State of Temperature Estimation in Smart Batteries using Artificial Intelligence

Abstract:
Lithium-ion batteries (LIBs) have been widely adopted in electric vehicles (EVs) because of their high energy and power density, high efficiency, and long cycle life. However, the safety, performance, and lifespan of LIBs are greatly affected by the temperature. High temperatures not only accelerate the battery aging rate but also bring some safety hazards to LIBs such as thermal runaway. Low temperatures, can slow down the reactions inside LIBs, which undermines the energy and power capability of LIBs. Moreover, charging LIBs at low temperatures will trigger lithium plating, causing significant and irreversible capacity loss. Accurate monitoring of battery temperature serves as the basis of effective battery management and thermal management. Therefore, this project develops accurate and robust algorithms for battery state-of-temperature based on artificial intelligence and big data, which would allow for battery performance and lifetime maximization.

Funding: Villum Fonden