Dynamic Ride Quality Investigation for Passenger Car

Park, Se Jin; Cheung, Wan‐Sup; Cho, Young-Gun; Yoon, Yoo‐Seok

doi:10.4271/980660

Cited by 19 publications

(8 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Vibroacoustic Comfort In Passenger Carsmentioning

confidence: 89%

“…Then, the seat dynamics may become significant in the ride quality since this element directly transmits the vibration to the passenger. 18 Moreover, the frequency responses of some body segments such as the head, the neck, the upper torso, the upper arms, the lower arms, and the central torso are dominant at 4.44 Hz, 19 which is in the fundamental human body frequency range of 4-6 Hz reported by Kitazaki and Griffin. 20 Consequently, in order to validate an electric Stewart Platform for ride comfort applications, the accelerations measured at the contact point between the seat and the driver in a hexapod and in a Toyota Prius will be correlated.…”

Section: Vibroacoustic Comfort In Passenger Carsmentioning

confidence: 89%

See 1 more Smart Citation

Validation of a ride comfort simulation strategy on an electric Stewart Platform for real road driving applications

Arconada¹,

García-Barruetabeña

Haas

2022

Journal of Low Frequency Noise, Vibration and Active Control

View full text Add to dashboard Cite

In this paper, the validation of the comfort simulation strategy on an electric Stewart Platform under road driving scenarios is explained. First, an introduction to the vibroacoustic comfort theory in passenger cars is presented. Second, the Stewart Platform used for the validation process is explained. Third, the methodology conducted for the validation of a hexapod for ride comfort applications is detailed. Finally, the Stewart Platform has been validated under real world road driving scenarios for the 6 degrees-of-freedom by means of the Vibration Dose Value. The final goal of the validation strategy of the electric Stewart Platform is to perform ride and comfort studies in a driving simulator for the 1–10 Hz frequency range.

show abstract

Section: Vibroacoustic Comfort In Passenger Carsmentioning

confidence: 89%

Section: Vibroacoustic Comfort In Passenger Carsmentioning

confidence: 89%

Validation of a ride comfort simulation strategy on an electric Stewart Platform for real road driving applications

Arconada¹,

García-Barruetabeña

Haas

2022

Journal of Low Frequency Noise, Vibration and Active Control

View full text Add to dashboard Cite

show abstract

“…However, these works utilize the data obtained from the driver and hence couldn't be personalized for the commuter. Works which directly target the comfort of a commuter also rely on data either from the car or the driver [51,61]. Join Driving [78] performs commuter comfort calculation using accelerometer data obtained from the driver's smartphone.…”

Section: Commuter Comfort In Cabsmentioning

confidence: 99%

“…A similar approach is followed by Machaj et al [43] utilizing smartphone sensors. Park et al [51] utilize vibrations observed from the commuter's body using sensors mounted on the seat to perceive comfort. On the other hand, Ruzic et al [61] utilize thermal sensors in the car to compute the comfort of the passenger.…”

Section: Commuter Comfort In Cabsmentioning

confidence: 99%

Impact of Driving Behavior on Commuter's Comfort during Cab Rides: Towards a New Perspective of Driver Rating

Verma,

Pargal,

Das

et al. 2021

Preprint

View full text Add to dashboard Cite

Commuter comfort in cab rides affects driver rating as well as the reputation of ride-hailing firms like Uber/Lyft. Existing research has revealed that commuter comfort not only varies at a personalized level but also is perceived differently on different trips for the same commuter. Furthermore, there are several factors, including driving behavior and driving environment, affecting the perception of comfort. Automatically extracting the perceived comfort level of a commuter due to the impact of the driving behavior is crucial for a timely feedback to the drivers, which can help them to meet the commuter's satisfaction. In light of this, we surveyed around 200 commuters who usually take such cab rides and obtained a set of features that impact comfort during cab rides. Following this, we develop a system Ridergo which collects smartphone sensor data from a commuter, extracts the spatial time series feature from the data, and then computes the level of commuter comfort on a five-point scale with respect to the driving. Ridergo uses a Hierarchical Temporal Memory model-based approach to observe anomalies in the feature distribution and then trains a Multi-task learning-based neural network model to obtain the comfort level of the commuter at a personalized level. The model also intelligently queries the commuter to add new data points to the available dataset and, in turn, improve itself over periodic training. Evaluation of Ridergo on 30 participants shows that the system could provide efficient comfort score with high accuracy when the driving impacts the perceived comfort.

show abstract

“…Indeed, studies in several industrial sectors aim at enlarging the life of the components, to increase the comfort of the user, and/or to enhance safety, by means of these vibrations damping. 1–4…”

Section: Introductionmentioning

confidence: 99%

Soft polymers dynamic characterisation using sandwich theory

Cortés,

Brun,

García-Barruetabeña

et al. 2023

Jnl of Sandwich Structures & Materials

View full text Add to dashboard Cite

This paper presents a method to identify the dynamic mechanical properties of soft not self-supporting viscoelastic materials at high frequencies using sandwich beams. The motivation of this alternative method comes from the fact that the method of Ross, Kerwin and Ungar (RKU), proposed by the standard ASTM E 756-05, adds structural rigidity to the sandwich as shear increases, for example at high frequencies, and consequently, the stiffness of the core material is underestimated. The proposed method is based on a homogenization technique for sandwich beams that takes into account quadratic shear stress in the formulation, instead of a constant shear as the RKU method. To prove its worth, the properties of a soft polymer are identified by both methods from experimental transmissibility measures carried out on a sandwich beam up to 2500 Hz. Then, finite element simulations are performed using the obtained material properties to compare the numerical transmissibility functions with the experimental one. A numerical comparison for the case of a sandwich beam with a thicker viscoelastic core is also completed, proving the improvement in the stiffness and damping properties identification in the high frequency range by considering quadratic shear in the formulation. As a result, the identified mechanical properties by the proposed method are more accurate at high frequencies and for thicker core beams, i.e., when the shear effect is significant.

show abstract

Dynamic Ride Quality Investigation for Passenger Car

Cited by 19 publications

References 2 publications

Validation of a ride comfort simulation strategy on an electric Stewart Platform for real road driving applications

Validation of a ride comfort simulation strategy on an electric Stewart Platform for real road driving applications

Impact of Driving Behavior on Commuter's Comfort during Cab Rides: Towards a New Perspective of Driver Rating

Soft polymers dynamic characterisation using sandwich theory

Contact Info

Product

Resources

About