Title: Electric vehicle battery consumption estimation model based on simulated environments

Authors: Iñaki Cejudo; Iker Arandia; Itziar Urbieta; Eider Irigoyen; Harbil Arregui; Estíbaliz Loyo

Addresses: Fundación Vicomtech, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, Spain ' Fundación Vicomtech, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, Spain ' Fundación Vicomtech, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, Spain ' Fundación Vicomtech, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, Spain ' Fundación Vicomtech, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, Spain ' Fundación Vicomtech, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, Spain

Abstract: Governmental policies are promoting using Electric Vehicles (EVs) to reduce carbon emissions and make transportation more energy efficient. Car manufacturers are putting much effort into making reliable EVs. However, consumers still have to deal with the lack of enough infrastructure and an immature technology readiness level. In order to have an accurate battery range prediction and lessen these issues, this research proposes an energy consumption estimation model based on factors related to battery consumption during a trip. As part of the process, Simulation of Urban Mobility (SUMO), a well-known traffic simulation tool, has been used to run many simulations, produce a heterogeneous data set and train the model with a neural network. The results show an accurate battery range forecast, with a coefficient of determination of 0.91. This model can determine trip consumption considering conditions that vehicle manufacturers' reference consumption values do not.

Keywords: electric vehicle; energy consumption; simulation; battery estimation; data set; deep learning.

DOI: 10.1504/IJVICS.2024.139759

International Journal of Vehicle Information and Communication Systems, 2024 Vol.9 No.3, pp.309 - 333

Received: 30 Nov 2022
Accepted: 08 Aug 2023
Published online: 05 Jul 2024 *

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