Using Simulation Software to Predict Automotive NVH
One of the most pressing challenges for today’s automotive manufacturers is to make lighter cars. A lighter car will maintain a lower level of gas consumption and thus is more eco-friendly. To achieve this goal, many companies switched from aluminum to composite materials and put smaller engines supported by superchargers in their cars. However, since composites do not insulate noise very well and the superchargers created too much noise and vibration, another problem was presented: NVH (Noise, Vibration, and Harshness). This is a business issue for auto manufacturers because noise and vibration are two aspects that highly affect potential buyers’ perception of the quality of the car. Additionally, not only did interior noise need to be optimized, but engine sound also needed to be adjusted to the tastes and expectations of various consumer types. This is where the need for virtual testing of NVH comes into play.
Moreover, it is important to test the NVH quality of the assembled product. For example, when you make noise improvements on powertrain, it may affect another noise source. It is crucial to fully understand the characteristics of the noise propagation inside the fully assembled car. However, while even one prototype is expensive for car manufacturers, it is not affordable at all to physically test the cars for different scenarios and make the needed adjustments after each experiment. It is neither cost nor time friendly.
In order to reduce production costs and time spent on testing, the world’s leading automotive companies have started using simulation software to virtually test and validate each design. Using CAE, companies can create fully assembled models of their products, detect where exactly the noise propagated from during different design changes and trace the noise from the source to the receiver. This results in reduced the time-to-market, increased their productivity and cost savings, all of which creates a huge competitive advantage.