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Vehicle Mechanics
Published in Iqbal Husain, Electric and Hybrid Vehicles, 2021
where wwh is the wheel speed and rwh is the driven wheel radius. The wheel speed of travel is equivalent to the vehicle translatory speed v. Vehicle linear velocity v and the tire speed vtire differ in magnitude and direction as shown in Figure 2.17. The angle between the tire velocity and the vehicle velocity is known as slip angle α, shown in Figure 2.17 with exaggeration. The difference in speed itself is generated due to the tire properties and the interaction of forces at the tire–road interface. The tire forces do not act through a point but are distributed over the contact patch area of the tire with the road surface. Furthermore, the forces are not uniform along the contact patch in either longitudinal or lateral directions. The vehicle traction force FTR works in the longitudinal direction. Longitudinal and lateral forces will be discussed further later; first, let us discuss the vehicle slip in the longitudinal direction.
Tire Models
Published in Donald E. Struble, John D. Struble, Automotive Accident Reconstruction, 2020
Donald E. Struble, John D. Struble
When the vehicle is traveling a straight path, the tire can generate longitudinal acceleration or deceleration forces because it deforms and serves as the interface between the moving vehicle and the stationary road. This is also true when the tire is at an angle to the path of travel, only now the tire deforms laterally, and lateral forces occur at the contact path. One might expect that the magnitude of such forces depends on just how much angle and how much normal force are present, and testing would confirm that expectation. (There may also be dependence on other factors, such as velocity and temperature, but those are generally considered to be second-order small for reconstruction purposes.) The angle between the tire’s longitudinal direction (heading) and its path of travel is known as the “slip angle” α; i.e., α=Arctan(VlatVlong)
Advantages of parameter estimation in electric vehicles
Published in Maksym Spiryagin, Timothy Gordon, Colin Cole, Tim McSweeney, The Dynamics of Vehicles on Roads and Tracks, 2018
This is where parameter estimation becomes important. In order to accurately and directly measure some of the above parameters, expensive sensors must be implemented which is not feasible in commercial vehicles due to cost, maintenance and reliability. Measuring slip angle directly for instance requires expensive, visual based sensors (Tanelli et al). Vehicle mass, similarly, requires measurement of suspension deflection using strain gauges or other sensors (Yang et al 2008, Nisthitani). This cost is deemed unsuitable for mass production and therefore a push for parameter and state estimation is preferred. This leads to the issue of being able to accurately estimate the desired parameters for the desired control implementation. This can be made difficult due to nonlinear relationships or noise affecting the measurement from which the estimation is made. Advanced algorithms and filters are chosen to mitigate the magnitude of error (Li et al, 2014). The last area for development in parameter estimation lies in bringing a working theoretical setup of sensors, control equipment, algorithms and filters from a working simulation to a real time test bed. Often simulated noise does not effectively imitate that seen in real time by sensors, and estimation algorithms cannot cope with the computational cost in real time. This is where most current research is now directed.
ContactGAN development – prediction of tire-pavement contact stresses using a generative and transfer learning model
Published in International Journal of Pavement Engineering, 2022
Xiuyu Liu, Angeli Jayme, Imad L. Al-Qadi
It is noteworthy that the free-rolling condition (i.e. a condition wherein the driving torque is zero) represents a slip angle of 0°, wherein the tire travels along a path at a given angle with the wheel plane. Generally, the slip angle influences the directional control and stability of a rolling tire (Liu et al. 2019). The numerical implementation of the slip angle arises from modifying the linear speed along the longitudinal () and lateral () directions, as defined by the following equations: where and are the longitudinal and transverse velocities in km/h and is the linear speed in km/h.
Switched model predictive controller for path tracking of autonomous vehicle considering rollover stability
Published in Vehicle System Dynamics, 2022
Ying Tian, Qiangqiang Yao, Chengqiang Wang, Shengyuan Wang, Jiaqi Liu, Qun Wang
The Fiala brush tire model shows high accuracy; it fully considers the nonlinear dynamics characteristic [31]. The tire lateral force can be described as a function of tire slip angle where α and Cα are the tire slip angle and cornering stiffness, respectively. μ is the adhesion coefficient between the road surface and tire. FZ is the vertical force.