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Speed profile optimization of an electric train with on-board energy storage and continuous tractive effort

机译:具有车载储能和持续牵引力的电动火车的速度曲线优化

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Electric traction system is the most energy efficient traction system in railways. Nevertheless, not all railway networks are electrified, which is due to high maintenance and setup cost of overhead lines. One solution to the problem is battery-driven trains, which can make the best use of the electric traction system while avoiding the high costs of the catenary system. Due to the high power consumption of electric trains, energy management of battery trains are crucial in order to get the best use of batteries. This paper suggests a general algorithm for speed profile optimization of an electric train with an on-board energy storage device, during catenary-free operation on a given line section. The approach is based on discrete dynamic programming, where the train model and the objective function are based on equations of motion rather than electrical equations. This makes the model compatible with all sorts of energy storage devices. Unlike previous approaches which consider trains with throttle levels for tractive effort, the new approach considers trains in which there are no throttles and tractive effort is controlled with a controller (smooth gliding handle with no discrete levels). Furthermore, unlike previous approaches, the control variable is the velocity change instead of the applied tractive effort. The accuracy and performance of the discretized approach is evaluated in comparison to the formal movement equations in a simulated experimented using train data from the Bombardier Electrostar series and track data from the UK.
机译:电牵引系统是铁路上最节能的牵引系统。然而,由于架空线的高维护成本和安装成本,并非所有铁路网络都电气化。解决该问题的一种方法是电池驱动的火车,它可以充分利用电力牵引系统,同时又避免了悬链线系统的高额成本。由于电动火车的高功耗,电池火车的能量管理对于获得电池的最佳使用至关重要。本文提出了一种通用算法,用于在给定的线路段上进行无接触线操作的情况下,使用车载储能装置优化电动火车的速度曲线。该方法基于离散动态规划,其中火车模型和目标函数基于运动方程而非电气方程。这使得该模型与各种储能设备兼容。与以前的方法考虑将油门高度用于牵引力的列车不同,新方法考虑的是其中没有油门且牵引力由控制器(平滑的滑行手柄,无离散水平)控制的列车。此外,与以前的方法不同,控制变量是速度变化,而不是所施加的牵引力。在使用Bombardier Electrostar系列的火车数据和英国的跟踪数据进行的模拟实验中,与形式运动方程进行了比较,对离散化方法的准确性和性能进行了评估。

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