Characterization of tire and suspension system nonlinearities in measured data is the first step in developing input-output quarter car models; however, system identification procedures, which require a priori knowledge of all nonlinearities within a system, often receive more attention in the research community. Furthermore, relatively few investigations have focused on nonlinear characterization and identification in the absence of input measurements. A new method for characterizing nonlinearities, in the absence of an input measurement, using transmissibility functions and ordinary coherence functions between response measurement degrees of freedom is discussed here. It is shown that the nonlinear nature of a vehicle system provides information about the nominal linear system when the input is unknown. Nonlinear frequency permutations, which create drops in the ordinary coherence function, serve to characterize the associated nonlinearities. In the absence of input measurements, coherence functions of the response transmissibility between the vehicle spindle and body allow the nonlinearities in the suspension system, but not the tires, to be characterized. Simulation results are discussed and the method is applied to experimental laboratory and operating data to validate the approach.

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