Energy consumption and modelling of the climate control system in the electric vehicle

With the introduction of electric vehicles in the automobile market, limited information is available on how the battery’s energy consumption is distributed. This paper focuses on the energy consumption of the vehicle when the heating and cooling system is in operation. On average, 18 and 14% for th...

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Main Authors: Aisling Doyle, Tariq Muneer
Format: Article
Language:English
Published: SAGE Publishing 2019-01-01
Series:Energy Exploration & Exploitation
Online Access:https://doi.org/10.1177/0144598718806458
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spelling doaj-2584ee7bc61049c6877adff27b9e17c12020-11-25T03:59:44ZengSAGE PublishingEnergy Exploration & Exploitation0144-59872048-40542019-01-013710.1177/0144598718806458Energy consumption and modelling of the climate control system in the electric vehicleAisling DoyleTariq MuneerWith the introduction of electric vehicles in the automobile market, limited information is available on how the battery’s energy consumption is distributed. This paper focuses on the energy consumption of the vehicle when the heating and cooling system is in operation. On average, 18 and 14% for the battery’s energy capacity is allocated to heating and cooling requirements, respectively. The conventional internal combustion engine vehicle uses waste heat from its engine to provide for passenger thermal requirements at no cost to the vehicle’s propulsion energy demands. However, the electric vehicle cannot avail of this luxury to recycle waste heat. In order to reduce the energy consumed by the climate control system, an analysis of the temperature profile of a vehicle’s cabin space under various weather conditions is required. The present study presents a temperature predicting algorithm to predict temperature under various weather conditions. Previous studies have limited consideration to the fluctuation of solar radiation space heating to a vehicle’s cabin space. This model predicts solar space heating with a mean bias error and root mean square error of 0.26 and 0.57°C, respectively. This temperature predicting model can potentially be developed with further research to predict the energy required by the vehicle’s primary lithium-ion battery to heat and cool the vehicle’s cabin space. Thus, this model may be used in a route planning application to reduce range anxiety when drivers undertake a journey under various ambient weather conditions while optimising the energy consumption of the electric vehicle.https://doi.org/10.1177/0144598718806458
collection DOAJ
language English
format Article
sources DOAJ
author Aisling Doyle
Tariq Muneer
spellingShingle Aisling Doyle
Tariq Muneer
Energy consumption and modelling of the climate control system in the electric vehicle
Energy Exploration & Exploitation
author_facet Aisling Doyle
Tariq Muneer
author_sort Aisling Doyle
title Energy consumption and modelling of the climate control system in the electric vehicle
title_short Energy consumption and modelling of the climate control system in the electric vehicle
title_full Energy consumption and modelling of the climate control system in the electric vehicle
title_fullStr Energy consumption and modelling of the climate control system in the electric vehicle
title_full_unstemmed Energy consumption and modelling of the climate control system in the electric vehicle
title_sort energy consumption and modelling of the climate control system in the electric vehicle
publisher SAGE Publishing
series Energy Exploration & Exploitation
issn 0144-5987
2048-4054
publishDate 2019-01-01
description With the introduction of electric vehicles in the automobile market, limited information is available on how the battery’s energy consumption is distributed. This paper focuses on the energy consumption of the vehicle when the heating and cooling system is in operation. On average, 18 and 14% for the battery’s energy capacity is allocated to heating and cooling requirements, respectively. The conventional internal combustion engine vehicle uses waste heat from its engine to provide for passenger thermal requirements at no cost to the vehicle’s propulsion energy demands. However, the electric vehicle cannot avail of this luxury to recycle waste heat. In order to reduce the energy consumed by the climate control system, an analysis of the temperature profile of a vehicle’s cabin space under various weather conditions is required. The present study presents a temperature predicting algorithm to predict temperature under various weather conditions. Previous studies have limited consideration to the fluctuation of solar radiation space heating to a vehicle’s cabin space. This model predicts solar space heating with a mean bias error and root mean square error of 0.26 and 0.57°C, respectively. This temperature predicting model can potentially be developed with further research to predict the energy required by the vehicle’s primary lithium-ion battery to heat and cool the vehicle’s cabin space. Thus, this model may be used in a route planning application to reduce range anxiety when drivers undertake a journey under various ambient weather conditions while optimising the energy consumption of the electric vehicle.
url https://doi.org/10.1177/0144598718806458
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