Low-Cost IoT Architecture for Remote Monitoring and SoH/SoC Estimation in Second-Life Batteries Using Sensor Networks

The widespread adoption of electric vehicles has led to an increasing number of lithium-ion (Li-ion) and lithium iron phosphate (LiFePO4) batteries reaching the end of their automotive service life while still retaining between 70% and 80% of their nominal capacity. Giving these batteries a second life in stationary storage extends their usefulness and supports circular-economy goals, but large-scale reuse is held back by the lack of affordable monitoring solutions.

We present a low-cost IoT-based sensor network architecture for remote monitoring and SoH/SoC estimation in second-life batteries. The proposed system employs ESP32-based acquisition nodes integrated with low-cost voltage, current, and temperature sensors, with an estimated hardware cost below USD 15 per node. Measurement data are transmitted through the MQTT protocol to a cloud-based platform for storage, visualization, and analysis. SoC estimation is performed using Coulomb Counting combined with Open Circuit Voltage (OCV) correction, while SoH assessment is based on capacity estimation derived from operational measurements. The architecture is designed to support the simultaneous monitoring of multiple battery cells.

Experimental validation will be conducted using Li-ion and LiFePO4 cells recovered from electric vehicles at different stages of degradation. Performance evaluation will consider estimation accuracy, communication latency, and long-term monitoring stability. Our study seeks to assess the technical viability of the proposed architecture as a cost-effective alternative for monitoring second-life battery systems, particularly in applications where commercial battery management solutions may be economically impractical.