Artificial intelligence (AI) and machine learning have been applied in two recent battery projects to reduce costs and improve sustainability.
The Berlin-based company camLine and theion, an innovative sulphur crystal battery company, will collaborate on the implementation of new AI-driven solutions. The aim is to accelerate the development of advanced battery technologies worldwide, from laboratory scale to mass production.
In a recent implementation, camLine’s Battery Lifetime Predictor system reduced theion’s R&D testing times from 42 days to just 15 hours, while maintaining a claimed prediction accuracy of 99.8%. AI has also facilitated early anomaly detection in the production process.
Separately, a recent study by a research team from Tokyo University of Science, Sweden’s Chalmers University of Technology and Japan’s Nagoya Institute of Technology leveraged machine learning to streamline the search for promising compositions.
The aim was to improve the performance of sodium-ion batteries. Sodium-containing transition-metal layered oxides (NaMeO2) are powerful materials for the positive electrode of sodium-ion batteries, but the sheer number of possible combinations makes finding the optimal composition both complex and time-consuming, it said.
Even minor changes in the selection and proportion of transition metals can bring about marked changes in crystal morphology and affect battery performance.
The team, led by Prof. Shinichi Komaba, sought to automate the screening of elemental compositions in various NaMeO2 O3-type materials. They first assembled a database of 100 samples from O3-type sodium half-cells with 68 different compositions, gathered over the course of 11 years by Komaba’s group.
The database included the composition of NaMeO2 samples, with Me being a transition metal like Mn, Ti, Zn, Ni, Zn, Fe, and Sn, among others, as well as the upper and lower voltage limits of charge-discharge tests, initial discharge capacity, average discharge voltage, and capacity retention after 20 cycles, Komaba said
