摘要
文章针对一款串联插电式混合动力城市公交,提出一种可实时应用的模型预测控制(MPC)能量管理策略,以能耗最小为目标优化整车功率分配。首先,基于马尔科夫链根据历史车速和加速度建立单步和多步速度预测模型;从而进行预测时域内滚动优化,选择动态规划算法(DP)得到动力系统最优控制序列;最后对比了基于模型预测、动态规划和庞特里亚金极小值原理(PMP)的能量管理策略。结果表明,提出的模型预测控制(MPC)能达到与全局优化算法相近的控制效果且能应用于实时控制,是其他两种方法不具备的,体现出该策略的优越性。
A series plug-in hybrid city bus is used to optimize control sequence of the powertrain system with the goal of minimizing energy consumption based on model predictive control(MPC)energy management strategy, which can be applied in real time. Firstly, a single and a multi-step speed prediction model based on Markov chain is established according to the historical speed and acceleration. The dynamic programming(DP) algorithm was used to obtain the optimal control sequence of the dynamical system. Finally, the energy management strategies based on model predictive control(MPC), DP and PMP are compared. The results show that the proposed MPC can achieve the control effect similar to the global optimization algorithm and can be applied to real time control, which is not available in the other two methods. It reflects the superiority of this strategy.
作者
王乐妍
WANG Leyan(School of Automotive Engineering,Chang’an University,Xi’an 710064,China)
出处
《汽车实用技术》
2022年第23期34-38,共5页
Automobile Applied Technology
