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A flexible rebound-type acoustic metamaterial with high sound transmission loss (STL) at low frequency is proposed, which is composed of a flexible, light-weight membrane material and a sheet material - Ethylene Vinyl Acetate Copolymer (EVA) with uneven distributed circular holes. STL was analyzed by using both computer aided engineering (CAE) calculations and experimental verifications, which depict good results in the consistency between each other. An obvious sound insulation peak exists in the low frequency band, and the STL peak mechanism is the rebound-effect of the membrane surface, which is proved through finite element analysis (FEA) under single frequency excitation. Then the variation of the STL peak is studied by changing the structure parameters and material parameters of the metamaterial, providing a method to design the metamaterial with high sound insulation in a specified frequency range.

The control strategy design of vehicle active noise control (ANC) relies too much on experiment experience, which costs a lot to gather mass data and the experimental results lack representation. To solve these problems, a new control strategy optimization method based on the genetic algorithm is proposed. First, a vehicle cabin sound field simulation model is built by sound transfer function. Based on the filtered-X Least Mean Squares (FX-LMS) algorithm and the vehicle cabin sound field simulation model, a vehicle ANC simulation model is proposed and verified by a vehicle field test. Furthermore, the genetic algorithm is used as a strategy optimization tool to optimize an ANC control strategy parameter set based on the vehicle ANC simulation model. The optimized results provide a reference for the ANC control strategy design of the vehicle.

Acoustic performance of auto interiors is definitely important to control the NVH (noise, vibration, and harshness) performance inside a vehicle, and it is determined by the material parameters, such as density (ρ), thickness (d), open porosity (OP), airflow resistivity (σ), tortuosity (T), viscous characteristic length (VCL), thermal characteristic length (TCL), young's modulus, poisson's ratio, and damping coefficient. Firstly, by making different felt samples (of different surface density and thickness), the sound absorption performance and related parameters were obtained. Then the correlation between the parameters and the sound absorption coefficient (SAC) was summarized. Through this method, database of acoustic parameters and the corresponding SAC for porous materials can be established and sound package design and adjustment can be easily conducted based on the database.

The ability to utilize existing infrastructure i.e. tools, equipment and machinery to generate a unique acoustic product offering with minimal changes is important. This is because no generic acoustic solution ( material or composite ) exists for different vehicle configurations. Also, recent developments in predictive acoustic engineering and enhanced CAE capabilities as applied to development of optimal flat sample criteria for in-vehicle transmission loss and absorption performance allow for reverse engineering of the noise control systems. This reverse engineering coupled with a flexible manufacturing system will allow customization or tuning for any given program. Cost effective acoustic systems that can provide optimal insertion loss/absorption ratios utilizing a common manufacturing process will be the enabler to sustain competitive advantage.