Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle

The energy consumption and CO2 emission of urban vehicles are highly dependent on their operation. Vehicle models can be used for optimizing driving strategy for emission reduction. This paper proposes a novel vehicle model of a one-seat electric vehicle dedicated for Shell Eco-marathon (SEM), the m...

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Autores principales:	Zoltán Pusztai, Péter Korös, Ferenc Friedler
Formato:	article
Lenguaje:	EN
Publicado:	AIDIC Servizi S.r.l. 2021
Materias:	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895
Acceso en línea:	https://doaj.org/article/e9e42d6a4b334ba2997c19953cb9dd14
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spelling	oai:doaj.org-article:e9e42d6a4b334ba2997c19953cb9dd142021-11-15T21:48:27ZVehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle10.3303/CET21880642283-9216https://doaj.org/article/e9e42d6a4b334ba2997c19953cb9dd142021-11-01T00:00:00Zhttps://www.cetjournal.it/index.php/cet/article/view/11857https://doaj.org/toc/2283-9216The energy consumption and CO2 emission of urban vehicles are highly dependent on their operation. Vehicle models can be used for optimizing driving strategy for emission reduction. This paper proposes a novel vehicle model of a one-seat electric vehicle dedicated for Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. The available vehicle dynamical formulas cannot be directly used to describe the characteristics of lightweight vehicles. In the current work, a novel grey-box vehicle model has been introduced, based on measurement scenarios. The whole model has been elaborated in MATLAB Simulink environment, where individual subassemblies were defined for driving resistance model, powertrain model, and the racetrack characteristics. The resistance force model manages the forces in straight line moving and also takes the effect of cornering into account. Based on test bench measurements the complete efficiency map of the drivetrain was created and implemented into the vehicle model. The presented vehicle model is suitable for driving strategy optimization. By optimizing this model, 7.1 % energy savings have been achieved compared to best human driven lap. Driving strategy optimization will be essential, especially for autonomous vehicles, expressing the importance of the presented results in the future.Zoltán PusztaiPéter KorösFerenc FriedlerAIDIC Servizi S.r.l.articleChemical engineeringTP155-156Computer engineering. Computer hardwareTK7885-7895ENChemical Engineering Transactions, Vol 88 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895
spellingShingle	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895 Zoltán Pusztai Péter Korös Ferenc Friedler Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle
description	The energy consumption and CO2 emission of urban vehicles are highly dependent on their operation. Vehicle models can be used for optimizing driving strategy for emission reduction. This paper proposes a novel vehicle model of a one-seat electric vehicle dedicated for Shell Eco-marathon (SEM), the most famous and largest race of energy efficient vehicles. The available vehicle dynamical formulas cannot be directly used to describe the characteristics of lightweight vehicles. In the current work, a novel grey-box vehicle model has been introduced, based on measurement scenarios. The whole model has been elaborated in MATLAB Simulink environment, where individual subassemblies were defined for driving resistance model, powertrain model, and the racetrack characteristics. The resistance force model manages the forces in straight line moving and also takes the effect of cornering into account. Based on test bench measurements the complete efficiency map of the drivetrain was created and implemented into the vehicle model. The presented vehicle model is suitable for driving strategy optimization. By optimizing this model, 7.1 % energy savings have been achieved compared to best human driven lap. Driving strategy optimization will be essential, especially for autonomous vehicles, expressing the importance of the presented results in the future.
format	article
author	Zoltán Pusztai Péter Korös Ferenc Friedler
author_facet	Zoltán Pusztai Péter Korös Ferenc Friedler
author_sort	Zoltán Pusztai
title	Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle
title_short	Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle
title_full	Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle
title_fullStr	Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle
title_full_unstemmed	Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle
title_sort	vehicle model for driving strategy optimization of energy efficient lightweight vehicle
publisher	AIDIC Servizi S.r.l.
publishDate	2021
url	https://doaj.org/article/e9e42d6a4b334ba2997c19953cb9dd14
work_keys_str_mv	AT zoltanpusztai vehiclemodelfordrivingstrategyoptimizationofenergyefficientlightweightvehicle AT peterkoros vehiclemodelfordrivingstrategyoptimizationofenergyefficientlightweightvehicle AT ferencfriedler vehiclemodelfordrivingstrategyoptimizationofenergyefficientlightweightvehicle
_version_	1718426818125496320

Vehicle Model for Driving Strategy Optimization of Energy Efficient Lightweight Vehicle

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