Altair and Summitech Develop New Methodology for Vehicle Chassis System Development

New process targets reductions in resources, timing, and costs for OEM’s and value chain.

TROY, Mich – Altair Engineering, Inc., a leading global provider of technology and services that empowers client innovation and decision-making, announced today that Altair ProductDesign has collaborated with Summitech Engineering, a subsidiary of Tempo Group, to develop an efficient method for creating correlated passenger car multi-body dynamics (MBD) models without requiring OEM information. The process employs a combination of computer simulation and physical testing performed at Altair’s Troy, Mich. world headquarters and Summitech’s, Detroit Technical Center in Canton, Mich.

Summitech partnered with Altair ProductDesign for its broad expertise in chassis development, including subjective vehicle evaluations, objective lab and proving ground measurement, target setting, MBD model creation and correlation, CAE driven design and vehicle development. The goal of this initial engagement was to establish a repeatable process, without requiring OEM and supplier data and resources, that allows a deeper understanding of benchmark vehicles and determination of baseline performances to employ simulation-driven design methods.

“We are delighted with the methodology this partnership has produced,” said Dr Hong Su, Engineering Director Summitech Engineering. “Using a combination of Summitech facilities, Altair MotionSolve software, and the experiences of both organizations, we have successfully created correlated vehicle dynamics models of two very different vehicles. These models will be central to the optimal design of future vehicle components.”

Tony Norton, Land Vehicles Practice Leader at Altair ProductDesign, stated “The model building process starts with key benchmark data and judicious population of half car models. After a comparison with kinematics and compliance test results, full vehicle models are assembled. The process has provided great correlation with the proving grounds data measured by our team.”