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Improvement of vibration isolation performance of multi-mode control seat suspension system through road recognition using wavelet-LSTM approach

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Abstract

Extensive research has significantly improved the vibration isolation performance of off-road vehicle seat suspensions, effectively addressing issues such as driver fatigue, and low-back pain. However, variations caused by road roughness, vehicle speed, and load can lead to stability switches and sudden events in seat vibration excitation. Ignoring these factors in semi-active and active seat suspensions can cause insufficient robustness and excessive costs. To address this, we propose an intelligent damping switching method that optimizes seat suspension damping mode by considering the stability and suddenness of excitation. Utilizing a long short-term memory (LSTM) network, we accurately identify stability, while the multi-input and multi-output optimization (MIMO) method labels the network input through system identification of the seat dynamics model. Event trigger (ET) handles suddenness effectively. By combining these techniques, our approach achieves effective vibration isolation while maintaining the desired suspension deflection. Comparative analysis validates our novel seat suspension control system design approach.

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Abbreviations

Z s :

Suspension response displacement

Z f :

Suspension excitation displacement

m s :

Sprung mass

k s :

Suspension stiffness

c s :

Suspension damping

k 2 :

Fixed stiffness introduced by variable dampers.

c 2 :

Variable damping coefficient

f m :

Variable damping force

f lim 2 :

Buffer block limiting force

J :

Parameter identification objective

f i :

Simulation transmissibility at frequency point

m i :

Experimental transmissibility at frequency point

Ψ a,b :

Wavelet function

W Ψ(a,b):

Wavelet coefficient corresponding to the scale a and the position b

W i :

Input gate state weight

U i :

Input gate input weight

b i :

Input gate bias

W c :

Input state weight

U c :

Input weight

b c :

Input bias

W f :

Forget gate state weight

U f :

Forget gate input weight

b f :

Forget gate bias

W o :

Output gate state weight

U o :

Output gate input weight

b o :

Output gate bias

W fc :

Fully connected layer state weight

b fc :

Fully connected layer bias

y t :

True classification vector

ŷ t :

Estimated classification vector

J(θ):

Network optimization objective

a rms :

RMS acceleration response

τ :

Height limit threshold

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Acknowledgments

Authors thank the seat OEM supplier, GoldRare automobile parts Co., Ltd, China, for supplying the Daimler Truck new project seat in the experimental research.

Author information

Authors and Affiliations

  1. School of Transportation Science and Engineering, Beihang University, Beijing, 102206, China

    Xiaofeng Zhang, Xiandong Liu, Qiang Pan & Tian He

  2. GoldRare Automobile Parts Co., Ltd., Beijing, 102204, China

    Canhang Sun

Authors
  1. Xiaofeng Zhang
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Corresponding author

Correspondence to Xiandong Liu.

Additional information

Xiaofeng Zhang received his B.S. and M.S. degrees in automobile engineering from Jilin University in Changchun, China, and Beihang University in Beijing, China, in 2004 and 2010, respectively. Presently, he is dedicated to pursuing a Ph.D. degree in the Department of Automotive Engineering at Beihang University. His ongoing research interests encompass vibration control and vehicle system dynamics.

Xiandong Liu received the B.S. degree in automobile engineering and the M.S. degree in computational mechanics from Jilin University in 1986 and 1989, respectively, and the Ph.D. degree in aerospace propulsion theory and engineering from Beihang University, China, in 1999. He is currently a Professor at the School of Transportation Science and Engineering, Beihang University. His research interests include vehicle system dynamics, noise and vibration control, fault diagnosis, acoustic emission, and vibration signal processing.

Canhang Sun is an engineer in New Technology Center at Goldrare, Beijing, China. He received his M.S. degree in Aerospace Science and Technology from Beihang University in 2017. His research interests include dynamics, control and vibration.

Qiang Pan received his B.S. degree in Department of Jet Propulsion from Beijing University of Aeronautics & Astronautics in China in 2001 and completed his Ph.D. degree in Department of Mechanical Engineering at Inha University, South Korea, in 2009. Presently he is an Associate Professor in School of Transportation Science and Engineering at Beihang University. His research interests include material and structure analysis of aero-engines, aircraft airworthiness and fault diagnosis.

Tian He received his B.S. and M.S. degrees in Mechanical Engineering from Shijiazhuang Tiedao University, China, in 2001 and 2004, respectively, and his Ph.D. in Aerospace Propulsion Theory and Engineering from Beihang University, China, in 2008. He is an Associate Professor in School of Transportation Science and Engineering, Beihang University. His research interests include fault diagnosis, acoustic emission, vibration control and vibration signal processing.

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Zhang, X., Liu, X., Sun, C. et al. Improvement of vibration isolation performance of multi-mode control seat suspension system through road recognition using wavelet-LSTM approach. J Mech Sci Technol 38, 121–136 (2024). https://doi.org/10.1007/s12206-023-1210-2

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  • DOI: https://doi.org/10.1007/s12206-023-1210-2

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