可视化
Python(编程语言)
计算机科学
预处理器
数据可视化
电池(电)
数据预处理
工作流程
服务(商务)
数据库
数据挖掘
操作系统
人工智能
经济
经济
功率(物理)
物理
量子力学
作者
Zuyi Liang,Zongwei Liang,Yubin Zheng,Beichen Liang,Linfeng Zheng
摘要
Battery operating data of electric vehicles is becoming increasingly quantified and complicated. A data analysis platform is necessary to excavate high-value battery status information for more efficient battery management. This paper proposes a Flask framework and Pyecharts-based lithium-ion data analysis and visualization platform. The design processes including the front-end and back-end frameworks, data preprocessing, data visualization, and data storage are elaborated. In the proposed data platform, a case study of battery state of charge estimation using different machine learning methods is demonstrated, and most of the estimation errors are less than 2.0%, highlighting the effectiveness of the platform.
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