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https://doi.org/10.1109/ever52...
Conference object . 2021 . Peer-reviewed
License: IEEE Copyright
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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Multiobjective GA Optimization for Energy Efficient Electric Vehicle Drivetrains

Authors: Chakraborty, Sajib; Padmaji, Vinayak; Tran, Dai-Duong; Araujo, Javier A. Corea; Geury, Thomas; El Baghdadi, Mohamed; Hegazy, Omar;

Multiobjective GA Optimization for Energy Efficient Electric Vehicle Drivetrains

Abstract

This paper investigates the impact of using wide bandgap (WBG) technology-based bidirectional interleaved HV DC/DC converters on the performance of battery electric vehicles (BEVs), An existing electric vehicle is upgraded using off-the-shelf components. There are a variety of batteries, high voltage (HV) DC/DCs, inverters, electric motors, transmissions, etc., available off-the-shelf; hence, numerous possible combinations can be formed, which make the optimal component selection process more complicated through analytical methods. In this paper, a multiobjective genetic algorithm (MOGA) is adopted to minimize the electric energy consumption by improving drivetrain efficiency based on the optimal variant selection of the components. It is found from the virtual simulation framework in MATLAB/Simulink® that overall, there is a 9.2% reduction in the energy consumption over a given driving cycle, i.e., Worldwide Harmonized Light Vehicles Test Procedure-3a (WLTP3a). To this end, the drivetrain performance in terms of acceleration time from 0–90 km/h is also improved by 10.2%, while the efficiency is improved by 1.5% compared to the conventional e-drivetrain.

Country
Belgium
Keywords

WBGSs, HV DC/DC Converter, energy consumption, Electric vehicle (EV), Multiobjective Genetic algorithm

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average