Implementation of Power Battery Voltage Fault Diagnosis System Based on Improved Shannon Entropy Algorithm

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2021-12-03 DOI:10.1109/ICNSC52481.2021.9702238

Weidong Fang, Yiting Jiang, H. Lv

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Abstract

Nowadays, electric vehicles have become one of the most promising new products. The research on the faults in the power battery system can effectively diagnose the faults in the power battery system, predict the occurrence of faults, and improve the service life of the power battery system. This paper uses Matlab / Simulink to simulate the sensor data acquisition system. It builds our own database on software to receive the data sent by MATLAB, and sends the data in the format of can message, so as to build the joint simulation system of CANoe and MATLAB. This enables data exchange between the two.By connecting Jetson Nano with CANoe software and big data platform onenet, the principle of Shannon entropy algorithm is studied, and the improved Shannon entropy is realized through software programming. The big data platform displays the single cell voltage data obtained by Jetson nano and the results of single cell voltage through Shannon entropy algorithm. The experimental results show that Shannon entropy can predict the voltage undervoltage fault of single cell 52 seconds in advance.

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基于改进香农熵算法的动力电池电压故障诊断系统实现

如今，电动汽车已经成为最有前途的新产品之一。对动力电池系统故障进行研究，可以有效地诊断动力电池系统故障，预测故障的发生，提高动力电池系统的使用寿命。本文利用Matlab / Simulink对传感器数据采集系统进行仿真。在软件上建立自己的数据库，接收MATLAB发送的数据，并以can报文的格式发送数据，从而构建CANoe与MATLAB的联合仿真系统。这使得两者之间的数据交换成为可能。通过将Jetson Nano与CANoe软件和大数据平台onenet连接，研究香农熵算法的原理，并通过软件编程实现改进后的香农熵。大数据平台显示Jetson nano获得的单电池电压数据和Shannon熵算法得到的单电池电压结果。实验结果表明，香农熵可以提前52秒预测单体电池的电压欠压故障。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2021 IEEE International Conference on Networking, Sensing and Control (ICNSC)

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