Anti-lock Braking System Control Research Articles

Design of ABS sliding mode control system for in-wheel motor vehicle based on road identification

Aiming at the problem that the current Anti-lock Braking System (ABS) control algorithm can not make full use of the ground friction to complete the braking when emergency braking on complex roads, an ABS sliding mode control method based on road surface identification is proposed. Combined with the in-wheel motor of in-wheel motor electric vehicle, a coordinated control method of motor regenerative braking and mechanical friction braking is designed. Based on the neural network control method, the road friction coefficient is estimated to realize the identification of typical roads and dynamically obtain the optimal slip ratio of different roads. The ABS sliding mode controler is designed with the optimal slip ratio and the actual slip ratio as input, and the saturation function is used to replace the symbol function in the traditional sliding mode control to weaken the chattering problem, and then the ABS controller is designed. The research results show that compared with the traditional ABS sliding mode controller, the designed ABS neural network sliding mode controller has the following advantages: 1. Through the identification of tire-road friction coefficient by neural network, the real-time performance and road adaptability of ABS controller are improved; 2. When the braking simulation is carried out at a given speed, the braking time is reduced by about 1.03 % and the braking distance is shortened by about 1.01%; 3. The identification of tire-road friction coefficient is realized, which weakens the chattering problem of traditional sliding mode control and improves the stability and robustness of ABS controller.

Anti-lock braking system control design using a non-linear multi-body dynamic model for a two wheeled vehicle

This paper investigates the design of an Antilock Braking System for a Two Wheeled Vehicle using a non-linear multi-body dynamic model developed by an approach widely used in robotics. The Antilock Braking System is controlled using Matlab/Simulink by applying the Bang-Bang, Proportional-Integral-Derivative and Fuzzy Logic controllers in order to set the longitudinal slip to a desired value. The developed model is used to study the braking performances of a Two Wheeled Vehicle in a straight-line maneuver under different road conditions: dry, wet and a transition between both. The simulation results indicate that the non-linear dynamic model can effectively simulate the behavior of the Two Wheeled Vehicle under emergency braking conditions and with the different types of controllers. The braking performance of the Two Wheeled Vehicle with Antilock Braking System was improved by decreasing the stopping distance, avoiding wheel lockup and therefore contributes to ensure the vehicle control and stability and to reduce the risk of falling. Also, it can be seen through comparative analysis that the Fuzzy logic is one of the most efficient controllers that improve the braking safety.

A Fault Diagnosis and Fault-tolerant Anti-lock Brake System Control for Actuator Stuck Failures in Braking System in Autonomous Vehicles

A Fault Diagnosis and Fault-tolerant Anti-lock Brake System Control for Actuator Stuck Failures in Braking System in Autonomous Vehicles

Nonlinear wheel-slip dynamics of battery electric vehicle for anti-lock brake system control by traction motor

Nonlinear wheel-slip dynamics of battery electric vehicle for anti-lock brake system control by traction motor

COMPARATIVE STUDY OF DIFFERENT TYPES OF CONTROLLERS IN AN ANTI-LOCK BRAKING SYSTEM USING MATLAB/SIMULINK

Anti-lock Braking System is one of the vital safety features in modern cars and trucks that can prevent the wheels from locking while the brakes are applied in the moving vehicles. During a braking condition, speed sensors in ABS send signals to the Anti-lock Braking System control unit to estimate the wheel slip ratio, and if the ratio is different from the desired value, the control unit will send a message to the braking actuator to control braking torque. In this paper, the dynamics and subsystems of the Anti-lock Braking System are presented and a model of the Anti-lock Braking System is developed in MATLAB/SIMULINK software. Different types of controllers, including the Bang-Bang controller, proportional-integral, proportional derivative, and proportional integral derivative controllers, are integrated into the model to investigate the effects of controlling strategies on the stopping distance, vehicle velocity, slip ratio, and braking torque. The simulation results show that the proportional derivative and proportional integral derivative controllers provide the shortest stopping distances and stopping times as compared with Bang-Bang and proportional-integral controllers on different types of roads. Furthermore, it also observed that the slip ratio during braking is kept similar to the desired value (20%) with the proportional derivative and proportional integral derivative controllers while it fluctuates between 10% and 30% for BangBang and proportional-integral controllers. The trend of the braking torque is also similar to the slip ratio. The model can be used to predict the braking performance of the Anti-lock Braking System under different conditions.

Design and Assessment of an Anti-lock Braking System Controller

"The anti-lock braking system is a safety equipment that prevents the vehicle wheels from locking up under emergency, panic, or harsh braking conditions, ensuring steering control during braking and reducing braking distance. This system is studied by automotive engineers for performance comparisons and for determining optimal control methods. For this reason, this paper presents a method to mathematically model the anti-lock braking system. The obtained model is afterwards used inside a Simulink simulation to investigate the results with and without the anti-lock braking system and to propose a three-position regulator instead of the generally used bang-bang controller. The simulation results show the improvement of the vehicle braking time and braking distance."

Blended Regenerative Anti-Lock Braking System and Electronic Wedge Brake Coordinate Control Ensuring Maximal Energy Recovery and Stability of All-Wheel-Motor-Drive Electric Vehicles

Blended Regenerative Anti-Lock Braking System and Electronic Wedge Brake Coordinate Control Ensuring Maximal Energy Recovery and Stability of All-Wheel-Motor-Drive Electric Vehicles

Dynamic Modeling and Control of Antilock Braking System for Four Wheel Vehicles

Nonlinear dynamics of longitudinal and lateral traction of ground vehicles has been investigated in this work and later on used these dynamics on usefulness of brake steer system which uses differential brakes for small steering interventions to keep the vehicle on line. A controller design for Antilock braking (ABS) of a four wheel vehicle whose two rear wheels are braking and front wheels are non-braking is proposed. The major part of our work is tuning to the suitable braking force for two rear wheels and minimizing the stopping distance in short time while front wheels are not braking then finding steer of vehicle by applying different forces on rear right and rear left wheels. These two different forces produce rotational torque in vehicle . These are known as differential brakes which are commonly used to steer the vehicle and its lateral position. Stability has been discussed. Both lateral and longitudinal control motion of the vehicle are simulated. The proposed control scheme is successfully tested in MATLAB simulation.

Redundancy Control of Anti-lock Braking System Based on Electro-hydraulic Braking System

Redundancy Control of Anti-lock Braking System Based on Electro-hydraulic Braking System

Performance of Anti-Lock Braking Systems Based on Adaptive and Intelligent Control Methodologies

Automobiles of today must constantly change their speeds in reaction to changing road and traffic circumstances as the pace and density of road traffic increases. In sophisticated automobiles, the Anti-lock Braking System (ABS) is a vehicle safety system that enhances the vehicle's stability and steering capabilities by varying the torque to maintain the slip ratio at a safe level. This paper analyzes the performance of classical control, model reference adaptive control (MRAC), and intelligent control for controlling the (ABS). The ABS controller's goal is to keep the wheel slip ratio, which includes nonlinearities, parametric uncertainties, and disturbances as close to an optimal slip value as possible. This will decrease the stopping distance and guarantee safe vehicle operation during braking. A Bang-bang controller, PID, PID based Model Reference Adaptive Control (PID-MRAD), Fuzzy Logic Control (FLC), and Adaptive Neuro-Fuzzy Inference System (ANFIS) controller are used to control the vehicle model. The car was tested on a dry asphalt and ice road with only straight-line braking. Based on slip ratio, vehicle speed, angular velocity, and stopping time, comparisons are performed between all control strategies. To analyze braking characteristics, the simulation changes the road surface condition, vehicle weight, and control methods. The simulation results revealed that our objectives were met. The simulation results clearly show that the ANFIS provides more flexibility and improves system-tracking precision in control action compared to the Bang-bang, PID, PID-MRAC, and FLC.

Research on Direct Braking Force Estimation and Control Strategy Using Tire Inverse Model

With the rapid development of computer control and vehicle intelligence technology, speed and safety of vehicles have been greatly improved, and the requirements for vehicle control performance are getting higher and higher. For the direct braking force control, in the process of deceleration, a fast braking response can be obtained, which improves the braking performance and vehicle safety. This paper concentrates on direct braking force estimation and control strategy using a tire inverse model based on the antilock braking system, and to solve the problem of the existing ABS system is mainly antilock braking function, no direct braking force control function. Taking magic formula model for reference inverse model, the critical parameters under different road surfaces are obtained according to experience data. Then, the desired slip ratio corresponding to braking force can be obtained via fast tire inverse model look-up table method. The tyre friction self-adjustment decision making is obtained using the tire inverse model method. A direct braking force antilock braking system (DBF-ABS) controller is built using the nonsingular fast terminal sliding mode method. The simulation results indicated that the control strategy has adaptability and stability to the change of road conditions.

An End-of-Line Test System for Pneumatic ABS Controllers in Commercial Vehicles

To remedy the defects of conventional pneumatic ABS (anti-lock Braking system) controller testing equipment for commercial vehicles, such as low efficiency and difficult testing condition configurations, a workflow was proposed based on the unit integration test mode. The relationship among the operation logic of the ABS valves, test conditions, and wheel speed was derived through the simulation of a multi-condition configuration. Then, a wheel speed simulation model was set up by taking the test conditions as inputs, and it was implanted into an embedded control unit. Next, the hardware module and the underlying drivers as well as an application algorithm for the application layer were designed. A prototype of the EOL (end-of-line) test system was built. The test results show that the prototype can not only achieve a rapid test condition configuration and accurate fault location but that it can also meet the requirements for test efficiency.

Longitudinal Dynamic Modeling and Driving Cycle Tracking Control of an Electric-Driven Vehicle by Means of MATLAB/Simulink/Simscape

MATLAB, Simulink, and Simscape are market-leading products in Model-Based Design (MBD). Applying acausal and causal modeling methods to model the physical plant and control algorithms of mechatronic systems results in high-fidelity virtual prototype models that can be used for Model-in-Loop (MiL) development. In this paper, an electric-driven vehicle is modeled, which can execute various driving cycle inputs. PID controllers are used in order to get the appropriate plant inputs. Idealized anti-lock braking system (ABS) and traction control system (TCS) algorithms provide robustness when the driving cycle input is near-infeasible. The control algorithm is validated in the cases of feasible and infeasible driving cycle inputs.

Roll dynamics of long combination semi-trailers with steerable axles

An assessment of the dynamic performance of long combination vehicles (LCV) with steerable axles was undertaken to facilitate the regulation of LCVs for wider use on Canadian roads. A base dry box van A-train LCV and four steered combinations with different steerable axle mechanisms on the trailer are modelled using TruckSim. TruckSim's driver logic is augmented through an optimised controller to more accurately capture the driver's decision-making in response to the LCV dynamics. Anti-lock braking system (ABS) and traction control mechanisms are added to compensate for the reduced stability caused by improving the manoeuvrability. The models are run through highspeed lane change and turn simulations, the primary manoeuvres for the assessment of roll dynamics of LCVs. The configurations are compared in terms of standard performance parameters: static roll threshold, rearward amplification (RWA), load transfer ratio (LTR), highspeed off-tracking and transient off-tracking. All mechanisms are shown to satisfy standard stability requirements.

Self Tuning PID Control of Antilock Braking System using Electronic Wedge Brake

This paper describes the design of an antilock braking system (ABS) control for a passenger vehicle that employs an electronic wedge brake (EWB). The system is based on a two-degree-of-freedom (2-DOF) vehicle dynamic traction model, with the EWB acting as the brake actuator. The developed control structure, known as the Self-Tuning PID controller, is made up of a proportional-integral-derivative (PID) controller that serves as the main feedback loop control and a fuzzy supervisory system that serves as a tuner for the PID controller gains. This control structure is generated through two structures, namely FPID and SFPID, where the difference between these two structures is based on the fuzzy input used. An ABS-based PID controller and a fuzzy fractional PID controller developed in previous works were used as the benchmark, as well as the testing method, to evaluate the effectiveness of the controller structure. According to the results of the tests, the performance of the SFPID controller is better than that of other PID and FPID controllers, being 10% and 1% faster in terms of stopping time, 8% and 1% shorter in terms of stopping distance, 9% and 1% faster in terms of settling time, and 40% and 5% more efficient in reaching the target slip, respectively.

A control strategy for efficient slip ratio regulation of a pneumatic brake system for commercial vehicles

This paper presents a control strategy for efficient slip ratio regulation of a pneumatic brake system for commercial vehicles. A model-based estimator for brake pressure estimation has been developed. The braking torque applied to the wheel has been computed using the estimated brake pressure for the control of the wheel slip both in braking and traction situations. The vehicle velocity and wheel slip ratio estimation algorithms have been designed using only wheel speed sensors. The proposed slip regulation algorithm has also been successfully implemented for the antilock braking system (ABS) and traction control system (TCS). In ABS, the slip ratio and wheel acceleration are stabilized by a limit cycle control of the braking pressure. The TCS has been implemented by combining engine torque control and pneumatic brake pressure control. The brake controller is based on the valve switched control that incorporates the wheel dynamics and valve on/off characteristics. The ABS and TCS algorithms are integrated into the slip regulation algorithm to reduce the computation load of an Electrical Control Unit (ECU). Four-wheel independent slip monitoring and slip ratio control algorithms have been implemented on the ECU, and their performance has been investigated via both computer simulations and vehicle tests. Both results show that the proposed algorithms enhance the acceleration and braking performance without vehicle acceleration information. Moreover, the proposed split-mu strategy has improved the lateral stability during braking, and the acceleration performance during accelerating on the split-mu road. It has been shown via vehicle tests that, compared to the reference commercial algorithm, the braking distance was reduced by more than 4% on the split-mu and low-mu roads, and the acceleration performance was improved by 7.9% on the split-mu road.

On the Security of Networked Control Systems in Smart Vehicle and Its Adaptive Cruise Control

With the benefits of Internet of Vehicles (IoV) paradigm, come along unprecedented security challenges. Among many applications of inter-connected systems, vehicular networks and smart cars are examples that are already rolled out. Smart vehicles not only have networks connecting their internal components e.g. via Controller Area Network (CAN) bus, but also are connected to the outside world through road side units and other vehicles. In some cases, the internal and external network packets pass through the same hardware and are merely isolated by software defined rules. Any misconfiguration opens a window for the hackers to intrude into vehicles’ internal components e.g. central lock system, Engine Control Unit (ECU), Anti-lock Braking System (ABS) or Adaptive Cruise Control (ACC) system. Compromise of any of these can lead to disastrous outcomes. In this paper, we study the security of smart vehicles’ adaptive cruise control systems in the presence of covert attacks. We define two covert/stealth attacks in the context of cruise control and propose a novel intrusion detection and compensation method to disclose and respond to such attacks. More precisely, we focus on the covert cyber attacks that compromise the integrity of cruise controller and employ a neural network identifier in the IDS engine to estimate the system output dynamically and compare it against the ACC output. If any anomaly is detected, an embedded substitute controller kicks in and takes over the control. We conducted extensive experiments in MATLAB to evaluate the effectiveness of the proposed scheme in a simulated environment.

Constrained Nonlinear Estimation of Road Friction Coefficient and Wheel Slip for Control of Anti-Lock Braking System

Constrained Nonlinear Estimation of Road Friction Coefficient and Wheel Slip for Control of Anti-Lock Braking System

Blending Control of Trolleybus Traction and Brake Drives to Enhance Braking Efficiency of Vehicle

The widespread use of green public transport is a priority strategy to reduce a congestion and pollution from road traffic in many cities. The trolleybus is a type of urban public electric transport, which is considered as a promising tool for increasing the efficiency of public transport and achieving the goals of sustainable development and quality of life in the city. The operation control of service brake system and secondary brake system (braking torque of traction electric motor) is realized with the help of one pedal in the trolleybus. Thus, there are modes of joint operation for these systems during the braking process. The author has focused his main attention on the development of an algorithm for blending control of the traction electric motor and the anti-lock braking system to enhance the overall braking efficiency of a vehicle. For this purpose, a mathematical model of the trolleybus braking dynamics has been developed. Bench and road tests have been carried out on various road surfaces to determine parameters of vehicle braking efficiency and to validate the developed mathematical model. The corresponding experimental data were used to analyse the efficiency of the proposed strategy for combining the blending control of traction electric motor and anti-lock braking system of the trolleybus. As a result, the efficiency of the proposed control algorithm has been confirmed, which provides the required braking efficiency and high braking stability of the vehicle.

Adaptive Estimation of Vehicle Velocity From Updated Dynamic Model for Control of Anti-Lock Braking System

The main challenge for designing the automotive control systems like the anti-lock braking system (ABS) is to access a reliable model because of uncertainties and variations in vehicle dynamics and tire forces. In this article, the initial dynamic model of the vehicle braking system is updated at each instant by estimation of model compensatory terms using a novel prediction approach. The proposed estimation method uses the global navigation satellite system (GNSS) as a reference to adaptively estimate the vehicle velocity with high frequency in the presence of variable bias of acceleration sensor. The proposed estimation algorithm is mathematically analyzed and experimentally evaluated to show its high accuracy obtained by the adaptive tuning of parameters. Accordingly, a nonlinear controller based on the estimated dynamic model is designed to prevent the tire from being locked by tracking the desired slip. The designed control system is tested within the CarSim software as a virtual vehicle experiment platform. The obtained results reveal that the designed model-based control system remarkably improves the braking performance compared with the conventional sensor-based ABS controllers.