Akademik Veri Yönetim Sistemi
Journal of Vibration Engineering and Technologies, cilt.13, sa.8, 2025 (SCI-Expanded)
Purpose: The objective of the present study is twofold: first, to compare the accelerations experienced by a rider, modeled with four degrees of freedom, while traversing a standard speed bump on an e-bike, with experimental measurements; and second, to determine the model that best represents the observed experimental response. Methods: To this end, wireless inertial measurement unit (IMU) sensors were placed on the rider’s head and the e-bike seat to enable real-time data acquisition. Experiments were conducted on a tiled test surface at three different speeds (5, 10, and 15 km/h). Acceleration data collected from seven healthy adult volunteers were integrated into three distinct 4 DoF biomechanical models sourced from the literature. Head vibration responses were computed through simulations using seat acceleration as input, and the results were compared with experimental measurements. Results: Model performance was quantitatively evaluated using root mean square error (RMSE) analysis, revealing that the Wan & Shimmel model consistently provided the closest approximation to the experimental data across all speeds. Statistical differences in RMS head acceleration were evaluated using three separate one-way ANOVA tests. The first test assessed within-model variations across riding speeds (5, 10, and 15 km/h), revealing statistically significant speed-dependent differences only for the Boileau & Rakheja model and the experimental data. The second test compared the models at each speed level, identifying significant differences at 5 km/h and 15 km/h, primarily between the experimental data and certain models. The third test considered all speeds combined and found significant differences between the experimental data and all biomechanical models, while no statistically significant differences were observed among the models themselves. Conclusions: The relatively better numerical performance of the Wan & Shimmel model is likely attributable to its more detailed representation of organ–spine coupling, which may serve as a physiological damping mechanism. This study contributes valuable insights into the vibration dynamics of e-bike riders, highlighting the importance of accurate biomechanical modeling for ergonomic design and rider safety optimization.