Advanced MacPherson Strut Bending Model for Improved Accuracy Using Simple Inputs

Paper #:
  • 2018-01-0137

  • 2018-04-03
Mechanism simulation of automotive suspension systems has been constantly evolving and improving, to add additional fidelity to results. This improves correlation to physical test data, and allows the tools to be used to study more advanced phenomenon. MacPherson strut suspensions have been popular for decades due to their decreased parts count resulting in lower system costs. The strut in this kind of suspension performs multiple tasks, in addition to supporting the springing and damping loads, it also functions as a kinematic support as part of the overall mechanism. In simplified MacPherson strut simulations, the rod of the MacPherson strut is treated as a rigid body. However, when one compares system level physical test data with simulation data using this rigid body approach, it is apparent that the bending of the strut road influences the system level kinematics and compliances of the suspension. The phenomenon is very non-linear, as the rod stiffness increases as the strut moves into jounce, which shortens the length of rod that extends outside the strut tube. Over the years, various approaches have been used to model the bending of the strut rod. Most of these still treat the rod as a rigid body with some compliance to approximate the rod bending, or two rigid bodies connected with a compliant element. There are a couple of challenges with these approaches. The compliances in the model are either a simplified representation of the non-linear bending of the rod, and therefore only give an accurate result over a narrow operating range. Or, the compliances are extremely complex, and require significant component testing (such as a bench test of the strut rod bending at various suspension travels). What is desired is a modeling approach for the strut bending that captures the physics correctly throughout a wide range of suspension travel, yet only requires simple dimensional measurements to populate the bending model. That approach is documented in this paper.
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