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As the mobility being developed becomes more complex and numerous, it is becoming difficult and inefficient to apply current vehicle-test-based development. To overcome this, research on combining test and simulation models has been actively conducted to perform objective and subjective evaluations more accurately and efficiently in the advance stage without a vehicle over the years. At first, test models for various systems such as tire, suspension and body were made compatible with simulation models by using various methodologies such as blocked forces, FBS decoupling, and Virtual Point Transformation (VPT). The second step was to objectively estimate road noise by using FBS coupling with system models and to deeply analyze transfer paths and system’s sensitivity. The results were verified by comparing with what was measured and analyzed on vehicle.

With the electrification trend in the automotive industry, a virtual and efficient development for exhaust noise performance of ICE (Internal Combustion Engine) vehicle has been demanding. To cope with this challenges, the test-data-driven MBSE (model based system engineering) has been emphasized from its credible correlation with phenomena in vehicle state. In this study, the prediction process for the exhaust noise in vehicle state with the engine and exhaust system models in system state was presented. The system models were built guaranteeing modularity, inherence and description in its operational boundary conditions such as temperature and valve openness of exhaust system. The adequate parameters describing engine source and exhaust system’s acoustic transmissibility were defined and measured experimentally.