Research on the design and evaluation method of vehicle seat comfort for driving experience

Li, Mingyue; Li, Biao; Chen, Guoying; Li, Hong; Ding, Baohua; Shi, Chongyue; Yu, Fei

doi:10.1016/j.ergon.2024.103567

Cited by 2 publications

(2 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It was found that the pressure distribution on the prototype seat pan was significantly closer to an ideal pressure distribution, and was also lighter and more comfortable than conventional foam cushioning materials [18]. Li and colleagues found a correlation between the distribution of seat interface pressure and the perceived comfort of vehicle occupants, and that by developing regression models based on pressure distribution data, the comfort rating experienced during driving can be effectively analyzed, and this approach can enhance the accuracy and effectiveness of research and evaluation of car seat comfort [19]. Yao explored the relationship between pressure maps and the comfort/discomfort of users in aircraft seats, while proposing a new six-point method on pressure maps collected at the bottom of the cushion [21].…”

Section: Introductionmentioning

confidence: 97%

“…Some researchers have assessed physiological parameters (such as mean and peak pressure) when designing other products for sitting and lying down and combined them with subjective comfort ratings to collectively understand the perceived comfort of the product [18][19][20][21][22][23][24]. Dangal and colleagues designed and developed a prototype aircraft seat pan using spring-foam technology, and utilized questionnaires and pressure chart recordings in a comparative evaluation of the test against a standard aircraft seat pan.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Determinants of Perceived Comfort: Multi-Dimensional Thinking in Smart Bedding Design

Bai,

Liu,

Dai

et al. 2024

Sensors

View full text Add to dashboard Cite

Sleep quality is an important issue of public concern. This study, combined with sensor application, aims to explore the determinants of perceived comfort when using smart bedding to provide empirical evidence for improving sleep quality. This study was conducted in a standard sleep laboratory in Quanzhou, China, from March to April of 2023. Perceived comfort was evaluated using the Subjective Lying Comfort Evaluation on a seven-point rating scale, and body pressure distribution was measured using a pressure sensor. Correlation analysis was employed to analyze the relationship between perceived comfort and body pressure, and multiple linear regression was used to identify the factors of perceived comfort. The results showed that body pressure was partially correlated with perceived comfort, and sleep posture significantly influenced perceived comfort. In addition, height, weight, and body mass index are common factors that influence comfort. The findings highlight the importance of optimizing the angular range of boards based on their comfort performance to adjust sleeping posture and equalize pressure distribution. Future research should consider aspects related to the special needs of different populations (such as height and weight), as well as whether users are elderly and whether they have particular diseases. The design optimization of the bed board division and mattress softness, based on traditional smart bedding, can improve comfort and its effectiveness in reducing health risks and enhancing health status.

show abstract

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Determinants of Perceived Comfort: Multi-Dimensional Thinking in Smart Bedding Design

Bai,

Liu,

Dai

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

Model-Free Adaptive Control of an Active Half-Vehicle-Seat System Coupled with a Nonlinear Energy Sink Inerter (NESI)

Zhang,

Ren,

Meng

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

In order to reduce vehicle vibration and improve vehicle ride comfort and handling stability, a nonlinear energy sink inerter (NESI) is designed by combing an inerter and nonlinear energy sink (NES) for use in the seat suspension and vehicle suspension for the half-vehicle-seat (HVS) system; furthermore, a model-free adaptive control (MFAC) method based on the genetic algorithm is proposed to enhance the dynamic performance of the passive HVS system. The dynamic model of the active HVS system coupled with NESI using the MFAC method is established; its dynamic responses under pavement random and shock excitations are acquired using the numerical method and the dynamic performance is evaluated by seven evaluation indicators. The efficacy of the MFAC method is demonstrated through comparative analysis with the original passive HVS system, the HVS system coupled with NESI, and the active HVS system coupled with NESI using the proportional integral derivative (PID) control method. In addition, the influence of the installed position of MFAC on the dynamic performance of the active HVS system coupled with NESI is examined. The results show that for the active HVS system coupled with NESI using the MFAC method, compared with the other three HVS systems, the root mean square (RMS) values of the vehicle body vertical acceleration, vehicle body pitch acceleration, seat vertical acceleration, and front and rear suspension dynamic travel under pavement random excitation are smaller, the corresponding peak amplitudes under pavement shock excitation reduce, and the vibration attenuation time shortens; the RMS values of the front and rear dynamic tire loading under pavement random excitation are slightly smaller, the corresponding peak amplitudes under pavement shock excitation increase, and the vibration attenuation time decreases, which reflects the best dynamic performance among the four HVS systems and shows the effectiveness of the MFAC method. Furthermore, the control effect of the MFAC method is the best when it acts both on the seat and vehicle suspensions.

show abstract

Research on the design and evaluation method of vehicle seat comfort for driving experience

Cited by 2 publications

References 47 publications

Determinants of Perceived Comfort: Multi-Dimensional Thinking in Smart Bedding Design

Determinants of Perceived Comfort: Multi-Dimensional Thinking in Smart Bedding Design

Model-Free Adaptive Control of an Active Half-Vehicle-Seat System Coupled with a Nonlinear Energy Sink Inerter (NESI)

Contact Info

Product

Resources

About