Parametric Sensitivity Analysis of Suspension Design Using Response Surface Techniques

The sensitivity analysis for the design of an automotive push-rod suspension is discussed. Conventional iterative design cycles rely heavily on repeated CAD and Finite Element Method (FEM) analyses. Here, the initial design is based on an alternative and uncommon approach. A pre-CAD diagram of the entire vehicle (for FSAE competition) integrated with drivers is fully parameterized. A series of simulations in which the virtual driver inputs are repeated while the geometry of the suspension varies is executed. A database with isolated geometric effects on suspension loads and performance is obtained. By employing multivariate regression techniques, specifically Response Surface Methodology (RSM), the complex (often nonlinear) relationship between design inputs and structural outputs is mapped. The geometric inputs for this optimization include the coordinates that define the lengths and angles of the suspension triangles, the kingpin angle, the hub length, and aerodynamic downforce coefficients. The key performance indicators analyzed include corner exit speed loss, load and force distribution on the tires and main suspension joints, and the roll and pitch angles of the chassis. This methodology allows for the rapid identification of an optimal design configuration, avoiding trial and error and reducing development time and costs. The proposed framework demonstrates how RSM can enable the configuration of an optimal push-rod design with enhanced performance characteristics and improved manufacturing efficiency. Different case studies based on the mentioned input–output are analyzed to validate the approach in a practical manner.