Vibration reduction performance of an innovative vehicle seat with a vibration absorber and variable damping cushion

Gao, Pu; Liu, Hui; Chen, Xiang; Yan, Pengfei

doi:10.1177/09544070211024042

Cited by 5 publications

(3 citation statements)

References 44 publications

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“…Motion sickness is a significant issue among passengers in vehicles, causing symptoms such as dizziness, nausea, vomiting, and reduced concentration, leading to unpleasantries [28,29]. Some studies suggest that the vibrations within vehicles, stemming from various sources such as the engine, steering, tires, and other components, can induce motion sickness and discomfort among passengers [30,31].…”

Section: Introductionmentioning

confidence: 99%

Development and Evaluation of Vibration Canceling System Utilizing Macro-Fiber Composites (MFCs) and Long Short-Term Memory (LSTM) Vibration Prediction AI Algorithms for Road Driving Vibrations

Kim,

Kim

2024

Materials

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This study developed an innovative active vibration canceling (AVC) system designed to mitigate non-periodic vibrations during road driving to enhance passenger comfort. The macro-fiber composite (MFC) used in the system is a smart material that is flexible, soft, lightweight, and applicable in many fields as a dual-purpose sensor and actuator. The target vibrations are road vibration data that were collected while driving on standard urban (Seoul) and highway roads at 40 km/s. To predict and cancel the target vibration accurately before passing it, we modeled the vibration prediction algorithm using a long short-term memory recurrent neural network (LSTM RNN). We regenerated vibrations on Seoul and highway roads at 40 km/s using MFCs and measured the displacements of the measured, predicted, and AVC vibrations of each road condition. To evaluate the vibration, we computed the root mean squared error (RMSE) and compared standard deviation (SD) values. The accuracies of LSTM RNN vibration prediction algorithms are 97.27% and 96.36% on Seoul roads and highway roads, respectively, at 40 km/s. Although the vibration ratio compared with the AVC results are different, there was no difference between the values of the AVC vibrations. According to a previous study and the principle of the AVC system, the target vibrations decrease by canceling the inverse vibration of the MFC actuator.

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Section: Introductionmentioning

confidence: 99%

Development and Evaluation of Vibration Canceling System Utilizing Macro-Fiber Composites (MFCs) and Long Short-Term Memory (LSTM) Vibration Prediction AI Algorithms for Road Driving Vibrations

Kim,

Kim

2024

Materials

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“…Improving tire and suspension parameters improves ride comfort while affecting tractor handling stability, braking performance, load-bearing capacity [12], etc. Comparatively speaking, because the seat system has the advantages of simple structure, convenient manufacture, and low cost, using seat suspension to improve tractor rides comfort is the most direct and effective method [13,14]. Tractors face complex operating conditions, and it is particularly important to improve seat suspension vibration attenuation [15].…”

Section: Introductionmentioning

confidence: 99%

Vibration Performance Analysis and Multi-Objective Optimization Design of a Tractor Scissor Seat Suspension System

et al. 2022

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The combination of characteristic parameters is the key and difficult point to improving the vibration attenuation of scissor seat suspension. This paper proposes a multi-objective optimization method based on entropy weight gray correlation to optimize the combination of characteristic parameters with better vibration attenuation. The differential equation of seat suspension motion is derived through mechanical analysis, and a simplified driver seat suspension single degree of freedom model is constructed. The range of spring stiffness and damper damping is calculated theoretically. Through main effect analysis and analysis of contribution, the main influencing factors of seat suspension vibration attenuation are studied, and the influence correlation of the main factors is analyzed. On this basis, the spring stiffness and damper damping are taken as control variables, and the upper plane acceleration, displacement, and transfer rate of the seat suspension are taken as optimization objectives. The Optimal Latin Hypercube Sampling (OLHS) was used to sample the Design of Experiments (DoE), fit the RBF surrogate model, and screen the optimal solution based on the MNSGA-II algorithm and entropy weight gray relation ranking method. The comparative analysis of the performance before and after optimization shows that the vibration reduction performance response indexes of the acceleration, displacement, and transmissibility of the optimized seats are increased by 66.41%, 2.31%, and 8.19%, respectively. The design and optimization method proposed in this study has a significant effect on the vibration reduction of seats, which provides a reference for the optimization of the vibration reduction performance of seat suspension.

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“…5 The ride comfort is strongly influenced by seat pressure distribution, sitting posture, amplitude, frequency of vibration, type of suspension, [6][7][8] properties of seat. 9 In various farming tasks, tractor drivers experience discomfort at lowfrequency vibration. 10 Although, the experimental investigation of static and dynamic seating comfort are the true feelings of the tested occupants.…”

Section: Introductionmentioning

confidence: 99%

Development and analysis of a novel biomechanical model for seated occupants

Guruguntla

Lal

2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Seated occupants may experience discomfort or meet with injuries if the vertical vibration frequency lies in the range of 4–20 Hz. To examine the effect of vibration on seated occupants, it is necessary to develop a biomechanical model that can precisely predict the biodynamic responses (seat to head transmissibility, driving point mechanical impedance, and apparent mass) of a real human. In the past, none of the studies segregated the human body mass into bones and muscles mass that have distinct mechanical properties. In this article, the work is carried out in four steps: first, development of a novel 8- dofs biomechanical model by considering both bone and muscle masses; second, development of all the feasible configurations of 8- dofs model followed by identification and optimization of model parameters with firefly algorithm (FA); third, calibration of all the feasible models as per the standards of biodynamics and selection of best four models; and fourth, comparison of biodynamic responses of best four models with experimental responses and past developed models. The goodness of fit of a seat to head transmissibility, driving point mechanical impedance, and apparent mass for the best model is obtained 0.986, 0.976, and 0.956, respectively.

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Vibration reduction performance of an innovative vehicle seat with a vibration absorber and variable damping cushion

Cited by 5 publications

References 44 publications

Development and Evaluation of Vibration Canceling System Utilizing Macro-Fiber Composites (MFCs) and Long Short-Term Memory (LSTM) Vibration Prediction AI Algorithms for Road Driving Vibrations

Development and Evaluation of Vibration Canceling System Utilizing Macro-Fiber Composites (MFCs) and Long Short-Term Memory (LSTM) Vibration Prediction AI Algorithms for Road Driving Vibrations

Vibration Performance Analysis and Multi-Objective Optimization Design of a Tractor Scissor Seat Suspension System

Development and analysis of a novel biomechanical model for seated occupants

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