Global Engineering Solutions Review

This study explores the application of AI in the electric mobility sector (EVs) to improve circular economy (CE) related strategies and identify challenges related to recycling and the second-life use of electric vehicle batteries (EVB). This study used the systematic literature review approach, analyzing the existing literature and case studies to understand contemporary innovations using AI and CE in the EVB segment. The study findings highlight that AI technologies improve the management of the EVBs and forecast battery health up to 95% through predictive analytics. It also enhances the recycling processes, reducing the carbon footprint up to 40% and increasing material recovery. AI also effectively evaluates the battery’s feasibility in second-life applications, thus maximizing resource utilization. The study also identifies the existing barriers, including the lack of data, the problem of compatibility, and the cost of implementation. It provides an opportunity for Synergizing AI and CE as the key to the strategy of the electric mobility ecosystem to become resource-efficient and sustainable. The study also suggested effective strategies to integrate AI technologies effectively by establishing regulatory infrastructures, allocating funds for AI research, establishing standardization, and partnering to tackle challenges that hinder the implementation of the EVB life cycle.