A domestic research team has made a significant breakthrough in the field of electric vehicle (EV) battery diagnostics, developing a technology that promises to enhance the long-term stability and efficiency of these batteries. On Oct. 17, the Korea Advanced Institute of Science and Technology (KAIST) announced that Professors Kwon Kyung-ha and Lee Sang-kook from the Department of Electrical Engineering have successfully developed electrochemical impedance spectroscopy (EIS) technology. This new system can diagnose and monitor the state of batteries with high precision using only a small amount of current.
The KAIST research team, which includes Ph.D. candidate Lee Young-nam, has created an EIS system that can be integrated into battery management systems (BMS) for electric vehicles. This system is capable of precisely measuring battery impedance with low current disturbances of just 10mA, significantly reducing thermal effects and safety issues during measurement. This development is expected to maximize the long-term stability and efficiency of EV batteries, addressing a critical need in the growing electric vehicle market.
EIS technology is a powerful tool that evaluates battery efficiency and losses by measuring the magnitude and changes in battery impedance. It can also identify thermal characteristics, chemical and physical changes, lifespan predictions, and the causes of failures in batteries. However, existing EIS equipment is costly and complex, making installation, operation, and maintenance challenging. Additionally, the high current disturbances required by traditional EIS systems impose significant electrical stress on batteries, increasing the risk of failure or fire.
The new low-current EIS system developed by the KAIST team overcomes these challenges. By minimizing bulky and expensive components, the system is easy to integrate into vehicles and has been proven effective in identifying the electrochemical characteristics of batteries under various operating conditions, such as different temperatures and state of charge (SOC) levels.
“This system can be easily integrated into Battery Management Systems (BMS) for electric vehicles, demonstrating high measurement precision while significantly reducing costs and complexity compared to traditional high-current EIS methods,” said Prof. Kwon. “It can contribute not only to electric vehicles but also to the diagnosis and performance enhancement of Energy Storage Systems (ESS) batteries.”
The results of this study were published in the international academic journal IEEE Transactions on Industrial Electronics on Sept. 5, highlighting the scientific rigor and peer-reviewed validation of the research.
