Artificial Intelligence-Based Lifetime Optimization in the Smart Batteries

Abstract: In this research plan, we aim to enhance the performance and extend the lifetime of smart batteries through intelligent control strategies. By effectively balancing the state of charge (SoC) and state of temperature (SoT), we can improve how batteries operate and make them last longer. We will develop innovative control methods for battery management systems, focusing on SoC and SoT balancing. Additionally, we will create a battery digital twin (BDT) using an advanced technology called impedance-based methodology. This will allow us to monitor and diagnose the batteries in real-time, ensuring performance enhancement. Through extensive testing and validation, including simulations and real-world experiments, we will confirm the effectiveness and reliability of our control strategies. The expected outcomes of this research include advancements in battery management systems, better battery performance, and longer-lasting batteries.

Funding: Villum Fonden