自动曲线识别的电池分类系统

Cell classification system based on automatic curve-recognition

介绍了一个建立在向量空间模型上的电池分类系统 ,提出了一个基于模糊决策的快速完成识别电池容量和曲线一致性的计算方法。算法以提取电池充放电特性曲线上的电压、时间作为识别特征 ,并建立了目标隶属函数 ,基于阈值准则 ,完成曲线类别归属的决策 ,给出了系统的基本结构和具体实现方法。实验表明了该方法的可行性 ,当测出电池容量时 ,可以快速准确地将放电容量和充放电特性曲线一致的电池分为一类 ,分类的准确率达到 98%以上 ,为制作高性能的电池组提供了一种实用检测技术。

A cell classify system based on vector space model was introduced and a fast fuzzy based algorithm for recognizing capacity and curve of battery was proposed. The algorithm made a feature of extracting voltage and time from charge/discharge curve of battery. The member degree function of an object to be recognized was established according to its feature parameters. Based on the threshold rules, the ascription of the class of curve was decided as well as the basic structure and the concrete implementation methods of the system were presented. The test results show that the algorithm is feasible. When the capacity of cell is measured, the cell, whose discharge capacity is accordant with its charge/discharge curve, can be classified quickly and accurately with the accuracy rate over 98%. The algorithm provides a valid detection technology for manufacturing battery with high property and high capacity.