当前位置: X-MOL 学术Control Eng. Pract. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Real-time energy-efficient optimal control of high-speed electric train
Control Engineering Practice ( IF 5.4 ) Pub Date : 2021-04-26 , DOI: 10.1016/j.conengprac.2021.104825
Hao Zhou , Yiming Wan , Hao Ye , Ming Jiang , Jia Wang

This paper studies the real-time energy-efficient optimal control of high-speed electric trains within a given trip time. In particular, we focus on the re-optimization of the driving strategy, in the case that the actual train speed deviates from the planned optimal speed profile due to uncertainties. The proposed optimization algorithm has a double-loop structure with simultaneous action implementation. It results in reduced computation complexity and shortened control period, compared to the conventional double-loop algorithm with delayed action implementation. Existence and uniqueness of the solution to the re-optimization problem are discussed, and the convergence of the proposed simultaneous action method is proved. Moreover, it is shown by perturbation analysis that the resulting energy consumption during speed switching process is reduced. The effectiveness of the proposed method is demonstrated by the simulation study on two tracks of Dongguan–Huizhou intercity railway in China.



中文翻译:

高速电动火车的实时节能优化控制

本文研究了在给定的行程时间内高速电动火车的实时节能优化控制。特别是,在实际火车速度由于不确定性而偏离计划的最佳速度曲线的情况下,我们将重点放在驾驶策略的重新优化上。所提出的优化算法具有双循环结构,具有同步动作实现。与传统的具有延迟动作实现的双环算法相比,它减少了计算复杂度并缩短了控制周期。讨论了再优化问题解的存在性和唯一性,并证明了所提同时行动方法的收敛性。此外,通过扰动分析表明,降低了速度切换过程中所产生的能耗。

更新日期:2021-04-26
down
wechat
bug