IoT-enhanced battery management system for real-time SoC and SoH monitoring using STM32-based programmable electronic load

作     者：Gozuoglu, Abdulkadir 

作者机构：Tokat Gaziosmanpasa Univ Elect & Energy Dept Tokat Turkiye 

出 版 物：《INTERNET OF THINGS》 (Internet. Thing.)

年 卷 期：2025年第30卷

核心收录：

主　　题：Electronic dummy load Power supply test Lithium-ion Lithium-polymer Batteries state of charge SoH MOSFET Linear/ohmic mode STM32 microcontroller Wi-Fi ESP-01 NodeMCU ESP32 Low-cost equipment 

摘      要：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.