融合充电路径规划的REEV里程自适应控制策略

Mileage Adaptive Control Strategy for REEV with Integrated Charging Path Planning

为充分利用电网电能,以增程式电动汽车(Range-Extended Electric Vehicles,REEV)为研究对象,基于车载导航系统、智能交通系统(ITS)以及智能电网系统,运用迪克斯特拉(Dijkstra)算法对REEV进行充电路径规划,引入里程信息以及参考电池剩余电量(SOC),并根据路径规划结果,综合考虑车辆的燃油经济性和排放性,对规划路径制定分段里程自适应控制策略,使REEV能够在不同里程段内合理分配辅助动力装置(APU)和电池的能量。基于Matlab/Simulink搭建整车控制策略仿真模型进行仿真验证,结果表明,当行驶里程约175km时,在牺牲一部分充电时间的代价下,车辆节省了1.77L燃油,REEV的油耗下降率为92.64%,所制定的分段里程自适应控制策略能够充分利用电网电能,车辆节能效果明显。

To fully utilize electric power,the Dijkstra algorithm is used to plan the charging path for range extended electric vehicles (REEVs),based on a vehicle navigation system,intelligent transportation system (ITS) and intelligent power grid system.In accordance with the path planning result,the driving mileage information and reference SOC are introduced,the fuel economy and emissions of the vehicle are considered synthetically,and the segmented mileage adaptive control strategy is developed for the planning path,to ensure that the REEV can allocate the APU and the battery energy reasonably for different mileages.Based on MATLAB/Simulink results,the simulation model for the vehicle control strategy has been built and a simulation test has been conducted.The results show that,at the expense of a portion of the charging time,1.77 L of fuel is saved and that the reduction in fuel consumption of the REEV can reach 92.64% when the mileage is approximately 175 km.The segmental range adaptive control strategy fully utilizes the power grid,and the positive effect of energy saving for vehicles is clear.