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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...

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Autores principales: Afianto, Darryl, Han, Yu, Yan, Peiliang, Yang, Yan, Elbarghthi, Anas F. A., Wen, Chuang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689435/
https://www.ncbi.nlm.nih.gov/pubmed/36359674
http://dx.doi.org/10.3390/e24111584
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author Afianto, Darryl
Han, Yu
Yan, Peiliang
Yang, Yan
Elbarghthi, Anas F. A.
Wen, Chuang
author_facet Afianto, Darryl
Han, Yu
Yan, Peiliang
Yang, Yan
Elbarghthi, Anas F. A.
Wen, Chuang
author_sort Afianto, Darryl
collection PubMed
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.
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spelling pubmed-96894352022-11-25 Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling Afianto, Darryl Han, Yu Yan, Peiliang Yang, Yan Elbarghthi, Anas F. A. Wen, Chuang Entropy (Basel) Article 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. MDPI 2022-11-01 /pmc/articles/PMC9689435/ /pubmed/36359674 http://dx.doi.org/10.3390/e24111584 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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/).
spellingShingle Article
Afianto, Darryl
Han, Yu
Yan, Peiliang
Yang, Yan
Elbarghthi, Anas F. A.
Wen, Chuang
Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling
title Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling
title_full Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling
title_fullStr Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling
title_full_unstemmed Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling
title_short Optimisation and Efficiency Improvement of Electric Vehicles Using Computational Fluid Dynamics Modelling
title_sort optimisation and efficiency improvement of electric vehicles using computational fluid dynamics modelling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689435/
https://www.ncbi.nlm.nih.gov/pubmed/36359674
http://dx.doi.org/10.3390/e24111584
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