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Modeling of a shell eco-marathon vehicle based on drive-train characteristic and driver modes to predict fuel consumption of the vehicle on a specific track
Shell Eco Marathon is a competition for fuel efficient vehicle organized by Shell annually for student around the word. Every team should present a uniquely designed vehicle targeted to be driven to an extreme distance using 1 liter of fuel. This study aimed to conduct a vehicle dynamic modelling by...
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Published in: | ARPN journal of engineering and applied sciences 2016-02, Vol.11 (4) |
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creator | Aulia, Diva Rahman, Habibie |
description | Shell Eco Marathon is a competition for fuel efficient vehicle organized by Shell annually for student around the word. Every team should present a uniquely designed vehicle targeted to be driven to an extreme distance using 1 liter of fuel. This study aimed to conduct a vehicle dynamic modelling by using Simulink program from MatLab to predict vehicle fuel consumption. The Model is build based on vehicle data and drive-train characteristic. To model the vehicle, various data such as body weight, tire/wheel weight and angular inertia, frontal area, drag coefficient and tire rolling resistance are collected. To model the drive-train, transmission ratio, engine torque and specific fuel consumption curves, mechanical efficiency of some rotating parts are also collected. Model of the vehicle is a close loop system in which engine as power unit gave its torque to wheel to move the vehicle. More speed developed by the engine would produce more resistance of vehicle dynamics. The calculations were conducted with changing vehicle speed, driver mode, and inclination of the track. Predictions of accuracy were done by using competition data from Sepang, Malaysia circuits within 5% of error. |
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source | Free E-Journal (出版社公開部分のみ) |
subjects | Automotive components Automotive wheels Dynamics Engines Fuel consumption Mathematical models Matlab Vehicles |
title | Modeling of a shell eco-marathon vehicle based on drive-train characteristic and driver modes to predict fuel consumption of the vehicle on a specific track |
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