Suppr超能文献

基于真实云计算系统的分布式智能电池管理系统。

Distributed Intelligent Battery Management System Using a Real-World Cloud Computing System.

机构信息

Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 Valencia, Spain.

出版信息

Sensors (Basel). 2023 Mar 24;23(7):3417. doi: 10.3390/s23073417.

Abstract

In this work, a decentralized but synchronized real-world system for smart battery management was designed by using a general controller with cloud computing capability, four charge regulators, and a set of sensorized battery monitors with networking and Bluetooth capabilities. Currently, for real-world applications, battery management systems (BMSs) can be used in the form of distributed control systems where general controllers, charge regulators, and smart monitors and sensors are integrated, such as those proposed in this work, which allow more precise estimations of a large set of important parameters, such as the state of charge (SOC), state of health (SOH), current, voltage, and temperature, seeking the safety and the extension of the useful life of energy storage systems based on battery banks. The system used is a paradigmatic real-world example of the so-called intelligent battery management systems. One of the contributions made in this work is the realization of a distributed design of a BMS, which adds the benefit of increased system security compared to a fully centralized BMS structure. Another research contribution made in this work is the development of a methodical modeling procedure based on Petri Nets, which establishes, in a visible, organized, and precise way, the set of conditions that will determine the operation of the BMS. If this modeling is not carried out, the threshold values and their conditions remain scattered, not very transparent, and difficult to deal with in an aggregate way.

摘要

在这项工作中,使用具有云计算能力的通用控制器、四个充电器和一组具有联网和蓝牙功能的传感器电池监视器,设计了一个去中心化但同步的智能电池管理实际系统。目前,对于实际应用,电池管理系统 (BMS) 可以采用分布式控制系统的形式,其中集成了通用控制器、充电器、智能监视器和传感器,如这项工作中提出的那样,可以更精确地估计一组重要参数,例如荷电状态 (SOC)、健康状态 (SOH)、电流、电压和温度,以确保储能系统基于电池组的安全性和延长其使用寿命。该系统是所谓智能电池管理系统的典型实际示例。这项工作的贡献之一是实现了 BMS 的分布式设计,与完全集中式 BMS 结构相比,增加了系统安全性的好处。这项工作的另一个研究贡献是开发了一种基于 Petri 网的有条理的建模过程,该过程以可见、有组织和精确的方式确定了将确定 BMS 运行的一组条件。如果不进行这种建模,阈值及其条件仍然分散,不透明,并且难以整体处理。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验