| 要約: | This study presents an advanced simulation-based methodology for evaluating the dynamic vibrational behavior of the operator–vehicle assembly in autonomous electric agricultural tractors. Using the TE-0 electric tractor as the experimental platform, the research is structured into three integrated stages. In the first stage, a seated anthropometric virtual model of the human operator is developed based on experimental data and biomechanical validation. The second stage involves a detailed modal analysis of the TE-0 electric tractor using Altair Sim Solid, with the objective of determining the natural frequencies and vibration modes in the [0–80] Hz range, in compliance with ISO 2631-1. This analysis captures both the structural-induced frequencies—associated with the chassis, wheelbase, and metallic frame—and the operational-induced frequencies, influenced by the velocity and terrain profile. Subsequently, the modal analysis of the “Grammer Cabin Seat” is conducted to assess its dynamic response and identify critical vibration modes, highlighting how the seat behaves under vibrational stimuli from the tractor and terrain. The third stage extends the analysis to the virtual operator model seated on the tractor seat, investigating the biomechanical response of the human body and the operator–seat–vehicle interaction during simulated motion. Simulations were carried out using SolidWorks 2023 and Altair Sim Solid over a frequency range of [0–80] Hz, corresponding to operation on unprocessed soil covered with grass, at a constant forward speed of 7 km/h. The results reveal critical resonance modes and vibration transmission paths that may impact operator health, comfort, and system performance. The research contributes to the development of safer, more ergonomic, and sustainable autonomous agricultural transport systems. By simulating real-world operation scenarios and integrating a rigorously validated experimental protocol—including vibration data acquisition, biomechanical modeling, and multi-stage modal analysis—this study demonstrates the importance of advanced modeling in optimizing system-level performance, minimizing harmful vibrations, and supporting the transition toward resilient and eco-efficient electric tractor platforms in smart agricultural mobility.
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