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<div class="section abstract"><div class="htmlview paragraph">The current trend toward hybrid and electric automotive powertrains increases the complexity of the vehicle development and integration work for the NVH engineers. For example, considering that the combustion noise is reduced or absent, secondary noise sources like drivetrain, auxiliary systems, road and wind noise become of relevance in terms of vehicle noise comfort. This trend combined with the shortening of vehicle development cycle, the increased number of vehicle variants and an increasingly competitive marketing landscape, force engineers to front-load their design choices to the early stages of the development process using advanced engineering analysis tools. In this context, innovative technologies such as Virtual Prototype Assembly (VPA) and NVH simulator provide the right support to the engineer’s needs when developing the vehicles of the future. The VPA technology enables target assembly noise predictions using the dynamic substructuring methodology starting from individual component models that are derived from simulation or test bench measurements. The NVH simulator, through a digital representation of the vehicle noise and vibration signature (NVH model), enables objective and subjective vehicle sound quality judgment while executing driving scenarios that have not been measured experimentally or fully simulated numerically. The NVH model can be based on data measured on an existing vehicle (top-down approach), on a VPA assembly of individual components characterized in laboratory or through simulation (bottom-up approach), or on a mix of both approaches. Moreover, engineers can, in an NVH simulator environment, interact with the virtual vehicle executing several driving scenarios in a realistic and interactive experience through a vehicle performance model connecting the running operation of the powertrain to the NVH model in a real-time co-simulation framework. In this paper the different technological building blocks will be described. Finally, industrial applications for road noise and electric powertrain noise will be presented and the elements of the methodological process will be validated.</div></div>

R oad induced noise is getting more and more significant in context of the electrification of the powertrain. The automotive industry is seeking for technologies to predict the contribution of vehicle components upfront, early in the development process. Classical Transfer Path Analysis (TPA) is a well-established technique that successfully identifies the transmission paths of noise and vibration from different excitation sources to the target responses. But it has a drawback: it requires the physical availability of the full vehicle. To achieve shorter development cycles, to avoid costly time-consuming design iterations and due to the limited availability of prototypes, engineers derived a method that addresses these requirements. Component-based TPA is a relatively new structure borne substructuring approach that allows to characterize the source excitation by a set of equivalent loads (blocked forces) independently from the receiver structure and to predict its behavior when coupled to different receivers. Frequency Based Substructuring, FBS, is applied in order to obtain the coupled assembly. However, there are a number of challenges affecting its applicability, such as the proper modelling of the coupling degrees of freedom and the difficulty to access the interface connection points. Geometrical reduction aims to solve those inconveniences. This paper aims to investigate these challenges of componentbased TPA by measurements on a tire-wheel suspension in static condition. The source component (the tire-wheel) is characterized by a set of blocked forces and transfer functions identified on a dedicated tire-wheel test-rig. These calculated loads are combined with the FRFs of the fully assembled system. The FRFs are calculated by using experimental substructuring methods. The sensitivity of applying FBS together with geometrical reduction in the frame of component-based TPA will be analyzed.

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