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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.

Based on the movement resistance forces, the vehicle longitudinal dynamics is related to power demand for a specific route. The vehicle gear shifting influences significantly the acceleration performance and fuel consumption because it changes the engine operation point and the powertrain inertia. This paper presents a study based on the US06 velocity profile which involves high speed and high acceleration phases, where the vehicle performance is limited by both the engine power and the tire traction limit. For improving A c c e p t e d M a n u s c r i p t the vehicle performance without increasing fuel consumption, a genetic algorithm (GA) technique is used.