Research on energy management strategy for fuel cell hybrid electric vehicles based on improved dynamic programming and air supply optimization

It is crucial to accurately calculate the cost function of the energy management strategy (EMS) of the hybrid powertrain to improve the hydrogen economy of the system. This paper proposes an EMS for fuel cell hybrid electric vehicles (FCHEV) based on improved dynamic programming (DP) and air supply optimization to improve economy and reliability. Taking the maximum net power output of the FC system as the target, the optimal oxygen excess ratio (OER) and cathode pressure of the FC system under different current densities are solved by using PSO. A velocity prediction method based on Bi-LSTM is developed to predict short-term velocity changes in real time. The DP algorithm is introduced and the EMS of the DP algorithm based on short-term velocity prediction is developed for real-time hybrid powertrain optimization and management. Based on the results of energy allocation and optimal gas supply conditions of FCs, the cost function of EMS is modified to reallocate the power of the FC system and battery. The results demonstrate that the proposed method achieves the lowest hydrogen consumption compared to the other two algorithms. Remarkably, it reduces the fuel cost by up to 8.85 % compared to the commonly used online DP algorithm.