ABS + active suspension control via sliding mode and linear geometric methods for disturbance attenuation

Hierarchical [formula omitted] fuzzy-neural control of anti-lock braking system and active suspension in a vehicle

<div class="htmlview paragraph">Various systems have been introduced recently in the automotive industry to improve the safety, ride and handling qualities of passenger vehicles, such as anti-lock braking system (ABS), active suspension system, four wheel steering system, traction control system, etc. Although each system has been shown to impose positive effects on the performance of a vehicle, the benefits of integrating various systems is yet to be determined.</div> <div class="htmlview paragraph">A feasibility study was conducted of a new non-linear control law for integration of anti-lock braking system and active suspension system. The control law is based on the use of a candidate Lyapunov function. Lyapunov stability theorem is applied to synthesize the control law and the adaptation law necessary to estimate the unknown parameters of the vehicle/road system. The proposed MIMO non-linear control strategy can maintain desired values of various variables while estimating the unknown parameters of the system. The desired values for various states are obtained by solving an optimal control problem for a simple vehicle model. Simulations of braking maneuvers were conducted using a non-linear vehicle model together with a non-linear tire model. The preliminary study indicates that the controller designed is capable of maintaining desired front and rear wheel longitudinal slip values as well as generating sufficient suspension forces to minimize sprung mass vibrations.</div>

Abstract: There are patents that consider some interesting characteristics as are [1] and [2] related with the pneumatic and in [3] the electrical elements for the rapid braking, in this paper, an uniformly stable observer for tire/road friction model estimation during braking process is proposed. In this observer the angular speed of the tire is taken as the output and it is used to estimate the internal friction state, the linear speed of the tire and the relative velocity of the vehicle [4]. It is proven that the state error of the observer applied to the nonlinear model is uniformly stable. The observer proposed is based on the solution of a Linear Matrix Inequality (LMI) equation [5]. A simulation shows the effectiveness of the suggested observer. Keywords: Braking process, observer, longitudinal dynamics. INTRODUCTION The tire/road friction phenomenon plays an important role in vehicle safety and handling. Researchers are often trying to improve the safety, driving comfort and traffic circulation. They also are trying to reduce the environmental pollution associated with vehicles. In this days, many con-trollers are available to improve safety and vehicle handling including anti-lock brake systems (ABS), traction control systems (TSC), adaptive intelligent cruise control, active yaw control systems and active suspension systems. How-ever these control systems only perform to their potential if they have access to the accurate information about the vehicle behavior in real time. Some authors have proposed the equations to model the dynamic behavior of the braking in a car. Two equations are related with the simplified motions of a wheel in a car are defined in [6-8], and other two equation are the Lumped LuGre friction model defined in [7-11]. In [12], they provide an excellent material for both service brake an parking brake. In [13], a device for selectively controlling and varying a frictional force level at an interface between two bodies was proposed. In [1], a pneumatic tire containing a combination plasticizer was proposed. In [2], a pneumatic tire with component containing asphaltene was proposed. In [4], improved methods and systems for controlling hydraulically or electrically actuated anti-lock brake systems (ABS) was proposed. In [3], the electrical engineering to processes for rapid braking was proposed.

During blueberry picking operations, changes in the blueberry harvester’s body posture (BHBP) caused by undulating farmland surfaces significantly affect the operational stability of the harvesting device. To mitigate these effects, an active suspension (AS) control system was developed. First, considering the coherence and time lag of the four-wheel tracks, the filtered white noise method was chosen to generate road excitations. Subsequently, the virtual prototype model of the blueberry harvester (BH) was built in ADAMS with the nonlinear properties of the passive suspension. A fuzzy proportion integral differential (PID) control algorithm and decoupled control strategy were employed to design the AS control system. Finally, ADAMS-MATLAB co-simulations and field tests were conducted. The results indicate that the measured farmland road profile conforms to standard D-level road excitations according to ISO8608, and the co-simulation model accurately predicts the BH’s dynamic response. Under AS control, the vertical acceleration, pitch acceleration, and roll acceleration of the BH decreased by 38.52%, 37.39%, and 34.29%, respectively, during simulations compared to the passive suspension. In field tests, these reductions were 36.51%, 33.84%, and 30.21%, respectively. The AS control system proposed in this study significantly improves the stability of the BH under farmland road excitation, effectively mitigating equipment impacts and wear caused by machine jolts while enhancing harvesting performance. This research addresses the gap in applying AS technology within the field of harvesting machinery, offering a novel technical approach for the development of vehicle control systems for harvesting machinery targeting blueberries and other shrub crops. It holds considerable theoretical value and practical significance.

The aim of this research is to apply vehicle dynamics control systems to mitigate the vehicle collision and study the effects of these systems on the kinematic behaviour of the vehicle’s occupant. An unique three-degree-of-freedom vehicle dynamics/crash mathematical model and a simplified lumped mass occupant model are developed. The first model is used to define the vehicle body crash parameters and it integrates a vehicle dynamics model with a vehicle front-end structure model. In this model, the anti-lock braking system and active suspension control system are co-simulated, and its associated equations of motion are developed. The second model aims to predict the effect of vehicle dynamics control systems on the kinematics of the occupant. The Lagrange’s equations are used to solve that model due to the complexity of the obtained equations of motion. It is shown from the numerical simulations that the vehicle dynamics/crash response and occupant behaviour can be captured and analysed quickly and accurately. Furthermore, it is shown that the vehicle dynamics control systems can affect the crash characteristics positively and the occupant behaviour is improved.

The aim of this paper is to improve vehicle crash worthiness using vehicle dynamics control systems (VDCS) integrated with an extendable front-end structure (extendable bumper). The work carried out in this paper includes developing and analyzing a new vehicle dynamics/crash mathematical model in case of vehicle-to-vehicle full frontal impact. This model integrates a vehicle dynamics model with the vehicle’s front-end structure to define the vehicle body crash kinematic parameters. In this model, the anti-lock braking system (ABS) and the active suspension control system (ASC) are co-simulated, and its associated equations of motion are developed and solved using Incremental Harmonic Balance Method (IHBM). An Under Pitch Control (UPC) technique is used to minimize the deformation zone, pitch angle and its acceleration. The simulations show considerable improvements using UPC along side ABS with and without the extendable bumper (EB), which produces additional significant improvements for both vehicle boy acceleration and intrusion.

Introduction (statement of the problem and relevance). In accordance to the current standards the requirements were assessed: for the braking process efficiency of M1vehicles category using an antilock braking system (ABS) and the combined possibility control of two actuators - electric machines installed in the vehicle driving wheels as well as the electro-hydraulic modulation pressure unit in the hydraulic circuit of the working brake cylinders.The purpose of the study was to evaluate the effectiveness of the newly developed ABS algorithm in accordance with current standards and additional requirements.Methodology and research methods. The braking process computer simulation of a M1 vehicle category equipped with four electric motors and an electro-hydraulic braking system was carried out. As a result of calculations, the obtained braking parameters were to be compared and evaluate according to the requirements of UN Regulation No. 13H, as well as evaluate the braking efficiency parameters.Scientific novelty and results. The effectiveness of the developed control algorithm for the ABS actuators (electro-hydraulic unit and electric machines in the drive wheels) has been proven in terms of meeting the requirements of UN Regulation No. 13H. Studies showed an efficiency improvement of the ABS operating due to the proposed algorithm, when compared to foreign-produced analogues.The practical significance of the work is the proof of the developed algorithm efficiency for M1 electric vehicles category.

Active suspension have not been used widely due to its magnificent energy consuming. A kind of electromechanical energy-regenerative suspension is proposed in this paper. Suspension dynamic equations are modeled by MATLAB/Simulink. In order to get an optimal performance of suspension, several indices are discussed in this paper with three control curve on a motor MAP diagram. The results indicated that optimal control strategy depends on subjective object; As for energy recovery, performance contour is the best choice. If the objective is the balance of all indices, middle torque curve is the ideal choose. Also an active control suspension and energy-regenerative suspension are compared in this paper. It can be concluded that the active control suspension can obtain good dynamic effects but consume considerable energy.

Anti-lock and also Anti-slip braking system controller designed for stability enhancement of vehicle during braking and turning circumstances is presented. Using available signals, a novel structure is proposed for vehicle stability improvement encountering critical braking conditions such as braking on slippery or μ-split road surfaces. In conventional vehicles, undesired lane changes may occur due to equal dispatch of braking torques to all wheels simultaneously. Also, intensive pressure on brake pedal can bring about wheels lockup which results in vehicle instability and undesired lane changes. The Anti-Lock Braking System (ALBS) and also Anti-Slip Braking System (ASBS) can serve as a driver assist system in vehicle path correction facing critical driving conditions during braking and turning round on different road surfaces. For these purposes, at first, a reference yaw angle is used for predicting of stable vehicle path. Then, slip of each wheel will be controlled by an Anti-Slip fuzzy controller which has been designed for each wheel. Also, a sliding mode controller has been designed so as to control the yaw angle concerning the yaw error where the yaw error is resulted from the difference between the reference value and actual yaw angle. Then, the difference between the left and the right wheels braking torques is used by the sliding mode controller in order to decrease the yaw error. Considering a model of Three-Degree-of-Freedom for chassis modeling and One-Degree-of-Freedom Dugoff's tire model for each wheel, a series of Matlab/Simulink simulation results will be presented in order to validate the effectiveness of the proposed controller.

Electric vehicles (EVs) have the advantage of using both regenerative braking and mechanical braking to produce the necessary braking torque. Currently, vehicles use Anti-lock Braking Systems (ABS) which provide intermittent braking torque to the vehicle and thereby prevents skidding or slipping of the vehicle by ensuring pure rolling of the wheels. Regenerative braking on the other hand generates the necessary braking torque by converting the kinetic energy of the vehicle to electrical energy via the motor(s). To coordinate both braking systems, the conventional method involves the use of crisp logic controllers that depend on lookup tables containing the data about various aspects of the vehicle such as battery state of charge (SoC), brake pedal input etc., to enable co-operative control of both systems. This paper presents a combined implementation of both braking systems in electric vehicles using separate fuzzy controllers for both ABS and regenerative braking. The control scheme is implemented such that when regenerative braking is not capable of providing enough braking torque, braking will be one by ABS. Two fuzzy logic controllers have been used, one to implement regenerative braking and the other to implement mechanical braking via ABS. If such a control algorithm is used, the driver will not have to manually adjust the level of regenerative braking in the vehicle and such an approach ensures that the braking process of an EV is smooth, safe and efficient. It also reduces the wear and tear of the brake pads thereby extending their life and reducing the cost of maintenance and by extension the total cost of ownership of the vehicle. The results demonstrate that the controllers for both ABS and regenerative braking can coordinate efficiently and reliably to produce proper and safe braking of the vehicle.

Braking system plays a major safety feature in any vehicle; it is considered as one of the key points in safe motoring. The main objective of a good braking system is to provide safe stopping, in addition to the fact that it provides repeatable stopping. Anti-lock Braking System (ABS) is one of the recently developed safety feature used in a vehicle in order to prevent wheels from locking. This article proposes an intelligent adaptive fuzzy logic (FL) genetic algorithm (GA) controller for the Anti-Lock Braking System (ABS) to control the braking of a vehicle by controlling the slip ratio based on quarter car model. The main objective of the proposed controller is to prevent wheels from locking, which is a major safety issue in any braking system for different road conditions. The proposed controller consists of a Fuzzy Logic (FL) Genetic Algorithm (GA) based controller. The Genetic Algorithm is utilized in tuning the membership functions of the Fuzzy logic controller, which is developed to calculate the amount of reduction of the applied torque due to applying brake based on the error of the measured slip ratio signal compared with the desired one. Then a Genetic Algorithm (GA) is utilized in tuning the Fuzzy Logic parameters, which are the center of the Gaussian membership function, and the spread (б). The simulation results of the proposed fuzzy logic genetic algorithm controller are compared with both the results of the Fuzzy logic controller and the PD controller developed in previous work of the authors. The simulation results present many advantages of using Fuzzy Logic Genetic Algorithm based controller over both the Fuzzy Logic and the PD controllers, and the simulation is carried out at different road conditions, namely dry, wet and icy road surface.

This paper focuses on the use of vehicle dynamics control systems (VDCS) to mitigate vehicle collisions in case of offset frontal vehicle-to-vehicle crash scenario. A unique 6-degree-of-freedom vehicle dynamics/crash mathematical model is developed and analyzed in this research. The model is used to define the vehicle body crash parameters by integrating a vehicle dynamics model with a vehicle front-end structure model. In this model, the anti-lock braking system and the active suspension control system are co-simulated with the full car vehicle dynamics model and integrated with the front-end structure. The associated equations of motion of the model are developed and solved numerically. Four different cases of VDCS are investigated in this paper and their associated results are compared with the free rolling case scenario. It is shown from the numerical simulations that the vehicle dynamics/crash response can be captured and analyzed quickly and accurately. Furthermore, it is shown that the VDCS affect the crash characteristics positively.

In this paper, a new crash/dynamics mathematical model is developed to optimise the crashworthiness using vehicle dynamics control systems (VDCS) in case of full frontal vehicle-to-vehicle crash scenario. In this model, the anti-lock braking system (ABS) and the active suspension control system (ASC) are co-simulated with the full car vehicle dynamics model and integrated with the front-end structure. The associated equations of motion of the model are developed and solved numerically. Validation of the vehicle crash structure of the proposed model is achieved to ensure that the modelling of the crumple zone and the dynamic responses are reliable. It is demonstrated from the numerical simulations that the vehicle dynamic responses are captured and analysed and the influence of VDCS is determined accurately. In addition, it is shown that the mathematical model is flexible, useful and can be used in optimisation studies. Furthermore, it is shown that the VDCS affect the crash characteristics positively.

Active suspension can improve vehicle vibrations caused by road excitation. For trucks, the vehicle mass change is usually large, and changes in vehicle mass will affect the control performance of the active suspension. In order to solve the problem of active suspension control performance decreasing due to large changes in vehicle mass, this paper proposes an active suspension control method integrating online mass estimation. This control method is designed based on the mass estimation algorithm of the recursive least squares method with a forgetting factor (FFRLS) and the Linear Quadratic Regulator (LQR) algorithm. A set of feedback control matrices K is obtained according to different vehicle masses. Then, the mass estimation algorithm can estimate the actual vehicle mass in real-time during the vehicle acceleration process. According to the mass estimation value, a corresponding feedback control matrix K is selected from the control matrix set, and K is used as the actual control gain matrix of the current active suspension. With specific simulation cases, the vehicle vibration response is studied by the numerical simulation method. The results of the simulation process have shown that when the vehicle mass changes largely, the suspension dynamic deflection and tire dynamic deformation are significantly reduced while keeping a good vehicle body attitude control effect by using an active suspension controller integrated with online mass estimation. In the random road simulation, suspension dynamic deflection is reduced by 3.26%, and tire dynamic deformation is reduced by 5.91% compared with the original active suspension controller. In the road bump simulation, suspension dynamic deflection and tire dynamic deformation are also significantly reduced. As a consequence, the stability and comfort of the vehicle have been greatly enhanced.

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.