Search Results

Statistical Energy Analysis (SEA) is a tool for estimating the response of complex dynamic systems at high modal density. This tool is seeing ever wider application in a range of industries, including aerospace industry, marine industry, and building trades. The automotive industry is beginning to explore the application of SEA to high frequency vehicle acoustic design. The SEA model of vibrational power transmission has a direct analogy to thermal power transmission (diffusion). As thermal power flow is proportional to temperature difference, vibrational power flow is proportional to modal energy difference. In this paper the thermal analogy is exploited to visualize the SEA results. This is accomplished by color coding a finite element representation of the structure. In this paper, the thermal analogy is used to correlate test data with SEA model results. This is accomplished by constructing a test based modal power thermogram.

To reduce dependence on petroleum resources and pollution to the natural environment, electric vehicles as new energy vehicles have become the focus of various original equipment manufacturers and component companies. At the same time, the NVH performance of electric vehicles is the focus of attention of automobile companies, and higher requirements are placed on sound-proof packaging, which is an important part of reducing automobile noise. Compared with traditional internal combustion engine vehicles, the biggest difference between electric vehicles (EV) is their electric drive system. High-frequency noise is generated when the electric motor is used as a power device. When there is no engine noise, the problem of electric drive noise is more obvious. Generally, an sound package is used to block the transmission path of noise. Therefore, an sound package is selected to cover the electric motor to reduce the impact of noise on the interior of the vehicle.

In the early stages of a vehicle program, sound package design is significantly complicated by numerous competing requirements including cost, weight, acoustical targets and packaging space. The problem is further convoluted due to a limited definition of the vehicle at this time. In this article, a Statistical Energy Analysis (SEA) model of the vehicle is created based on a gross description of the vehicle architecture. A large material database of commonly used sound package configurations is then linked to the SEA model. Genetic Algorithms (GA) are finally applied to optimize the sound package design to satisfy cost, weight, acoustical targets and packaging requirements in the vehicle design.

Statistical Energy Analysis (SEA) is being actively pursued in the automotive industry as a tool for vehicle high frequency noise and vibration analysis. A D-class passenger car SEA model has been developed for this purpose. This paper describes the development of load cases for the SEA model to simulate road noise on rumble road. Chassis roll test with rough shells was performed to simulate rumble road noise. Sound radiation from tire patch and vibration transmission through spindles were measured to construct the SEA load cases. Correlation between SEA model predictions and measured data was examined. Test and SEA result comparisons have shown that simulation of airborne road noise requires only a trimmed body SEA model, while simulation of structure-borne road noise may require SEA modeling of chassis components.