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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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Published in:Entropy (Basel, Switzerland) Switzerland), 2022-11, Vol.24 (11), p.1584
Main Authors: Afianto, Darryl, Han, Yu, Yan, Peiliang, Yang, Yan, Elbarghthi, Anas F. A., Wen, Chuang
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container_title Entropy (Basel, Switzerland)
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creator Afianto, Darryl
Han, Yu
Yan, Peiliang
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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
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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. 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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
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