Optimization Design of Body-in-White Stiffness Test Rig Based on the Global Adaptive Algorithm of the Hybrid Element Model

One of the challenging aspects of designing body-in-white stiffness test rigs is measuring test accuracy. This paper proposes a method of integrating the body-in-white stiffness test rig and the body-in-white into an overall model for the optimization design. It establishes an optimization mathematical model based on the overall structure of the stiffness test rig, taking into account the factors affecting the accuracy of the test results of the body-in-white stiffness test rig. The stiffness test rig’s testing accuracy can be significantly increased by designating the degrees of freedom at each connection position as discrete variables. The Hybrid and Adaptive Metamodeling Method (HAM) is used to optimize the mathematical model. This approach uses and integrates three distinct metamodels with various attributes. The body-in-white torsional stiffness test result error is only 1.1%, and the body-in-white bending stiffness test result error is only 3.4%, owing to the optimization result that was used to design and manufacture a set of body-in-white stiffness test rigs and use them for a body-in-white stiffness test verification.