Customer Focus in Ride Development

Badiru, Ibrahim A.; Cwycyshyn, W. Bradley

doi:10.4271/2013-01-1355

Cited by 11 publications

(5 citation statements)

References 5 publications

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“…Ride motion control is the ability of vehicle to constrain pitch/bounce motions, especially the resonant vibration of the sprung mass (1.0-1.5 Hz). Resonant vibration at these low frequencies can cause driver discomfort and in the extreme case can lead to sea sickness [1].…”

Section: Subjective Evaluation and Measurementsmentioning

confidence: 99%

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Objective Evaluation Method of Vehicle Ride Comfort Based on Small-Sample Statistics

Li¹,

Fu²

2021

SAE Int. J. Veh. Dyn., Stab., and NVH

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Although ride comfort has been researched for many years, there is still no de nite objective evaluation method which can match the subjective assessment feeling well. The mainly presented approaches are mostly based on ISO 2631, but the consistency and correlation between subjective evaluation and objective evaluation are inadequate in these studies. Taking the motion control as the study content, which is primary ride comfort. Different type components of vehicle have been combined in a tuning car to achieve various ride performance, such as springs, dampers, jounce bumpers and tires. Then corresponding subjective evaluation results and acceleration measurement data have been collected when driving the tuning car on a sine wave road. With correlation and clustering analysis, the most representative features of measurement data for subjective assessment were extracted. Based on the small-sample statics theory, a new objective evaluation method for ride motion control has been established using the features by the LASSO model. The cross validation and comparison results indicate that the new objective evaluation method has a good estimation for ride motion control and the method can be a complement for ISO 2631.

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Section: Subjective Evaluation and Measurementsmentioning

confidence: 99%

“…Ride comfort can be separated into ve components: impact feel, shake, isolation, motion control and smoothness [1]. Many researches of objective ride comfort evaluation method for one or more components have been studied.…”

Section: Introductionmentioning

confidence: 99%

Objective Evaluation Method of Vehicle Ride Comfort Based on Small-Sample Statistics

Li¹,

Fu²

2021

SAE Int. J. Veh. Dyn., Stab., and NVH

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“…The discomfort caused by vertical WBV has long been assessed using a self-report questionnaire or acceleration. In the self-report questionnaire, discomfort has been quantified by subjective ratings (often on a scale of 1–10) from test drivers during product development ( Griffin, 2007 ; Badiru and Cwycyshyn, 2013 ; Taluja et al, 2017 ). In addition, several researchers have used the equivalent comfort contour to quantify discomfort in terms of the magnitude, frequency, and direction of the vibration ( Griffin and Erdreich, 1991 ; Morioka and Griffin, 2006 ; Zhou and Griffin, 2014 ; Huang and Zhang, 2019 ; Lin et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

“…Subjective ratings are not as sensitive to small changes in vibration; for example, reductions in vibration magnitude of less than 10% are generally undetectable by subjective ratings ( Morioka and Griffin, 2000 ). Meanwhile, in the acceleration-based method, the international standards ISO 2631-1 and BS-6841 proposed a ride index to quantify discomfort by applying a frequency weighting and axis multiplication factors to accelerations measured at different locations on the body ( Griffin and Erdreich, 1991 ; Griffin, 2007 ; Badiru and Cwycyshyn, 2013 ; Taluja et al, 2017 ). Several studies have used the ride index to evaluate discomfort in different modes of transport, such as a car ( Cantisani and Loprencipe, 2010 ; Song et al, 2023 ), a train ( Zoccali et al, 2018 ), a helicopter ( Delcor et al, 2022 ), and a cruise flight ( Huang and Li, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Removal of movement artifacts and assessment of mental stress analyzing electroencephalogram of non-driving passengers under whole-body vibration

Song,

Kang

2024

Front. Neurosci.

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The discomfort caused by whole-body vibration (WBV) has long been assessed using subjective surveys or objective measurements of body acceleration. However, surveys have the disadvantage that some of participants often express their feelings in a capricious manner, and acceleration data cannot take into account individual preferences and experiences of their emotions. In this study, we investigated vibration-induced mental stress using the electroencephalogram (EEG) of 22 seated occupants excited by random vibrations. Between the acceleration and the EEG signal, which contains electrical noise due to the head shaking caused by random vibrations, we found that there was a strong correlation, which acts as an artifact in the EEG, and therefore we removed it using an adaptive filter. After removing the artifact, we analyzed the characteristics of the brainwaves using topographic maps and observed that the activities detected in the frontal electrodes showed significant differences between the static and vibration conditions. Further, frontal alpha asymmetry (FAA) and relative band power indices in the frontal electrodes were analyzed statistically to assess mental stress under WBV. As the vibration level increased, EEG analysis in the frontal electrodes showed a decrease in FAA and alpha power but an increase in gamma power. These results are in good agreement with the literature in the sense that FAA and alpha band power decreases with increasing stress, thus demonstrating that WBV causes mental stress and that the stress increases with the vibration level. EEG assessment of stress during WBV is expected to be used in the evaluation of ride comfort alongside existing self-report and acceleration methods.

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“…In the automotive industry, both subjective and objective measurements are commonly used to evaluate the ride comfort of a vehicle. In subjective measures, various kinds of experimental studies have been used to correlate with subjective ratings of occupants exposed to specific driving or seating conditions [6,7]. On the other hand, the quantitative analysis of whole-body vibrations is attracting attention in order to objectively investigate ride comfort because this evaluation can detect small variations in the passenger's dynamic response compared to subjective evaluations [8].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Quantification of Ride Comfort Based on gPC Framework for a Fully Coupled Human–Vehicle Model

2023

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We investigated the stochastic response of a person sitting in a driving vehicle to quantify the impact of an uncertain parameter important in controlling defect reduction in terms of ride comfort. Using CarSim software and MATLAB/Simulink, we developed a fully coupled model that simulates a driving vehicle combined with an analytical nonlinear human model. Ride comfort was evaluated as a ride index considering the frequency weights defined in BS 6841. Additionally, to investigate the uncertainty of the ride index, a framework for calculating the ride index was proposed using the generalized polynomial (gPC) method. Further, sensitivity analysis of the ride index was performed for each uncertainty parameter, such as stiffness and damping. The results obtained through the gPC method were in good agreement with those obtained via Monte Carlo simulation (MCS) and were excellent in terms of computation time without a loss of numerical accuracy. Through in-depth investigation, we found that the stochastic distribution of the ride index varies differently for each uncertain parameter in the human model. By comparing linear and nonlinear human models, we also found that the nonlinearity of the human model is an important concern in the stochastic estimation of ride comfort.

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Customer Focus in Ride Development

Cited by 11 publications

References 5 publications

Objective Evaluation Method of Vehicle Ride Comfort Based on Small-Sample Statistics

Objective Evaluation Method of Vehicle Ride Comfort Based on Small-Sample Statistics

Removal of movement artifacts and assessment of mental stress analyzing electroencephalogram of non-driving passengers under whole-body vibration

Uncertainty Quantification of Ride Comfort Based on gPC Framework for a Fully Coupled Human–Vehicle Model

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