Energy management strategy of fuel cell bus based on working condition identification

Abstract:

To solve the problem that energy management strategy based on optimization in fuel cell hybrid electric buses is difficult to apply to real life vehicles, an energy management strategy based on SOM-K-means driving condition identification is proposed with reference to the analysis of the fixedness and fragmentation of the fuel cell bus (FCHB) driving route. Firstly, the driving route is divided into driving segments according to bus stops. When the vehicle stops, the SOM-K-means second-order clustering model is used to identify the driving condition, and obtain the predictive co-state of the next driving segment. When the vehicle runs in the next driving segment, a predictive co-state is used to complete the real-time application of the minimum fuel equivalent fuel consumption strategy based on the PMP solution. Secondly, the simulation experiments based on the actual driving data of the bus are established. Finally, the proposed strategy is applied to the vehicle control unit (VCU). The results show that compared with the rule-based strategy, the proposed strategy reduces hydrogen consumption by 19.77%. The calculation time of each step in the VCU is about 30 ms, and the calculation results prove to be completely consistent with the simulation results, meeting the requirements of vehicle for the timeliness and accuracy of energy management strategy.