Predictive thermal management systems for lithium ion batteries using linear regression for enhanced efficiency and longevity

The demand for efficient thermal management systems of lithium-ion batteries is increasing with the proliferation of battery-powered devices and electric vehicles. A predictive thermal management system leveraging Machine Learning (ML) techniques, specifically the linear regression algorithm, to enhance battery safety and performance is proposed. The system integrates a DS18B20 temperature sensor with an Arduino microcontroller to monitor real-time temperature data of the battery. By employing linear regression, the system predicts future temperature trends based on historical data, allowing proactive cooling actions to be taken to maintain the battery within its optimal temperature range. This predictive capability not only enhances battery lifespan and reliability but also improves overall system efficiency. The experimental results demonstrate the effectiveness of the proposed system in accurately predicting battery temperatures and managing thermal conditions, enabling battery management solutions in various applications.