为降低插电式混合动力汽车（PHEV）的油耗，提出了一种基于等效因子自适应的等效油耗最小策略(ECMS)。首先，采用动态规划算法求解不同标准工况下SOC在不同里程下的最优变化轨迹；其次，利用对数函数对等效因子进行实时修正和更新，使SOC能够跟随理论参考轨迹，进而构建自适应等效油耗最小能量管理策略(A-ECMS)。仿真结果表明，本研究提出的A-ECMS策略油耗相较于传统ECMS策略减少了2.41%，且其控制效果与DP算法更接近。

To reduce the fuel consumption of hybrid vehicles, an equivalent fuel consumption minimum strategy (ECMS) based on equivalent factor adaptive was proposed. The optimal change trajectories of SOC under different standard operating conditions and mileages were solved based on dynamic programming algorithm. A logarithmic function was then used to dynamically compensate and update the equivalence factor, enabling battery SOC to track the theoretical reference trajectory. Then the A-ECMS was constructed. The simulation results show that the proposed A-ECMS strategy reduces fuel consumption by 2.41% compared to the ECMS strategy, and the control effect of A-ECMS is closer to that of the dynamic programming algorithm.