Hardware and Software Development of an Open Source Battery Management System

被引:10
|
作者
Sylvestrin, Giovane Ronei [1 ]
Scherer, Helton Fernando [2 ]
Ando Junior, O. H. [3 ]
机构
[1] Univ Estadual Oeste Parana Unioeste, Programa PGEEC, Cascavel, Parana, Brazil
[2] Fundacao Parque Tecnol Itaipu, Foz Do Iguacu, Parana, Brazil
[3] Univ Fed Integracao Latinoamer UNILA, PPGIES, Foz Do Iguacu, Parana, Brazil
关键词
Hardware; Software; Batteries; State of charge; Monitoring; Battery management systems; Sodium; Battery Charging; BMS; battery management; hardware; PACKS; OPERATION; BUS;
D O I
10.1109/TLA.2021.9461844
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to guarantee adequate operating conditions in an energy storage system (SAE), extending its useful life, and offering safety to the user, a device known as the battery management system (BMS) is used. Most devices currently sold are restricted to operating characteristics of lithium battery technologies, which are different in different ways from the operation of other types of batteries that are studied and developed in laboratories. The restriction of use in other technologies could be circumvented through open platforms, allowing modifications in the BMS in order to adapt to the application technology. This adaptive characteristic is rarely found in commercialized devices, being fundamental when the objective of the BMS is linked to academic research that requires experimental steps. Therefore, this work proposes a low cost adaptive open source BMS prototype, capable of monitoring the variables of voltage, current, temperature and state of charge for a battery with up to 10 cells in series. The development includes hardware and software for the basic functioning of BMS functions. The proposed BMS was developed based on two cell technologies with: 18650 lithium ions, and sodium nickel chloride. The versatility of BMS in operating on these two technologies aims to demonstrate the adaptive capacity of the system. For remote monitoring, an interface was developed using the Node-RED and IBM Watson tools.
引用
收藏
页码:1153 / 1163
页数:11
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