Tire Friction Research Articles

ADAPTIVE MODEL PREDICTIVE CONTROLLER FOR TRAJECTORY TRACKING AND OBSTACLE AVOIDANCE ON AUTONOMOUS VEHICLE

Advancement in active steering technology is vital as the autonomous vehicle technology is preparing to enter the commercialization phase. Accurate trajectory tracking and collision free motion have become an active topic being discussed in research field recently. During an emergency obstacle avoidance manoeuvre conditions, tyre force saturation can easily happened when availability of lateral tyre forces is limited by the law of tyre friction circle. This greatly affects the trajectory tracking performance of the vehicle. Existing controllers such as generic model predictive controller (MPC) and geometric controller (Stanley) need a proper gain tuning to cope with this condition. This is due to the control gains were determined by trial and error basis via linearization process at a certain targeted speed. Therefore, the control performance is limited considering the presence of speed variation as well as extreme manoeuvre trajectory. This paper proposes an Adaptive Model Predictive Controller (MPC) controller to solve aforementioned issues. First, optimized weighting gains for the steering control were obtained using PSO algorithm. The optimised weighting gains were then scheduled into the proposed Model predictive Controller via a look-up table strategy. In this work, the proposed adaptive MPC controller was designed by using the linearization of the 7 degree-of-freedom (DOF) non-linear vehicle model. Here, the linearized model for controller design was update based on the instantaneous longitudinal speed of the vehicle system plant.

Lap Time Optimization and Path Following Control for 4WS & 4WID Autonomous Vehicle

<div class="section abstract"><div class="htmlview paragraph">In contrast to a normal vehicle, a 4-wheel steer (4WS) and 4-wheel independent drive (4WID) vehicle provides more flexibilities in vehicle dynamic control and better handling performance, since both the steer angle and drive torque of each wheel can be controlled. However, for motorsports, how much lap time can be improved with such a vehicle is a problem few discussed. So, this paper focuses on the racing line optimization and lap time improvement for a 4WS &4WID vehicle. First, we optimize the racing line and lap time of three given circuits with the genetic algorithm (GA) and interior-point method, and several objective functions are compared. Next, to evaluate the lap time improvement of 4WS & 4WID, a detailed vehicle dynamic model of our 4WS & 4WID platform vehicle is built in Carsim. To follow the racing line, a path following controller which contains a PID speed controller and a model predictive control (MPC) yaw rate controller is built. Moreover, a sliding mode (SMC) 4WS controller is designed to adjust the steer angle of wheels, meanwhile another SMC direct yaw moment (DYC) controller is proposed to track the target yaw rate and allocate the wheel torque considering the appropriate usage of tire friction. Results have demonstrated that the optimized racing line and lap time have tolerable error (<3%), and the proposed 4WS & 4WID method can reduce 3% of the lap time by enlarging the G-G diagram.</div></div>

Torque Distribution Algorithm for Four In-wheel Motors Drive Electric Vehicle Based on Torque Vector Control

Torque distribution algorithm, including the calculation of additional yaw moment and the distribution of four in-wheel motors torque, is studied. An additional yaw moment controller based on the MPC is designed. The predictive model is constructed based on 2-DOF vehicle model. The optimal additional yaw moment is obtained by solving the equivalent quadratic programming problem, which considers the constraints of target yaw rate, CG sideslip angle and minimum variation of additional yaw moment.Wheel torque distribution based on the optimal tire adhesion coefficient is established to realize additional yaw moment. Combined with the constraints of front and rear axle driving force, additional yaw moment and tire friction circle, the optimal wheel force distribution problem is transformed into a quadratic programming problem. In the special conditions such as lateral force saturation and driving anti-skid function trigger, the constraints are relaxed to avoid the equation without feasible solution.The simulation results of transient steering test, steady state steering test and extreme steering test showed that the application of the algorithm can shorten the response time of yaw rate, improve the cornering behavior of the vehicle under large lateral acceleration, and reduce the maximum passing speed under in slalom test to improve the handling and stability of the vehicle.

Fabrication of flexible sound absorption composite by constructing membrane with damping function on fabric

Noise, such as people talking, car whistle, tire friction, etc., affect people’s lives. In practical applications, curtains and wall coverings have sound absorption function to reduce noise annoyance is expected by people. In order to improve the sound absorption of the widely used woven fabric, a damping membrane was constructed on the fabric surface to prepare a flexible sound-absorbing composite material. Effects of fabric structure, constructed structure, membrane thickness, filler on the sound absorption of the composite were explored. From the results, the sound absorption of composite is caused by the porous sound absorption of the fabric, the damping and noise reduction of the membrane and the resonance sound absorption of the structure, which cannot be simply predicted by the model. When the membrane thickness of the structure was about 50 μm and the filler was vermiculite, the composite exhibited the best sound absorption performance: the sound absorption coefficient (α) reached 0.56, which was about 2.8 times that of the fabric. Moreover, the sound absorption bandwidth of the composite was nearly 1500 Hz wider than that of fabrics. This flexible composite material can be used as sound-absorbing products such as wall coverings, thin curtains and other products.

Towards longitudinal and lateral coupling control of autonomous vehicles using offset free MPC

Model predictive control (MPC) is widely used in the motion control of autonomous vehicles. However, the conventional MPC relies on an accurate model and cannot achieve offset-free tracking in steady-state when the autonomous vehicle encounters external disturbance and parameter perturbation. Based on our recently designed C++ offset-free MPC (OF-MPC) solver, this paper uses MPC to solve the longitudinal and lateral coupling control problem directly. In the modeling stage, the constraints of the tire friction circle are approximated by the polygon. And then the polygon constraints are mapped into the state and control space. Finally, the tire friction circle constraints are approximated as convex linear inequality constraints, which are used as the vehicle stability boundary condition. Meanwhile, a convex optimization method is used to solve the reference value problem of MPC, and a systematic method that can prevent the reference value from being outside the feasible region is proposed. The real-time simulation and actual vehicle results show that the algorithm can solve both lateral and longitudinal disturbances problems. The algorithm achieves better tracking accuracy and high-speed stability due to consideration of the longitudinal and lateral coupling constraints. Benefiting from the proposed efficient solver, the average time to complete all calculations, including logic processing and input–output processing, is only about 5ms when the horizon length is 50.

Characterization of Counter-Surface Substrates for a Laboratory Abrasion Tester (LAT100) Compared with Asphalt and Concrete to Predict Car Tire Performance

Tire performance is determined based on the interaction between the tire and the road as a counter-surface, and is of the utmost importance for driving safety. When studying tire friction and abrasion, the characteristics of the roads/counter-surfaces are crucial. The excitations on the tire come from the road asperities. A proper characterization of the counter-surface texture is, therefore, an absolute necessity in order to optimize tire performance. The present study provides the required knowledge over the counter-surfaces employed as common substrates in a Laboratory Abrasion Tester (LAT100), which are typically based on embedded corundum particles for dry/wet friction and abrasion experiments. All surfaces are scanned and characterized by laser microscopy. The surface micro and macro roughness/textures are evaluated and compared with asphalt and concrete as the real roads by power spectral densities (PSD). The reliability of the high-frequency data based on the device type should be considered carefully. The reliable cut-off wavenumber of the PSDs is investigated based on image analyses on the range of tested frequency for micro and macro textures obtained by optical scanning devices. The influence of the texture wavelength range on the rubber−surface interaction is studied on a laboratory scale.

Heat Generation of Aircraft Tires at Landing

When the aircraft lands on a runway, the great speed difference between tires and runway causes non-negligible friction and speeds up wheels. The generated heat rapidly raises tire temperature and causes material decomposition, which leads to replacement cost and flight safety issues; the chemical substances in the air can also cause emission problems. Many studies on aircraft tire temperature are based on software simulation or experiments. The simulation result may be affected by unnecessary variables due to cumbersome modelling, and the observation result may be inaccurate due to a particularly dynamic friction process. On the other side, there are few theoretical calculations about it. Therefore, A dynamic and thermal MATLAB model based on Laplace's heat equation is developed in this study to simulate the tire friction and heat generation. The temperature rise can be treated as an indicator to predict wear under variable landing conditions. The model can also be used to develop tire wear prevention methods.

A Neural Network Approach for Roughness-Dependent Update of Tyre Friction

The paper presents a unique application of artificial neural networks (ANN) for replicating the predictions of Persson's flash-temperature viscoelastic friction model. This allows the efficient calculation of the coefficient of friction between a tyre and the road surface, given the operating conditions, the tread material properties, and the power spectral density of road roughness. This is important because it allows the update of friction in a computationally efficient manner and therefore presents an opportunity for carrying out vehicle simulations on several road surfaces, without the requirement for tyre testing on every surface. To this end, a method is also proposed for integrating the most successful ANN configuration with a tyre model that had its baseline parameters identified by flat-track testing on a sandpaper surface. It is shown that the ANN-enhanced tyre model operates several times faster than real-time, predicting reduced peak and asymptotic tyre forces, as expected in most cases when moving from sandpaper to regular asphalt. The enhanced tyre model is further integrated with a vehicle model to illustrate the significant effect of reduced friction in stopping distance and handling dynamics.

Comparison and Harmonization of the Locked-Wheel Skid Tester and the Sideway-Force Coefficient Routine Investigation Machine

Abstract Skid resistance is a characteristic of a pavement surface that is critical to pavement safety. Skid resistance can be measured with different types of equipment, but because of the differences in the system configurations and the testing methods (fixed slip, locked-wheel, sideway-force, and variable-slip), the measured friction characteristics are not the same. To compare the measurements, analysts have attempted to harmonize measurements to a common scale by integrating the effects of macrotexture and slip-speed on skid resistance. Examples of these efforts include the Penn State model, the Rado Model, the Permanent International Association of Road Congresses International Friction Index (IFI), and the Rolling Resistance, Skid Resistance, and Noise Emission (ROSANNE) Skid Resistance Index (SRI). In the United States, skid resistance is traditionally measured with a locked-wheel skid trailer (LWST), but there has been increasing interest in the use of continuous friction measurement equipment. This paper compares friction measured using a LWST ribbed tire and smooth tire with measurements collected with a Sideway-Force Routine Investigation Machine (SCRIM). The first objective is to evaluate the influence of macrotexture on the friction measured with both devices. The second objective is to compare the friction measurements using orthogonal regression (OR) and derive equations for interconversion between both devices. The findings in this paper establish that the LWST ribbed tire and the SCRIM shared similar sensitivity to changes in microtexture, whereas smooth tire was more sensitive to changes in microtexture. The direction of the OR of both devices produced a greater correlation for the SCRIM and ribbed tire than did the smooth tire. The correlation was increased when the measurements with the SCRIM and smooth tire were converted to 60 km/h using the IFI FR60 conversion. The higher correlation using FR60 conversion provides further support for the dependence of smooth tire friction on macrotexture measurements.

A sensorless traction strategy for all-wheel drive electric motorcycles

Motorcycle designers aim to enhance vehicle performance, stability, and safety, especially when the vehicle is approaching the tyres' friction limit. A strategy to achieve these purposes is to design All-Wheel Drive (AWD) vehicles with active torque distribution. Nowadays, effective technical solutions for powering the front wheel of a motorcycle have been proposed. The use of traction on both front and rear wheel is convenient when tyre friction is low, enhancing vehicle safety and performance. In this context, this paper presents a sensorless, open-loop traction strategy for AWD motorcycles that improves performance and stability both in straight running and in cornering, without requiring the knowledge of road-tyre adherence. This novel traction distribution strategy is based on the idea of maximising the area of the motorcycle performance envelope, also known as g-g diagram. A simplified mathematical model is used to find closed-form solution to this problem, then converted into a control algorithm for the front and rear driving torques. The performance of the proposed method is assessed with simulations: a detailed model of a light electric motorcycle is used for calculating the non-linear vehicle performance envelope, the acceleration response in straight running and cornering, and the response to road irregularities. Moreover, a comparison with feedback slip-based traction control system is conducted. Simulation results indicate that the AWD motorcycle outperforms the conventional rear wheel drive motorbike almost in all situations, especially when road-tyre adherence is low, and that no counter-indication for the adoption of the AWD architecture exists.

An integrated control of front in-wheel motors and rear electronic limited slip differential for high-speed cornering performance

This paper presents an integrated control of in-wheel motor (IWM) and electronic limited slip differential (eLSD) for high-speed cornering performance. The proposed algorithm is designed to improve the handling performance near the limits of handling. The proposed controller consists of a supervisor, upper-level controller, and lower-level controller. First, the supervisor determines a target motion based on the yaw rate reference with a target understeer gradient. The target understeer gradient is devised to improve the lateral stability with in-wheel motor control based on a nonlinear static map. The yaw rate reference is designed based on the target understeer gradient to track the yaw reference with eLSD control. Second, the upper-level controller calculates the desired yaw moments for IWM and eLSD to generate the target motion. Third, the lower-level controller converts the desired yaw moment to the actuator torque commands for IWMs and eLSD. The tire friction limits are estimated based on the tire model and friction circle model to prevent tire saturation by limiting the torque inputs. The proposed algorithm has been investigated via both simulations and vehicle tests. The performance of the integrated control was compared with those of individual control and uncontrolled case in the simulation study. The vehicle tests have been performed using a rear wheel drive vehicle equipped with two front IWMs and eLSD in the rear axle. The vehicle test has been conducted at a racing track to show that the proposed algorithm can improve the lateral stability near the limits of handling.

Winter road surface condition classification using convolutional neural network (CNN): visible light and thermal image fusion

During winter, road conditions play a crucial role in traffic flow efficiency and road safety. Icy, snowy, slushy, and wet road conditions reduce tire friction and affect vehicle stability which could lead to dangerous crashes. To keep traffic operations safe, cities spend a significant budget on winter maintenance operations such as snow plowing and spreading of salt and sand. This paper proposes a methodology for automated winter road surface condition classification using convolutional neural network (CNN) and the combination of thermal and visible light cameras. As part of this research, 4244 pairs of visible light and thermal images are captured from pavement surfaces and classified into snowy, icy, wet, and slushy surface conditions. Two single-stream CNN models (visible light and thermal streams) and one dual-stream CNN model are developed. The average F1-Score of dual-stream model is 0.866, 0.935, 0.985, and 0.888 on snowy, icy, wet, and slushy, respectively. The weighted average F1-Score is 0.94.

Should a Vehicle Always Deviate to the Tire Blowout Side?—A New Tire Blowout Model With Toe Angle Effects

Abstract As a severe tire failure, tire blowout during driving can significantly threaten vehicle stability and road safety. Tire blowout models were developed in the literature to conclude that a vehicle always deviates to the tire blowout side. However, this conclusion is proved to be inaccurate in this paper, since one important factor was largely ignored in the existing tire blowout models. Toe angle, as a basic and widely applied setup on ground vehicles, can provide preset and symmetric lateral tire forces for normal driving. However, when tire blowout occurs, different toe angle setups can impact vehicle motions in different ways. For the first time, the toe angle is explicitly considered and integrated into a tire blowout model in this paper. For different tire blowout locations, driving maneuvers, and drivetrain configurations, the impacts of different toe angle setups on the variations of tire friction forces and vehicle motions are analyzed. The developed tire blowout model with toe angles is validated through both high-fidelity carsim simulation results and experimental results of a scaled test vehicle. Both simulation and experimental results show that a vehicle may not deviate to the tire blowout side, depending on the toe angle setups and driving maneuvers. Moreover, the experimental results also validate that the proposed tire blowout model can accurately evaluate the tire blowout impacts on vehicle dynamics.

Lane-deviation penalty formulation and analysis for autonomous vehicle avoidance maneuvers

Autonomous vehicles hold promise for increased vehicle and traffic safety, and there are several developments in the field where one example is an avoidance maneuver. There it is dangerous for the vehicle to be in the opposing lane, but it is safe to drive in the original lane again after the obstacle. To capture this basic observation, a lane-deviation penalty (LDP) objective function is devised. Based on this objective function, a formulation is developed utilizing optimal all-wheel braking and steering at the limit of road–tire friction. This method is evaluated for a double lane-change scenario by computing the resulting behavior for several interesting cases, where parameters of the emergency situation such as the initial speed of the vehicle and the size and placement of the obstacle are varied, and it performs well. A comparison with maneuvers obtained by minimum-time and other lateral-penalty objective functions shows that the use of the considered penalty function decreases the time that the vehicle spends in the opposing lane.

Online Bayesian inference and learning of Gaussian-process state–space models

This paper addresses the recursive joint inference (state estimation) and learning (system identification) problem for nonlinear systems admitting a state–space formulation. We model the system as a Gaussian-process state–space model (GP-SSM) and leverage a recently developed reduced-rank formulation of GP-SSMs to enable efficient, online learning. The unknown dynamical system is expressed as a basis-function expansion, where a connection to the GP makes it possible to systematically assign priors to the basis-function weights. The approach is formulated within the sequential Monte Carlo framework, wherein each particle retains its own weights of the basis functions, which are updated recursively as measurements arrive. We report competitive results when compared to a state-of-the art offline Bayesian learning method. We also apply the method to a case study concerning tire-friction estimation. The results indicate that our method can accurately learn the tire friction using automotive-grade sensors in an online setting, and quickly detect sudden changes on the road surface.

Ecological cooperative adaptive cruise control of over‐actuated electric vehicles with in‐wheel motor in traffic flow

Since electric vehicle with in-wheel motor has advantages in aspects of vehicle dynamics control and energy-efficient control, it has been widely applied in the vehicle platoon in the highway. This paper proposes an optimization and control structure that integrates ecological cooperative adaptive cruise control (CACC) for the vehicle platoon, and path tracking and ecological control allocation (Eco-CA) for individual vehicle to improve the energy efficiency of electric vehicles in traffic flow. First, in the upper layer, the suitable driving mode is selected by finite-state machine (FSM) based on surrounding environment. Then the path-planner and ecological CACC in the higher layer are proposed to determine the desired path and desired speed and acceleration profile. After that, in the middle layer, longitudinal motion controller and yaw stability controller are integrated to achieve the desired control targets from upper layer. Finally, in the lower layer, each in-wheel motor torque is optimized by Eco-CA subsystem to reduce the energy consumption of driving motor and tyre friction loss. The simulation results demonstrate that the proposed control strategy can improve the energy efficiency and dynamics control performance.

Transient abrasion on a rubber sample due to highly dynamic contact conditions

Abrasive processes, primarily the local slip, are the dominant contributor to friction and wear of vehicle tires in service. The time history of forces accompanying acceleration, braking, and cornering in particular, lead constantly to changing contact conditions under the tire. Consequently, a laboratory test taking into account not only surface texture but also tire contact times (in the range of milliseconds) as well as realistic contact forces in a freely controllable temporal sequence is desirable. This paper presents the study of the dynamic contact between a rubber block and the abrasive surface at conditions close to those in a tire footprint. In our case, the test samples are a miniaturized tread block allowing to reproduce the intermittent tire contact including correct contact timings, pressure and friction coefficients in dependence on the driving maneuver to be tested. An analysis and comparison of friction and wear mechanisms for continuous contact and defined contact times is presented surpassing the characterization capabilities of DIN abrasion testers.Two different compounds with a variation of stiffness are examined. The grip and wear rates are analyzed and compared. It is shown that understanding the dominant mechanisms and quantifying tire tread friction and wear in detail require the consideration of realistic transient dynamics of a tire tread block impacting the road at each revolution of the tire.

Impacts of Model Fidelity on Trajectory Optimization for Autonomous Vehicles in Extreme Maneuvers

In this paper, we quantify the impacts of model fidelity on the effectiveness of trajectory optimization for autonomous vehicles when driving at the limits of friction through experiments with a full-size vehicle. Models ranging from a double-track model with lateral and longitudinal load transfer dynamics to a simple point-mass model are used in combination with direct numerical optimization to generate optimal trajectories subject to the limits imposed by each model. The effectiveness of each model for trajectory planning is evaluated by testing the trajectories on an automated vehicle across friction conditions ranging from ice to dry asphalt. Comparisons between the outright performance of the car and the car's ability to track the optimal trajectory are made across the various models. The tests reveal that the advantage of more complex models is less that they better predict the vehicle's behavior, but that they provide a more nuanced view of the vehicle's limits and guidance on the proper coordination of the various actuators on the vehicle in order to make most efficient use of the available tire friction.

Experimental investigation of tire performance on slush

An investigation of tires behaviour on winter roads was always a high importance in the context of road safety. This paper presents the experimental investigation of tire performance on slush that is identified as two mixtures: a mixture of snow and water, and a mixture of crushed ice and water. The measurements of longitudinal and lateral performance including tire traction, braking and cornering were performed. Tire traction tests were performed for both mixtures with different amount of material. A decreasing in the tire friction was observed when amount of the mixture of snow and water was increased twice. For the mixture of crushed ice and water, an opposite trend was observed. The standard deviation values for the peak force coefficient showed a good reproducibility and reliability of performed tire tests.

Design of Torque Distribution Strategy for Four-Wheel-Independent-Drive Electric Vehicle

In order to further improve the handling stability of four-wheel-independent-drive electric vehicle, the control strategy designed in this paper adopts the hierarchical structure. The upper controller uses the vehicle dynamics principle and relevant expert control experience to formulate the corresponding fuzzy control rules to build the fuzzy controller. The linear two-degree-of-freedom reference model is built to obtain the desired driving state information of the vehicle, and the corresponding deviations are obtained by comparing with the actual vehicle state information, which are the input of the designed fuzzy controller to obtain the additional yaw moment required for stable driving of the vehicle. The lower controller obtains the generation mechanism of additional yaw moment through the 7-degree-of-freedom vehicle model and the characteristics of tire friction ellipse. Based on this, the regular distribution strategy is designed to obtain the driving torque on each driving motor. Through Carsim/Simulink joint simulation and hardware-in-the-loop experiments based on MicroAutoBox, the effectiveness and real-time performance of the designed control strategy are fully verified, and accelerate the development process of vehicle controller.