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首页> 外文期刊>IEEE Transactions on Intelligent Transportation Systems >A Novel Dual Speed-Curve Optimization Based Approach for Energy-Saving Operation of High-Speed Trains
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A Novel Dual Speed-Curve Optimization Based Approach for Energy-Saving Operation of High-Speed Trains

机译：基于双曲线优化的新型高速列车节能运行方法

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摘要

This paper studies the problem of high-speed train operation with special attention to minimizing the energy consumption. The performance characteristics of a high-speed train, including traction characteristic and regenerative braking, and the railway geographical conditions consisting of slope, curve, and tunnel parameters, are fully considered in the dynamic model in order to make it more effective and practical. A new optimal strategy for train operation is developed, and its novelty lies in the fact that it is the first time to optimize the actual speed curve using the method of dual speed curve optimization, which contains two processes of offline global optimization and online local optimization, thus leading to more energy saving as compared with most existing methods with only one-time optimization process. We utilize combination optimization techniques, in tandem with the speed codes and subsections, to solve the global optimization problem with a genetic algorithm. Predictive control is developed for local optimization to refine the global optimization in real time, more particularly, the train operation modes including traction, cruise, coast, and braking are switched on the base of the line slope information, from which a more energy-efficient speed trajectory is generated under the constraints of fixed time and distance. To verify the effectiveness of the proposed strategy, operation of CHR-3 on high-speed railway is tested. Through the comparison of energy consumption in two typical cases, it verifies that the proposed energy-saving strategy works better than that of single optimization strategy. At the same time, the actual speed deviation can be corrected in a timely manner with the proposed method.
机译：本文研究高速列车的运行问题，并特别注意降低能耗。动态模型中充分考虑了高速列车的性能特征，包括牵引特性和再生制动，以及由坡度，弯道和隧道参数组成的铁路地理条件，以使其更加有效和实用。提出了一种新的列车运行优化策略，其新颖之处在于，这是首次采用双速曲线优化的方法对实际速度曲线进行优化，它包含离线全局优化和在线局部优化两个过程。与仅需一次优化过程的大多数现有方法相比，可以节省更多能源。我们结合速度代码和小节使用组合优化技术，以遗传算法解决全局优化问题。针对局部优化开发了预测控制，以实时优化全局优化，更具体地说，基于线坡度信息切换了包括牵引，巡航，滑行和制动在内的列车运行模式，从而提高了能源效率速度轨迹是在固定的时间和距离的约束下生成的。为了验证所提出策略的有效性，测试了CHR-3在高速铁路上的运行。通过比较两种典型情况下的能耗，验证了所提出的节能策略比单一优化策略更好地工作。同时，使用所提出的方法可以及时纠正实际速度偏差。

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