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Method for estimating the energy consumption of electric vehicles and plug-in hybrid electric vehicles under real-world driving conditions
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Shankar, R. and Marco, James (2013) Method for estimating the energy consumption of electric vehicles and plug-in hybrid electric vehicles under real-world driving conditions. IET Intelligent Transport Systems, Volume 7 (Issue 1). pp. 138-150. doi:10.1049/iet-its.2012.0114 ISSN 1751-956X.
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Official URL: http://dx.doi.org/10.1049/iet-its.2012.0114
Abstract
This study presents a novel framework by which the energy consumption of an electric vehicle (EV) or the zero-emissions range of a plug-in hybrid electric vehicle (PHEV) may be predicted over a route. The proposed energy prediction framework employs a neural network and may be used either `off-line' for better estimating the real-world range of the vehicle or `on-line' integrated within the vehicle's energy management control system. The authors propose that this approach provides a more robust representation of the energy consumption of the target EVs compared to standard legislative test procedures. This is particularly pertinent for vehicle fleet operators that may use EVs within a specific environment, such as inner-city public transport or the use of urban delivery vehicles. Experimental results highlight variations in EV range in the order of 50% when different levels of traffic congestion and road type are included in the analysis. The ability to estimate the energy requirements of the vehicle over a given route is also a pre-requisite for using an efficient charge blended control strategy within a PHEV. Experimental results show an accuracy within 20-30% when comparing predicted and measured energy consumptions for over 800 different real-world EV journeys.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||
Journal or Publication Title: | IET Intelligent Transport Systems | ||||
Publisher: | The Institution of Engineering and Technology | ||||
ISSN: | 1751-956X | ||||
Official Date: | March 2013 | ||||
Dates: |
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Volume: | Volume 7 | ||||
Number: | Issue 1 | ||||
Page Range: | pp. 138-150 | ||||
DOI: | 10.1049/iet-its.2012.0114 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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