混合动力汽车经济型巡航的车速规划策略

选取功率分流式混合动力汽车为对象，以燃油消耗最小为目标开展巡航场景下的经济车速规划研究. 结合车辆动能管理与等效燃油最小化策略（ECMS），提出增强型等效燃油最小化策略（R-ECMS）. 运用极小值原理推导油电等效系数，建立动能与电能间的等效关系；结合电能与燃油之间的等效关系，将车辆动能变化和电能消耗统一转化成燃油消耗. 为了兼顾电池SOC平衡以及车辆通行速度，采取非支配排序遗传算法优化R-ECMS权重系数中的参数. 仿真结果表明，与传统能量管理策略ECMS相比，R-ECMS可以降低8.06%的燃油消耗. 与采用最优算法的动态规划策略相比，R-ECMS能在实现次优的优化效果的同时大幅降低计算时间. 同时，与ECMS相比，R-ECMS在其他仿真场景下能实现6.94%的节油率，具有较好的泛化性能和应用前景.

Velocity planning strategy for economic cruise of hybrid electric vehicles

Economic velocity planning in cruise scenario was studied for the power-split hybrid electric vehicle aiming at minimizing the fuel consumption. A reinforced equivalent consumption minimization strategy (R-ECMS) was proposed based on kinetic energy management and equivalent consumption minimization strategy (ECMS). The equivalent coefficient between fuel and electric energy was derived using minimum principle. Meanwhile, the equivalent relationship between kinetic energy and electric energy was established. The vehicle kinetic change and electric consumption were unified into fuel consumption, combined with the equivalent relationship between fuel and electric energy. The non-dominated sorting genetic algorithm was adopted to optimize the parameters in the weight coefficients of the proposed strategy, to ensure battery SOC balance and meet vehicle travel time at the same time. Simulation results demonstrate that R-ECMS can reduce fuel consumption by 8.06% compared with the traditional control strategy ECMS. The proposed R-ECMS not only achieves sub-optimal optimization performance, but also sharply reduces the computing burden, as compared to dynamic programming. Moreover, its performance is robust to various driving scenarios. The simulation using another road profile in reality shows that the R-ECMS can achieve a 6.94% reduction in the corresponding fuel consumption compared to the ECMS. Thus, the R-ECMS has a good application prospect.