论文标题
使用智能充电器控制可充电电池中的树突
Control of Dendrites in Rechargeable Batteries using Smart Charging
论文作者
论文摘要
在本文中，我们开发了一个馈回控制框架，以实时最小化可充电电池内生长的微观结构。由于分支进化的加快性质，我们在早期阶段确定了关键的受损峰，并根据状态计算那些分支手指的浓度的放松时间。控制参数是分支微观结构的最大曲率（即最小半径）的函数，其中较高的速率树突发展将导致要控制的更关键的状态。为了生成最多的微观结构，充电时间最小化，并获得与充电时间较高的结果密切相关的结果。开发的框架可以用作安全可持续操作的智能充电协议，可充电电池，其中微结构的分支可以与当前/电压突然变化相关。
In this paper we develop a feed-back control framework for the real-time minimization of microstructures grown within the rechargeable battery. Due to quickening nature of the branched evolution, we identify the critical ramified peaks in the early stages and based on the state we compute the relaxation time for the concentration in those branching fingers. The control parameter is a function of the maximum curvature (i.e. minimum radius) of the branched microstructure, where the higher rate dendritic evolution would lead to the more critical state to be controlled. The charging time is minimized for generating the most packed microstructures and obtained results correlate closely with those of considerably higher charging time periods. The developed framework could be utilized as a smart charging protocol for the safe and sustainable operation the rechargeable batteries, where the branching of the microstructures could be correlated to the sudden variation in the current/voltage.
