Modelling and Analytics of Driving-related Energy Performance of Electric Vehicles

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Modelling and Analytics of Driving-related Energy Performance of Electric Vehicles
Title:
Modelling and Analytics of Driving-related Energy Performance of Electric Vehicles
Journal Title:
2019 IEEE Intelligent Transportation Systems Conference (ITSC)
Keywords:
Publication Date:
27 October 2019
Citation:
Y. R. D. Neo, D. Tran, Y. M. Yeap and L. H. I. Lim, "Modelling and Analytics of Driving-related Energy Performance of Electric Vehicles," 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, 2019, pp. 714-719.
Abstract:
Large scale adoption of electric vehicles (EV) has yet to be accelerated due to fundamental challenges such as the availability of charging infrastructure, mileage of the EV, as well as the higher lifetime costs associated with the batteries. In order to address these challenges, this paper introduces a framework to model, analyze and visualize the driving-related energy performance of electric vehicles. Based on a case study of real-world data inputs of throttle, brake and road conditions in Singapore, the proposed framework illustrates several findings in terms of modelling accuracy and driving behaviour identification together with visualization and simulation results in open-source Simulation of Urban Mobility software.
License type:
PublisherCopyrights
Funding Info:
Description:
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISBN:
978-1-5386-7024-8
978-1-5386-7023-1
978-1-5386-7025-5
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