Wheel Slip Control Research Articles

Stability Control of an Autonomous Vehicle in Overtaking Manoeuvre Using Wheel Slip Control

Advanced driver assistance systems (ADAS) has been introduced to address driver-related accidents. One of the advantages of ADASs is that they can provide autonomous control and tracking in overtaking manoeuvres via GPS through the designed trajectory. In this study, using adaptive sliding mode control, an integrated longitudinal and lateral control of 4-DOF vehicle’s nonlinear dynamic model, in presence of uncertainties, has been proposed. Adaptive control law is utilized for switching gain based on the variations in the sliding surface. Furthermore, a sliding mode control is designed in order to control the longitudinal slip of front wheels. Simulation results show proper tracking for dry roads and acceptable tracking in low adherence roads (wet roads) in overtaking manoeuvres.

The Use of Integral Adaptation Principle to Synthesize Robust Control of Electric Vehicle Wheel Slip

The usage of "motor-wheel" systems requires the electric vehicle control system improvement by using the characteristics of the wheel adhesion to the road surface. One of the aspects of such improvement is the enhancement of the algorithms for the functioning of the antilock braking system (ABS). In developing the ABS control algorithms, various approaches and methods of modern control theory are used, including methods based on the estimation of wheel slip, traction force, wheel friction coefficient using linear and nonlinear estimation methods, linear and nonlinear regulators. This work illustrates the application of the principle of high order integral adaptation (PIA) of Synergetic Control Theory (SCT) for constructing a robust control law for an electric vehicle wheel slip. The main features of the SCT contain: firstly, a fundamental change in the goals of the behavior of the synthesized systems; secondly, direct consideration of the natural properties of nonlinear objects; thirdly, the formation of an analytical mechanism for generating feedbacks, i.e. control laws. PIA consists in introducing nonlinear integrators into the control law that compensate for disturbances without their immediate estimation. The obtained in this work control law has a fairly simple structure, is focused on using physically accessible state variables of the braking system, and its implementation does not require immediate estimation of disturbances or building a complex neural network to calculate disturbances. The results of computer simulations of the synthesized robust control law for ABS indicate its effectiveness in functioning under conditions of external environment uncertainty.

A Novel Wheel Skid Control Based On Motor Energy Distribution Model

How to realize wheel slip control with parameters that can be measured and not relying on hardware precision is a difficult problem in vehicle traction control. From the point of view of energy transfer, this paper uses the feature that the rotational kinetic energy of the wheel increases abnormally when slipping, and proposes a wheel slip control method based on the motor energy distribution model. This method only requires the motor phase voltage, phase current and wheel speed that are easy to measure. In this paper, a complete vector control model of permanent magnet synchronous motor is established, and a PI control algorithm framework is built based on one-wheel vehicle model. The simulation results verify the effectiveness of the proposed algorithm.

Applied nonlinear control of vehicle stability with control and state constraints

For the vehicle dynamic control system, to guarantee directional stability in risky maneuvers, the side-slip angle should be restricted to the admissible range when the yaw rate tracks the proposed desired response for enhanced steerability. Meanwhile, the control input of the external yaw moment produced by asymmetric braking forces should be calculated in the practical range according to the capacity of tire forces. In the present study, a novel constrained controller with input and state constraints is developed. To this aim, a cost function consisting of predicted continuous response of yaw rate tracking error is expanded in terms of current control signal. Concurrently, the state constraint of side slip is transformed to the equivalent constraint of control signal by a novel nonlinear prediction approach. After that, the expanded performance index is analytically minimized in the presence of all input constraints to obtain the control law. The computed yaw moment is optimally distributed to asymmetric braking forces by designing a wheel slip control system. Simulation studies are conducted to evaluate the performance of proposed constrained controller compared with the unconstrained controller and a conventional nonlinear model predictive controller developed in the recent papers using a 14-degree-of-freedom vehicle model which includes suspension system dynamics. The results show that the proposed controller is much faster and easy to solve and implement.

A Wheel Slip Control Approach Integrated With Electronic Stability Control for Decentralized Drive Electric Vehicles

Wheel slip control, as a basis for vehicle stability control, prevents loss of traction. A new wheel slip control approach that does not require chassis velocity is proposed in this paper. The proposed approach uses the wheel speeds and the chassis acceleration measured on the acceleration sensor to estimate the maximum tire-road friction. Then, the motor torque is constrained using the maximum tire-road friction. To ensure the vehicle starts smoothly and to enhance its acceleration performance, a fuzzy controller is used to determine whether the output torque should be constrained. The main advantage of this approach is that it is indifferent to the vehicle mass and driving resistance. Hardware-in-the-loop (HIL) simulation results validated that the proposed approach could improve the vehicle stability when the vehicle corners on slippery conditions, which is attributable to the approach's robustness to vehicle mass and driving resistance. Moreover, HIL simulation proved that it was feasible to implement the proposed approach in real vehicles.

A two-wheel load balance control strategy for an HVTL inspection robot based on second-order sliding-mode

PurposeOverhead high-voltage transmission line (HVTL) inspection robots are used to inspect the transmission lines and/or maintain the infrastructures of a power transmission grid. One of the most serious problems is that the load on the front wheel is much larger than that on the back one when the robot travels along a sloping earth wire. Thus, ongoing operation of the inspection robot mainly depends on the front wheel motor’s ability. This paper aims to extend continuous operation time of the HVTL inspection robots.Design/methodology/approachBy introducing a traction force model, the authors have established a dynamic model of the robot with slip. The total load is evenly distributed to both wheels. According to the traction force model, the desired wheel slip is calculated to achieve the goal of load balance. A wheel slip controller was designed based on second-order sliding-mode control methodology.FindingsThis controller accomplishes the control objective, such that the actual wheel slip tracks the desired wheel slip. A simulation and experiment verify the feasibility of the load balance control system. These results indicate that the loads on both wheels are generally equal.Originality/valueBy balancing the loads on both wheels, the inspection robot can travel along the earth wire longer, improving its efficiency.

An AWID and AWIS X-By-Wire UGV: Design and Hierarchical Chassis Dynamics Control

In this paper, an all-wheel independently driven and all-wheel independently steered unmanned ground vehicle (UGV) is described. This paper investigates the hierarchical chassis yaw dynamics control (CYDC) and the tyre force control of the UGV in the remote control mode (RCM). The hierarchical CYDC scheme in RCM is proposed. As the key part in the control scheme, a yaw moment controller is proposed to deal with the oversteer problem of the UGV. Through the robust-based pole placement technique, the ideal poles’ zones of the lateral UGV dynamics system are able to be tuned to meet different dynamics behavior requirements in different UGV tasks. The robust state feedback yaw dynamics controller is investigated based on the linear matrix inequalities approach. It considers the unavoidable parametric disturbance and uncertainty, such as the variation of the UGV’s mass, yaw inertia, and tyre-road characteristics. In addition, in order to improve its performance in off-road conditions, the tyre traction force distribution algorithm and sliding mode wheel slip controller are designed to negotiate uneven terrains. The experiments in paved and off-road conditions are conducted to demonstrate the performance of the proposed controller.

Robust Two-Degree-of-Freedom Wheel Slip Controller Structure for Anti-lock Braking

Abstract A robust wheel slip controller for use in anti-lock braking systems is proposed, that entails a two-degree-of-freedom structure with a robustly designed PID controller for the linearized quartercar model and a model reference tracking prefilter based on exact feedback linearization.

Robust Continuous Wheel Slip Control With Reference Adaptation: Application to the Brake System With Decoupled Architecture

Modern and coming generations of electric and automated vehicles are characterized by higher requirements to robust and fault-tolerant operation of chassis systems independently from driving situations and road conditions. In this regard, this paper introduces an adaptive continuous wheel slip control (WSC) developed for the sport utility vehicle equipped with a high-dynamic decoupled electrohydraulic brake system. The system architecture, mathematical formulation of the WSC and state estimator as well as the experimental WSC validation is described in this paper. The focus is given on three continuous WSC strategies based on proportional integral (PI), sliding-mode PI and integral-sliding-mode control techniques. The proposed WSC also includes the state and parameter estimator for the adaptation of the reference wheel slip depending on current road conditions and using the standard on-board vehicle sensors and extremum-seeking algorithm. Adaptability and robustness of all WSC configurations were confirmed by the road experiments performed on low- and high- $ \mu$ surfaces with mandatory condition of the same controls adjustments for all test cases. Tests show an enhancement of the vehicle safety and ride quality, compared to the vehicle with the rule-based WSC control.

Evaluation of the wheel slip control quality during braking with the ABS system acting

The paper presents the method of assessing the degree of the wheel slip utilization during braking in relation to the slip adopted as optimal in the analyzed braking process.In an ideal ABS system, the wheel slip should be equal to the slip assumed to be optimal under the given braking conditions. In a real, pulsed system ABS, wheel slip changes in a wide range of values.The quantitative assessment of the correct operation of the real ABS/ESP system can be made on the basis of indicators showing the degree of approximation of the actual slip of the wheel s to the value assumed to be optimal due to the wheel’s adhesion to the roadway sopt.In the paper has been analyzed the wheel slip utilization ΔL as the difference of the actual circumferential speed of the wheel vk and the speed of the wheel vkopt, at which the slip is optimal in the given braking conditions, referenced to a specific braking time Δt = t2 − t1:The calculation of this indicator requires the measurement of the car’s speed vs and wheel speed vk and the determination of the optimal slip value sopt on a given surface. The paper analyzes the impact of the optimal slip value on the assessment of ABS performance with various control algorithms (Independent Regulation IR, Select Low SL).The article presents the results of tests of the slip utilization index in various braking conditions and for brakes with damaged mechanical components.

Adaptive backstepping sliding mode control for wheel slip tracking of vehicle with uncertainty observer

The wheel slip tracking control is the basis of automatic braking control systems, and the accurate tracking for the desired wheel slip in the presence of lumped uncertainty is a vital guarantee of automatic braking control systems reliable operation. Therefore, an adaptive backstepping sliding mode control approach with radial basis function neural network is proposed to design the nonlinear robust wheel slip controller based on a quarter-vehicle model with lumped uncertainty. The radial basis function neural network as the uncertainty observer can effectively reduce the chattering of sliding mode by estimating the lumped uncertainty, and the adaptive law for the unknown weight vector of radial basis function neural network is derived by Lyapunov-based method. The influence of changes in tire sideslip angle and camber angle on the tire -road friction coefficient acts as an unknown scaling factor, and the adaptive law for the unknown scaling factor is derived via Lyapunov-based method. Then, the performance of the proposed controller is verified through simulations of various maneuvers on a full-vehicle dynamics simulation software.

Robust predictive control of wheel slip in antilock braking systems based on radial basis function neural network

Anti-Lock Braking System (ABS) is a well-known technology for vehicle safety enhancement during hard braking. The wheel slip control has been a challenging problem due to a complex behavior of the tire and strong nonlinearity in a braking process. Furthermore, the system is subjected to unknown uncertainties that would arise from changing the vehicle parameters and un-model dynamics. Thus, it is required to design a nonlinear robust control law for ABS to overcome these problems. In this paper, a novel robust prediction-based controller for ABS is proposed that guarantees the stability against uncertainties. An optimal control law is firstly designed for ABS using nonlinear predictive method. Then, the unknown uncertainties are adaptively approximated utilizing a radial basis function neural network (RBFNN). The Lyapunov approach is employed to develop an update control law to determine the network weights. Finally, some simulations are conducted to examine the performance of the proposed control system for tracking the reference wheel slip in the presence of uncertainties in different maneuvers. Also, the performance of the proposed controller is compared with the conventional sliding mode controller (SMC) through simulation results.

Locomotive Wheel Slip Control Method Based on an Unscented Kalman Filter

Railway traction vehicles transfer forces between wheels and rails through an adhesion coefficient. The adhesion coefficient value can decrease abruptly during the train run. Therefore, the wheels can simply gain high value of the wheels slip velocity. Thus, the vehicles are equipped with slip controllers for this case. During the past decades, many types of slip control strategies were developed, and the new methods are also developed today. Some perspective methods are based on an estimation of the adhesion coefficient or an adhesion force. However, correct operation of these methods is not guaranteed in all cases. Moreover, these methods have some weakness that can decrease their efficiency. Therefore, a novel method based on the adhesion condition estimation is presented in this paper. The adhesion condition is estimated by an unscented Kalman filter. When the method is connected to a controller, it is possible to eliminate the rising wheel slip velocity at its beginning and limit it to the appropriate value. The output of the method is directly used as an input of the controller without any additional calculation as it is used in traditional methods. The input signal does not need any additional filtration, and the method does not require information about the actual train velocity for its proper work. The verification of the method is done with the measured data that were measured on a freight train hauled by an electric locomotive. This paper also presents simulation results of the method with a controller based on the locomotive mathematical model.

MPC-based Slip Control System for In-wheel-motor Drive EV

A new slip control system for electric vehicles (EVs) equipped with four in-wheel motors is presented in this paper to solve the problem of the risk of locking up of EV wheels on brakes. This controller is designed on the basis of a model predictive control (MPC) scheme. Thus, the proposed MPC slip controller guarantees the optimal braking torque on each wheel by individually controlling the slip ratio of each tire within the stable zone over a considerably shortened response time. The wheel slip control performance is improved given the shortened response of the regenerative braking system. Theoretical analyses and simulation show that the proposed controller delivers an effective antilock performance.

EXTENDED KALMAN FILTER DESIGN FOR RAILWAY TRACTION MOTOR

Monitoring the adhesion force between a railway wheel and a rail surface is very essential in maintaining the high acceleration and braking performance of railway vehicles. Due to the difficulties encountered in direct measurement of friction coefficient, creepage and adhesion force, state observers are used as indirect estimation methods. This paper proposes an effective estimation method, which exploits railway traction motor behaviour to give an assistance for realizing wheel slip and adhesion control in order to be used in railway applications. This method plays an active role in optimizing the use of the existing adhesion and reducing wheel wear by decreasing high creep values. With this method, adhesion force can be indirectly estimated by measuring stator currents, and angular speed of the AC traction motor and using dynamic relationships based on the extended Kalman filter (EKF) simulation model. The re-adhesion controller can be designed to regulate the motor torque command according to the maximum available adhesion depending on the estimated results. To test the proposed method, simulations were performed under different friction coefficients.

Fuzzy Scheduled Optimal Control of Integrated Vehicle Braking and Steering Systems

The safe hard braking of a turned vehicle requires short stopping distance while maintaining the vehicle in the path. To achieve the first aim, a wheel slip controller is designed to calculate the maximum braking force of each wheel according to the tire/road conditions. For the second aim, a new optimal multivariable controller for integrated active front steering and direct yaw moment control is analytically developed to control the vehicle directional stability directly. Since the required stabilizing external yaw moment has to be produced by reducing the maximum achievable braking forces of one side wheels, it leads to increase the stopping distance and should be kept as low as possible. In an effective way to manage the integrated control inputs, a fuzzy logic is defined to determine the weight factor of each control input in the integrated optimal control law. This logic is defined using the stability index obtained by the phase plane analysis of nonlinear vehicle model. Therefore, the proposed controller can be tuned automatically for different driving conditions. The simulation results carried out using a validated vehicle model demonstrate that the integrated control system has a better performance compared with stand-alone braking and steering systems to attain the desired purposes.

ADAR Method and Theory of Adaptive Control in the Tasks of Synthesis of the Nonlinear Control Systems

This work continues a series of artides devoted to an illustrative comparison of the methods of modern control theory and the method of Analytical Design of Aggregated Regulators (ADAR). The ADAR method suggests two ways to ensure a nonlinear system adaptability to the external and parametric perturbations. The first way is the use of the principle of integral adaptation, when the influence of the parametric or external perturbations is compensated for by the nonlinear control laws introduced by integrators in a spedal manner. The design pгoceduгe of the adaptive control laws, according to this way, does not require a synthesis of the state and perturbation observers and consequently eliminate a real-time estimation of these perturbations. The second way is a design of the nonlinear observers of the parametric and external perturbations. In this case the designed nonlinear control laws are supplemented by a subsystem of observation, which realizes a dynamic estimation of the nonmeteringperturbations and a compensation for them. The above ways are illustrated in the artide by the known control tasks: the task of a wheel slip control in an anti-lock braking system; and the task of identification of the parameters and monitoring of the state of electгochemical pгocesses in the cell membranes in accordance with Hindmarsh and Rose model. The examples of the design procedures presented in the article demonstrate the advantages of the ADAR method concerning the analytical design of the adaptive regulators for the nonlinear objects. The theoretical results were confirmed by simulation of the closed-loop system in MATLAB software.

Robust Integrated Control of Wheel Slip and Direct Yaw Moment for Stabilizing the Dynamics of Skid-Steering Vehicles

This paper presents a robust integrated control system to improve the stability and the handling performance of skid-steering vehicles. The control strategy is based on two layers: direct yaw moment control and wheel slip control. In the first layer, the direct yaw moment is obtained based on the nonlinear sliding mode control theory using the exact second order yaw rate response of the conventional steering vehicle. In the second layer, the direct yaw moment is optimally distributed to the four wheels in order to calculate the torque command needed at each wheel individually. Then, the sliding mode control theory is used again to control the torque command at each wheel individually and maintain the wheel slip at the desired value. A closed-loop driver-vehicle system subjected to a turning maneuver accompanied with braking at different surface conditions is simulated in Matlab/SIMULINK to validate the effectiveness of the proposed integrated control system. The simulation results show that the combination of wheel slip control and direct yaw moment is essential for stabilizing the motion of skid-steering vehicles. Moreover, the proposed control system is robust against uncertainty in the adhesion between the road surface and the wheel.

Robust Linear Parameter Varying Model Predictive Control and its Application to Wheel Slip Control

This paper proposes a robust model predictive controller for linear parameter varying (LPV) systems subject to additive disturbances. The proposed controller relies on the constraint tightening method to guarantee that the MPC’s optimization problem remains feasible in the presence of additive disturbances. In order to decrease the conservativeness, the controller synthesis considers bounded parameter rate variations in the construction of the tightened constraints. Relevant features, such as recursive feasibility and stability of the LPV-MPC, are theoretically proven. Finally, the proposed controller is applied to a wheel-slip control problem and its effectiveness is shown by simulation results.

Wheel slip control with torque blending using linear and nonlinear model predictive control

ABSTRACTModern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.