As the recent paradigm shifts from combustion to electric automobiles, research on lithium batteries is actively being conducted. For batteries are directly related to the driving distance of electric cars, research on a fast and correct prognostics of battery capacity and life is necessary. 

In the meantime, Hanyang University announced that on the 19th, a co-research team by Professor Oh Ki-yong of the School of Mechanical Engineering (adjuncting the Department of Automotive Engineering) developed a 'next-generation physics-informed artificial intelligence technology'. This research was conducted together with  Professor Lee Seung-chul of the Department of Mechanical Engineering (POSTECH) and a Ph. D. course researcher Kim Seung-wook.

Two methods are used in prognostics of the battery capacity; one is a physics-informed model that simplified the inner structure of a battery, and another is a data-informed model that utilizes the electric and mechanical response of a battery. The data-informed technology was not performing well in unlearned data expecting accuracy although it needs a vast amount of data for learning and this required a next-generation artificial intelligence technology to overcome such limitations.

The research team, to improve the accuracy of the prognostics in an environment where there are only a few learning data available, fused a differentiated impedance-based key parameter extraction technique and a physics-informed neural network and this enabled them secure the prognostics and robustness on battery capacity and end-of-life distribution.

Based on more than a hundred battery state-of-health estimations and experiments based on them, it showed an accuracy and robustness that is in a maximum of 20% more improved to test batteries that have the various capacity and end-of-life distribution. Through this, they prepared a base of an application of physics-informed artificial intelligence that is robust and trustworthy for various industries.

Professor Lee Seung-chul of POSTECH said, "The main research achievement of this research is that it overcame data-informed artificial intelligence through physics information and it overcame a difficulty in constructing big data by developing a key parameter extraction technique." Professor Oh Ki-yong said in a general review, "This research result is more meaningful as it will be dedicated to the supply of electric cars, it by being applied to a battery life prognostics of the next-generation electric car."

In the meantime, this research was performed under the support of a civil-military technology cooperation program and the National Research Foundation of Korea and the research result was recently listed to 「Applied Energy, IF=9.746」, a world-class energy journal.