Digital Road Load Data Acquisition Methodology for Automotive Durability Analysis

Durability is an important indicator to measure the automobile quality and reliability. Automotive industry is striving to develop products having excellent performance to weight ratios and along with high safety standards. A successful product should have adequate robustness during normal customer operation and the ability to withstand high impact events without impairment of function or safety relevant damage. Road Load Data Acquisition (RLDA) along with efficient design and validation processes are, among others, critical factors for success in the automotive industry. Physical RLDA is expensive and time consuming, the prototype vehicles being costly and only available at a later stage in the vehicle development cycle. Component failures occurring on the proto test vehicles can prove to be a major setback, delaying the product launch by months. In order to overcome above challenge this paper presents an innovative methodology to carry out Digital RLDA. The methodology consists of development of high-fidelity digital vehicle and digital torture tracks. Digital vehicle is based on mixed rigid-flexible bodies approach to accurately capture the load transfer paths and includes F-tire based tire models to capture high frequency, low wavelength excitation. Digital tracks are developed using a hybrid 3D Pixel technique, which converts 3D CAD into digital data for creation of digital tracks. Developed Digital vehicle model is run on digital tracks to capture the loads, strains, accelerations, displacements etc. on vehicle components using virtual sensors. Digital RLDA methodology is validated with two case studies: 1) Wheel hub loads, 2) Engine mount loads. The results suggest data obtained by Digital RLDA is in good agreement with physical RLDA data and the proposed methodology can be deployed for automotive durability analysis.