ABSTRACT

Cooler running tires with a reduced rolling resistance is a consideration for both tire makers and automotive original equipment manufacturers. To investigate the mechanics of energy loss and temperature rise, a nonlinear viscoelastic model suitable for numerical analysis of rolling tires is developed and demonstrated. The rubber compounds are represented as nonlinear viscoelastic materials with temperature and frequency, strain, and strain history–dependent response. Several applications to different tire designs are provided to demonstrate the impact of this new material constitutive law in improving the quality of the numerical predictions over other methods. One application is a rolling tire model that was used to delineate the tire temperature distribution and the resultant rolling resistance for different three-dimensional tread patterns.

ABSTRACT

An intelligent tire–based algorithm was developed to reinforce the vehicle longitudinal velocity estimation, from the vehicle inertial measurement unit (IMU). A tire was instrumented using a triaxis accelerometer (intelligent tire) in an instrumented vehicle with an IMU, and a global positioning system (GPS) based speed sensor (VBOX) as the ground truth for vehicle velocity. A testing matrix was developed, including two tire inflation pressures, two normal loads, and variable speed between 4 m/s to 14 m/s. A signal processing algorithm was developed to analyze the data from the accelerometer. Variational mode decomposition and Hilbert spectrum analysis were used for extracting features from each tire revolution. Later, a machine learning algorithm was trained to estimate the velocity using the acceleration data from the intelligent tire. Because the sampling rates of the IMU data and the intelligent tire data were different, sensor fusion was implemented. This calculated velocity was then used to correct the IMU-based estimated velocity. This new velocity can be used to enhance the performance of all advanced chassis control systems, such as anti-lock braking system (ABS) and electronic stability program (ESP).

ABSTRACT

The concept “relaxation length” serves as one of several ways to characterize the transient lateral response for a rolling tire. Most test methods developed to identify relaxation length tightly link to Pacejka’s single-contact-point linear transient model. Its underlying assumption is that the traveled distance during the transition interval is always a constant regardless of the wheels’ linear rolling speed. The current research provides physical data against this strong assumption. The data is acquired through a newly-developed test method named the “ramp-step steer method”.

The ramp-step steer method features a nonstop, high rolling speed, and fast-changing slip angle procedure that cannot be fulfilled by the conventional “start-stop-resume” step steer method. Thanks to the high dynamic capability of the equipment in GCAPS Corp., the proposed test method becomes feasible. A novel data postprocessing scheme accompanies the test method as well. The ramp-step steer method is independent of any specific models and replicates the scenario of a rolling tire subjected to a sudden slip angle change from on-vehicle to an indoor environment. The wheel speed effect on the tires’ transient lateral response is reflected through a proposed quantity, L_y , which is a more general descriptor and can downscale to relaxation length under specific circumstances. Ly itself does not associate with any model, so the remaining study explains the speed effect through an updated model. The present research aims to provide a better way of characterizing tires’ lateral transient behavior and is not an alternative to identify the key parameter “relaxation length” in Pacejka’s model. Another contribution of the research is categorizing and separating the hierarchy of various transient tire models.

ABSTRACT

Virtual steering system layout in the early development phase requires adequate tire models to predict realistic steering rack forces. An accurate representation of parking is particularly important, as the largest steering rack forces occur during this maneuver. Physical tire models are mainly parameterized for rolling conditions. Since the tire exhibits different mechanical behavior under nonrolling conditions, this article introduces a new parameterization procedure for the physical tire model FTire that characterizes the conditions during parking maneuvers. To this end, an additional full vehicle measurement setup is used to understand the tire motions, forces, and torques during parking. It is also shown that a tire model based on a standard parameterization procedure results in steering speed-dependent parking torque deviations of up to 17.5% when compared with component measurements. Thus, new measurement methods are developed to help parameterize the tire model for this maneuver. A linear friction tester is used to determine the friction interaction between tire and road at the relevant relative velocities. In addition, measurements are performed on a tire stiffness test rig, in which translatory and rotatory movements are overlaid. Furthermore, the contact patch shape, ground pressure distribution, and tire outer contour are digitalized and added into the model. A tire model based on the new parking optimized parameterization is then compared with the standard tire modeling approach and component measurements as well as the full vehicle measurements. In conclusion, improvements of up to 12% for drilling torque, up to 15% for longitudinal force, a more realistic lateral stiffness, a more realistic pressure distribution, and improvements of up to 8% when simulating the steering rack force can be stated. After the results are evaluated and interpreted, recommendations for future developments of this parameterization procedure and an extension of the virtual tire model are discussed.