An optimal torque distribution strategy for an integrated starter—generator parallel hybrid electric vehicle based on fuzzy logic control

Abstract

This paper presents a systemic design method of a multi-energy management control strategy by using fuzzy logic control to realize the optimal torque distribution between the internal combustion engine and electric motor. The controller which is the brain of the hybrid electric vehicle receives vehicle information such as the acceleration and brake pedal, the engine speed, and the absolute state of charge of the battery package as inputs and sends a direct torque command to control the electric motor and the engine throttle angle to command the diesel engine. Fuzzy control logic consists of three parts to realize the interpolation mechanism: the trapezoid membership, the Mamdani rule reference machine, and the centre of gravity as the defuzzification method. A novel technique to fuzzify the vehicle torque demand that can enable a point-to-point optimization is introduced and more than 130 rules are classified into four subrule bases. Hardware-in-the-loop simulation results reveal that the efficiency of the integrated starter—generator hybrid system has been improved greatly and the fuel economy is better than the default rule-based control strategy.