Open AccessElectric vehicle drivetrain optimisation
Author(s) -
Eckert Jony J.,
Silva Ludmila C.A.,
Costa Eduardo S.,
Santiciolli Fabio M.,
Dedini Franco G.,
Corrêa Fernanda C.
Publication year - 2017
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
eISSN - 2042-9746
pISSN - 2042-9738
DOI - 10.1049/iet-est.2016.0022
Subject(s) - drivetrain , powertrain , automotive engineering , electric vehicle , torque , traction motor , engineering , driving range , battery electric vehicle , manual transmission , electronic differential , battery (electricity) , power (physics) , clutch , physics , steering wheel , quantum mechanics , thermodynamics
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.