Skip to main navigation Skip to search Skip to main content

Numerical investigation on head and brain injuries caused by windshield impact on riders using electric self-balancing scooters

  • Shi Shang
  • , Yanting Zheng
  • , Ming Shen
  • , Xianfeng Yang
  • , Jun Xu*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

To investigate head-brain injuries caused by windshield impact on riders using electric self-balancing scooters (ESS). Numerical vehicle ESS crash scenarios are constructed by combining the finite element (FE) vehicle model and multibody scooter/rider models. Impact kinematic postures of the head-windshield contact under various impact conditions are captured. Then, the processes during head-windshield contact are reconstructed using validated FE head/laminated windshield models to assess the severity of brain injury caused by the head-windshield contact. Governing factors, such as vehicle speed, ESS speed, and the initial orientation of ESS rider, have nontrivial influences over the severity of a rider’s brain injuries. Results also show positive correlations between vehicle speed and head-windshield impact speeds (linear and angular). Meanwhile, the time of head-windshield contact happens earlier when the vehicle speed is faster. According to the intensive study, windshield-head contact speed (linear and angular), impact location on the windshield, and head collision area are found to be direct factors on ESS riders’ brain injuries during an impact. The von Mises stress and shear stress rise when relative contact speed of head-windshield increases. Brain injury indices vary widely when the head impacting the windshield from center to the edge or impacting with different areas.

Original languageEnglish
Article number5738090
JournalApplied Bionics and Biomechanics
Volume2018
DOIs
StatePublished - 2018

Fingerprint

Dive into the research topics of 'Numerical investigation on head and brain injuries caused by windshield impact on riders using electric self-balancing scooters'. Together they form a unique fingerprint.

Cite this