关键词: 质量估算；自适应能量管理；联合仿真；经济性

Abstract: As environmental protection and emission requirements become increasingly stringent, power batteries are gradually replacing internal combustion engines as the power source for a growing number of commercial vehicles. Compared with passenger vehicles, commercial vehicles have a wider range of load variations. To further improve the economic performance of battery electric commercial vehicles, it is necessary to develop an energy management algorithm. Therefore, an adaptive energy management algorithm suitable for battery electric commercial vehicles is proposed. First, based on the vehicle driving equation, a variable forgetting factor recursive least squares algorithm is introduced to estimate the vehicle mass, and the estimation results are corrected in combination with the driving cycle characteristics of battery electric commercial vehicles. Second, based on the mass estimation results, an adaptive energy management algorithm is proposed, which adapts to the economic requirements under different load conditions during vehicle operation. Finally, verification is conducted through the MATLAB-Cruise co-simulation platform and actual vehicle tests. The test results show that for a light-duty electric truck, the corrected vehicle mass estimation error is less than 10%, and the adaptive energy management algorithm can improve vehicle economy by more than 3.6%.

Key words: mass estimation; adaptive energy management; co-simulation; economy