Towards Qualification of Female Human Body Model for Virtual Testing: Setup for 50th percentile female human body model and parametric study of the boundary conditions

Abstract

Road traffic injuries pose a major global safety challenge for vehicle occupants and vulnerable road users, such as pedestrians and cyclists. To prevent injuries, crash testing plays a vital role in automotive safety assessment. While early biomechanical evaluations relied on post-mortem human surrogates (PMHS), standard physical crash testing today is primarily conducted using Anthropomorphic Test Devices (ATDs). However, ATDs possess structural limitations: their rigid responses cannot fully replicate complex human soft-tissue and skeletal injury mechanisms. Additionally, physical testing using ATDs is constrained by high financial costs and testing complexity. To address this limitation, virtual testing is being proposed as a complement to physical testing for vehicle safety assessment, for example the HBM4VT framework under Euro NCAP has established qualification protocols for the 50th percentile male HBM (50M) through the Crash Protection 550 (CP550) protocols. This thesis evaluates the biofidelity scoring of a 50th percentile female HBM (50F) across key hub impact scenarios: Kroell (frontal thoracic), Viano (thoracic, abdominal, and pelvic), Compigne (shoulder), and Agnew (angled thoracic) and performs a parametric study on uncertainties that can influence the biofidelity scores. Simulation results were compared against experimental post-mortem human subject (PMHS) reference corridors generated using the ARCGen, with objective metric scores calculated using the Ellipse and Dynamic arc-length warping (DALW) scoring method and, ISO 18571. Evaluated parameters included physical setup variables (seating angle, HBM posture, and arm orientation) and ARCGen algorithmic parameters (cut_simulation with boolean values and number of warping points (nWarpCtrlPts) ranging from 0 to 5. Results demonstrate that scores exhibit higher sensitivity to physical setup variations than corridor algorithm configurations.