基于动力电池海量数据的特性化压缩处理研究  

Research on characteristic compression processing based on massive data of power battery

作　　者：王瑞[1,2] 张维戈 张言茹[1,2] 吕亚军 Wang Rui;Zhang Weige;Zhang Yanru;Lv Yajun(School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China;National Active Distribution Network Technology Research Center,Beijing 100044,China)

机构地区：[1]北京交通大学电气工程学院,北京100044 [2]国家能源主动配电网技术研发中心,北京100044

出　　处：《电测与仪表》2020年第1期99-105,共7页Electrical Measurement & Instrumentation

基　　金：国家重点研发计划项目(2017YFB1201005)

摘　　要：动力电池数据的后台存储和分析无论是对于动力电池故障预警、动力电池回收、溯源管理,还是为动力电池的后续价值评估,都提供了数据支撑。面向海量数据传输存储的发展需求,文章提出针对动力电池数据特性的处理压缩方法。将多种压缩算法进行对比选择;针对动力电池的不同数据类型、不同运行场景进行多方面分析研究,给出相应的处理方法;最终经过对运行数据的处理压缩,实现数据传输、存储成本的有效降低。The background storage and analysis of power battery data provides data support for power battery failure warning,power battery recovery,traceability management,and subsequent value evaluation of power battery. For the requirement of massive data transmission and storage,this paper proposes a compression processing method for the characteristics of power battery data. In this paper,a variety of compression algorithms are compared and selected;for different data types of power batteries,different operating scenarios are analyzed and researched in various aspects,and the corresponding processing methods are given. Finally,the cost of data transmission and storage is effectively reduced after processing and compressing the running data.

关 键 词：动力电池 数据处理 哈夫曼编码 LZ77算法 BWT 

分 类 号：TM76[电气工程—电力系统及自动化]