The hybrid energy storage system (HESS), which is composed of battery and ultracapacitor, is established to enhance the performance of an electric vehicle (EV). Moreover, several studies highlight the gains of split the traction power demand among electric motors (EMs) with different characteristics and drivetrain configurations, allowing these to operate at higher efficiency. In this paper, we unite the advantages of the multi EM drive train with the HESS power split and propose a novel two HESS system, in which each HESS is in charge of one of the drivetrain configurations (front and rear system). The EV is driven by two in-wheel EM at the front wheels and a single EM assembled with a differential transmission that moves the rear wheels. In this paper, a multiobjective optimization, based on a genetic algorithm (GA), is formulated to minimize the HESS sizing and maximize the driving range of the vehicle. Also employing the fuzzy control, this strategy is responsible to split the power between the front and rear wheels systems in a more reasonable way to satisfy the demands of better performance. The complete strategy has been developed under the FTP-75 (urban), HWFET (highway) and the US06 (high speed and required acceleration) driving cycles using the MATLAB/Simulink software environment. As compared to a similar EV with a single HESS system, the proposed dual-HESS configuration was able to improve the driving range in 145.15 km also decreasing 23.93% of the HESS mass.
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.