Coordination control strategy for PEM fuel cell system considering vehicle velocity prediction information

Accurate air supply and stable temperature control are important factors to ensure fuel cell safety and high efficiency. In automotive applications, frequent load changes challenge the air supply and thermal management systems of fuel cells. In this paper, a coordination model predictive control strategy based on velocity prediction is proposed to regulate the oxygen excess ratio and stack temperature to improve the fuel cell system efficiency. First, the impact of load current, temperature and oxygen excess ratio on the efficiency is analyzed to obtain the optimal control reference. Then, the future velocity information is predicted by the long short term memory algorithm and integrated into the disturbance sequences. Optimal control trajectory obtained by collaborative optimization of the global objective function for sub-controllers. Finally, the impact of parameters on control performance is analyzed, and the effectiveness of the coordination control strategy is verified under the com-bined driving condition. The results show that the proposed method can reduce the oxygen excess ratio and temperature control errors by 13.8% and 4.5% compared to the control algorithm without velocity prediction. In addition, the system efficiency is increased by 1.15% due to the introduction of the optimal control reference.

Automated summary

This paper proposes a coordination model predictive control strategy based on velocity prediction to improve the efficiency of fuel cell systems. The impact of load current, temperature, and oxygen excess ratio on efficiency is analyzed to obtain the optimal control reference. The future velocity information is predicted using the long short term memory algorithm and integrated into the disturbance sequences.