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E-REV全局能量管理策略优化与研究

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以整车燃油经济性为优化目标,将Dijkstra算法应用于增程式电动汽车能量管理策略.对中国轻型商用车行驶工况(CLTC-C)的仿真结果表明,Dijkstra算法花费时间约为动态规划的 40%,Dijkstra算法的终点一定是给定的SOC终点的值,而动态规划终点SOC值与给定SOC值有一定误差;同时,考虑发动机启停损耗和最小工作时间,使得发动机启停次数降低 40%左右,改善发动机工况,更符合实际,燃油经济性也得到一定提高.
Research and optimization on global energy management strategy of E-REV
Dijkstra algorithm was applied to the global energy management strategy of extended-range electric vehicles(E-REVs)with the optimization objective of the whole vehicle's fuel economy.The simulation results of China Light Commercial Vehicle Operating Condition(CLTC-C)showed that,Dijkstra algorithm took about 40%of the time of dynamic programming;The endpoint of the algorithm Dijkstra must be the given SOC endpoint,while there was a certain error between the value of the endpoint of dynamic programming and the given SOC value.Considering the engine start-stop loss and minimum working time,the engine start-stop frequency was reduced by about 40%,and the engine working condition was improved,which was more in line with the practice and fuel economy was also improved.

extended-range electric vehicleDijkstra algorithmdynamic programmingenergy management strategy

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合肥工业大学 汽车工程技术研究院,安徽 合肥 230009

增程式电动汽车 Dijkstra算法 动态规划 能量管理策略

2024

农业装备与车辆工程
山东省农业机械科学研究所 山东农机学会

农业装备与车辆工程

影响因子:0.279
ISSN:1673-3142
年,卷(期):2024.62(3)
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