Vehicle drivetrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle

Abstract

The plug-in hybrid electric vehicle (PHEV) stands out among hybrid vehicles due to the ability to recharge the battery from an external source and improve vehicle performance and efficiency by increasing fuel economy and reducing emissions. Due to the use of two power sources, a power management strategy must be determined to ensure the operation of both systems achieves higher global efficiency. Therefore, this paper presents three fuzzy controllers. Two controllers act hierarchically to perform the power management, and the third controller is responsible for performing the gear shift. A multi-objective optimization based on the particle swarm algorithm is proposed to reduce the driver's action on the steering angle, minimize the mass of electrical components (electric motors and battery), the equivalent fuel consumption, and exhaust emissions. To do this, the electric motor torque curve, battery capacity and voltage, fuzzy controller parameters are optimized, and the best gearbox and mechanical differential configuration are determined. The best trade-off solution, when compared to the conventional vehicle, was able to improve the handling performance with a 71.9% reduction in the driver steering action, decrease fuel consumption by 18.44%, and reduce pollutant emissions by 69.34% of CO, 20.33% of HC, and 22.11% of NOx.