Evaluation of finite element models of seat structures with integrated safety belts using full-scale experiments

Gavelin, Anders; Iraeus, Johan; Lindquist, Mats; Oldenburg, Mats

doi:10.1080/13588260903250994

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…In this study, AIS 3+ and Δv were used as dependent and independent variables, respectively, in the regression model. We generated different collision accelerations at different initial collision speeds in the sled test simulation model and FIGURE 19 Scatter plot and regression of P head3+ calculated the corresponding Δv using Equation (7). The obtained collision acceleration data were input to the rear-seat occupant simulation model, and a syn , F x , F z , M y , D max were determined.…”

Section: Regression Modelmentioning

confidence: 99%

“…Gavelin et al. [19] explored the influence of seat configurations on the pelvis and torso responses of occupants. However, they did not present an injury prediction model.…”

Section: Introductionmentioning

confidence: 99%

“…Alternatively, rear-seat occupant simulation models were developed based on actual vehicle data [9,17,18]; however, these models should be validated by considering actual crashes before the FE model can be generated for more cases with various parameters. Gavelin et al [19] explored the influence of seat configurations on the pelvis and torso responses of occupants. However, they did not present an injury prediction model.…”

Section: Introductionmentioning

confidence: 99%

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Injury prediction algorithm for rear‐seat occupants in advanced automatic crash notification systems

Lü

Liu

Shu

et al. 2021

IET Intelligent Trans Sys

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An advanced automatic crash notification (AACN) system can predict the injuries of a vehicle's occupants when the vehicle is involved in a collision accident. The rear‐seat occupants are at significant risk in collision accidents owing to an inferior protection system and the absence of mandatory seat belt laws. However, only a few studies have focused on the injury prediction for rear‐seat occupants, which can be used in AACN system. Therefore, an injury prediction algorithm is proposed for rear‐seat occupants. Initially, a rear‐seat occupant simulation model is established and verified and the relationship between the head, neck, and chest injury levels and velocity variation is examined. Then, a rear‐seat occupant injury prediction algorithm is developed and AACN terminal is constructed to analyse the effects of the algorithm. The comparison of the obtained results with actual accident data validated that the proposed algorithm can effectively evaluate the injury levels of rear‐seat occupants. The study findings can enhance the prediction accuracy of all occupants’ injury levels based on their positions inside the vehicle and improve the efficiency of rescue operations, particularly in the case of rear‐seat occupants.

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Section: Regression Modelmentioning

confidence: 99%

“…Gavelin et al. [19] explored the influence of seat configurations on the pelvis and torso responses of occupants. However, they did not present an injury prediction model.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Injury prediction algorithm for rear‐seat occupants in advanced automatic crash notification systems

Lü

Liu

Shu

et al. 2021

IET Intelligent Trans Sys

View full text Add to dashboard Cite

show abstract

“…The main problems generated by the introduction of safety belts in the manufacture of vehicles are presented in [31]. Marginal aspects of belt use were also studied, such as the wearing of seat belts by overweight people [32].…”

Section: Introductionmentioning

confidence: 99%

Three-Point Safety Polymeric Belt Webbing versus Four-Point Belt for a Race Car in Frontal Crashes

Itu,

Vlase

2023

Materials

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Polyester is currently the main material used for the manufacture of safety belts used in car transport for the protection of passengers and the driver. The seat belt is the main passive safety element used in vehicle engineering. In this work, the behavior of two safety belts, one with three-point fastening and the other with four-point fastening, which equip the seat of a racing car used in Formula Student for use in a frontal impact with a vertical wall. A model with finite elements is used to describe the entire car–driver shock-absorber assembly. The von Mises stresses calculated for both cases under consideration are below the tensile strength. The tensions arising in the belt and the accelerations required at various points of the driver’s body are determined by both the properties of the utilized polyester and the chosen construction variant. The obtained results justify the use of the three-point and four-point belt in the cases of both common and race cars.

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Frontal impact sled testing of a new designed vehicle seat track bracket

Deveci¹,

Durmuş

2021

International Journal of Crashworthiness

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Evaluation of finite element models of seat structures with integrated safety belts using full-scale experiments

Cited by 4 publications

References 7 publications

Injury prediction algorithm for rear‐seat occupants in advanced automatic crash notification systems

Injury prediction algorithm for rear‐seat occupants in advanced automatic crash notification systems

Three-Point Safety Polymeric Belt Webbing versus Four-Point Belt for a Race Car in Frontal Crashes

Frontal impact sled testing of a new designed vehicle seat track bracket

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