Electric Vehicle Operation Scheduling Optimization Considering Electrochemical Characteristics of Li-Ion Batteries

Mingyu Lyu, B. Han, Shaofeng Lu
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引用次数: 1

Abstract

Ahstract-With the development of Electric Vehicles (EVs), charging and discharging scheduling for the EV fleet becomes an interesting topic with its large impact on economic costs and power systems. In many recent studies, the adopted models ignore the special electrochemical characteristics of Li-ion batteries, i.e. the correlation between the charging power limit and battery's state of energy and this has led to an inaccurate presentation of the charging and discharging scheduling of the EV fleet. This paper proposes a Li-ion battery charging dynamic model to incorporate this correlation to more accurately approximate the real-life battery charging characteristics. The proposed dynamic model is compared to the static model used in some papers, in which the charging power limit is considered constant regardless of battery state of energy. The differences in cost and time are observed. The result shows in the dynamic model, charging time is longer and the cost is higher than that of in the static model. Increment rate of charging time and cost have been observed in 0.2C (slow charging) and 1C (fast charging) cases for 1000 EVs respectively. These differences can be well attributed to the decreasing charging power limit caused by the increase of SOE.
考虑锂离子电池电化学特性的电动汽车运行调度优化
摘要随着电动汽车的发展,电动汽车的充放电调度问题对经济成本和电力系统的影响越来越大。在最近的许多研究中,所采用的模型忽略了锂离子电池的特殊电化学特性,即充电功率限制与电池能量状态之间的相关性,这导致了电动汽车车队充放电调度的不准确表示。本文提出了一个锂离子电池充电动态模型,将这种相关性纳入其中,以更准确地近似实际电池充电特性。本文提出的动态模型与一些文献中使用的静态模型进行了比较,在静态模型中,无论电池的能量状态如何,充电功率限制都是恒定的。观察到成本和时间的差异。结果表明,与静态模型相比,动态模型的充电时间更长,成本更高。在1000辆电动汽车的0.2C(慢充)和1C(快充)情况下,分别观察到充电时间和成本的增量率。这些差异可以很好地归因于SOE的增加导致充电功率极限的降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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