首页> 外文期刊>Electrical Systems in Transportation, IET >Optimisation of reference state-of-charge curves for the feed-forward charge/discharge control of energy storage systems on-board DC electric railway vehicles
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Optimisation of reference state-of-charge curves for the feed-forward charge/discharge control of energy storage systems on-board DC electric railway vehicles

机译:直流电动铁路车辆储能系统前馈充电/放电控制的参考荷电状态曲线的优化

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摘要

The charge/discharge control of OBESS's (on-board energy storage systems) on-board DC electric railway vehicles based on the feed-forward data is proposed in this study. The feed-forward data, called the reference SOC (state-of-charge) curve, determines the SOC of an OBESS against the train position. The detailed simulation model of this charge/discharge control scheme has been implemented in a multi-train power network simulator. A rule-based approach to the design of the SOC curve is proposed, in which the trajectory of charge/discharge power of an OBESS on a train is generated using a simple set of rules from the trajectory of input/output power of the traction system. From the evaluation using the developed simulation model, it can be concluded that the system having OBESS's with the proposed feed-forward control effectively reduces energy consumption. However, the proposed SOC curve design process includes hand-adjusting of many parameters; therefore, the numerical optimisation of these parameters is proposed, in which the developed simulation model is embedded for calculating the evaluation function. Results yielded from several attempts of optimisation show that the optimisation yields sufficiently effective SOC curves, although the improvement from the result yielded by hand-adjusted parameters is small.
机译:本研究提出了基于前馈数据的OBESS(车载储能系统)车载DC电动铁路车辆的充电/放电控制。前馈数据(称为参考SOC(荷电状态)曲线)确定了相对于列车位置的OBESS的SOC。该充电/放电控制方案的详细仿真模型已在多列电网仿真器中实现。提出了一种基于规则的SOC曲线设计方法,其中,从牵引系统的输入/输出功率轨迹使用一组简单的规则生成火车上OBESS的充电/放电功率轨迹。从使用开发的仿真模型进行的评估中可以得出结论,具有OBESS且具有建议的前馈控制的系统有效地降低了能耗。但是,建议的SOC曲线设计过程包括许多参数的手动调整。因此,提出了这些参数的数值优化,其中嵌入了开发的仿真模型以计算评估函数。通过几次优化尝试得出的结果表明,尽管通过手工调整的参数得出的结果改进很小,但该优化过程可以产生足够有效的SOC曲线。

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