Structure-borne road noise prediction using component-based TPA

Road induced noise is getting more and more significant in context of the electrification of the powertrain. Due to the current trends emerging in the automotive industry (increased vehicle variants, shorter development cycles, ...), technologies enabling full vehicle noise predictions from the individual source components are becoming very attractive. In this sense, Component-based TPA was derived, in order to predict the noise contribution of vehicle components early in the development process. In this method, source excitation is characterized by a set of equivalent loads, derived from test bench or in-situ measurements, that independently represent the source from any receiving structure. In this work, this methodology is validated on a tire-suspension system in static condition. The tire is characterized in a rig by a set of invariant input loads (i.e. blocked forces) identified at the spindle location. The blocked forces identified are used to derive the spindle contact forces, by means of frequency based substructuring (FBS). The estimated spindle forces are then combined with the receiving structure FRFs and used for road vibro-acoustic prediction. The proposed methodology allows to combine the existing components with other existing or simulated components without being physically assembled, allowing to streamline the vehicle development.