Choice of Efficiency and Economy: The Role of Machine Learning in Advancing Battery Technologies

With the growth in global energy demands and the prominent need for sustainable development, battery technology has attracted significant attention as a crucial means of energy storage. Applying machine learning in battery technology offers new avenues for enhancing battery performance, safety, and lifespan. Through a literature review, this study comprehensively analyses the current status of machine learning in battery capacity prediction, solid electrolyte research and new material screening. It also explores the related research achievements, existing problems and future development directions, emphasising the importance of high-quality data, appropriate model selection, strict validation and interdisciplinary collaboration in promoting the progress of battery technology.