Real-time energy management of parallel hybrid electric vehicle based on BP neural network

In order to improve fuel economy of parallel hybrid electric vehicle(PHEV),a real-time energy management strategy(EMS) is proposed for PHEV based on BP neural network.Firstly,the energy management rules are got by offline simulation using instantaneous optimization EMS based on many kinds of drive cycles.Then the energy management rules are classified by fuzzy C-mean cluster and selected as training sample of neural network.The BP neural network controller is used to control the torque distribution of hybrid powertain for the sake of optimizing energy distribution.Finally,the energy management strategy is implemented on a PHEV prototype in ADVISOR.And the simulation results demonstrate that,compared with instantaneous optimization EMS,the proposed EMS not only satisfies the fuel economy,but also increases real-time performance of energy management effectively.