Human ride comfort prediction of drive train using modeling method based on artificial neural networks

Lerspalungsanti, Sarawut; Albers, Albert; Ott, Sascha; Düser, Tobias

doi:10.1007/s12239-015-0017-2

Cited by 14 publications

(4 citation statements)

References 6 publications

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“…ANN have been used in various applications in the field of ergonomics (Brindisi & Concilio, 2008;Gholipour & Arjmand, 2016;Lerspalungsanti, Albers, Ott, & Düser, 2015). An ANN model has been applied to predict the automobile seat comfort (Quigley, Southall, Freer, Moody, & Porter, 2001).…”

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confidence: 99%

Predicting aircraft seat comfort using an artificial neural network

Zhao

Miller³

et al. 2018

Hum Ftrs & Erg Mfg Svc

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Aircraft seat pitch is one of the most important factors affecting passengers ability to sit comfortably for a longer time on the plane. The purpose of this study was to illustrate the association between different seat pitches and overall comfort index, and seat‐interface pressure variables as well as try to predict aircraft seat comfort. Through an experimental study, 11 subjects (age, 26.3 ± 1.6; height, 169.8 ± 8.5; body mass, 65.1 ± 15.6) rated five different seat pitch settings (55 examples, 11 participants and five scenarios). Descriptive statistics, together with one‐way analysis of variance were used to determine which of the metrics could be used to distinguish the overall comfort index. The results show that overall comfort index was statistically significant (p < 0.05) between different seat pitches, but there was no statistically significant difference (p > 0.05) in interface pressure variables. In addition, a multilayer feed forward neural network with one hidden layer was proposed with the help of Matlab Neural Network Toolbox. The model explained 99% of the variance in overall comfort index with the root mean square error (RMSE) of 0.12551. The remainder of the total data was used for validation purposes; the correlation is r = 0.775, p < 0.01, and the RMSE is 1.21031. That suggests this model has a significant relationship between the actual and predicted overall comfort index.

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confidence: 99%

Predicting aircraft seat comfort using an artificial neural network

Zhao

Miller³

et al. 2018

Hum Ftrs & Erg Mfg Svc

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“…[29]. It has been used and modified in many investigations in the automotive industry [30,31]. In this study, it ranges from 2 (worst result possible) to 10 (best result possible).…”

Section: Rating Scalementioning

confidence: 99%

Objective Rating of the Launch Behavior of Conventional, Hybrid and Electric Vehicles

2021

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The calibration of conventional, hybrid and electric drivetrains is an important process during the development phase of any vehicle. Therefore, to optimize the comfort and dynamic behavior (known as driveability), many test drives are performed by experienced drivers during different driving maneuvers, e.g., launch, re-launch or gear shift. However, the process can be kept more consistent and independent of human-based deviations by using objective ratings. This study first introduces an objective rating system developed for the launch behavior of conventional vehicles with automatic transmission, dual-clutch transmission, and alternative drivetrains. Then, the launch behavior, namely comfort and dynamic quality, is compared between two conventional vehicles, a plug-in hybrid electric vehicle and a battery electric vehicle. Results show the benefits of pure electric drivetrains due to the lack of launch and shifting elements, as well as the usage of a highly dynamic electric motor. While the plug-in hybrid achieves a 10% higher overall rating compared to the baseline conventional vehicle, the pure electric vehicle even achieves a 21% higher overall rating. The results also highlight the optimization potential of battery electric vehicles regarding their comfort and dynamic characteristics. The transitions and the gradient of the acceleration build-up have a major influence on the launch quality.

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“…Relevant studies have shown [20,21] that the discomfort caused by the previous vibration will aggravate the discomfort within 60 seconds after the human body is subjected to a high-amplitude vibration. When the two vibration intervals exceed 120 s, the discomfort caused by the two vibrations basically does not affect each other, that is, the subjective discomfort caused by a large vibration will gradually disappear within 120 s.…”

Section: Driving Comfort Indicatormentioning

confidence: 99%

Research on Subgrade Differential Settlement Control Standard and Treatment Technology Based on Driving Comfort

Wang

Ding

Gao

et al. 2020

Advances in Materials Science and Engineering

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At present, the geogrid is commonly used to treat the differential settlement of the subgrade at the joint of the filling and excavation effectively. In order to further improve the utilization rate of geogrid in the treatment of subgrade, the driving comfort index was proposed innovatively to control the subgrade differential settlement. Based on the human-vehicle-road coupling system model, the influence of subgrade differential settlement area, subsidence value, and vehicle speed on the maximum vertical acceleration of the human body was analyzed. The correlation between the vertical acceleration of the human body under different vehicle speeds and the differential settlement value was obtained through multiple regression calculations, and the subgrade differential settlement control standard based on driving comfort was proposed. By establishing the finite element model of the cut to fill subgrade, the characteristics of differential settlement at the top surface of the subgrade under different geogrid laying positions, densities, and lengths were calculated and analyzed. In addition, the differential settlement layout scheme of the geogrid disposal subgrade based on driving comfort was proposed, and the effectiveness of the scheme was verified by experiments. The results show that the position and length of the grid are the main factors affecting the treatment effect of the vertical and horizontal cut to fill subgrade. The proposed layout scheme can effectively control the differential settlement of the subgrade and raise the utilization rate of the geogrid. The research results can provide theoretical value and reference for the laying of geogrid in mountainous roads.

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Human ride comfort prediction of drive train using modeling method based on artificial neural networks

Cited by 14 publications

References 6 publications

Predicting aircraft seat comfort using an artificial neural network

Predicting aircraft seat comfort using an artificial neural network

Objective Rating of the Launch Behavior of Conventional, Hybrid and Electric Vehicles

Research on Subgrade Differential Settlement Control Standard and Treatment Technology Based on Driving Comfort

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