IoT-enhanced battery management system for real-time SoC and SoH monitoring using STM32-based programmable electronic load
•IoT-enabled real-time battery management system enhances SoC and SoH monitoring. Integrating IoT technology in the battery management system provides continuous, real-time monitoring of the State of Charge (SoC) and State of Health (SoH), offering more accurate and responsive data for decision-maki...
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| Vydané v: | Internet of things (Amsterdam. Online) Ročník 30; s. 101509 |
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| Hlavný autor: | |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier B.V
01.03.2025
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| Predmet: | |
| ISSN: | 2542-6605, 2542-6605 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | •IoT-enabled real-time battery management system enhances SoC and SoH monitoring. Integrating IoT technology in the battery management system provides continuous, real-time monitoring of the State of Charge (SoC) and State of Health (SoH), offering more accurate and responsive data for decision-making and system optimization.•Customizable constant current load ensures accurate discharge and capacity measurement. The system's electronic load is designed to be fully customizable, allowing precise control over current levels during discharge tests, which leads to more accurate measurements of battery capacity and health.•ESP32 integration provides real-time data logging and remote monitoring via WebSocket. Using the ESP32 microcontroller as the central control unit, the system allows for real-time data collection, logging, and monitoring through WebSocket, enabling remote control and real-time user interaction via web interfaces.•The hybrid MQTT and WebSocket communication ensures efficient data exchange and control. The combination of MQTT for efficient sensor data transmission and WebSocket for real-time control provides a robust and flexible communication infrastructure, balancing the need for low-latency interactions and efficient data exchange in the IoT network.•Cost-effective design supports scalability for various lithium-ion battery configurations. The system is built using low-cost components such as the ESP32, making it affordable yet scalable for different configurations of lithium-ion battery systems, supporting both small-scale and larger battery setups in practical applications.
Electronic dummy loads (EDLs) are essential for characterizing the discharge behavior of batteries and power supplies. Accurate battery performance monitoring is critical for applications ranging from renewable energy storage to electric vehicles. This study presents the design and implementation of an advanced, low-cost EDL integrated with Internet of Things (IoT) capabilities using Espressif Systems Platform (ESP) -based microcontrollers, specifically the NodeMCU or ESP32. The primary objective is to monitor lithium-ion battery packages' state of charge (SoC) and state of health (SoH). The designed system maintains a constant current during discharge, ensuring precise capacity measurement despite the decreasing voltage levels of batteries. This feature is essential for accurately determining the battery's capacity and health status. The integration with IoT networks significantly enhances the functionality of the device. Using the ESP-based microcontroller, real-time voltage, current, and power data is transmitted to an online platform, allowing for remote monitoring and data logging. This capability not only improves the accessibility and usability of the system but also facilitates long-term data analysis and performance tracking. The developed dummy load system is versatile, supporting both single-cell batteries and multiple-cell configurations. The adjustable current selection property allows it to draw a constant current from batteries, making it suitable for various applications. Simulation and real-world application results demonstrate the system's effectiveness, providing reliable SoC and SoH information. Our results underscore the potential of integrating IoT technologies with battery monitoring systems, offering enhanced monitoring, improved accuracy, and the convenience of remote access. This innovative, cost-effective approach can significantly contribute to developing more intelligent and reliable battery-powered systems.
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| ISSN: | 2542-6605 2542-6605 |
| DOI: | 10.1016/j.iot.2025.101509 |