Machine Learning Aids in Preventing Car Battery Fires

New research led by a University of Arizona doctoral student is shedding light on a potential solution to predict and prevent temperature spikes in lithium-ion batteries commonly used to power electric vehicles. The paper titled "Advancing Battery Safety," led by College of Engineering doctoral student Basab Goswami, has been published in the prestigious Journal of Power Sources.

One of the major challenges with lithium-ion batteries is the occurrence of thermal runaway, which can be extremely dangerous and difficult to predict. Electric vehicle battery packs consist of numerous closely connected battery cells, with some vehicles having over 1,000 cells in each pack. If thermal runaway initiates in one cell, it can quickly spread to neighboring cells, leading to a chain reaction that could potentially result in the entire battery pack exploding, as highlighted by Goswami.

To address this critical issue, the researchers have put forward a novel approach involving the use of thermal sensors wrapped around the battery cells. These sensors collect historical temperature data, which is then fed into a machine learning algorithm. By analyzing this data, the algorithm can predict future temperature trends and identify potential areas where a thermal runaway event is likely to begin.

Goswami emphasized the importance of this predictive capability, stating, "If we know the location of the hotspot, we can implement preventive measures to halt the battery's progression before it reaches a critical stage." This proactive approach could significantly enhance the safety and reliability of lithium-ion batteries in electric vehicles, ultimately reducing the risk of catastrophic failures.

By leveraging advanced technologies such as machine learning and real-time monitoring, the research team aims to revolutionize battery safety standards in the automotive industry. The implementation of thermal sensors coupled with predictive algorithms could pave the way for early intervention strategies that mitigate the risks associated with thermal runaway, ensuring the continued growth and adoption of electric vehicles worldwide.