As the move to decrease physical prototyping increases the need to virtually prototype vehicles become more critical. Assessing NVH vehicle targets and making critical component level decisions is becoming a larger part of the NVH engineer’s job. To make decisions earlier in the process when prototypes are not available companies need to leverage more both their historical and simulation results. Today this is possible by utilizing a hybrid modelling approach in an NVH Simulator using measured on road, CAE, and test bench data.
By starting with measured on road data from a previous generation or comparable vehicle, engineers can build virtual prototypes by using a hybrid modeling approach incorporating CAE and/or test bench data to create the desired NVH characteristics. This enables the creation of a virtual drivable model to assess subjectively the vehicles acoustic targets virtually before a prototype vehicle is available. This approach can also be used with, but not limited to, (pre)prototype powertrain, exhaust, and intake systems.
To create drivable NVH models for target setting, operating source level and path sensitivities are required. While these measurements can typically be a limiting factor without a prototype vehicle the hybrid model approach allows for flexibility. This flexibility comes from the fact that any combination of on road data, CAE, or test bench data can be utilized to build the model. This flexibility allows for models to be built earlier than by using a traditional model that would require measured on road data of a prototype vehicle.
Once a model is assembled it is possible to assess "what if" scenarios to determine targets or to do A-To-B comparisons of different sub-systems or components. This can be completed by applying filters to already assembled contributions or substituting CAE or test bench data for new parts. This paper will share an example of how using an NVH simulator allows for a powertrain subsystem to be substituted into a different vehicle virtually and made it possible to drive and assess subjectively to identify NVH concerns at an early stage. This was done by creating a source/path/contribution model and including where needed simulation data from CAE.