I. Introduction
Electric vehicles (EVs) rely on lithium-ion batteries for power storage, making battery health a critical factor in the performance, range, and lifecycle of EVs [2]. As the adoption of EVs grows, understanding and accurately predicting battery degradation has become essential for both manufacturers and end-users [3], [4]. Battery degradation not only affects the capacity and efficiency of the vehicle but also impacts the cost of ownership and the sustainability of EV technology. Consequently, the development of reliable models to forecast battery lifespan and manage its health is a high priority in EV research [5]. The transition to electric vehicles (EVs) is rapidly advancing across the globe, driven by rising concerns over climate change, government regulations on emissions, and shifting consumer preferences toward cleaner, more sustainable transportation. In recent years, EV adoption rates have surged, with global EV sales exceeding expectations across major markets like the United States, Europe, and China. This growth has been fueled by both policy incentives, such as tax rebates, EV purchase subsidies, and stricter emission standards, and technological advancements that have increased EV affordability, efficiency, and range. As EVs continue to move from niche products to mainstream transportation options, their penetration into the global market is expected to accelerate even further.