A real-time energy management strategy for fuel cell vehicle based on Pontryagin’s minimum principle

Highlights•Propose a real-time EMS for fuel cell vehicle based on driving cycle recognition•The PMP EMS considered the equivalent hydrogen consumption and fuel cell durability•The numerical model of fuel cell vehicle was established•The advantage of the proposed EMS was validated with comparative experimentsSummaryThis paper proposes a Pontryagin's minimum principle (PMP) energy management strategy (EMS) based on driving cycle recognition for fuel cell vehicle powertrains, aiming to minimize hydrogen consumption and fuel cell degradation. Firstly, the neural network-based driving cycle recognizer is optimized using the tuna swarm optimization (TSO) algorithm and trained under four typical driving cycles. Then, the optimal co-state variables for the four driving cycles are obtained by iteration. Finally, the co-state variables are dynamically updated based on real-time driving cycle recognition results. Comparative analysis demonstrates that the PMP-DCR effectively improves fuel cell lifetime and vehicle economy under short-distance driving cycles. Based on the combined driving cycle, the proposed PMP-DCR EMS exhibits similar economy performance to optimal dynamic programming (DP) EMS, reducing equivalent hydrogen consumption by 13.8% and 9.2%, and decreasing fuel cell degradation rates by 93% and 8.7% in comparison to the conventional power-following and PMP EMS, respectively.Graphical abstract