Statistical evaluation of mechanical load on technicians during electric vehicle battery replacement using Python simulation
Abstract
Electric vehicle (EV) battery replacement poses significant mechanical strain on technicians, increasing the risk of musculoskeletal disorders (MSDs). This study uses Python-based simulations and biomechanical modeling to evaluate the mechanical load distribution during the battery replacement process, focusing on joint stress and technician posture. The analysis covers different task phases, including battery removal, transport, and installation, with statistical methods used to assess forces and torques applied to critical joints. The results indicate that the removal and installation phases exert the highest mechanical loads on the lower back and shoulders. The study suggests ergonomic interventions such as workstation redesign, lifting tools, and improved posture techniques to reduce the risk of injury and enhance the safety and efficiency of EV maintenance tasks.
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