单轴联结式并联混合动力汽车分层切换控制设计

Hierarchical switching control design for single-axle parallel hybrid electric vehicles

中文关键词  混合动力汽车(HEV)  分层控制  切换控制  Lyapunov优化算法

英文关键词  hybrid electric vehicle (HEV)  hierarchical control  switching control  Lyapunov optimal algorithm

中文摘要

      为提高整车燃油经济性, 降低尾气排放, 本文针对单轴联结式并联混合动力汽车(parallel hybrid electric vehicle, PHEV)提出了一种分层切换控制方法. 首先, 在分析发动机稳态效率和电池充放电内阻变化规律基础上, 采 用分层切换思想, 制定了PHEV各运行模式间切换规则. 然后, 研究了不同目标运行模式下的能量分配策略, 针对单 一驱动模式和3种制动模式, 设计了基于规则的转矩分配策略; 针对混合模式, 分别设计了行车充电/混合驱动模式 下的Lyapunov优化功率分配策略以及驻车充电模式下的Willans line模型极值法功率分配策略. 最后, 仿真结果表明, 所提出方法可确保发动机和电池工作在高效区. 在UDDS+HWFET工况下, 与电辅助策略相比, 百公里油耗降低了 40.82%, CH, CO和NOx 的排放量分别减少了2.86%, 4.41% 和8.02%; 与基于庞特里亚金最小值原理(Pontryagin’s minimum principle, PMP)的全局优化策略相比, 百公里油耗降低了9.37%.

英文摘要

      In order to improve the fuel economy and reduce the exhaust emissions, a hierarchical switching control method for single-axle parallel hybrid electric vehicles (PHEVs) is proposed in this paper. Firstly, based on analyzing the steady-state efficiency of the engine and the change laws of batteries charge/discharge internal resistance, the switching rules between operation modes of PHEV are formulated by a hierarchical switching idea. Then, the energy allocation strategies under different target operating modes are researched. For single driving modes and three braking modes, a torque distribution strategy based on rules is devised. For the hybrid modes, a power allocation strategy on the basis of the Lyapunov optimal algorithm is designed in driving charge or hybrid driving mode, and a Willans line model extreme-value method of power allocation strategy is developed to split the power in the parking charge mode, respectively. Finally, simulation results show that the proposed strategy can ensure the engine and batteries work in high-efficiency area. Under UDDS+HWFET cycle conditions, the fuel consumption per hundred kilometers is reduced by 40.82%, CH, CO and NOx emissions by 2.86%, 4.41% and 8.02% respectively compared with that of the electric assist control strategy. The fuel consumption per hundred kilometers decreases by 9.37% compared with that of the global optimization strategy based on Pontryagin’s minimum principle (PMP).