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The authors are responsible for the development of a structural 3D shell based bead-to-bead model with sidewalls and belt that separately models all functional layers of a modern tire [4]. In this model, the inflation pressure is modeled as a uniform stress acting normal to the shell’s inner face. The pressure can vary depending on the application: prescribed by the MBS-tool to align to a constant pressure specified for a vehicle or scenario, but it can also be modified dynamically to simulate e.g. a sudden pressure loss in a tire [1]. For many applications, this description of the inflation pressure as a time dependent quantity is sufficient. However, there are applications where it is needed to describe the inflation gas using a dynamic gas equation (Euler or Navier-Stokes). One such example is when the tire model is used in NVH (Noise-Vibration-Harshness) applications where the frequency range extends the 200 Hz range.

This paper presents the most recent advancement in the vehicle development process using the one-step or auto Transfer Path Analysis (TPA) in conjunction with the superelement, component mode synthesis, and automated multi-level substructuring techniques. The goal is to identify the possible ways of energy transfer from the various sources of excitation through numerous interfaces to given target locations. The full vehicle model, consists of superelements, has been validated with the detailed system model for all loadcases. The forces/loads can be from rotating components, powertrain, transfer case, chain drives, pumps, prop-shaft, differential, tire-wheel unbalance, road input, etc., and the receiver can be at driver/passenger ears, steering column/wheel, seats, etc. The traditional TPA involves two solver runs, and can be fairly complex to setup in order to ensure that the results from the two runs are consistent with subcases properly labeled as input to the TPA utility.

There are various optimization tools available on the market and they are successfully used for improving vehicle component designs in terms of performance and light weight [6][7][9][10]. But when it comes to full vehicle optimization, optimization tools are only one aspect of the entire process. To build up a FEM Model for NVH analysis the assembly process and load case definition play an important role. Both steps are very complex and the chance to make mistakes is very high. After initial analysis the results has to be interpreted to understand the NVH behavior and detect optimization potential. Diagnostic tools could be used to determine modal or panel participation factors or do transfer path analysis. Then components or subsystems could be optimized using numerical optimization tools. For this step often super elements are used to reduce calculation time without losing too much of accuracy.

The application of SEA (Statistical Energy Analysis) to the sound package design for a convertible is presented. SEA modeling was used optimize the soft-top construction and the acoustic insulation in the top-stack area (where the soft-top is stored) which were shown to be important transmission paths for tire noise. Correlation between measurement data and predictions from the SEA model is presented and good agreement shown. It is concluded that SEA can be applied to determine the special sound package requirements for convertible vehicles.

Vehicle sound package serves two basic functions: general acoustic insulation and local problem treatment. The former is often done at the up-front phase of the vehicle development process, and the latter at the downstream phase when representative prototype hardware becomes available and specific noise problems are identified. This paper examines the goals and key tasks of practical SEA CAE applications in the two phases of the sound package development process. Topics on CAE model requirement, typical analysis applications, and ways to improve the effectiveness of SEA applications to compliment hardware testing are discussed.

Closed cell foam has been used for filling vehicle pillar cavities at select locations to block road noise transmitted through pillars. In the past, most pillar foam implementations in vehicle programs were driven by subjective improvements in interior sound. In this study road test results are used to correlate a detailed CAE (Computer-Aided Engineering) model based on the statistical energy analysis method. Noise reduction characteristics of pillar with a number of foam block fillings were then studied using the CAE model. The CAE models provided means to model and understand the mechanism of noise energy flow through pillar cavities. A number of insightful conclusions were obtained as result of the study.