Adaptive Control Strategy Based on Online Fuzzy Recognition for Parallel Hybrid Electric Vehicle

An adaptive control strategy based on online fuzzy recognition was put forward for a parallel hybrid vehicle. A typical driving cycle in line with the local actual vehicle driving road conditions was constructed based on the independent research and development of the hybrid data acquisition and monitoring system. And then a fuzzy recognition algorithm was designed to carry on the on-line identification of the vehicle real driving cycle type, some corresponding optimal control parameters were taken for the real-time optimization calculation of the motor and battery power allocation based on the minimal equivalent fuel consumption control algorithm and the battery balance control method, combining with the results of condition recognition to realize the control of the whole vehicle finally. The experiment results show that the designed fuzzy recognition method can fulfill the recognition of the working condition type well, and the proposed adaptive control strategy based on this method can complete the optimal power allocation between the engine and the battery under the premise of meeting the demand of vehicle power and battery SOC maintaining within the effective working range, and can significantly improve the fuel economy of the vehicle.