Wheel Slip Control Research Articles

Wheel Slip Equilibrium Point Model Reference Adaptive Control Based PID Controller for Antilock Braking System: A New Approach

This paper presents a new approach to wheel slip control in Antilock Braking System (ABS) using an Approximated First Order Wheel Slip (AFOWS) Model Reference Adaptive Control (MRAC) based PID (AFOWS-MRAC-PID) controller. An ABS was modeled in a MATLAB/Simulink environment using a quarter car model with the proposed controller. Simulations were conducted with a wide range of adaptation gains (50, 100, 150, 200, and 250) to study the effectiveness of the proposed control system. The results revealed that the proposed system could track and maintain 10% wheel slip and eliminate oscillation (instability) in terms of overshoot associated with conventional PID controllers, particularly on wet and snowy road surfaces, using adaptation gains of 150, 200, and 250. Overall, the proposed system provided the best performance in terms of stopping distance, vehicle braking velocity, and braking torque on all road surfaces with an adaptation gain of 250, although braking on dry road surfaces was the most effective.

Effect of Weight Distribution and Active Safety Systems on Electric Vehicle Performance.

This paper describes control methods to improve electric vehicle performance in terms of handling, stability and cornering by adjusting the weight distribution and implementing control systems (e.g., wheel slip control, and yaw rate control). The vehicle is first simulated using the bicycle model to capture the dynamics. Then, a study on the effect of weight distribution on the driving behavior is conducted. The study is performed for three different weight configurations. Moreover, a yaw rate controller and a wheel slip controller are designed and implemented to improve the vehicle's performance for cornering and longitudinal motion under the different loading conditions. The simulation through the bicycle model is compared to the experiments conducted on a rear-wheel driven radio-controlled (RC) electric vehicle. The paper shows how the wheel slip controller contributes to the stabilization of the vehicle, how the yaw rate controller reduces understeering, and how the location of the center of gravity (CoG) affects steering behavior. Lastly, an analysis of the combination of control systems for each weight transfer is conducted to determine the configuration with the highest performance regarding acceleration time, braking distance, and steering behavior.

An Investigation in the Control Effectiveness of the Driving Wheel Slip Prevention System of a Diesel Engine Dump Truck

<div>This article proposes the structure and algorithm to design a PID controller for the driving wheel slip prevention system (DWSPs) of a dump truck using a diesel engine, which is equipped just only with a traditional high-pressure pump (HPP) under low-adhesion coefficient conditions. First, a longitudinal dynamic model, and a dynamic model of the wheel and powertrain of a dump truck are, respectively, established, and an experiment in the torque determination of a diesel engine is set up to investigate longitudinal vehicle dynamics as well. Then, a control system structure of the DWSPs for a dump truck using a diesel engine with a high-pressure inline fuel pump is proposed. Finally, based on performance analysis of other types of controllers, a PID controller is selected to control actual load level of a diesel engine. The criteria representing the vehicle’s acceleration such as the vehicle speed, vehicle acceleration, total slip time, and time to reach vehicle speed are selected to examine the effectiveness of the proposed controller when vehicles are being operated under the road surface conditions with low values of adhesion coefficient. The obtained results show that the proposed controller has greatly limited the driving wheel slipping phenomenon and increased the acceleration of the original dump truck. In addition, these findings can be used as a theoretical basis for the improvement of the wheel slip controllers in trucks using diesel engines.</div>

Sliding Mode Wheel Slip Control for Regenerative Braking of an All-Wheel-Drive Electric Vehicle

Abstract Regenerative braking is one of the main advantages of electric propulsion systems. In such systems, the vehicle brake controller has to prioritize safety while maximizing the recovered energy at all times. This paper proposes a two-step hierarchical brake controller for a dual-motor all-wheel-drive electric vehicle. In the first step, a novel sliding mode controller (SMC) generates the total braking torque on each axle to independently control the slip on the front and rear wheels. In the second step, the torque split controller assigns motor and friction brake torques to maximize the recovered energy. By incorporating the effects of changing vehicle speed, the proposed SMC controller accounts for the nonlinearities in vehicle dynamics and tire model and considers the weight transfer due to vehicle deceleration while being robust to disturbances. Using simulations, we show that while the traditional SMC formulation is not effective during emergency braking scenarios, the proposed formulation successfully generates control commands to bring the vehicle to a stop position at a minimum distance. Furthermore, our controller can maintain both wheels in the stable slip region, even when starting from a locked position. The performance of the proposed controller is evaluated for an emergency braking scenario and on an aggressive segment of the US06 cycle.

Theoretical Systematisation of Wheel Slip Control Methods Based on Excessive Torque and Angular Momentum

Theoretical Systematisation of Wheel Slip Control Methods Based on Excessive Torque and Angular Momentum

Bifurcation analysis of a wheel‐slip control loop under low wheel‐slip regulation considering time‐delay

AbstractSafety and efficiency are key aspects of research and development in the automotive industry, especially in the field of safety‐critical subsystems, such as brake systems. The effect of time delay arise in brake systems, this adverse effect can cause performance degradations or make the brake system unstable. In this study, the bifurcation analysis of a wheel slip control feedback loop is presented. The control system consists of a wheel and a tyre, delayed actuator dynamics, and an LQR (linear quadratic regulator) that is designed to operate under relatively low wheel slip, during service braking. As a result, it is shown, that if time delay is neglected, the steady‐state solution of the model is globally stable using the LQ optimal controller gains. However, considering nonzero time‐delay may cause a subcritical Hopf‐bifurcation, and an unstable limit‐cycle exists around the steady‐state solution in a large domain of time‐delay parameters. Critical bifurcation maps and simulation results with more detailed system models are generated and shown in the study.

Design and Verification of Offline Robust Model Predictive Controller for Wheel Slip Control in ABS Brakes

Wheel slip control is a critical aspect of vehicle safety systems, notably the antilock braking system (ABS). Designing a robust controller for the ABS faces the challenge of accommodating its strong nonlinear behavior across varying road conditions and parameters. To ensure optimal performance during braking and prevent skidding or lock-up, the ideal wheel slip value can be determined from the peak of the tire–road friction curve and maintained throughout the braking process. Among various control approaches, model predictive control (MPC) demonstrates superior performance and robustness. However, online MPC implementation encounters significant computational burdens and real-time limitations, particularly when dealing with larger problem sizes. To address these issues, this study introduces an offline robust model predictive control (RMPC) methodology. The proposed approach is based on the robust asymptotically stable invariant ellipsoid methodology, which employs linear matrix inequalities (LMIs) to calculate a collection of invariant state feedback laws associated with a sequence of nested invariant stable ellipsoids. Simulation results indicate a significant reduction in computational burden with the offline RMPC approach compared to online implementation, while effectively tracking the desired wheel slip reference values and system constraints. Moreover, the offline RMPC design aligns well with the online MPC design and verifies its effectiveness in practice.

Determination of the dynamic characteristics of locomotive drive systems under re-adhesion conditions using wheel slip controller

Determination of the dynamic characteristics of locomotive drive systems under re-adhesion conditions using wheel slip controller

Brake-by-Wire System Redundancy Concept for the Double Point of Failure Scenario

<div>Brake-by-wire (BbW) systems are one key technology in modern vehicles. Due to their great potential in the areas of energy efficiency and automated driving, they receive more and more attention nowadays. However, increased complexity and reliance on electric and electrical components in BbW systems bring about new challenges. This applies in particular to the fault tolerance of the brake system. Since drivers cannot form a fallback layer of braking functions due to the mechanical decoupling of the brake pedal, known BbW concepts provide a redundant system layer. However, driving is significantly limited in the event of a failure in the BbW system and is only possible under certain restrictions. The reason for that is a further possible failure (double point of failure scenario), which can result in a significant loss of braking performance.</div> <div>To improve the availability level of the braking functions, a principally new redundancy concept for the double point of failure scenario is presented. This allows for a less restricted driving operation when the BbW system is subject to failures. For this purpose, a central electric motor (CEM) and modified electronic parking brake (EPB) actuators are used on the front axle of a vehicle to form a separate redundancy layer. Strategies for deceleration and wheel slip control are developed for the individual actuators as well as for their simultaneous operation. The performance of the different brake modes is evaluated in road tests. The analysis shows that especially the combined operating mode of the CEM and EPB leads to high deceleration levels and robust operation in low road friction conditions.</div>

Predictive Anti-Jerk and Traction Control for V2X Connected Electric Vehicles With Central Motor and Open Differential

V2X connectivity and powertrain electrification are emerging trends in the automotive sector, which enable the implementation of new control solutions. Most of the production electric vehicles have centralized powertrain architectures consisting of a single central on-board motor, a single-speed transmission, an open differential, half-shafts, and constant velocity joints. The torsional drivetrain dynamics and wheel dynamics are influenced by the open differential, especially in split- scenarios, i.e., with different tire-road friction coefficients on the two wheels of the same axle, and are attenuated by the so-called anti-jerk controllers. Although a rather extensive literature discusses traction control formulations for individual wheel slip control, there is a knowledge gap on: a) model based traction controllers for centralized powertrains; and b) traction controllers using the preview of the expected tire-road friction condition ahead, e.g., obtained through V2X, for enhancing the wheel slip tracking performance. This study presents nonlinear model predictive control formulations for traction control and anti-jerk control in electric powertrains with central motor and open differential, and benefitting from the preview of the tire-road friction level. The simulation results in straight line and cornering conditions, obtained with an experimentally validated vehicle model, as well as the proof-of-concept experiments on an electric quadricycle prototype, highlight the benefits of the novel controllers.

Instantaneous optimum wheel slip estimation of anti-lock braking system based on extremum seeking algorithm and fuzzy method

The anti-lock braking system (ABS) adjusts the longitudinal wheel slip at its optimum value to achieve the maximum braking forces. The highest braking force capacity happens at a specific slip value and depends on the friction coefficient between the tire and the road, vertical tire force, and vehicle speed. Hence, using a fixed value for the desired longitudinal slip is not appropriate. To solve this problem, the instantaneous optimum wheel slip is determined via the sliding mode-based extremum seeking algorithm in combination with the fuzzy method to achieve the maximum possible brake deceleration. Then the nonlinear prediction-based controller is designed to find the braking torque by adjusting the longitudinal slip in the calculated desired value. In addition, a nonlinear half-vehicle model considering pitch dynamics is developed and validated with the Carsim software. The main contribution of the present work involves the combination of the optimal nonlinear predictive control method with the fuzzy extremum seeking algorithm to design a wheel slip controller. Additionally, the pitch dynamics has been taken into account in the design of the control system. The performance of the designed control system is investigated through conducted simulations in Matlab/Simulink software environment. The obtained results show an enhancement in the braking performance along with a considerable reduction in the stopping distance.

Balancing-Prioritized Anti-Slip Control of a Two-Wheeled Inverted Pendulum Robot Vehicle on Low-Frictional Surfaces with an Acceleration Slip Indicator

When a two-wheeled inverted pendulum (TWIP) robot vehicle travels on slippery roads, the occurrence of wheel slip extremely threatens its postural stability owing to the loss of wheel traction. If a severe wheel slip happens between the driving wheels and contact surfaces, no control techniques can guarantee the driving performance and stability of the TWIP robots in the absence of an extra wheel slip control strategy. In this paper, a TWIP-compatible countermeasure against the wheel slip phenomena is investigated for enhancing the reliability of the vehicle and the robustness of the motion control performance on low-frictional surfaces. To this end, we propose a balancing-prioritized anti-slip control method based on the maximum transmissible torque estimation, which is activated only when a wheel slip is detected by the acceleration slip indicator utilizing accessible data from the IMU and wheel encoders. It is proved that the TWIP vehicles applying the proposed method can successfully cope with low frictional surfaces while maintaining postural stability. Finally, comparative simulations and experiments demonstrate the effectiveness and feasibility of the proposed scheme.

Novel ARC-Fuzzy Coordinated Automatic Tracking Control of Four-Wheeled Mobile Robot

Four-wheeled, individual-driven, nonholonomic structured mobile robots are widely used in industries for automated work, inspection and exploration purposes. The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure. The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots. However, there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion. As a result, the mobile robot has limited performance, such as chattering during curved movement. In this research work, a three-tiered adaptive robust control with fuzzy parameter estimation, including dynamic modeling, direct torque control and wheel slip control is proposed. Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller (ARC) parameters and tracking the trajectories with less tracking error as well as high tracking accuracy. This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique. Our suggested approach outperforms the existing control methods such as Fuzzy, proportional–integral–derivative (PID) and adaptive robust controller with discrete projection (ARC–DP). The experimental results show that the scheduled performance index decreases by 2.77% and 4.76%. All the experimental simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.

Piecewise integral-proportional wheel slip control for an in-wheel motor driven vehicle

Because the wheel torque of an in-wheel motor driven vehicle (IMDV) is controllable independently and has a quick motor response, vehicle dynamics control performance is excellent, especially in wheel slip control. In this paper, a novel wheel slip controller for based on torque vectoring control scheme IMDVs is proposed. The upper limit torque is regulated by slip control torque, which changes the effective operational range of the motor. Torque coordination is naturally executed by re-distribution, with no additional rules. Further, the piecewise integral-proportional control strategy for slip regulation is introduced to reduce dependence on model fidelity. The integral control mitigates the slip phenomenon quickly through withdrawing wheel torque step by step, and proportional control recovers the driving force with the wheel remaining in the stable region. These two stages are independent so that the control parameters can be tuned individually. A stability control analysis is also presented. Moreover, detached and split roads are chosen as simulation scenarios, with performance comparable to the traditional PI method, and real vehicle tests are performed to verify the effectiveness and feasibility of the proposed method.

Amelioration of Energy Dissipation Through Robotic Evacuation Process of Solid Bulk Materials: Effectiveness of Wheel Slip Control System

Amelioration of Energy Dissipation Through Robotic Evacuation Process of Solid Bulk Materials: Effectiveness of Wheel Slip Control System

Acceleration slip regulation by electric motor torque of battery electric vehicle with nonlinear model predictive control approach

Step increase of electric motor torque results in wheel slip during the acceleration of battery electric vehicle (BEV), making vehicle body instability paramount. This is particularly challenging for regulating the torque of electric motor to keep stability in the process of acceleration, for which regulating the wheel slip to an ideal set-point is difficult for the central driving powertrain that adopts one electric motor to drive both left and right wheels by a differential. While much of the research on acceleration slip regulation has focused on solving the wheel anti-slip of internal combustion powertrain by electronic stability programme, comparatively little is known about the wheel slip control by electric motor torque of the central driving powertrain that is the most common style of driveline in the market of BEV currently. Here we discuss a series of studies on the acceleration slip regulation by electric motor torque that, collectively, design an approach of how the nonlinear model predictive controller based on a novel driving dynamics model regulates the wheel slip to an ideal set-point from the ideal slip ratio curve. Testing and validating this approach embedded into vehicle control unit are carried out in a BEV to fully realise the wheel slip control by electric motor torque during the acceleration.

A wheel slip control scheme for aeronautical braking applications based on neural network estimation

Due to safety reasons, anti-skid braking control strategies in aircraft can rely only on sensors that are integral to the landing gear, and these currently are limited to wheel rotational speed and braking pressure. Thus, up to now anti-lock-braking systems (ABS) are developed as threshold-based algorithms that regulate the wheel deceleration. However, as it is known from the Automotive field, slip control offers superior closed-loop properties and robustness, paired with a much easier and time-saving tuning phase. This work aims at investigating first of all if slip control does indeed offer the same performance advancement also in the aeronautical braking context and, secondly, whether the wheel slip can be effectively estimated and employed in a closed-loop braking controller without the need of additional sensors on the landing gear. To do this, we propose a wheel slip control scheme where a data-driven approach using a neural network architecture is used to solve the problem of wheel slip estimation. The proposed control scheme is tested within a very realistic simulation setting, capturing all the non-linear effects peculiar of the aeronautical context, and compared with a standard deceleration-based ABS in multiple braking maneuvers carried out within a large operational envelope. The results show that superior performance and robustness can indeed be achieved with the proposed control approach, paving the way for the adoption of wheel slip abs strategies also for aircraft braking.

Wheel Slip Control Applied to an Electric Tractor for Improving Tractive Efficiency and Reducing Energy Consumption.

This work presents an automatic slip control solution applied to a two-wheel-drive (2WD) electric tractor. Considering that the slip can be maintained within a specific range that depends on the type of soil, it is possible to increase the tractive efficiency of the electric vehicle (EV). The control system can be easily designed considering only the longitudinal dynamics of the tractor while using simple proportional-integral (PI) controllers to drive the inverters associated with the rear wheels. The introduced solution is tested on an experimental electric tractor prototype traveling on firm soil considering case studies in which the slip control is enabled and disabled. The acquired results demonstrate that the slip control allows for obtaining a more stable performance and reduced energy consumption.

Design of an NSMCR Based Controller for All-Electric Aircraft Anti-Skid Braking System

In this paper, a relative threshold event-triggered based novel complementary sliding mode control (NSMCR) algorithm of all-electric aircraft (AEA) anti-skid braking system (ABS) is proposed to guarantee the braking stability and tracking precision of reference wheel slip control. First, a model of the braking system is established in strict-feedback form. Then a virtual controller with a nonlinear control algorithm is proposed to address the problem of constraint control regarding wheel slip rate with asymptotical stability. Next, a novel approaching law-based complementary sliding mode controller is developed to keep track of braking pressure. Moreover, the robust adaptive law is designed to estimate the uncertainties of the braking systems online to alleviate the chattering problem of the braking pressure controller. Additionally, to reduce the network communication and actuator wear of AEA-ABS, a relative threshold event trigger mechanism is proposed to transmit the output of NSMC in demand. The simulation results under various algorithms regarding three types of runway indicate that the proposed algorithms can improve the performance of braking control. In addition, the hardware-in-the-loop (HIL) experimental results prove that the proposed methods are practical for real-time applications.

Acceleration‐based wheel slip control realized with decentralised electric drivetrain systems

Traction control is one of the most important functions in vehicle drivetrain systems. When a vehicle is driven on a low-friction road surface, loss of traction force can cause the driven wheels to spin. This reduces vehicle acceleration performance and can even cause the driver to lose control of the vehicle. The high bandwidth of electric machine control in electric vehicles gives more possibilities to regulate driving torque on wheels and prevent wheel spin. An acceleration-based wheel slip control is designed and investigated. Compared to traditional slip-based traction control, the proposed method does not depend on the estimation of the vehicle speed and only relies on the driven wheel rotational acceleration. The control method is verified using the simulation of an electric vehicle with a decentralised electric drivetrain system. The vehicle and the electric drive are modelled in CarMaker and PLECS, respectively. The simulation results show that the proposed method is able to prevent the driven wheel from spinning when the vehicle is accelerated on an ice road. In addition, the control is fast enough and requires only half a second to reduce the wheel acceleration to a normal range.