Statistical evaluation of mechanical load on technicians during electric vehicle battery replacement using Python simulation

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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Publication Details

Journal
Molecular & cellular biomechanics
Published
2024-11-04
DOI
https://doi.org/10.62617/mcb.v21i1.492
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
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article

Statistical evaluation of mechanical load on technicians during electric vehicle battery replacement using Python simulation

Xulong Dai
Molecular & cellular biomechanics
Advanced Battery Technologies Research
article

Statistical evaluation of mechanical load on technicians during electric vehicle battery replacement using Python simulation

Xulong Dai
article en

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.

Molecular & cellular biomechanicsVol. 21(1)
Openalex Percentile: Top 79%
Advanced Battery Technologies Research
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