A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles

This article proposes a novel framework to develop computationally efficient energy consumption models of electric and internal combustion engine vehicles. The number of calculations in a conventional energy consumption model prevents the model’s usage in applications where time is limited. As many...

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Main Authors: Anil K. Madhusudhanan, Xiaoxiang Na, David Cebon
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/7/2031
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spelling doaj-bf1661a272ff447f93921cf51c07e3072021-04-06T23:06:11ZengMDPI AGEnergies1996-10732021-04-01142031203110.3390/en14072031A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric VehiclesAnil K. Madhusudhanan0Xiaoxiang Na1David Cebon2Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UKDepartment of Engineering, University of Cambridge, Cambridge CB2 1PZ, UKDepartment of Engineering, University of Cambridge, Cambridge CB2 1PZ, UKThis article proposes a novel framework to develop computationally efficient energy consumption models of electric and internal combustion engine vehicles. The number of calculations in a conventional energy consumption model prevents the model’s usage in applications where time is limited. As many fleet operators around the world are in the process of transitioning towards electric vehicles, a computationally efficient energy consumption model will be valuable to analyse the vehicles they trial. A vehicle’s energy consumption depends on the vehicle characteristics, drive cycles and vehicle mass. The proposed modelling framework considers these aspects, is computationally efficient, and can be run using open source software packages. The framework is validated through two use cases: an electric bus and a diesel truck. The model error’s standard deviation is less 5% and its mean is less than 2%. The proposed model’s mean computation time is less than 20 ms, which is two orders of magnitude lower than that of the baseline model. Finally, a case study was performed to illustrate the usefulness of the modelling framework for a fleet operator.https://www.mdpi.com/1996-1073/14/7/2031energy consumptiondrive cyclemodelling frameworkelectric vehiclediesel vehicle
collection DOAJ
language English
format Article
sources DOAJ
author Anil K. Madhusudhanan
Xiaoxiang Na
David Cebon
spellingShingle Anil K. Madhusudhanan
Xiaoxiang Na
David Cebon
A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles
Energies
energy consumption
drive cycle
modelling framework
electric vehicle
diesel vehicle
author_facet Anil K. Madhusudhanan
Xiaoxiang Na
David Cebon
author_sort Anil K. Madhusudhanan
title A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles
title_short A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles
title_full A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles
title_fullStr A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles
title_full_unstemmed A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles
title_sort computationally efficient framework for modelling energy consumption of ice and electric vehicles
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2021-04-01
description This article proposes a novel framework to develop computationally efficient energy consumption models of electric and internal combustion engine vehicles. The number of calculations in a conventional energy consumption model prevents the model’s usage in applications where time is limited. As many fleet operators around the world are in the process of transitioning towards electric vehicles, a computationally efficient energy consumption model will be valuable to analyse the vehicles they trial. A vehicle’s energy consumption depends on the vehicle characteristics, drive cycles and vehicle mass. The proposed modelling framework considers these aspects, is computationally efficient, and can be run using open source software packages. The framework is validated through two use cases: an electric bus and a diesel truck. The model error’s standard deviation is less 5% and its mean is less than 2%. The proposed model’s mean computation time is less than 20 ms, which is two orders of magnitude lower than that of the baseline model. Finally, a case study was performed to illustrate the usefulness of the modelling framework for a fleet operator.
topic energy consumption
drive cycle
modelling framework
electric vehicle
diesel vehicle
url https://www.mdpi.com/1996-1073/14/7/2031
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