基于实时路况信息的插电式混合动力汽车预测性能量管理算法研究

Research on Predictive Energy Management Algorithm of PHEV Based on Real-Time Traffic Information

为提高插电式混合动力汽车的燃油经济性,对基于实时路况信息的预测性能量管理算法展开研究。根据实时路况信息采用能耗分配法规划全局SOC参考轨迹,利用自适应等效燃油消耗最小策略(A-ECMS)跟随目标SOC轨迹实现能量管理。以上海市某行驶工况数据进行仿真,结果表明:全局SOC参考轨迹可在低、高速区间合理分配电量,真实SOC轨迹与参考轨迹变化趋势一致,燃油经济性较电量消耗-电量维持(CD-CS)策略提高7.65%,接近动态规划(DP)算法的全局最优解。

In order to improve the fuel economy of plug-in hybrid electric vehicle,the researchers study a predictive energy management algorithm based on real-time traffic information.Energy consumption distribution method is used to plan a global SOC reference trajectory based on the real-time traffic information,and Adaptive Equivalent Fuel Consumption Minimization Strategy(A-ECMS)is used to follow the target SOC trajectory to achieve energy management.The simulation is carried out based on the data of a driving condition in Shanghai.The result shows that:the global SOC reference trajectory could reasonably distribute power at low speed and high speed separately,the trend of real SOC trajectory is consistent with that of the reference trajectory,and the fuel economy is 7.65%higher than that of CD-CS strategy,which is close to the global optimal solution of Dynamic Programming(DP).