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Research on Airborne Noise of Battery Electric Vehicles Based on Transfer Path Analysis South China University of Technology

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Zhang, Yue, author.
Contributor:
Mei, Dongting
Shangguan, Wen-Bin
Xie, Xinxing
Conference Name:
SAE WCX Digital Summit (2021-04-13 : Live Online, Pennsylvania, United States)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2021
Summary:
With the popularity of battery electric vehicles, the engine of the vehicle disappears, so the problem of road noise in cars is becoming more and more prominent. Road noise into the car can be divided into structure-borne noise and airborne noise, this paper only focuses on the airborne noise above 500Hz, completely ignoring the structure-borne noise. A transfer path analysis model with "Intermediate Response Points" is proposed to accurately represent the transfer path of each airborne noise through the setting of "Intermediate Points". In the Vehicle Semi-Anechoic Room With 44 NVH Chassis Dyno, it is possible to create a working condition with only four tires running, so only the tire noise is considered in this paper. The frequency response function is tested in the Semi-Anechoic Chamber and the operating data is tested in the Vehicle Semi-Anechoic Room With 44 NVH Chassis Dyno. The calculations are performed by the Conventional Transfer Path Analysis (CTPA) method and the Operational Transfer Path Analysis (OPA) method, respectively. The total responses were calculated for the three operating conditions of 60 kph, 90kph, and 120kph. Both the CTPA and OPA methods have errors within an acceptable range, but the CTPA method is more accurate. The CTPA method requires testing a large number of frequency response functions, which is time-consuming, while the OPA method is more efficient
Notes:
Vendor supplied data
Publisher Number:
2021-01-0323
Access Restriction:
Restricted for use by site license

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