NVH Testing – Noise, Vibration and Harshness  

Noise, vibration, and harshness (NVH) is the study and adjustment of noise and vibration characteristics which affect the driving comfort of vehicles, particularly cars or trucks. A car that rattles or a motorbike that vibrates are tiring and annoying to use, and on longer journeys, the comfort of good NVH is one of the strongest brand differentiators. NVH refinement is a necessity for luxury vehicles as any edge gained over competitors will pay back handsomely in brand equity and loyalty.

 

While noise and vibration can be readily measured and quantified, harshness is a subjective quality, therefore the human factor is critically important for the target setting process and performance evaluation. The NVH process is very much a mixture of subjective and objective evaluations with NVH Simulation playing an ever more important role. 

Vehicle NVH Workflow

NVH testing plays an important role throughout the vehicle lifecycle, from initial vehicle concept to final production and in-service operation.

 

  • Vehicle and system benchmarking
  • Target setting for vehicles, systems, and components
  • NVH problem identification and troubleshooting
  • Data input for NVH simulation models to be used throughout the design and development process
  • Vehicle certification and conformity of production

 

HBK offers a complete range of NVH measurement and analysis solutions, including high-quality, precision measurement hardware and powerful software.

Explore NVH Simulation and Testing by Application

Bring sound and vibration data to life. Experience the sound and vibration of virtual NVH prototypes, understand and communicate NVH information, and make decisions on NVH targets, content and designs faster and with more confidence than ever before possible. Design and engineer the “right” sound and vibration characteristics into the vehicle. Combine benchmark data, measured data, and CAE analysis results of multiple types into virtual NVH prototypes that can be driven and experienced in highly realistic scenarios. Understand NVH data both subjectively and objectively and make NVH decisions easily. 

Vibration energy from an engine travels into the structure, through the engine mounts, and through the car seat into the driver. But energy from the same source can take a similar path through the structure to become acoustic noise when it is amplified by the cabin. Both interior and exterior noise are critical and subject to regulation. There can be too much or – in the case of EV – too little noise. Noise and vibration characteristics of components, sub-assemblies and the entire vehicle need to be tested at an early stage of development to avoid costly design changes and a delayed go-to-market. Therefore, optimizing these factors is not only of utmost importance for the overall user experience of the vehicle. It also ensures the finished product will meet noise emission targets and certification requirements. HBK offers a comprehensive suite of best-in-class NVH test equipment and highly skilled engineering service.

Acoustic Analysis

Noise in a vehicle cabin directly impacts the driving comfort. HBK’s spherical beamforming solution is ideal for fast in-cabin noise source identification and leak detection.

Tyre Noise

Indoor tyre noise measurements are complemented by field tests to meet ISO noise standards and achieve product certification. Benefit from HBK’s proven vehicle pass-by noise measurement solutions and comprehensive support to ensure compliance.

Acoustic quality analysis and vibration production line testing is an integral part of manufacturing automotive components. Besides maximizing the production line yield and cost effectiveness, they ensure the quality and customer acceptance of the entire powertrain.

 

HBK solutions for End-of-Line (EoL) provide full functional and acoustical behavior analyses of each eDrive unit directly in the production. Automatic evaluation of path/fail criteria enable maximum quality and high productivity. In case of failure digital twin model can identify the root cause.