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基于闭塞区间的高速列车运行时间与节能协同优化方法
引用本文:赵辉,代学武.基于闭塞区间的高速列车运行时间与节能协同优化方法[J].自动化学报,2020,46(3):471-481.
作者姓名:赵辉  代学武
作者单位:1.东北大学流程工业综合自动化国家重点实验室 沈阳 110819
基金项目:国家自然科学基金(61790574, 61773111, U1834211), 中国国家铁路集团有限公司科技研究开发计划课题(N2019G020)资助
摘    要:提出了一种高速列车运行时间与节能协同优化方法.针对由动态调度层、优化控制层、跟踪控制层组成的列车运行控制与动态调度一体化结构,设计了面向动态调度层和优化控制层的列车运行时间调整策略和节能速度位置曲线.基于高速铁路闭塞区间,建立了列车区间模型和列车速度曲线节能优化模型.利用模型预测控制方法对列车区间运行时间进行调整,优化列车总延误时间;根据调整后的区间运行时间设计列车运行优化速度位置曲线,减少列车运行能耗.仿真算例验证了设计的运行时间与节能协同优化策略的有效性.

关 键 词:高速列车  一体化  运行时间与节能  协同优化
收稿时间:2019-03-20

Cooperative Optimization Method for High-speed Trains Running Time and Energy Saving Based on Block Sections
ZHAO Hui,DAI Xue-Wu.Cooperative Optimization Method for High-speed Trains Running Time and Energy Saving Based on Block Sections[J].Acta Automatica Sinica,2020,46(3):471-481.
Authors:ZHAO Hui  DAI Xue-Wu
Affiliation:1.State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819
Abstract:A cooperative optimization method for high-speed trains running time and energy saving is proposed. For the integrated scheme of train operation control and dynamic rescheduling which consists of dynamic rescheduling layer, optimization control layer and tracking control layer, the running time adjustment strategy and energy saving speed-position trajectory are designed for dynamic rescheduling layer and optimization control layer. The train-section model and energy saving speed trajectory model are established based on the block sections of high-speed railway. The model predictive control method is utilized to adjust the section running time of trains and optimize the total delay time of trains. Then according to the adjusted section running time, the optimal speed-position trajectory is generated for each train so as to reduce the energy consumption. Numerical examples are given to illustrate the effectiveness of the proposed running time and energy saving cooperative optimization strategy.
Keywords:High-speed train  integration  running time and energy saving  cooperative optimization
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