电池SOC和道路预测的混合动力最优能量管理

Optimal energy management for hybrid electric vehicle based on path forecasting and battery SOC

混合动力电动车能量控制策略是提高车辆性能的关键技术之一,重点研究基于部分道路预测的混合动力电动车(HEV)能量管理策略。通过预测电动车的行驶轨迹优化电池的充电和放电性能,结合不同路段电池的实时荷电状态(SOC)值估算燃油消耗量,从而达到提高混合动力整车能量利用效率的目的。新方法将电动车整段行驶轨迹分割成连续相连的部分路段,动态估算每段轨迹的车辆参数值,利用动态编程工具验证可用道路信息的优越性。NEDC工况仿真结果和实际电动车实验结果显示,新算法可动态模拟电动车电池在每个路段的电量消耗情况,在相同路段条件下燃油节省率达到10.8%和12.5%。

The energy management strategy for the hybrid electric vehicle （HEV） based on the path forecasting was the key technology and the State of Charge estimation of the lithium battery was the major study. The charge and discharge performance of the battery in the hybdd system was optimized according to the route of the vehicles. The fuel consumption could be estimated by the information of the real-time battery SOC value and sought to improve HEV fuel economy. The characteristics of this new method were： Firstly, the vehicle route was decomposed into a sedes connection of route segments with known properties. Secondly, the dynamic programming was used to obtain the battery SOC value and the parameters of the hybdd system. The experimental results of the simulation condition and the prac＇dcel vehicle confirm that the fuel consumption of the hybrid vehicle by estimating the battery SOC value in each route segment can be improved by the new method. The supplementary fuel savings could reach to 10.8% and 12.5% in two different traffic conditions.