Data Analysis and Visualization Platform Design for Batteries Using Flask-Based Python Web Service

World Electric Vehicle Journal

Zongwei Liang¹  Yubin Zheng¹  Linfeng Zheng¹  Zuyi Liang¹  Beichen Liang¹ 

[1] International Energy School, Jinan University, Zhuhai 519070, China;

关键词: lithium-ion battery;    visualization platform design;    data analysis;    machine learning method;    state of charge (SOC) estimation;   

DOI  :  10.3390/wevj12040187

来源: DOAJ

【 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.

【 授权许可】

Unknown