Energy management strategy for extended range electric logistics vehicle based on type-2 fuzzy control

To overcome the limitations of fuzzy energy management strategy (EMS) in describing uncertainty, this paper proposes an EMS based on type-2 fuzzy (T2F), which optimizes energy consumption for extended range electric logistics vehicle (ERELV). Firstly, establish an energy consumption simulation model for ERELV. Then, an EMS based on T2F controller is designed. The strategy takes the state of charge (SOC) and the demand power as the input, and the range extender power as the output. This paper analyses the influence of T2F control strategy on the energy consumption of the ERELV, and uses the model-based design method to verify the EMS in the Hardware-in-the-loop (HIL) simulation test. The test results show that compared with the traditional fuzzy control strategy, the T2F strategy can reduce the engine’s energy loss by 12.58%. Finally, actual fuel consumption tests were conducted on the established ERELV model. By comparing the results of C-WTVC and CHTC-HT operating conditions, the model was verified to meet the research requirements of EMSs in this paper and has practical significance.