Due to the increasing number of hybrid and full electric vehicles and the trend of generally decreasing noise levels in vehicles, the engineering fields regarding driving comfort and NVH issues become more challenging: The masking effect of combustion engines vanish while customer expectations towards NVH and driving comfort are growing. Also the trend to high-speed concepts in electric vehicles combined with high transmission ratios implies that dominant powertrain noise will shift from low frequency phenomena as in combustion engines to higher frequencies that have a much higher annoyance potential [1]. In most cases the vibroacoustic behavior of a drivetrain or that of the whole vehicle is not known until the system is already in operation, since vibroacoustic behavior is very complex and difficult to simulate. So a common situation is that unpleasant NVH behavior is not noticed until the product is in a very late stage of development, where time is limited and design changes are very expensive. To handle this situation, it is important to find the source of the noise and identify components that take part in transmitting or amplifying it as fast as possible. Using the example of a battery electric vehicle, such a method for efficient cause-and-effect analysis for NVH issues is presented in this paper. At first a subjective rating under real world driving conditions is conducted. The obtrusive noise is then described using a comparative, onomatopoeic system as well as through its correlation with system parameters. This allows to link the perceived noise to a specific phenomenon in the measured data, and in many cases already to a specific component. This component and its bordering structure and relevant transfer paths are analyzed. These findings can then be used as input parameters for the definition of countermeasures.
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