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Optimizing the Geometrical Dimensions of the Seat Suspension Equipped with a Negative Stiffness Structure Based on a Genetic Algorithm
- Jili Zha - Hubei Polytechnic University, School of Mechanical and Electrical Engineering, China Hubei Polytechnic University, Hubei Key Laboratory of Intelligent Conveying Technology and Device, China ,
- Vanliem Nguyen - Hubei Polytechnic University, School of Mechanical and Electrical Engineering, China Hubei Polytechnic University, Hubei Key Laboratory of Intelligent Conveying Technology and Device, China ,
- Dengke Ni - Hubei Polytechnic University, School of Mechanical and Electrical Engineering, China Hubei Polytechnic University, Hubei Key Laboratory of Intelligent Conveying Technology and Device, China ,
- Beibei Su - Hubei Polytechnic University, School of Mechanical and Electrical Engineering, China Hubei Polytechnic University, Hubei Key Laboratory of Intelligent Conveying Technology and Device, China
Journal Article
10-06-02-0010
ISSN: 2380-2162, e-ISSN: 2380-2170
Sector:
Citation:
Zha, J., Nguyen, V., Ni, D., and Su, B., "Optimizing the Geometrical Dimensions of the Seat Suspension Equipped with a Negative Stiffness Structure Based on a Genetic Algorithm," SAE Int. J. Veh. Dyn., Stab., and NVH 6(2):147-158, 2022, https://doi.org/10.4271/10-06-02-0010.
Language:
English
Abstract:
Based on the negative stiffness structure (NSS) designed on the seat suspension
and the effect of the geometrical parameters of the designed NSS on improving
the driver’s ride comfort, a new optimal method of the multi-objective genetic
algorithm (MOGA) is then researched and applied for optimizing the stiffness
ratio β of the seat suspension and the geometrical parameters
α
1 and α
2 of the NSS to further improve the driver’s ride comfort and health.
The reduction of the root-mean-square (RMS) displacement of the driver’s seat
(xRMSs
), the weighted RMS acceleration of the driver’s seat
(aRMSs
), and the seat effective amplitude transmissibility (SEAT) of the seat
suspension are chosen as the objective functions. The study results show that
with the optimal parameters of α
1 = 1.355, α
2 = 1.001, and β = 0.511, the seat suspension using
the optimized NSS has a good effect on isolating low-frequency vibration under
various excitation sources of the random, harmonic, and bumpy functions.
Particularly, the results of xRMSs
, aRMSs
, and SEAT with the optimized NSS are remarkably reduced by 13.35%,
22.51%, and 22.47%, respectively, compared to the designed NSS, and by 44.65%,
69.45%, and 69.44% in comparison without the NSS under a random excitation of
the floor of the cab or vehicle. Therefore, this research results not only
contribute to the existing body of knowledge on the seat suspensions equipped
with the NSS but also can provide an important reference for optimal design or
control of the seat suspension to further improve its isolating efficiency.