Browse Topic: Tires
This study introduces an innovative intelligent tire system capable of estimating the risk of total hydroplaning based on water pressure measurements within the tread grooves. Dynamic hydroplaning represents an important safety concern influenced by water depth, tread design, and vehicle longitudinal speed. Existing intelligent tire systems primarily assess hydroplaning risk using the water wedge effect, which occurs predominantly in deep water conditions. However, in shallow water, which is far more prevalent in real-world scenarios, the water wedge effect is absent at higher longitudinal speeds, which could make existing systems unable to reliably assess the total hydroplaning risk. Groove flow represents a key factor in hydroplaning dynamics, and it is governed by two mechanisms: water interception rate and water wedge pressure. In both the shallow water and deep water cases, the groove water flow will increase as a result of increasing the longitudinal speed of the vehicle for a
This paper presents an analytical approach for identifying suspension kingpin alignment parameters based on screw axis theorem and differential calculation model. The suspension kingpin caster and inclination alignment parameters can produce additional tire force, which affects vehicle handling dynamics. In wheel steering process, the multi-link suspension control arms lead to movement of the imaginary kingpin, which can cause change in suspension kingpin alignment parameters. According to the structure mechanism of commercial vehicle multi-link independent suspension, the kinematics characteristics of imaginary kingpin were analyzed based on the screw axis theorem. The angular velocity and translation velocity vectors were calculated. In order to avoid the influence of bushing deformation, the unique differential identification model was established to evaluate the suspension kingpin alignment parameters, and the identification results were compared with the ADAMS/Car data. The
A test and signal processing strategy was developed to allow a tire manufacturer to predict vehicle-level interior response based on component-level testing of a single tire. The approach leveraged time-domain Source-Path-Contribution (SPC) techniques to build an experimental model of an existing single tire tested on a dynamometer and substitute into a simulator vehicle to predict vehicle-level performance. The component-level single tire was characterized by its acoustic source strength and structural forces estimated by means of virtual point transformation and a matrix inversion approach. These source strengths and forces were then inserted into a simulator vehicle model to predict the acoustic signature, in time-domain, at the passenger’s ears. This approach was validated by comparing the vehicle-level prediction to vehicle-level measured response. The experimental model building procedure can then be adopted as a standard procedure to aid in vehicle development programs.
The problem of monitoring the parametric failures of a traction electric drive unit consisting of an inverter, a traction machine and a gearbox when interacting with a battery management system has been solved. The strategy for solving the problem is considered for an electric drive with three-phase synchronous and induction machines. The drive power elements perform electromechanical energy conversion with additional losses. The losses are caused by deviations of the element parameters from the nominal values during operation. Monitoring gradual failures by additional losses is adopted as a key concept of on-board diagnostics. Deviation monitoring places increased demands on the information support and accuracy of mathematical models of power elements. We take into account that the first harmonics of currents and voltages of a three-phase circuit are the dominant energy source, higher harmonics of PWM appear as harmonic losses, and mechanical losses in the rotor and gearbox can be
The increased importance of aerodynamics to help with overall vehicle efficiency necessitates a desire to improve the accuracy of the measuring methods. To help with that goal, this paper will provide a method for correcting belt-whip and wheel ventilation drag on single and 3-belt wind tunnels. This is primarily done through a method of analyzing rolling-road only speed sweeps but also physically implementing a barrier. When understanding the aerodynamic forces applied to a vehicle in a wind tunnel, the goal is to isolate only those forces that it would see in the real-world. This primarily means removing the weight of the vehicle from the vertical force and the rolling resistance of the tires and bearings from the longitudinal force. This is traditionally done by subtracting the no-wind forces from the wind at testing velocity forces. The first issue with the traditional method is that a boundary layer builds up on the belt(s), which can then influence a force onto the vehicle’s
Vehicle handling is significantly influenced by aerodynamic forces, which alter the normal load distribution across all four wheels, affecting vehicle stability. These forces, including lift, drag, and side forces, cause complex weight transfers and vary non-linearly with vehicle apparent velocity and orientation relative to wind direction. In this study, we simulate the vehicle traveling on a circular path with constant steering input, calculate the normal load on each tire using a weight transfer formula, calculate the effect of lift force on the vehicle on the front and rear, and calculate the vehicle dynamic relation at steady state because the frequency of change due to aerodynamic load is significantly less than that of the yaw rate response. The wind velocity vector is constant while the vehicle drives in a circle, so the apparent wind velocity relative to the car is cyclical. Our approach focuses on the interaction between two fundamental non-linearity’s: the nonlinear
From humble Chevrolet Bolts to six-figure Lucid Airs, every EV can reverse its electric motors to slow the vehicle while harvesting energy for the battery, the efficient tag-team process known as regenerative braking. Today's EVs do this so well that traditional friction brakes, which clamp onto a spinning wheel rotor or drum, can seem an afterthought. Witness Volkswagen's decision to equip its ID.4 with old-fashioned rear drum brakes, with VW claiming drums reduce EV rolling resistance and offer superior performance after long periods of disuse.
This SAE Recommended Practice describes the classification of off-road tires and rims for use on earthmoving machines (refer to SAE J1116), defines related terminology in common use, and shows representative construction details of component parts.
Researchers have developed a new soft robot design that engages in three simultaneous behaviors: rolling forward, spinning like a record, and following a path that orbits around a central point. The device, which operates without human or computer control, holds promise for developing soft robotic technologies that can be used to navigate and map unknown environments.
The sideslip angle and tire-road peak adhesion coefficient (TRPAC) are crucial parameters for intelligent active safety systems in automobiles. The accuracy and real-time estimation of these parameters significantly affect control effectiveness. And there is a strong coupling between the two parameters, which brings great challenges to the joint estimation. This paper proposes a nonlinear dynamic estimator that pre-estimates tire lateral force to achieve synchronous estimation of sideslip angle and TRPAC. Additionally, to cope with sudden changes in road adhesion condition, a TRPAC preliminary estimation optimization algorithm is introduced. Moreover, an adaptive gain adjustment algorithm for the sideslip angle estimator is implemented to address large lateral excitation conditions. Simulation results on various road surfaces and under various lateral excitation conditions demonstrate that the proposed joint estimator enables accurate and rapid estimation of sideslip angle and TRPAC.
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