Longitudinal wheel slip control using dynamic neural networks

The control of automotive braking systems performance and a wheel slip is a challenging problem due to nonlinear dynamics of a braking process and a tire–road interaction. When the wheel slip is not between the optimal limits during braking, the desired tire–road friction force cannot be achieved, which influences braking distance, the loss in steerability and maneuverability of the vehicle. In this paper, the new approach, based on dynamic neural networks, has been employed for improving of the longitudinal wheel slip control. This approach is based on dynamic adaptation of the brake actuation pressure, during a braking cycle, according to the identified maximum adhesion coefficient between the wheel and road. The brake actuated pressure was adjusted on the level which provides the optimal longitudinal wheel slip versus the brake actuated pressure selected by a driver, the current vehicle speed, load conditions, the brake interface temperature and the current value of the wheel slip. The dynamic neural network has been used for modeling of a nonlinear functional relationship between the brake actuation pressure and the longitudinal wheel slip during a braking cycle. It provided preconditions for control of the brake actuation pressure based on the wheel slip change.     

Real-time slip-based estimation of maximum tire-road friction coefficient

This paper presents a real-time maximum tire-road friction coefficient estimation method and field test results. The estimator is based on the relationship between the wheel slip ratio and the friction coefficient. An effective tire radius observer and a tire normal force observer have been designed for the computation of the slip ratio from wheel speed and vehicle speed measurements. The effective tire radius observer has been used so that the proposed method works for all driving situations. A tractive force estimator, a brake gain estimator, and a normal force observer have been used for the estimation of the friction coefficient. The proposed estimation method for the maximum tire-road friction coefficient has been implemented using a fifth wheel and typical vehicle sensors such as engine speed, carrier speed, throttle position, and brake pressure sensors.     

一种基于DMA的汽车制动检测台驱动电机控制策略

在利用滚筒反力式制动性能检测台对汽车制动性能进行检测的过程中,由于粘砂滚筒附着系数较高,汽车在制动时,轮胎与滚筒之间会产生很大的摩擦力,容易发生剥胎现象。因此,合理采集汽车制动性能相关参数的同时,及时关停制动性能检测台驱动电机以保证被检车辆的安全,成为汽车制动性能检测的关键技术之一。通过对现有的汽车制动性能检测中各种控制方法优缺点的比较,提出了一种基于DMA的汽车制动检测台驱动电机控制方法,提高了控制的实时性和灵活性,在采集到汽车制动性能相关参数的同时,最大限度地保护了车辆安全。试验结果表明,该控制策略稳定有效,检测精度高,具有较高的实用性。     

Adaptive Vehicle Lateral-Plane Motion Control Using Optimal Tire Friction Forces With Saturation Limits Consideration

This paper presents an adaptive nonlinear control scheme aimed at the improvement of the handling properties of vehicles. The control inputs for steering intervention are the steering angle and wheel torque for each wheel, i.e., two control inputs for each wheel. The control laws are obtained from a nonlinear 7-degree-of-freedom (DOF) vehicle model. A main loop and eight cascade loops are the basic components of the integrated control system. In the main loop, tire friction forces are manipulated with the aim of canceling the nonlinearities in a way that the error dynamics of the feedback linearized system has sufficient degrees of exponential stability; meanwhile, the saturation limits of tires and the bandwidth of the actuators in the inner loops are taken into account. A modified inverse tire model is constructed to transform the desired tire friction forces to the desired wheel slip and sideslip angle. In the next step, these desired values, which are considered as setpoints, are tackled through the use of the inner loops with guaranteed tracking performance. The vehicle mass and mass moment of inertia, as unknown parameters, are estimated through parameter adaptation laws. The stability and error convergence of the integrated control system in the presence of the uncertain parameters, which is a very essential feature for the active safety means, is guaranteed by utilizing a Lyapunov function. Computer simulations, using a nonlinear 14-DOF vehicle model, are provided to demonstrate the desired tracking performance of the proposed control approach.     

Longitudinal vehicle state estimation using nonlinear and parameter-varying observers

A corner-based velocity estimation approach is proposed which is used for vehicle’s traction and stability control systems. This approach incorporates internal tire states within the vehicle kinematics and enables the velocity estimator to work for a wide range of maneuvers without road friction information. Tire models have not been widely implemented in velocity estimators because of uncertain road friction and varying tire parameters, but the current study utilizes a simplified LuGre model with the minimum number of tire parameters and estimates velocity robust to model uncertainties. The proposed observer uses longitudinal forces, updates the states by minimizing the longitudinal force estimation error, and provides accurate outcomes at each tire. The estimator structure is shown to be robust to road conditions and rejects disturbances and model uncertainties effectively. Taking into account the vehicle dynamics is time-varying, the stability of the observer for the linear parameter varying model is proved, time-varying observer gains are designed, and the performance is studied. Road test experiments have been conducted and the results are used to validate the proposed approach.     

Safety brake performance evaluation and optimization of hydraulic lifting systems in case of overspeed dropping

Safety is the most important issue for mobile and industrial machinery, and overspeed dropping of lifting actuators is extremely hazardous to the equipment, environment and operators. In this paper, to evaluate and improve the safety brake performance of hydraulic lifting systems in this emergent case, a multi-objective optimization model was proposed. Considering the load impacts in the braking process, a novel indicator named remaining vibration energy was defined to simply quantify the cushion performance. A mathematical and simulation model was established, and then the simulation model was verified by experimental tests. Minimization of the remaining vibration energy, the brake distance and the pressure loss of the hydraulic fuse on normal working conditions were considered as optimization objectives after analysis of the system dynamic behavior. The optimization model using a genetic algorithm was applied to a heavy hydraulic elevator system. The results indicated that the pressure impact was reduced, and the plunger stopped more smoothly in the optimized system. Also the brake distance and the pressure loss of the fuse are limited by the design criterion. Therefore, this paper presents an optimization method of hydraulic fuses to design safer hydraulic lifting systems.     

Adaptive sliding mode pressure control for an electro-hydraulic brake system via desired-state and integral-antiwindup compensation

Brake-by-wire (BBW) systems are electronically regulated actuators, which are capable of producing a desired braking torque to the vehicle's wheel. This paper focuses on the motor-type electro-hydraulic brake (EHB) system: an electric motor driven rotational-to-linear reducing mechanism that directly pushes the master cylinder to generate hydraulic pressure. A simple and practicable controller is developed to reduce the negative influence of system nonlinearities and uncertainties. Unlike the complicated stribeck-speed-detected and precise-parameter-identified friction model, a novel efficiency model is developed to describe the friction. Sliding mode control is used to reduce the non-parametric disturbances. Adaptation law based on non-smooth mapping is employed to weaken the parametric uncertainties. Desired-state compensation is applied to prevent the real pressure fluctuation weakening the performance of adaptation law. Anti-windup mechanism is adopted to compensate the integral windup action and tracking the desired pressure high-precisely. The stability of system is proved based on the Lyapunov function approach. The simulation and experimental results in the typical braking scenarios are conducted to verify the enhanced performance.     

Adaptive vehicle traction force control for intelligent vehicle highway systems (IVHSs)

This paper is concerned with robust longitudinal control of vehicles in intelligent vehicle highway systems by adaptive vehicle traction force control. Two different traction force controllers, adaptive fuzzy logic control and adaptive sliding-mode control, are proposed and applied to the fastest stable acceleration/deceleration and robust vehicle platooning problems. The motivation for investigating adaptive techniques arises from the unknown time-varying nature of the tire/road surface interaction that governs vehicle traction. Synchronous application of the engine or brake torques is also proposed for more stable vehicle maneuvers. The lack of controllability during braking (only one net input torque for the two control objectives, i.e., front and rear wheel slips) is partly overcome by applying auxiliary engine torque. Simulations of the two control methods are conducted using a complex nonlinear vehicle model which fully describes the dynamic behavior of the vehicle. Both controllers result in good performance under time-varying operating conditions.     

Electric vehicles-pursuing efficiency

The approaches being used to make electric vehicles (EVs) highly efficient given the limitations of EV batteries are described. They include reducing vehicle weight, aerodynamic drag, tire rolling resistance, and bearing friction; eliminating brake drag; and increasing the efficiency of the electric motor and its control electronics. The intrinsic efficiency of electric motors and the choice of power electronics are discussed. Energy management and the use of regenerative braking are examined     

Coordinated motion control and event-based obstacle-crossing for four wheel-leg independent motor-driven robotic system

This work investigates the coordinated motion control and obstacle-crossing problem for a four wheel-leg independent motor-driven robotic system via a model predictive control (MPC) approach based on an event-triggering mechanism. The modeling of a wheel-leg robotic control system with a dynamic supporting polygon is organized. The system dynamic model is 3 degrees of freedom ignoring the pitch, roll, and vertical motions. The single wheel dynamic is analyzed considering the characteristics of the motor-driven and the Burckhardt nonlinear tire model. As a result, an over-actuated predictive model is proposed with the motor torques as inputs and the system states as outputs. As the supporting polygon is only adjusted at certain conditions, an event-based triggering mechanism is designed to save hardware resources and energy. The MPC controller is evaluated on a virtual prototype as well as a physical prototype. The simulation results guide the parameter tuning for the controller implementation in the physical prototype. The experimental results on these two prototypes verify the efficiency of the proposed approach.     

Salient video cube guided nighttime vehicle braking event detection

In nighttime driving brake lights are particularly important because they offer a warning signal to prevent potential collisions. In this work, we propose a novel visual-based approach for nighttime brake light detection using three-dimensional Nakagami imaging to analyze tail lights of vehicles in front. Rather than heuristic features, such as symmetry of taillights and appearance of the third brake light, the proposed approach extracts invariant features by modeling the scattering of brake lights, thus allowing detection to proceed in a part-based manner. Experiments from extensive datasets show that the proposed system can effectively detect vehicle braking under different lighting and traffic conditions, making it a realistic option for real-world applications.     

Adaptive robust motion control of single-rod hydraulic actuators:theory and experiments

High-performance robust motion control of single-rod hydraulic actuators with constant unknown inertia load is considered. The two chambers of a single-rod actuator have different areas, so the dynamic equations describing the pressure changes in them cannot be combined into a single load pressure equation. This complicates controller design since it not only increases the system dimension but also brings in the stability issue of the added internal dynamics. A discontinuous projection-based adaptive robust controller (ARC) is constructed. The controller takes into account not only the effect of parameter variations coming from the inertia load and various hydraulic parameters but also the effect of hard-to-model nonlinearities such as uncompensated friction forces and external disturbances. It guarantees a prescribed output tracking transient performance and final tracking accuracy in general while achieving asymptotic output tracking in the presence of parametric uncertainties. In addition, the zero error dynamics for tracking any nonzero constant velocity trajectory is shown to be globally uniformly stable. Experimental results are obtained for the swing motion control of a hydraulic arm and verify the high-performance nature of the proposed strategy. In comparison to a state-of-the-art industrial motion controller, the proposed algorithm achieves more than a magnitude reduction of tracking errors. Furthermore, during the constant velocity portion of the motion, it reduces the tracking errors almost down to the measurement resolution level     

On the implementation and control of a pneumatic power active lower-limb orthosis

This paper develops a pneumatic power active lower-limb orthosis (PPALO) to be a controlled plant. Due to the use of pneumatic actuators, the PPALO inherently possesses non-smooth nonlinearities, such as asymmetric dynamics, friction, and dead zone. In order to eliminate the influence of these nonlinearities on the pneumatic actuators and the dynamic coupling terms included in the dynamics of the lower-limb orthosis, an inner-loop PI controller with a differential pressure feedback and an outer-loop filter-based iterative learning control (FILC) scheme which consists of an outer PD feedback controller as well as a feedforward filter are used. Finally, a trajectory tracking control experiment is conducted to validate that the proposed method can effectively control the system to track the desired trajectory and reduce the vibration caused by nonlinearities of the pneumatic actuators.     

Adaptive displacement control with hysteresis modeling for piezoactuated positioning mechanism

An adaptive displacement control with hysteresis modeling for a piezoactuated positioning mechanism is proposed in this paper because the dynamic performance of piezosystems is often severely deteriorated due to the hysteresis effect of piezoelectric elements. First, a new mathematical model based on the differential equation of a motion system with a parameterized hysteretic friction function is proposed to represent the dynamics of motion of the piezopositioning mechanism. As a result, the mathematical model describes a motion system with hysteresis behavior due to the hysteretic friction. Then, by using the developed mathematical model, the adaptive displacement tracking control with the adaptation algorithms of the parameterized hysteretic function and of an uncertain parameter is proposed. By using the proposed control approach on the displacement control of the piezopositioning mechanism, the advantages of the asymptotical stability in displacement tracking, high-performance displacement response, and robustness to the variations of system parameters and disturbance load can be provided. Finally, experimental results are illustrated to validate the proposed control approach for practical applications.     

A low-cost driving simulator for full vehicle dynamics simulation

This paper describes the construction of a low-cost PC-based driving simulator that can perform five degree-of-freedom (DOF) motions similar to a road vehicle. The mathematical equations of vehicle dynamics are first derived from the 2-DOF bicycle model and incorporated with the tire, steering, and suspension subsystems. The equations of motion are then programmed by MATLAB, transferred into C++ code in the MIDEVA environment, and further developed into a motion platform control program by C++Builder. To achieve the simulator functions, a motion platform that is constructed by five hydraulic cylinders is designed, and its kinetics/inverse kinetics analysis is also conducted. Driver operation signals such as steering wheel angle, accelerator pedal, and brake pedal positions are measured to trigger the vehicle dynamics calculation and further actuate the cylinders by the motion platform control program. In addition, a digital PID controller is added to achieve the stable and accurate displacements of the motion platform. The experiments prove that the designed simulator is adequate in performing some special road driving situations discussed in this paper.     

A performance evaluation of an automotive magnetorheological brake design with a sliding mode controller

The aim of this work is to develop a magnetorheological brake (MRB) system that has performance advantages over the conventional hydraulic brake system. The proposed brake system consists of rotating disks immersed in a MR fluid and enclosed in an electromagnet, which the yield stress of the fluid varies as a function of the magnetic field applied by the electromagnet. The controllable yield stress causes friction on the rotating disk surfaces, thus generating a retarding brake torque. The braking torque can be precisely controlled by changing the current applied to the electromagnet. In this paper, an optimum MRB design with two rotating disks is proposed based on a design optimization procedure using simulated annealing combined with finite element simulations involving magnetostatic, fluid flow and heat transfer analysis. The performance of the MRB in a vehicle was studied using a quarter vehicle model. A sliding mode controller was designed for an optimal wheel slip control, and the control simulation results show fast anti-lock braking.     

Comparison between braking and steering yaw moment controllers considering ABS control aspects

Two yaw motion control systems that improve a vehicle lateral stability are proposed in this study: a braking yaw motion controller (BYMC) and a steering yaw motion controller (SYMC). A BYMC controls the braking pressure of the rear inner wheel, while a SYMC steers the rear wheels to allow the yaw rate to track the reference yaw rate. A 15 degree-of-freedom vehicle model, simplified steering system model, and driver model are used to evaluate the proposed BYMC and SYMC. A robust anti-lock braking system (ABS) controller is also designed and developed. The performance of the BYMC and SYMC are evaluated under various road conditions and driving inputs. They reduce the slip angle when braking and steering inputs are applied simultaneously, thereby increasing the controllability and stability of the vehicle on slippery roads. The SYMC performs better than the BYMC because the SYMC vehicle has four-wheel steering. However, both the BYMC and SYMC vehicles show improved performance during lane-change maneuvers.