Abstract

Avoiding quality problems in passenger cars, such as squeak and rattle (S&R), has been a remarkable cost-saving consideration. The introduction of electric engines and autonomous driving is expected to further stress the need for quieter cabins. However, the complexity of S&R events has obstructed the practical treatment of these quality issues in the pre-design-freeze phases of product development. In this study, new quantified frequency-domain metrics are proposed to measure the risk of S&R generation in car subsystems. The proposed metrics measure the resonance risk and the mode shape similarity in the critical interfaces for S&R. The calculations are done based on the system response in the frequency domain. Compared with the time-domain evaluation methods, the knowledge about the system excitation levels is not essential and the calculations are more time-efficient. The proposed metrics can be used in design optimization processes to involve S&R attributes in the pre-design-freeze attribute trade-off activities besides other attributes. In this work, these metrics were used in a previously developed two-stage optimization approach to determine the connection configuration in two industrial cases. As compared with the baseline design, the risk for S&R was reduced by improving the system behavior in terms of resonance risk and mode shape similarity. This was achieved by applying adjustments to the location of the fasteners while maintaining the same general connection configuration concept.

References

1.
Trapp
,
M.
, and
Chen
,
F.
,
2012
,
Automotive Buzz, Squeak and Rattle: Mechanisms, Analysis, Evaluation and Prevention
, 1st ed.,
Butterworth-Heinemann/Elsevier
,
Oxford
.
2.
Kavarana
,
F.
, and
Rediers
,
B.
,
1999
, “Squeak and Rattle—State of the Art and Beyond,”
SAE Technical Papers 1999-01-1728
,
Traverse City, MI
.
3.
Bayani
,
M.
,
2020
, “
Squeak and Rattle Prediction for Robust Product Development in The Automotive Industry
,”
Licentiate thesis
,
Chalmers University of Technology
,
Gothenburg
. https://research.chalmers.se/en/publication/519934
4.
Fard
,
M.
,
Subic
,
A.
,
Lo
,
L.
, and
Fuss
,
F. K.
,
2014
, “
Characterisation of Vehicle Seat Rattle Noise From Seat Structural Dynamics
,”
Int. J. Veh. Noise Vib.
,
10
(
3
), pp.
226
240
.
5.
Harrison
,
M.
,
2004
,
Vehicle Refinement: Controlling Noise and Vibration in Road Vehicles
,
Elsevier Ltd. on behalf of SAE International
,
Warrendale, PA
.
6.
Maia
,
N. M. M.
, and
eSilva
,
J. M. M.
,
1997
,
Theoretical and Experimental Modal Analysis
, 1st ed.,
Research Studies Press
,
Taunton, Somerset, UK
, pp.
1
468
.
7.
Ewins
,
D. J.
,
2009
,
Modal Testing: Theory, Practice and Application
, 2nd ed.,
Wiley
,
New York
.
8.
Møller
,
N.
, and
Gade
,
S.
,
2003
, “Application of Operational Modal Analysis on Cars,”
SAE Technical Papers
,
Traverse City, MI
.
9.
Gracewski
,
S. M.
, and
Ramoutar
,
N. D.
,
2015
, “Vibration Measurement,”
Handbook of Measurement in Science and Engineering
, Vol.
1
,
M.
Kutz
, ed.,
Wiley
,
New York
, pp.
367
432
.
10.
Rades
,
M.
,
2010
,
Mechanical Vibrations II: Structural Dynamic Modeling
,
Editura PRINTECH
,
Bucharest
.
11.
Wang
,
X.
, ed.,
2010
,
Vehicle Noise and Vibration Refinement
,
Woodhead Publishing
,
Cambridge
.
12.
Allemang
,
R. J.
,
2003
, “
The Modal Assurance Criterion—Twenty Years of Use and Abuse
,”
Sound Vib.
,
37
(
8
), pp.
14
23
.
13.
Caamaño
,
E.
,
Lama
,
I.
,
Rousounelos
,
A.
, and
Viñas
,
J.
,
2011
, “
Improved Methodology for Squeak & Rattle Analysis With Abaqus and Correlation With Test Results
,”
SIMULIA Customer Conference
,
Barcelona, Spain
.
14.
Kreppold
,
E. M.
,
2007
, “A Modern Development Process to Bring Silence Into Interior Components,”
SAE Technical Papers 2007-01-1219
,
Detroit, MI
.
15.
Naganarayana
,
B. P.
,
Shankar
,
S.
,
Bhattachar
,
V. S.
,
Brines
,
R. S.
, and
Rao
,
S. R.
,
2003
, “N-Hance: Software for Identification of Critical BSR Locations in Automotive Assemblies Using Finite Element Models,”
SAE Technical Papers 2003-01-1522
,
Traverse City, MI
.
16.
Park
,
S.-H.
, and
Choi
,
J.-H.
,
2014
, “
Probabilistic Analysis of Rattle Occurrence in the Gap of Automotive Interior Parts
,”
J. Mech. Sci. Technol.
,
28
(
10
), pp.
3991
3996
.
17.
Daams
,
H.
,
2009
, “
Squeak and Rattle Prevention
,”
Symposium on International Automotive Technology (SIAT 2009)
,
Pune, India
,
Jan. 21
.
18.
de Silva
,
C. W.
,
2006
,
Vibration: Fundamentals and Practice
, 2nd ed.,
CRC Press
,
Boca Raton, FL
.
19.
Papagiannopoulos
,
G. A.
, and
Hatzigeorgiou
,
G.
,
2011
, “
On the Use of the Half-Power Bandwidth Method to Estimate Damping in Building Structures
,”
Soil Dyn. Earthquake Eng.
,
31
(
7
), pp.
1075
1079
.
20.
Olmos
,
B.
, and
Roesset
,
J. M.
,
2009
, “
Analytical Evaluation of the Accuracy of the Half-Power Bandwidth Method to Estimate Damping Ratios in a Structure
,”
Proceedings of the 4th International Conference on Structural Health Monitoring on Intelligent Infrastructure
,
Zurich, Switzerland
,
July 22
.
21.
Akay
,
A.
,
1978
, “
A Review of Impact Noise
,”
J. Acoust. Soc. Am.
,
64
(
4
), pp.
977
987
.
22.
Nasseri
,
A.
, and
Heszler
,
V.
,
2020
, “
Simulation of Stick-Slip Friction: Nonlinear Modelling and Experimental Validation
,”
Master’s thesis
,
Chalmers University of Technology
,
Gothenburg
, https://odr.chalmers.se/handle/20.500.12380/301612, Accessed December 23, 2020.
23.
Abrahamsson
,
T.
,
2012
,
Calibration and Validation of Structural Dynamics Models
, 1st ed.,
Chalmers University of Technology
,
Gothenburg
.
24.
Bayani
,
M.
,
Wickman
,
C.
,
Lindkvist
,
L.
, and
Söderberg
,
R.
,
In press
, “
Squeak and Rattle Prevention by Geometric Variation Management Using a Two-Stage Evolutionary Optimisation Approach
,”
ASME J. Comput. Inform. Sci. Eng.
25.
Cai
,
W.
,
Feb, 2008
, “
Fixture Optimization for Sheet Panel Assembly Considering Welding Gun Variations
,”
Proc. Inst. Mech. Eng. Part C: J. Mech. Eng. Sci.
,
222
(
2
), pp.
235
246
. SAGE Publications UK: London, England,
26.
Ölvander
,
J.
,
2000
,
A Survey of Multiobjective Optimization in Engineering Design
,
Linköping University
,
Linköping, Sweden
.
27.
Coello
,
C. A.
,
Lamont
,
G. B.
, and
Van Veldhuisen
,
D. A.
,
2007
,
Evolutionary Algorithms for Solving Multi-Objective Problems
, 2nd ed.,
Springer
,
New York
.
28.
Fonseca
,
C. M.
, and
Fleming
,
P. J.
,
1993
, “
Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion and Generalization
,”
Proceedings of the Fifth International Conference on Genetic Algorithms
,
San Mateo, CA
,
July
, pp.
416
423
.
29.
Pronzato
,
L.
, and
Müller
,
W.
,
2012
, “
Design of Computer Experiments: Space Filling and Beyond
,”
Stat. Comput.
,
22
(
3
), pp.
681
701
. Springer Verlag.
30.
Santner
,
T. J.
,
Williams
,
B. J.
, and
Notz
,
W. I.
,
2003
,
The Design and Analysis of Computer Experiments
, 1st ed.,
Springer
,
New York
.
31.
Fang
,
K.-T.
,
Liu
,
M.-Q.
,
Qin
,
H.
, and
Zhou
,
Y.-D.
,
2018
,
Theory and Application of Uniform Experimental Designs
, 1st ed., vol.
221
,
Springer
,
Singapore
.
32.
Rigoni
,
E.
, and
Turco
,
A.
,
2010
, “
Metamodels for Fast Multi-Objective Optimization: Trading off Global Exploration and Local Exploitation
,”
8th International Conference on Simulated Evolution and Learning, SEAL
,
Kanpur, India
,
Dec. 1
, Vol. 6457, LNCS, pp.
523
532
.
33.
Kucherenko
,
S.
,
Albrecht
,
D.
, and
Saltelli
,
A.
,
2015
, “
Exploring Multi-Dimensional Spaces: A Comparison of Latin Hypercube and Quasi Monte Carlo Sampling Techniques
,”
arXiv—University of Cornell
, http://arxiv.org/abs/1505.02350, Accessed January 8, 2021.
34.
2019
,
modeFRONTIER User Guide
,
ESTECO SpA
,
Trieste
,
1
2952
.
35.
Goldberg
,
D. E.
,
1989
,
Genetic Algorithms in Search, Optimization and Machine Learning
, 1st ed.,
Addison-Wesley Longman Publishing Co., Inc.
,
Boston
.
36.
Krishnaswamy
,
A. D.
, and
Sathappan
,
C.
,
2020
, “
Multidisciplinary Optimisation of Geometric Variation and Dynamic Behaviour for Squeak & Rattle
,”
Master’s thesis
,
Chalmers University of Technology
,
Gothenburg
, https://odr.chalmers.se/handle/20.500.12380/301763, Accessed April 6, 2021.
You do not currently have access to this content.