The article presents a novel energy management strategy (EMS) for fuel cell hybrid electric vehicles (FCHEVs) based on improved dynamic programming (DP) and air supply optimization. By optimizing the air supply system conditions and power allocation, the EMS aims to enhance the hydrogen economy and reliability of the system. The study solves for optimal oxygen excess ratios and cathode pressures under different current densities using a Particle Swarm Optimization (PSO) algorithm. Additionally, a Bi-LSTM-based velocity prediction method is introduced for real-time velocity changes prediction. The DP algorithm is implemented for real-time hybrid powertrain optimization. By modifying the cost function of the EMS in real-time, power allocation between the FC system and battery is optimized. Results indicate that the proposed method reduces hydrogen consumption significantly and lowers fuel costs compared to traditional online DP algorithms. The article emphasizes the importance of optimal air supply conditions in improving FC system performance and achieving higher efficiency. Various studies on FC system optimization under different conditions are referenced, highlighting the significance of EMS in enhancing fuel economy in hybrid powertrains.