ZHANG, Jintao ;JING, Zhecheng ;ZHOU, Haichao ;ZHANG, Yu ;WANG, Guolin . Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip. Articles in Press, [S.l.], v. 0, n.0, p. 179-191, april 2025. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/identification-method-of-tire-road-adhesion-coefficient-based-on-tire-physical-model-and-strain-signal-for-pure-longitudinal-slip/>. Date accessed: 04 jul. 2025. doi:http://dx.doi.org/10.5545/sv-jme.2024.1036.
Zhang, J., Jing, Z., Zhou, H., Zhang, Y., & Wang, G. (0). Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip. Articles in Press, 0(0), 179-191. doi:http://dx.doi.org/10.5545/sv-jme.2024.1036
@article{sv-jmesv-jme.2024.1036,
author = {Jintao Zhang and Zhecheng Jing and Haichao Zhou and Yu Zhang and Guolin Wang},
title = {Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip},
journal = {Articles in Press},
volume = {0},
number = {0},
year = {0},
keywords = {intelligent tire; tire-road adhesion coefficient estimation; slip point; slip rate; nonlinear regression; },
abstract = {To precisely calculate the tire-road adhesion coefficient of rolling tires at various slip rates, and enhance the safety and stability of vehicle operation, an approach for estimating the tire-road adhesion coefficient based on strain sensors and brush models was proposed. First, a finite element model of 205/55R16 radial tire was established, and the effectiveness of the model was verified through static ground contact and radial stiffness experiments. Then, the circumferential strain signal of the inner liner centerline of the tire during braking was extracted, utilizing the average peak angle spacing of the first-order and second-order circumferential strain curves, and the contact area length was estimated using the arc length formula. Subsequently, the braking simulation of rolling tires confirmed the asymmetry of pressure distribution within the ground contact area, estimating the position of slip points within the contact area based on arbitrary pressure distribution function and brush model, nonlinear regression was utilized to fit the estimation function of slip point under various slip rates. Finally, a functional relationship was developed between tire-road adhesion coefficient and slip rate, considering the friction characteristics between tire rubber and road surface, the friction model used is based on exponential decay. The results suggest that the methods described above enable rolling tires to estimate the tire-road adhesion coefficient under different slip rates, providing valuable insights for intelligent tire applications in vehicle dynamics control.},
issn = {0039-2480}, pages = {179-191}, doi = {10.5545/sv-jme.2024.1036},
url = {https://www.sv-jme.eu/article/identification-method-of-tire-road-adhesion-coefficient-based-on-tire-physical-model-and-strain-signal-for-pure-longitudinal-slip/}
}
Zhang, J.,Jing, Z.,Zhou, H.,Zhang, Y.,Wang, G. 0 April 0. Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip. Articles in Press. [Online] 0:0
%A Zhang, Jintao %A Jing, Zhecheng %A Zhou, Haichao %A Zhang, Yu %A Wang, Guolin %D 0 %T Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip %B 0 %9 intelligent tire; tire-road adhesion coefficient estimation; slip point; slip rate; nonlinear regression; %! Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip %K intelligent tire; tire-road adhesion coefficient estimation; slip point; slip rate; nonlinear regression; %X To precisely calculate the tire-road adhesion coefficient of rolling tires at various slip rates, and enhance the safety and stability of vehicle operation, an approach for estimating the tire-road adhesion coefficient based on strain sensors and brush models was proposed. First, a finite element model of 205/55R16 radial tire was established, and the effectiveness of the model was verified through static ground contact and radial stiffness experiments. Then, the circumferential strain signal of the inner liner centerline of the tire during braking was extracted, utilizing the average peak angle spacing of the first-order and second-order circumferential strain curves, and the contact area length was estimated using the arc length formula. Subsequently, the braking simulation of rolling tires confirmed the asymmetry of pressure distribution within the ground contact area, estimating the position of slip points within the contact area based on arbitrary pressure distribution function and brush model, nonlinear regression was utilized to fit the estimation function of slip point under various slip rates. Finally, a functional relationship was developed between tire-road adhesion coefficient and slip rate, considering the friction characteristics between tire rubber and road surface, the friction model used is based on exponential decay. The results suggest that the methods described above enable rolling tires to estimate the tire-road adhesion coefficient under different slip rates, providing valuable insights for intelligent tire applications in vehicle dynamics control. %U https://www.sv-jme.eu/article/identification-method-of-tire-road-adhesion-coefficient-based-on-tire-physical-model-and-strain-signal-for-pure-longitudinal-slip/ %0 Journal Article %R 10.5545/sv-jme.2024.1036 %& 179 %P 13 %J Articles in Press %V 0 %N 0 %@ 0039-2480 %8 2025-04-01 %7 2025-04-01
Zhang, Jintao, Zhecheng Jing, Haichao Zhou, Yu Zhang, & Guolin Wang. "Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip." Articles in Press [Online], 0.0 (0): 179-191. Web. 04 Jul. 2025
TY - JOUR AU - Zhang, Jintao AU - Jing, Zhecheng AU - Zhou, Haichao AU - Zhang, Yu AU - Wang, Guolin PY - 0 TI - Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip JF - Articles in Press DO - 10.5545/sv-jme.2024.1036 KW - intelligent tire; tire-road adhesion coefficient estimation; slip point; slip rate; nonlinear regression; N2 - To precisely calculate the tire-road adhesion coefficient of rolling tires at various slip rates, and enhance the safety and stability of vehicle operation, an approach for estimating the tire-road adhesion coefficient based on strain sensors and brush models was proposed. First, a finite element model of 205/55R16 radial tire was established, and the effectiveness of the model was verified through static ground contact and radial stiffness experiments. Then, the circumferential strain signal of the inner liner centerline of the tire during braking was extracted, utilizing the average peak angle spacing of the first-order and second-order circumferential strain curves, and the contact area length was estimated using the arc length formula. Subsequently, the braking simulation of rolling tires confirmed the asymmetry of pressure distribution within the ground contact area, estimating the position of slip points within the contact area based on arbitrary pressure distribution function and brush model, nonlinear regression was utilized to fit the estimation function of slip point under various slip rates. Finally, a functional relationship was developed between tire-road adhesion coefficient and slip rate, considering the friction characteristics between tire rubber and road surface, the friction model used is based on exponential decay. The results suggest that the methods described above enable rolling tires to estimate the tire-road adhesion coefficient under different slip rates, providing valuable insights for intelligent tire applications in vehicle dynamics control. UR - https://www.sv-jme.eu/article/identification-method-of-tire-road-adhesion-coefficient-based-on-tire-physical-model-and-strain-signal-for-pure-longitudinal-slip/
@article{{sv-jme}{sv-jme.2024.1036},
author = {Zhang, J., Jing, Z., Zhou, H., Zhang, Y., Wang, G.},
title = {Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip},
journal = {Articles in Press},
volume = {0},
number = {0},
year = {0},
doi = {10.5545/sv-jme.2024.1036},
url = {https://www.sv-jme.eu/article/identification-method-of-tire-road-adhesion-coefficient-based-on-tire-physical-model-and-strain-signal-for-pure-longitudinal-slip/}
}
TY - JOUR AU - Zhang, Jintao AU - Jing, Zhecheng AU - Zhou, Haichao AU - Zhang, Yu AU - Wang, Guolin PY - 2025/04/01 TI - Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip JF - Articles in Press; Vol 0, No 0 (0): Articles in Press DO - 10.5545/sv-jme.2024.1036 KW - intelligent tire, tire-road adhesion coefficient estimation, slip point, slip rate, nonlinear regression, N2 - To precisely calculate the tire-road adhesion coefficient of rolling tires at various slip rates, and enhance the safety and stability of vehicle operation, an approach for estimating the tire-road adhesion coefficient based on strain sensors and brush models was proposed. First, a finite element model of 205/55R16 radial tire was established, and the effectiveness of the model was verified through static ground contact and radial stiffness experiments. Then, the circumferential strain signal of the inner liner centerline of the tire during braking was extracted, utilizing the average peak angle spacing of the first-order and second-order circumferential strain curves, and the contact area length was estimated using the arc length formula. Subsequently, the braking simulation of rolling tires confirmed the asymmetry of pressure distribution within the ground contact area, estimating the position of slip points within the contact area based on arbitrary pressure distribution function and brush model, nonlinear regression was utilized to fit the estimation function of slip point under various slip rates. Finally, a functional relationship was developed between tire-road adhesion coefficient and slip rate, considering the friction characteristics between tire rubber and road surface, the friction model used is based on exponential decay. The results suggest that the methods described above enable rolling tires to estimate the tire-road adhesion coefficient under different slip rates, providing valuable insights for intelligent tire applications in vehicle dynamics control. UR - https://www.sv-jme.eu/article/identification-method-of-tire-road-adhesion-coefficient-based-on-tire-physical-model-and-strain-signal-for-pure-longitudinal-slip/
Zhang, Jintao, Jing, Zhecheng, Zhou, Haichao, Zhang, Yu, AND Wang, Guolin. "Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip" Articles in Press [Online], Volume 0 Number 0 (01 April 2025)
Articles in Press
© The Authors 2025. CC BY 4.0 Int.
To precisely calculate the tire-road adhesion coefficient of rolling tires at various slip rates, and enhance the safety and stability of vehicle operation, an approach for estimating the tire-road adhesion coefficient based on strain sensors and brush models was proposed. First, a finite element model of 205/55R16 radial tire was established, and the effectiveness of the model was verified through static ground contact and radial stiffness experiments. Then, the circumferential strain signal of the inner liner centerline of the tire during braking was extracted, utilizing the average peak angle spacing of the first-order and second-order circumferential strain curves, and the contact area length was estimated using the arc length formula. Subsequently, the braking simulation of rolling tires confirmed the asymmetry of pressure distribution within the ground contact area, estimating the position of slip points within the contact area based on arbitrary pressure distribution function and brush model, nonlinear regression was utilized to fit the estimation function of slip point under various slip rates. Finally, a functional relationship was developed between tire-road adhesion coefficient and slip rate, considering the friction characteristics between tire rubber and road surface, the friction model used is based on exponential decay. The results suggest that the methods described above enable rolling tires to estimate the tire-road adhesion coefficient under different slip rates, providing valuable insights for intelligent tire applications in vehicle dynamics control.