Hybrid Electric Vehicle Torque Distribution Control Method and System with Environmental Temperature Protection Battery Integration

Abstract

This research presents a hybrid electric vehicle (HEV) torque distribution control method and system that incorporates an environmental temperature protection battery. The study involves the collection of ambient temperature information to determine the vehicle's location and utilizes a battery equivalent circuit model to calculate the actual temperature of the battery. The state of charge (SoC) values of the battery are determined based on battery energy dump and maximum capacity. The research utilizes a neural network control method to optimize control parameters considering the actual temperature and SoC values of the battery. Furthermore, an online minimum equivalent oil consumption strategy is developed to model the target function and constraint formulas for fuel consumption, which enables the determination of optimal motor torque values during equivalent fuel consumption. The torque distribution and control commands for the vehicle's power train and dynamics module are established based on the calculated engine torque and motor torque values. By considering battery behavior and controlling the power-driven system, the research aims to protect against galvanic actions and demonstrates its practical significance.