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This paper investigates the sensitivity of stiffness of front and rear suspension systems on the structure-borne road noise inside a vehicle cabin. A flexible multi-body dynamics based approach is used to simulate the structural dynamics of suspension systems including rubber bushings, suspension arms, a subframe and a twist beam. This approach can accurately predict the force transfer to the trimmed body at each suspension mounting point up to a frequency range of 0 to 300 Hz, which is validated against a force measurement test using a suspension test rig. Predicted forces at each mounting point are converted to road noise inside the cabin by multiplying it with experimentally obtained noise transfer functions. All of the suspension components are modeled as flexible bodies using Craig-Bampton component mode synthesis method.

This paper describes an approach to simulate spindle coupled full vehicle durability tests for the purpose of completing virtual durability evaluations on components and full vehicles before a prototype is available. The reproduction of measured spindle loads was achieved on a virtual model of a passenger car coupled to a 4 Degree of Freedom (DOF) and 6 DOF spindle coupled test system. The tools and process improvements developed here will aid both test and analysis engineers in working closer together in solving their durability problems. By using Remote Parameter Control® (RPC®) technology in the virtual world, analysts have a new method to understand the virtual model by reproducing field-measured or generic road predicted signals for a variety of road surfaces. With newly created test rig models and a user friendly RPC™ iteration process, virtual testing that accurately replicates laboratory tests are now a reality.

This paper describes an automated path following system using vision sensor. Lateral control law for path following is especially underlined which is developed by using the backstepping control design methodology. To establish the proposed control system, the lateral offset to the reference path, the heading angle of vehicle relative to tangent line to the path, and path curvature are required. Those inputs to the controller have been calculated through Kalman filter which is frequently adopted for the purpose. The lane mark detection has been achieved in an ECU (Electric Control Unit) platform with vision sensor. The yaw rate and side-slip angle also needed in the controller are estimated by Kalman estimator. To show the performance of the proposed controller under different speeds, experiment has been conducted on a proving ground having straight and curve sections with the curvature of about 260m.