IoT-enabled advanced monitoring system for tubular batteries: Enhancing efficiency and reliability

Abstract

Monitoring battery health is crucial for predicting the lifespan of batteries in electric vehicles. Real time voltage, current, and operating temperature are the key factors influencing longevity. An efficient data acquisition (DAQ) system becomes essential for accurately monitoring real-time battery operating parameters. For commercially viable three-wheeled electric vehicles, a cost-effective yet highly accurate DAQ is imperative. Current commercially available lead-acid three-wheeled electric vehicles lack a dedicated DAQ for monitoring battery health. In this investigation, we address this gap by developing a low-cost, multi-channel DAQ tailored for such electric vehicles, integrated with a cloud server for subsequent data analysis and Remaining Useful Life (RUL) prediction. The implemented prototype excels in measuring individual battery terminal voltage and battery pack voltage under operating conditions, employing the node voltage subtraction method. It also features real-time detection of high current discharges up to 30A using a Hall effect-based current sensor. A custom temperature sensor probe was designed to detect battery electrolyte temperatures up to 60 °C, with multiple probes operating in multiplexed mode to reduce circuit complexity. The system is proficient in storing recorded data locally and in the cloud. A mobile device platform has been developed and interfaced with the system for real-time monitoring of battery parameters. After testing multiple prototypes in running vehicles for over 1000h without failure, the system demonstrated a high accuracy level of 98.6 %. Multiple prototypes were designed to validate the measured accuracy.