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Electromagnetic compatibility (EMC) is becoming more important in power converters and motor drives as seen in hybrid electric vehicles (HEV) to achieve higher reliability of the vehicle and its components. Electromagnetic interference (EMI) of the electronic components for a vehicle are evaluated and validated at a component-level test bench; however, it is sometimes observed that the EMI level of the components can be changed in a vehicle-level test due to differences in the vehicle's configuration (cable routing, connecting location etc.). In this presentation, a vehicle-level EMC simulation methodology is introduced to estimate radiated emissions from a vehicle. The comparison between the simulation and measurement results is also presented and discussed.

To validate the integrity of a commercial vehicle's exhaust system's structural design is a challenging job. An integrated approach to use both simulation/modeling and hardware testing must be employed to reduce product development cost. In addition to the considerations of the geometry and configuration specs of 70-90 parts and joints as well as material's thermal and mechanical property data in model development, representative loading must be used. For base excitation type of loading, such as the one experienced by the vehicle's exhaust system, one must decide whether to conduct the time domain transient analysis or frequency domain random vibration analysis. Although both methods are well known, few discussions can be found in the literature regarding their effective use in the framework of product design and development. Based on our study, the random vibration method should be used first for identifying high stress locations in the system and for design optimization.

Engineers often use different types of modeling and simulation to test crew station prototypes. A variety of tools exist to perform these types of analyses each with their own advantages. However, using these tools can be time-consuming and quite difficult, especially when engineers try to utilize the output of one tool as the input to another. The Crew Station Design Tool (CSDT) attempts to simplify this process by integrating three different software tools: 1) Micro Saint Sharp - a task network modeling tool, 2) Open Inventor™ - a three-dimensional graphics environment, and 3) Jack® - an anthropometric (human figure) modeling tool. The CSDT allows engineers to visualize and optimize their choices of controls and displays, and the position of those elements in a workstation. It automatically (and objectively) determines the optimum arrangement of controls and displays based upon sound human engineering and ergonomic principles.

Transmission loss and insertion loss are the most frequently used acoustic performance criteria of automotive exhaust mufflers. Transmission loss of a muffler is usually determined and analyzed computationally and experimentally in the development stage of an exhaust system, while insertion loss is the final acoustic performance indicator of the system. In this paper, numerical and experimental approaches are employed to investigate the transmission loss characteristics of an exhaust system and its components separately. The contribution of each component to the overall acoustic attenuation of the system is analyzed and discussed. The insertion loss of the exhaust system is measured and compared with the transmission loss.

The component response synthesis approach utilizing frequency response function (FRF) has been used to analyze the dynamic interaction of two or more vehicle components coupled at discrete interface points. This method is somewhat suitable for computing higher frequency response because experimental component FRFs can be incorporated into the formulation directly. However its calculations are quite sensitive to measurement errors in the FRFs due to the several matrix inversion steps involved. In the past, researchers have essentially used a combined direct inverse and truncated singular valued decomposition (TSVD) technique to ensure a stable calculation, which is typically applied semi-empirically due to the lack of understanding of the influence of measurement error.