A Frequency Domain Fitting Algorithm Method for Automotive Suspension Structure under Colored Noise

The suspension of a car has different structural forms but usually consists of springs, shock absorbers, guiding mechanisms, etc. As a vehicle moves, the terrain often induces a multifaceted non-white noise vibration within the vehicle. Research on this type of vibration often uses the operational m...

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Main Authors: Xiangyu Lu, Huaihai Chen, Xudong He
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:World Electric Vehicle Journal
Subjects:
Online Access:https://www.mdpi.com/2032-6653/15/9/410
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author Xiangyu Lu
Huaihai Chen
Xudong He
author_facet Xiangyu Lu
Huaihai Chen
Xudong He
author_sort Xiangyu Lu
collection DOAJ
description The suspension of a car has different structural forms but usually consists of springs, shock absorbers, guiding mechanisms, etc. As a vehicle moves, the terrain often induces a multifaceted non-white noise vibration within the vehicle. Research on this type of vibration often uses the operational modal analysis (OMA) method, due to its advantages of not requiring knowledge of excitation signals. The disadvantage is that it can only analyze systems under white noise excitation, otherwise it will bring errors. So, this paper proposes a frequency domain fitting algorithm (FDFA) based on colored noise excitation. Initially, an exposition on the foundational principles of the FDFA technique was provided, followed by a demonstration of the modal identification approach. Subsequently, a simulation scenario involving a cantilever beam, akin to a suspension system, was chosen for examination in three instances, revealing that the frequency discrepancies are under 2.94%, and for damping coefficients, they are less than 2.76%. In conclusion, the paper’s introduced FDFA technique, along with the frequency–spatial domain decomposition (FSDD) approach, were employed to determine the modal characteristics of aluminum cantilever beams subjected to four distinct colored noise stimulations. The findings indicate that when utilizing the FDFA technique, the error in modal frequency is kept below 2.5%, while the error for the damping ratio does not exceed 15%. Compared with FSDD, the accuracy was improved.
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spelling doaj-art-0bf9cb0c78d54577bc3d677d3d083c342025-08-20T01:56:13ZengMDPI AGWorld Electric Vehicle Journal2032-66532024-09-0115941010.3390/wevj15090410A Frequency Domain Fitting Algorithm Method for Automotive Suspension Structure under Colored NoiseXiangyu Lu0Huaihai Chen1Xudong He2Yangzhou Polytechnic Institute, Jiangsu Province Engineering Research Center of Intelligent Application for Advanced Plastic Forming, Yangzhou 225127, ChinaCollege of Aerospace Engineering NUAA, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaCollege of Aerospace Engineering NUAA, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaThe suspension of a car has different structural forms but usually consists of springs, shock absorbers, guiding mechanisms, etc. As a vehicle moves, the terrain often induces a multifaceted non-white noise vibration within the vehicle. Research on this type of vibration often uses the operational modal analysis (OMA) method, due to its advantages of not requiring knowledge of excitation signals. The disadvantage is that it can only analyze systems under white noise excitation, otherwise it will bring errors. So, this paper proposes a frequency domain fitting algorithm (FDFA) based on colored noise excitation. Initially, an exposition on the foundational principles of the FDFA technique was provided, followed by a demonstration of the modal identification approach. Subsequently, a simulation scenario involving a cantilever beam, akin to a suspension system, was chosen for examination in three instances, revealing that the frequency discrepancies are under 2.94%, and for damping coefficients, they are less than 2.76%. In conclusion, the paper’s introduced FDFA technique, along with the frequency–spatial domain decomposition (FSDD) approach, were employed to determine the modal characteristics of aluminum cantilever beams subjected to four distinct colored noise stimulations. The findings indicate that when utilizing the FDFA technique, the error in modal frequency is kept below 2.5%, while the error for the damping ratio does not exceed 15%. Compared with FSDD, the accuracy was improved.https://www.mdpi.com/2032-6653/15/9/410colored noiseoperational modal analysismodal parameter identificationenvironmental excitationfrequency domain fitting algorithmfrequency–spatial domain decomposition
spellingShingle Xiangyu Lu
Huaihai Chen
Xudong He
A Frequency Domain Fitting Algorithm Method for Automotive Suspension Structure under Colored Noise
World Electric Vehicle Journal
colored noise
operational modal analysis
modal parameter identification
environmental excitation
frequency domain fitting algorithm
frequency–spatial domain decomposition
title A Frequency Domain Fitting Algorithm Method for Automotive Suspension Structure under Colored Noise
title_full A Frequency Domain Fitting Algorithm Method for Automotive Suspension Structure under Colored Noise
title_fullStr A Frequency Domain Fitting Algorithm Method for Automotive Suspension Structure under Colored Noise
title_full_unstemmed A Frequency Domain Fitting Algorithm Method for Automotive Suspension Structure under Colored Noise
title_short A Frequency Domain Fitting Algorithm Method for Automotive Suspension Structure under Colored Noise
title_sort frequency domain fitting algorithm method for automotive suspension structure under colored noise
topic colored noise
operational modal analysis
modal parameter identification
environmental excitation
frequency domain fitting algorithm
frequency–spatial domain decomposition
url https://www.mdpi.com/2032-6653/15/9/410
work_keys_str_mv AT xiangyulu afrequencydomainfittingalgorithmmethodforautomotivesuspensionstructureundercolorednoise
AT huaihaichen afrequencydomainfittingalgorithmmethodforautomotivesuspensionstructureundercolorednoise
AT xudonghe afrequencydomainfittingalgorithmmethodforautomotivesuspensionstructureundercolorednoise
AT xiangyulu frequencydomainfittingalgorithmmethodforautomotivesuspensionstructureundercolorednoise
AT huaihaichen frequencydomainfittingalgorithmmethodforautomotivesuspensionstructureundercolorednoise
AT xudonghe frequencydomainfittingalgorithmmethodforautomotivesuspensionstructureundercolorednoise