Real-time Energy Management Strategy of Fuel Cell Vehicles Based on Multi-objective Optimization.

In order to reduce the equivalent hydrogen consumption of the hybrid system and delay the aging of the fuel cell, an Energy management strategy (EMS) was proposed based on multi-objective optimization and road condition classification. Firstly, the electrical model of the fuel cell and lithium battery hybrid system power was constructed, and the equivalent hydrogen consumption model and fuel cell aging model were introduced. Then, a rule-based multi-mode EMS was designed; on this basis, in order to further reduce the equivalent hydrogen consumption of the system and prolong its service life, the multi-objective beluga whale optimization algorithm (MOBWO) was proposed to optimize the control parameters. Furthermore, in order to make the designed EMS suitable for different road conditions, a real-time classification method of driving road conditions based on long short-term memory (LSTM) network was proposed, aiming to switch the control parameters of EMS according to the classification results to achieve the optimal effect. Finally, the proposed algorithm was analyzed on the simulation platform. The results showed that the hydrogen consumption of the hybrid system with the proposed method was reduced by 2.3% and the aging degree of the fuel cell was reduced by 1.02% compared with the rule-based method, The proposed EMS could effectively reduce the equivalent hydrogen consumption of the hybrid system and delay the aging of the fuel cell. [ABSTRACT FROM AUTHOR]