Department of Automotive Engineering, School of Transportation Science and Engineering, Beihang University, Beijing 100191, PR China; Advanced Vehicle Research Center, Beihang University, Beijing 100191, PR China; Beijing Key Laboratory for High-efficient Power Transmission and System Control of New Energy Resource Vehicle, Beihang University, Beijing 100191, China.
Department of Automotive Engineering, School of Transportation Science and Engineering, Beihang University, Beijing 100191, PR China; Advanced Vehicle Research Center, Beihang University, Beijing 100191, PR China.
Accid Anal Prev. 2016 Apr;89:128-41. doi: 10.1016/j.aap.2016.01.013. Epub 2016 Feb 8.
The safety performance of an electric self-balancing scooter (ESS) has recently become a main concern in preventing its further wide application as a major candidate for green transportation. Scooter riders may suffer severe brain injuries in possible vehicle crash accidents not only from contact with a windshield or bonnet but also from secondary contact with the ground. In this paper, virtual vehicle-ESS crash scenarios combined with finite element (FE) car models and multi-body scooter/human models are set up. Post-impact kinematic gestures of scooter riders under various contact conditions, such as different vehicle impact speeds, ESS moving speeds, impact angles or positions, and different human sizes, are classified and analyzed. Furthermore, head-ground impact processes are reconstructed using validated FE head models, and important parameters of contusion and laceration (e.g., coup or contrecoup pressures and Von Mises stress and the maximum shear stress) are extracted and analyzed to assess the severity of regional contusion from head-ground contact. Results show that the brain injury risk increases with vehicle speeds and ESS moving speeds and may provide fundamental knowledge to popularize the use of a helmet and the vehicle-fitted safety systems, and lay a strong foundation for the reconstruction of ESS-involved accidents. There is scope to improve safety for the use of ESS in public roads according to the analysis and conclusions.
电动自平衡滑板车（ESS）的安全性能最近成为防止其进一步广泛应用作为绿色交通主要候选者的主要关注点。滑板车骑手在可能的车辆碰撞事故中不仅可能因与挡风玻璃或引擎盖接触，还可能因与地面的二次接触而遭受严重的脑损伤。在本文中，建立了结合有限元（FE）汽车模型和多体滑板车/人体模型的虚拟车辆-ESS 碰撞场景。对不同接触条件下（如不同的车辆碰撞速度、ESS 移动速度、碰撞角度或位置以及不同的人体大小）的滑板车骑手的碰撞后运动姿态进行了分类和分析。此外，使用经过验证的 FE 头模型重建了头部与地面的碰撞过程，并提取和分析了挫伤和撕裂的重要参数（例如，冲击或对冲压力以及冯·米塞斯应力和最大剪切应力），以评估头部与地面接触引起的区域挫伤的严重程度。结果表明，脑损伤风险随着车辆速度和 ESS 移动速度的增加而增加，这可能为普及使用头盔和车辆配备的安全系统提供基础知识，并为重建 ESS 涉及的事故奠定坚实基础。根据分析和结论，有改进在公共道路上使用 ESS 的安全的空间。
