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This paper introduces a reliable method to calculate body mount loads from wheel-force-transducer (WFT) measurements on framed vehicles. The method would significantly reduce time and cost in vehicle development process. The prediction method includes two parts: Hybrid Load Analysis (HLA) that has been used by DaimlerChrysler Corporation and Body Mount Load Analysis (BMLA) that is introduced by this paper for the first time. The method is validated on a body-on-frame SUV and a pickup truck through one proving ground events. The example shown in this paper is for a SUV and one of the most severe events. In HLA, the loads at suspension-to-frame attachments are calculated from spindle loads measured by WFT. In BMLA, body mount loads were calculated using outputs of HLA with detailed finite-element-modeled frame and body. The loads are compared with measured body mount loads. The comparisons are conducted in range, standard deviation (S.D.), and fatigue pseudo-damage.

In this paper, a comprehensive evaluation index for impact harshness (IH) is proposed. A mid-sized uni-body SUV is selected for this study, with the acceleration responses at the various vehicle body locations as objective functions. A sensitivity study is conducted using an ADAMS full vehicle model with flexible body structure representation over an IH event to analyze the influence of various suspension tuning parameters, including suspension springs, shock damping, steer gear ratio, unsprung mass, track-width, and bushing stiffness.

Engine mount loads are mostly measured from load cells or calculated from measured engine accelerations. This paper introduces an innovative new method to calculate engine mount loads from measured spindle loads. The method starts from calculating suspension attachment loads to body or chassis frame, then calculating engine center of gravity accelerations, and finally calculating engine mount loads from engine inertia forces. This spindle-based engine mount load analysis method is validated by a vehicle with measurements by wheel force transducers and engine load cells. The correlation includes load time history, peak-to-peak load range, and pseudo-damage values. The correlations show good comparisons between measured and predicted in all the categories, especially for the high load components. It is recommended to implement this method in early vehicle design phases.