded in reducing drag and were validated through some appropriate sources. The final model has been assembled with all modifications and is represented in this research. The results show that the base model attained an aerodynamic drag coefficient of 0.464, while the final design achieved a reasonably better overall performance by recording a 10% reduction in the drag coefficient. Moreover, within individual comparison with the final model, the second model with front spitter had an insignificant improvement, limited to 1.17%, compared with 11.18% when the rear diffuser was involved separately. In addition, the lift coefficient was significantly reduced to 73%, providing better stabilities and accounting for the safety measurements, especially at high velocity. The prediction of the airflow improvement was visualised, including the pathline contours consistent with the solutions. These research results provide a considerable transformation in the transportation field and help reduce fuel expenses and global emissions.</description><identifier>ISSN: 1099-4300</identifier><identifier>EISSN: 1099-4300</identifier><identifier>DOI: 10.3390/e24111584</identifier><identifier>PMID: 36359674</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Aerodynamic characteristics ; Aerodynamic coefficients ; Aerodynamic drag ; aerodynamics ; Air flow ; Automobile industry ; Automobiles ; Bans ; Boundary conditions ; Computational fluid dynamics ; Computer simulation ; Computer-generated environments ; Consumption ; Control ; design ; Design optimization ; Diffusers ; Drag ; Drag coefficients ; Drag reduction ; electric hatchback ; electric vehicle ; Electric vehicles ; Energy efficiency ; Energy use ; Fluid dynamics ; fuel efficiency ; Mathematical optimization ; Methods ; Numerical models ; optimization ; Simulation ; Turbulence models ; Velocity ; Wind</subject><ispartof>Entropy (Basel, Switzerland), 2022-11, Vol.24 (11), p.1584</ispartof><rights>COPYRIGHT 2022 MDPI AG</rights><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c485t-fe968b0db10373917df50c2a4fee2afbcd45e3e3d714c36c45b4b43f178747d33</citedby><cites>FETCH-LOGICAL-c485t-fe968b0db10373917df50c2a4fee2afbcd45e3e3d714c36c45b4b43f178747d33</cites><orcidid>0000-0002-4445-1589 ; 0000-0002-4187-3655</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2734621247/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2734621247?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids></links><search><creatorcontrib>Afianto, Darryl</creatorcontrib><creatorcontrib>Han, Yu</creatorcontrib><creatorcontrib>Yan, Peiliang</creatorcontrib><creatorcontrib>Yang, Yan</creatorcontrib><creatorcontrib>Elbarghthi, Anas F. A.</creatorcontrib><creatorcontrib>Wen, Chuang</creatorcontrib><title>Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling</title><title>Entropy (Basel, Switzerland)</title><description>Due to the rise in awareness of global warming, many attempts to increase efficiency in the automotive industry are becoming prevalent. Design optimization can be used to increase the efficiency of electric vehicles by reducing aerodynamic drag and lift. The main focus of this paper is to analyse and optimise the aerodynamic characteristics of an electric vehicle to improve efficiency of using computational fluid dynamics modelling. Multiple part modifications were used to improve the drag and lift of the electric hatchback, testing various designs and dimensions. The numerical model of the study was validated using previous experimental results obtained from the literature. Simulation results are analysed in detail, including velocity magnitude, drag coefficient, drag force and lift coefficient. The modifications achieved in this research succeeded in reducing drag and were validated through some appropriate sources. The final model has been assembled with all modifications and is represented in this research. The results show that the base model attained an aerodynamic drag coefficient of 0.464, while the final design achieved a reasonably better overall performance by recording a 10% reduction in the drag coefficient. Moreover, within individual comparison with the final model, the second model with front spitter had an insignificant improvement, limited to 1.17%, compared with 11.18% when the rear diffuser was involved separately. In addition, the lift coefficient was significantly reduced to 73%, providing better stabilities and accounting for the safety measurements, especially at high velocity. The prediction of the airflow improvement was visualised, including the pathline contours consistent with the solutions. These research results provide a considerable transformation in the transportation field and help reduce fuel expenses and global emissions.</description><subject>Aerodynamic characteristics</subject><subject>Aerodynamic coefficients</subject><subject>Aerodynamic drag</subject><subject>aerodynamics</subject><subject>Air flow</subject><subject>Automobile industry</subject><subject>Automobiles</subject><subject>Bans</subject><subject>Boundary conditions</subject><subject>Computational fluid dynamics</subject><subject>Computer simulation</subject><subject>Computer-generated environments</subject><subject>Consumption</subject><subject>Control</subject><subject>design</subject><subject>Design optimization</subject><subject>Diffusers</subject><subject>Drag</subject><subject>Drag coefficients</subject><subject>Drag reduction</subject><subject>electric hatchback</subject><subject>electric vehicle</subject><subject>Electric vehicles</subject><subject>Energy efficiency</subject><subject>Energy use</subject><subject>Fluid dynamics</subject><subject>fuel efficiency</subject><subject>Mathematical optimization</subject><subject>Methods</subject><subject>Numerical models</subject><subject>optimization</subject><subject>Simulation</subject><subject>Turbulence models</subject><subject>Velocity</subject><subject>Wind</subject><issn>1099-4300</issn><issn>1099-4300</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdksFuGyEQhlHVqkndHvoGSL20B6ewwLJ7qRQ5TmMpVS5Nr4iFwcHahS3sRvLbF9tRlFQcBg0_38z8GoQ-U3LBWEu-Q8UppaLhb9A5JW275IyQty_uZ-hDzjtCKlbR-j06YzUTbS35OfJ34-QHn_XkY8A6WLx2zhsPwezxZhhTfIQBwoSjw-sezJS8wX_gwZseMr7PPmzxKg7jPB0JusfX_ewtvtoHPXiT8a9ooe-L7CN653Sf4dNTXKD76_Xv1c3y9u7nZnV5uzS8EdPSQVs3HbEdJUyylkrrBDGV5g6g0q4zlgtgwKyk3LDacNHxjjNHZSO5tIwt0ObEtVHv1Jj8oNNeRe3VMRHTVuk0HfpXxDW1tJ1rtSsOurpU5rU0RhYvSwOusH6cWOPcDWBNMSLp_hX09UvwD2obH1UhtZyJAvj6BEjx7wx5UsVrUwzRAeKcVSWZaMqQJS7Ql_-kuzin4uhRxeuKVvygujiptroM4IOLpa4px0KxOwZwvuQvJReStEJW5cO30weTYs4J3HP3lKjD9qjn7WH_AICPtlM</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Afianto, Darryl</creator><creator>Han, Yu</creator><creator>Yan, Peiliang</creator><creator>Yang, Yan</creator><creator>Elbarghthi, Anas F. A.</creator><creator>Wen, Chuang</creator><general>MDPI AG</general><general>MDPI</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-4445-1589</orcidid><orcidid>https://orcid.org/0000-0002-4187-3655</orcidid></search><sort><creationdate>20221101</creationdate><title>Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling</title><author>Afianto, Darryl ; Han, Yu ; Yan, Peiliang ; Yang, Yan ; Elbarghthi, Anas F. A. ; Wen, Chuang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c485t-fe968b0db10373917df50c2a4fee2afbcd45e3e3d714c36c45b4b43f178747d33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aerodynamic characteristics</topic><topic>Aerodynamic coefficients</topic><topic>Aerodynamic drag</topic><topic>aerodynamics</topic><topic>Air flow</topic><topic>Automobile industry</topic><topic>Automobiles</topic><topic>Bans</topic><topic>Boundary conditions</topic><topic>Computational fluid dynamics</topic><topic>Computer simulation</topic><topic>Computer-generated environments</topic><topic>Consumption</topic><topic>Control</topic><topic>design</topic><topic>Design optimization</topic><topic>Diffusers</topic><topic>Drag</topic><topic>Drag coefficients</topic><topic>Drag reduction</topic><topic>electric hatchback</topic><topic>electric vehicle</topic><topic>Electric vehicles</topic><topic>Energy efficiency</topic><topic>Energy use</topic><topic>Fluid dynamics</topic><topic>fuel efficiency</topic><topic>Mathematical optimization</topic><topic>Methods</topic><topic>Numerical models</topic><topic>optimization</topic><topic>Simulation</topic><topic>Turbulence models</topic><topic>Velocity</topic><topic>Wind</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Afianto, Darryl</creatorcontrib><creatorcontrib>Han, Yu</creatorcontrib><creatorcontrib>Yan, Peiliang</creatorcontrib><creatorcontrib>Yang, Yan</creatorcontrib><creatorcontrib>Elbarghthi, Anas F. A.</creatorcontrib><creatorcontrib>Wen, Chuang</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Entropy (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Afianto, Darryl</au><au>Han, Yu</au><au>Yan, Peiliang</au><au>Yang, Yan</au><au>Elbarghthi, Anas F. A.</au><au>Wen, Chuang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling</atitle><jtitle>Entropy (Basel, Switzerland)</jtitle><date>2022-11-01</date><risdate>2022</risdate><volume>24</volume><issue>11</issue><spage>1584</spage><pages>1584-</pages><issn>1099-4300</issn><eissn>1099-4300</eissn><abstract>Due to the rise in awareness of global warming, many attempts to increase efficiency in the automotive industry are becoming prevalent. Design optimization can be used to increase the efficiency of electric vehicles by reducing aerodynamic drag and lift. The main focus of this paper is to analyse and optimise the aerodynamic characteristics of an electric vehicle to improve efficiency of using computational fluid dynamics modelling. Multiple part modifications were used to improve the drag and lift of the electric hatchback, testing various designs and dimensions. The numerical model of the study was validated using previous experimental results obtained from the literature. Simulation results are analysed in detail, including velocity magnitude, drag coefficient, drag force and lift coefficient. The modifications achieved in this research succeeded in reducing drag and were validated through some appropriate sources. The final model has been assembled with all modifications and is represented in this research. The results show that the base model attained an aerodynamic drag coefficient of 0.464, while the final design achieved a reasonably better overall performance by recording a 10% reduction in the drag coefficient. Moreover, within individual comparison with the final model, the second model with front spitter had an insignificant improvement, limited to 1.17%, compared with 11.18% when the rear diffuser was involved separately. In addition, the lift coefficient was significantly reduced to 73%, providing better stabilities and accounting for the safety measurements, especially at high velocity. The prediction of the airflow improvement was visualised, including the pathline contours consistent with the solutions. These research results provide a considerable transformation in the transportation field and help reduce fuel expenses and global emissions.</abstract><cop>Basel</cop><pub>MDPI AG</pub><pmid>36359674</pmid><doi>10.3390/e24111584</doi><orcidid>https://orcid.org/0000-0002-4445-1589</orcidid><orcidid>https://orcid.org/0000-0002-4187-3655</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1099-4300 |
ispartof | Entropy (Basel, Switzerland), 2022-11, Vol.24 (11), p.1584 |
issn | 1099-4300 1099-4300 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_0f867dbf9af241f6968467cc7158db1f |
source | Publicly Available Content Database; DOAJ Directory of Open Access Journals; PubMed Central |
subjects | Aerodynamic characteristics Aerodynamic coefficients Aerodynamic drag aerodynamics Air flow Automobile industry Automobiles Bans Boundary conditions Computational fluid dynamics Computer simulation Computer-generated environments Consumption Control design Design optimization Diffusers Drag Drag coefficients Drag reduction electric hatchback electric vehicle Electric vehicles Energy efficiency Energy use Fluid dynamics fuel efficiency Mathematical optimization Methods Numerical models optimization Simulation Turbulence models Velocity Wind |
title | Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T03%3A25%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Optimisation%20and%20Efficiency%20Improvement%20of%20Electric%20Vehicles%20Using%20Computational%20Fluid%20Dynamics%20Modelling&rft.jtitle=Entropy%20(Basel,%20Switzerland)&rft.au=Afianto,%20Darryl&rft.date=2022-11-01&rft.volume=24&rft.issue=11&rft.spage=1584&rft.pages=1584-&rft.issn=1099-4300&rft.eissn=1099-4300&rft_id=info:doi/10.3390/e24111584&rft_dat=%3Cgale_doaj_%3EA745709572%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c485t-fe968b0db10373917df50c2a4fee2afbcd45e3e3d714c36c45b4b43f178747d33%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2734621247&rft_id=info:pmid/36359674&rft_galeid=A745709572&rfr_iscdi=true |