2016IET Electrical Systems in TransportationRequires access

Electric vehicle drivetrain optimisation

Jony Javorski Eckert, Ludmila C. A. Silva, Eduardo S. Costa, Fabio Mazzariol Santiciolli, Franco Giuseppe Dedini, Fernanda Cristina Corrêa

Open publisher page 47 citations

Abstract

This study provides a detailed analysis of an optimal drivetrain configuration, based on multi‐cycles, for a plug‐in electric vehicle (EV). The investigation aims to identify the best EV configuration according to the required power and the transmissible traction torque. The study focuses on an EV with four different combinations of drive systems among in‐wheel motors and differential ones. To find out the best EV drive system configuration, it is adopted an optimisation process by means of a genetic algorithm that defines the electric motors (EMs) torque curves and powertrain transmission ratio in order to improve vehicle travel range and performance. The vehicle power demand is divided between the drive systems following rules established by the power management control which aims to reduce the lithium‐ion battery discharges during the driving cycles: FTP‐75 (urban driving), HWFET (highway driving) and US06 (high speeds and accelerations). After the simulations, the potential of each configuration is indicated according to its respective drive system and hence the best configurations are determined.

About this research paper

What this paper is about

This study provides a detailed analysis of an optimal drivetrain configuration, based on multi‐cycles, for a plug‐in electric vehicle (EV). The investigation aims to identify the best EV configuration according to the required power and the transmissible traction torque. The study focuses on an EV with four different combinations of drive systems among in‐wheel motors and differential ones. To find out the best EV drive system configuration, it is adopted an optimisation process by means of a genetic algorithm that defines the electric motors (EMs) torque curves and powertrain transmission ratio in order to improve vehicle travel range and performance. The vehicle power demand is divided between the drive systems following rules established by the power management control which aims to reduce the lithium‐ion battery discharges during the driving cycles: FTP‐75 (urban driving), HWFET (highway driving) and US06 (high speeds and accelerations). After the simulations, the potential of each configuration is indicated according to its respective drive system and hence the best configurations are determined.

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OpenAlex reports 47 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This study provides a detailed analysis of an optimal drivetrain configuration, based on multi‐cycles, for a plug‐in electric vehicle (EV). The investigation aims to identify the best EV configuration according to the required power and the transmissible traction torque. The study focuses on an EV with four different combinations of drive systems among in‐wheel motors and differential ones. To find out the best EV drive system configuration, it is adopted an optimisation process by means of a genetic algorithm that defines the electric motors (EMs) torque curves and powertrain transmission ratio in order to improve vehicle travel range and performance. The vehicle power demand is divided between the drive systems following rules established by the power management control which aims to reduce the lithium‐ion battery discharges during the driving cycles: FTP‐75 (urban driving), HWFET (highway driving) and US06 (high speeds and accelerations). After the simulations, the potential of each configuration is indicated according to its respective drive system and hence the best configurations are determined.

Key concepts: Drivetrain, Powertrain, Automotive engineering, Electric vehicle, Torque, Traction motor, Engineering, Driving range

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