Vehicle Interior Noise Mechanism and Prediction

The studies for vehicle noise, vibration and harshness (NVH) are related to the modification and optimization of noise and vibration characteristics of vehicles, particularly cars or trucks. This chapter introduces vehicle interior noise generation mechanisms, including air-borne and structure-borne noises. An automobile is a complex vibration system with multiple excitation sources (engine, intake/exhaust system, transmission system, tire/road excitation, vehicle body, and wind noise) which deliver vibrational energy to multiple target points through different transfer paths. Several transfer path analysis methods are introduced to identify the transmission and contribution of each vibration/ noise source. Furthermore, the vibration/noise prediction methods based on the model and data are discussed. Under varying high-speed conditions, the vehicle interior noises are nonlinear and nonstationary. Based on machine learning and compressed sensing approaches, the so-called signal decomposition optimization-based back propagation neural network for ear-side noise reconstruction (DBENR) and the multi-variable based time-domain signal reconstruction (MTSR) are introduced for vehicle interior noise. The research results suggest that the two methods can effectively reconstruct the nonlinear and nonstationary vehicle interior noise signals and may provide high-precision reference signals for vehicle active noise control.