Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD)

Develop of drag estimation by using Computational Fluid Dynamics (CFD) on Hybrid Electric Vehicle (HEV) model was carried out on this project. The HEV model here means the Proton Iswara Hatchback body developed by researcher of Automotive Focus Group, Universiti Malaysia Pahang. To develop th...

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Main Author: Redzuan, Ahmad
Format: Undergraduates Project Papers
Language:English
Published: 2008
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/279/
http://umpir.ump.edu.my/id/eprint/279/1/Redzuan_Bin_Ahmad.pdf
id ump-279
recordtype eprints
spelling ump-2792015-03-03T06:16:13Z http://umpir.ump.edu.my/id/eprint/279/ Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD) Redzuan, Ahmad TL Motor vehicles. Aeronautics. Astronautics Develop of drag estimation by using Computational Fluid Dynamics (CFD) on Hybrid Electric Vehicle (HEV) model was carried out on this project. The HEV model here means the Proton Iswara Hatchback body developed by researcher of Automotive Focus Group, Universiti Malaysia Pahang. To develop this HEV model, one of factor needs to consider and studied for giving better efficiency on the road is aerodynamics drag. Therefore, simulation of CFD and FEM have been the key features to aerodynamics drag studies in this project for the HEV model specifically is Proton Iswara Hatcback body. The objectives of this project are to estimate the drag of Proton Iswara Hatcback body at ranging speed between 40km/h to 110 km/h that designed by Computational Aided Design (CAD). The terminology to getting the drag estimation is by using input of CFD then export to FEM analysis to find the value of aerodynamics drag in terms of drag forces and drag coefficient. Besides that, CFD simulation results such as contour and trajectories plot also used to analyze the characteristics of streamlines flow or boundary layer that occurs on the body of this HEV model especially for the forebody, upperbody and rearbody. To achieve these objectives and rationalization made of project, aerodynamics studies, and study of CAD, CFD, and FEA engineering’s software needed to optimize the development of aerodynamic design on HEV model and to estimate the drag using CFD and FEA software as an alternative after experimental process. In this project also, a simple experiment was done to validate the CFD simulation analysis. The experiment known as Pressure Experiment that gives valuable results to compare with the simulation results as a validation process to this project. 2008-11 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/279/1/Redzuan_Bin_Ahmad.pdf Redzuan, Ahmad (2008) Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD). Faculty of Mechanical Engineering , Universiti Malaysia Pahang .
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TL Motor vehicles. Aeronautics. Astronautics
spellingShingle TL Motor vehicles. Aeronautics. Astronautics
Redzuan, Ahmad
Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD)
description Develop of drag estimation by using Computational Fluid Dynamics (CFD) on Hybrid Electric Vehicle (HEV) model was carried out on this project. The HEV model here means the Proton Iswara Hatchback body developed by researcher of Automotive Focus Group, Universiti Malaysia Pahang. To develop this HEV model, one of factor needs to consider and studied for giving better efficiency on the road is aerodynamics drag. Therefore, simulation of CFD and FEM have been the key features to aerodynamics drag studies in this project for the HEV model specifically is Proton Iswara Hatcback body. The objectives of this project are to estimate the drag of Proton Iswara Hatcback body at ranging speed between 40km/h to 110 km/h that designed by Computational Aided Design (CAD). The terminology to getting the drag estimation is by using input of CFD then export to FEM analysis to find the value of aerodynamics drag in terms of drag forces and drag coefficient. Besides that, CFD simulation results such as contour and trajectories plot also used to analyze the characteristics of streamlines flow or boundary layer that occurs on the body of this HEV model especially for the forebody, upperbody and rearbody. To achieve these objectives and rationalization made of project, aerodynamics studies, and study of CAD, CFD, and FEA engineering’s software needed to optimize the development of aerodynamic design on HEV model and to estimate the drag using CFD and FEA software as an alternative after experimental process. In this project also, a simple experiment was done to validate the CFD simulation analysis. The experiment known as Pressure Experiment that gives valuable results to compare with the simulation results as a validation process to this project.
format Undergraduates Project Papers
author Redzuan, Ahmad
author_facet Redzuan, Ahmad
author_sort Redzuan, Ahmad
title Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD)
title_short Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD)
title_full Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD)
title_fullStr Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD)
title_full_unstemmed Develop drag estimation on hybrid electric vehicle (HEV) model using computational fluid dynamics (CFD)
title_sort develop drag estimation on hybrid electric vehicle (hev) model using computational fluid dynamics (cfd)
publishDate 2008
url http://umpir.ump.edu.my/id/eprint/279/
http://umpir.ump.edu.my/id/eprint/279/1/Redzuan_Bin_Ahmad.pdf
first_indexed 2023-09-18T21:52:18Z
last_indexed 2023-09-18T21:52:18Z
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