基于随机动态规划的混联式混合动力客车能量管理策略

The Energy Management Strategy for a Series-Parallel Hybrid Electric Bus Based on Stochastic Dynamic Programming

针对实际行驶工况中不确定的行驶环境和不同的驾驶员风格等因素对新型混联式混合动力客车燃油经济性的影响,在统计若干城市循环工况数据的基础上建立驾驶员需求功率的马尔科夫模型,提出了一种基于随机动态规划算法的能量管理策略,获得了发动机和电池之间的功率分配控制规则。对新型混联式混合动力客车模型的仿真和硬件在环实验结果表明,所提出的策略能使电池荷电状态在预定的区域内保持平衡,使发动机运行工作点处于高效区域内,且整车100km油耗比原型客车和采用规则控制策略时分别降低了30.17%和11.29%。

Aiming at the effects of many factors such as uncertain driving environment and different driver＇s styles on the fuel economy of novel series-parallel hybrid electric bus （SPHEB） in real world driving conditions, a Markov model for driver＇s required power is built based on statistical data of several city driving cycles, and an ener- gy management strategy based on stochastic dynamic programming （SDP） algorithm is proposed and the control rules for power distribution between engine and battery are obtained. Both the results of simulation on the forward model for novel SPHEB and hardware-in-the-loop test demonstrate that the proposed strategy enables the battery SOC to keep balance within its preset range and makes the engine operate in high efficiency region. In addition the fuel consumption per 100km of novel SPHEB reduces by 30.17% and 11.29% respectively compared with original bus and that with rule-based strategy.