Battery Predictive Analytics
Enabling a circular economy for batteries through predictive analytics
Battery failure and end-of-life (EOL) are major challenges facing the electric vehicle (EV) and renewable energy industries. Current battery management systems are not equipped to predict EOL with accuracy, leading to premature battery replacement and waste. Furthermore, retired batteries are often not recycled, posing environmental and economic concerns.
Our startup aims to tackle the problem of battery failure and EOL by developing a Physics informed data-driven battery management system that optimizes battery performance and predicts EOL with high accuracy. By utilizing machine learning algorithms, our system will enable preventive maintenance and extend battery lifespan, reducing waste and saving costs. In addition, we will work with industry partners to facilitate the repurposing of retired batteries for secondary applications, such as energy storage systems, further enhancing battery sustainability. Through our innovative solution, we seek to drive a more sustainable and circular economy for batteries.