采用动态规划策略可以极大地改善混联式混合动力汽车(hybrid electric vehicle,HEV)的燃料消耗和动力部件的运行效率。因此,本文通过动态规划策略来研究电池荷电状态(state of charge,SOC)在全球轻型汽车测试循环(world light vehicle t...采用动态规划策略可以极大地改善混联式混合动力汽车(hybrid electric vehicle,HEV)的燃料消耗和动力部件的运行效率。因此,本文通过动态规划策略来研究电池荷电状态(state of charge,SOC)在全球轻型汽车测试循环(world light vehicle test cycle,WLTC)工况下的变化趋势。将等效燃油消耗最低的能量管理策略作为基础,以SOC目标值与瞬时值的差值作为比例积分控制器的输入,实时调整油电转换等效因子,使电池荷电状态的实际状态与理论预测的状态相接近,从而获得一种具有实时调节功能的自适应等效油耗最小的能量管理策略。经过仿真探究证明,在WLTC工况条件下,相比于传统等效油耗最小的能量管理策略,自适应等效油耗最小的能量管理策略能够达到节能目标,混联式HEV百公里可降低1.82%的燃料消耗,且自适应等效燃油消耗最小能量管理策略的控制效果与动态规划控制策略更加接近。展开更多
With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid elec...With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid electric vehicles(HEVs).Moreover,the terrain along the driving route is a non-ignorable factor for energy efficiency of HEV running on the hilly streets.This paper proposes a look-ahead horizon-based optimal energy management strategy to jointly improve the efficiencies of powertrain and vehicle for connected and automated HEVs on the road with slope.Firstly,a rule-based framework is developed to guarantee the success of automated driving in the traffic scenario.Then a constrained optimal control problem is formulated to minimize the fuel consumption and the electricity consumption under the satisfaction of inter-vehicular distance constraint between ego vehicle and preceding vehicle.Both speed planning and torque split of hybrid powertrain are provided by the proposed approach.Moreover,the preceding vehicle speed in the look-ahead horizon is predicted by extreme learning machine with real-time data obtained from communication of vehicle-to-everything.The optimal solution is derived through the Pontryagin’s maximum principle.Finally,to verify the effectiveness of the proposed algorithm,a traffic-in-the-loop powertrain platform with data from real world traffic environment is built.It is found that the fuel economy for the proposed energy management strategy improves in average 17.0%in scenarios of different traffic densities,compared to the energy management strategy without prediction of preceding vehicle speed.展开更多
文摘采用动态规划策略可以极大地改善混联式混合动力汽车(hybrid electric vehicle,HEV)的燃料消耗和动力部件的运行效率。因此,本文通过动态规划策略来研究电池荷电状态(state of charge,SOC)在全球轻型汽车测试循环(world light vehicle test cycle,WLTC)工况下的变化趋势。将等效燃油消耗最低的能量管理策略作为基础,以SOC目标值与瞬时值的差值作为比例积分控制器的输入,实时调整油电转换等效因子,使电池荷电状态的实际状态与理论预测的状态相接近,从而获得一种具有实时调节功能的自适应等效油耗最小的能量管理策略。经过仿真探究证明,在WLTC工况条件下,相比于传统等效油耗最小的能量管理策略,自适应等效油耗最小的能量管理策略能够达到节能目标,混联式HEV百公里可降低1.82%的燃料消耗,且自适应等效燃油消耗最小能量管理策略的控制效果与动态规划控制策略更加接近。
文摘With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid electric vehicles(HEVs).Moreover,the terrain along the driving route is a non-ignorable factor for energy efficiency of HEV running on the hilly streets.This paper proposes a look-ahead horizon-based optimal energy management strategy to jointly improve the efficiencies of powertrain and vehicle for connected and automated HEVs on the road with slope.Firstly,a rule-based framework is developed to guarantee the success of automated driving in the traffic scenario.Then a constrained optimal control problem is formulated to minimize the fuel consumption and the electricity consumption under the satisfaction of inter-vehicular distance constraint between ego vehicle and preceding vehicle.Both speed planning and torque split of hybrid powertrain are provided by the proposed approach.Moreover,the preceding vehicle speed in the look-ahead horizon is predicted by extreme learning machine with real-time data obtained from communication of vehicle-to-everything.The optimal solution is derived through the Pontryagin’s maximum principle.Finally,to verify the effectiveness of the proposed algorithm,a traffic-in-the-loop powertrain platform with data from real world traffic environment is built.It is found that the fuel economy for the proposed energy management strategy improves in average 17.0%in scenarios of different traffic densities,compared to the energy management strategy without prediction of preceding vehicle speed.
