Electric bicycle battery management system based on NB-IoT

Qingyao Lin; Qiuhong Gao

doi:10.1117/12.3031217

19 July 2024 Electric bicycle battery management system based on NB-IoT

Qingyao Lin, Qiuhong Gao

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131816U (2024) https://doi.org/10.1117/12.3031217
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

The birth of electric bicycles greatly facilitated people's lives. However, due to the increasing voltage of electric vehicle batteries, the discharge power and capacity have also increased. The Battery Management System (BMS) developed in the early stage has been unable to accurately estimate the battery capacity and provide timely battery protection. In order to improve the safety, reliability and accuracy of capacity estimation of electric vehicle batteries, this project has designed an intelligent electric vehicle battery management system that can use NB-IoT technology to communicate and measure the battery impedance in real time. There is an NTC temperature sensor array inside the battery pack that can detect the temperature of each battery. When the battery is abnormal, the abnormal data can be sent to the nearby base station through the NB-IoT module. Then, the user and administrator can be informed through the cloud platform to ensure the safety of the battery. The NB-IoT module also supports the location tracking, which can periodically send the location data to the cloud platform. Additionally, the battery pack is also equipped with an Impedance Track Algorithm coulometer that can calculate the remaining capacity of the battery and discharge time at any time. The accuracy can reach 99%.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qingyao Lin and Qiuhong Gao "Electric bicycle battery management system based on NB-IoT", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131816U (19 July 2024); https://doi.org/10.1117/12.3031217

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KEYWORDS

Batteries

Telecommunications

Field effect transistors

Clouds

Power consumption

Power meters

Control systems

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