Automated disassembly of electric vehicle battery packs: A category-based review of methods, robotics, and intelligent control

As large volumes of electric vehicles approach end-of-life, efficient and scalable recycling of lithium-ion battery packs is becoming a critical challenge. Due to the high variability in battery pack designs and safety requirements, current battery recycling facilities in Europe largely rely on manual disassembly processes. At scale, these approaches would be labour-intensive and expose workers to significant safety risks, motivating the development of automated disassembly solutions. This review provides a category-based analysis of 49 papers on automated electric vehicle battery disassembly published between 2018 and 2026, organised around robotic frameworks and operations, perception and feature recognition, and control and decision-planning methods. Existing approaches are examined across different levels of autonomy, including teleoperation, human–robot collaboration (HRC), and fully autonomous systems, each offering distinct trade-offs in feasibility and scalability. Particular attention is given to learning-based methods, such as reinforcement learning, as enabling technologies for adaptive disassembly. However, a central challenge identified across the literature is the limited generalisation capability of current approaches when faced with high variability in battery designs and conditions. The reviewed methods are compared across the identified categories, with particular attention to technical capabilities, validation level, safety considerations, adaptability, and relevance for industrial deployment. The paper concludes by identifying key research gaps, such as fragmented research efforts and battery pack variability, before outlining future directions towards integrated, fully autonomous disassembly systems.