Design and implementation of online battery monitoring and management system based on the internet of things

Author:

Chen Kena,Luo Lei,Lei Wei,Lv Pinlei,Zhang Liang

Abstract

Battery pack provides the backup power supply for DC system of power substations. In the event of an AC power outage or other accidents, it is an important guarantee for the reliable operation of power substation. To prevent possible failures, batteries usually require careful maintenance. Common methods are online monitoring, condition assessments, and health management. Among these, model-based techniques are widely used for battery monitoring and prognostics optimization. Data-driven methods are a good alternative solution when no mathematical models are available. As substations develop towards intelligent and unmanned modes, this paper proposes an online battery monitoring and management system based on the “cloud-network-edge-end” Internet of Things (IoT) architecture. Firstly, advanced battery monitoring system based on IoT architecture is reviewed in depth. It provides basis for later designing. Secondly, the battery online monitoring and management system is designed considering functional requirements and data link. Designing functions include ledger management, basic battery information display, real-time display of battery monitoring data, and the visualization of battery alarm information. It can implement online monitoring and intelligent maintenance management for battery operating status. Finally, the designed and developed system is applied in a 110 kV offshore substation, mainly providing battery maintenance suggestions and fault alarm prompts. Typical results of ledger information management, key parameter monitoring and alarm prompt are presented. This verifies the effectiveness and convenience of IoT-based system for the monitoring and management of batteries.

Publisher

Frontiers Media SA

Reference31 articles.

1. IoT-based battery monitoring system for electric vehicle;Abd Wahab;Int. J. Eng. and Technol. (IJET).,2018

2. Task partitioning and offloading in IoT cloud-edge collaborative computing framework: a survey;Chen;J. Cloud Comput.,2022

3. Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression;Deng;Energy,2020

4. Development of battery monitoring system in smart microgrid based on internet of things (IoT);Friansa;Procedia Eng.,2017

5. An online application of edge-cloud computing for lithium-ion battery with SOC estimation;Gotz,2023

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