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.     

Load sensing bearing based road-tyre friction estimation considering combined tyre slip

This work discusses a road-tyre friction estimator considering combined tyre slip. The friction estimator design is motivated by its importance in vehicle dynamics control as accurate friction estimation can improve performance and safety. The estimator uses tyre force measurements from Load Sensing Bearing (LSB) technology and does not rely on parameterized tyre model. The tyre force measurements benefit the estimator mainly because of the uncertainties and nonlinearities of the tyre force characteristics. The proposed estimator uses tyre slip and tyre force representations where the longitudinal and lateral tyre slips and forces are combined into a single tyre slip and tyre force values. This representation makes the method effective during pure longitudinal dynamics, pure lateral dynamics and for combined slip. In addition, individual tyre-road friction estimation is possible with the proposed estimator and a computationally inexpensive algorithm, suitable for real-time implementation, is used to estimate the friction. The estimator is studied in simulation during pure braking, pure cornering and for combined slip. Further, the estimator is simulated in closed loop with a yaw rate controller to study whether the estimator improves vehicle safety. Finally the estimator is validated using test data from several maneuvers performed on a test vehicle instrumented with LSB technology.     

The use of GPS for vehicle stability control systems

This paper presents a method for using global positioning system (GPS) velocity measurements to improve vehicle lateral stability control systems. GPS can be used to calculate the sideslip angle of a vehicle without knowing the vehicle model. This measurement is combined with other traditional measurements to control the lateral motion of the vehicle. Noise estimates are provided for all measurement systems to allow the sensors to be accurately represented. Additionally, a method to calculate the lateral forces at the tires is presented. It is shown that the tire estimation algorithm performs well outside the linear region of the tire. Results for the controller and force calculations are shown using a nonlinear model to simulate the vehicle and the force calculations are validated with experimental measurements on a test vehicle.     

Gain-scheduled robust control for lateral stability of four-wheel-independent-drive electric vehicles via linear parameter-varying technique

This paper proposes a robust gain-scheduled H_∞ controller for lateral stability control of four-wheel-independent-drive electric vehicles via linear parameter-varying technique. The controller aims at tracking the desired yaw rate and vehicle sideslip angle by controlling the external yaw moment. In the design of controller, uncertain factors such as vehicle mass and tire cornering stiffness in vehicle lateral dynamics are represented via the norm-bounded uncertainty. To address the importance of time-varying longitudinal velocity for vehicle lateral stability control, a linear parameter-varying polytopic vehicle model is built, and the built vehicle model depends affinely on the time-varying longitudinal speed that is described by a polytope with finite vertices. In order to reduce conservative, the hyper-rectangular polytope is replaced by a hyper-trapezoidal polytope. Simultaneously, the quadratic D-stability is also applied to improve the transient response of the closed-loop system. The resulting gain-scheduling state-feedback controller is finally designed, and solved utilizing a set of linear matrix inequalities derived from quadratic H_∞ performance and D-stability. Simulations using Matlab/Simulink-Carsim® are carried out to verify the effectiveness of the proposed controller with a high-fidelity, CarSim®, full-vehicle model. It is found from the results that the robust gain-scheduled H_∞ controller suggested in this paper provides improved vehicle lateral stability, safety and handling performance.     

Model predictive control of vehicle stability using coordinated active steering and differential brakes

This paper studies model predictive control of lateral stability of vehicles using coordinated active front steering and differential brakes. The controller is designed based on a bicycle model of the vehicle and the moment of the differential brakes is considered as an external torque. The prediction model calculates the prospective values of the vehicle’s yaw rate, lateral velocity, and tire slip angles over the prediction window. The sideslip angle of the vehicle is enforced within a permissible range using soft constraints on the lateral velocity in order to guarantee persistent feasibility. Using computer simulations, the controller is shown to provide proactive control actions to control the vehicle’s sideslip angle. The closed-loop response of the controller is also studied in experimental tests on an instrumented test vehicle. The results show satisfactory performance in various combinations of active front steering and differential brakes. In addition, the computational time of the controller is measured and shown to be safely below the sample time of the controller.     

Lateral stabilization of a four wheel independent drive electric vehicle on slippery roads

In this paper, a new controller is proposed for lateral stabilization of four wheel independent drive electric vehicles without mechanical differential. The proposed controller has three levels including high, medium and low control levels. Desired vehicle dynamics such as reference longitudinal speed and reference yaw rate are determined by higher level of controller. Moreover, using a neural network observer and a fuzzy logic controller, a novel reference longitudinal speed generator system is presented. This system guarantees the vehicle’s stable motion on the slippery roads. In this paper, a new sliding mode controller is proposed and its stability is proved by Lyapunov stability theorem. This sliding mode control structure is faster, more accurate, more robust, and with smaller chattering than classic sliding mode controller. Based on the proposed sliding mode controller, the medium control level is designed to determine the desired traction force and yaw moment. Therefore, suitable wheel forces are calculated. Finally, the effectiveness of the introduced controller is investigated through conducted simulations in CARSIM and MATLAB software environments.     

Modular integrated longitudinal and lateral vehicle stability control for electric vehicles

In this paper, the problem of integrated longitudinal and lateral vehicle stability control is addressed using a modular optimal control structure. The optimization process of the high level model predictive control (MPC) controller determines required longitudinal force and yaw moment adjustments to minimize the error between vehicle longitudinal and lateral vehicle stability dynamic states with respect to the target courses. The low level controller is designed to optimally regulate torque at each wheel based on the control inputs of the high level controller, and distribute required torque between the wheels via actuation system. The actuation system that is utilized to implement the proposed control structure functions based on all-wheel drive technology that can provide active control of both traction and yaw moment control with differential torque. The multi-layered structure of the control system allows modularity in design. The performance of the control structure is investigated by conducting experimental tests. The experimental tests have been performed on an electric Chevrolet Equinox vehicle equipped with four independent motors. The results show that the integration of the vehicle longitudinal and lateral dynamics preserves vehicle stability in a planar motion and improves the vehicle dynamic response, especially in challenging driving maneuvers.     

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.     

Ein Beitrag zur nichtlinearen Fahrdynamik-regelung: die differentielle Flachheit des Einspurmodells

This contribution is primarily concerned with the system analysis of the bicycle dynamics, revealing the differential flatness property as a main result. A physically relevant representative for the flat output is introduced, with its components given as the lateral and the longitudinal velocity of a distinguished point located on the longitudinal axis of the vehicle. This flatness property is shown for the front-, rear- and all-wheel driven vehicle, without referring to particular representatives of the functions modelling the lateral tire forces. Following the flatness based control theory, a novel approach to nonlinear vehicle dynamics control is discussed.     

Sliding-mode motion controller with adaptive fuzzy disturbance estimation

This paper proposes a motion control scheme which belongs to the class of the control schemes known as sliding-mode control with disturbance estimation. A novel adaptive fuzzy disturbance estimator works as an estimator of a major part of robot dynamics. The adaptation algorithm is derived by using the Lyapunov stability theory and provides global asymptotic stability of the state errors, resulting in the sliding-mode regime. The structure of the disturbance estimator is optimized by the introduction of three fuzzy logic subsystems, based on the physical properties of the robot mechanism. This also significantly lowers the computational burden and enables real-time implementation. Performance of the proposed controller scheme, as well as some practical design aspects, are demonstrated by the control of a direct-drive robot.     

Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer

A stabilizing observer-based control algorithm for an in-wheel-motored vehicle is proposed, which generates direct yaw moment to compensate for the state deviations. The control scheme is based on a fuzzy rule-based body slip angle (beta) observer. In the design strategy of the fuzzy observer, the vehicle dynamics is represented by Takagi-Sugeno-like fuzzy models. Initially, local equivalent vehicle models are built using the linear approximations of vehicle dynamics for low and high lateral acceleration operating regimes, respectively. The optimal beta observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall control system by using fuzzy rules. These fuzzy rules represent the qualitative relationships among the variables associated with the nonlinear and uncertain nature of vehicle dynamics, such as tire force saturation and the influence of road adherence. An adaptation mechanism for the fuzzy membership functions has been incorporated to improve the accuracy and performance of the system. The effectiveness of this design approach has been demonstrated in simulations and in a real-time experimental setting.     

Automobile Brake-by-Wire Control System Design and Analysis

The automobile brake-by-wire (BBW) system, which is also called the electromechanical brake system, has become a promising vehicle braking control scheme that enables many new driver interfaces and enhanced performances without a mechanical or hydraulic backup. In this paper, we survey BBW control systems with focuses on fault tolerance design and vehicle braking control schemes. At first, the system architecture of BBW systems is described. Fault tolerance design is then discussed to meet the high requirements of reliability and safety of BBW systems. A widely used braking model and several braking control schemes are investigated. Although previous work focused on antilock and antislip braking controls on a single wheel basis, we present a whole-vehicle control scheme to enhance vehicle stability and safety. Simulations based on the whole-vehicle braking model validate a proposed fuzzy logic control scheme in the lateral and yaw stability controls of vehicles.     

Robust Yaw Stability Controller Design and Hardware-in-the-Loop Testing for a Road Vehicle

Unsymmetrical loading on a car like $mu$-split braking, side wind forces, or unilateral loss of tire pressure results in unexpected yaw disturbances that require yaw stabilization either by the driver or by an automatic driver-assist system. The use of two-degrees-of-freedom control architecture known as the model regulator is investigated here as a robust steering controller for such yaw stabilization tasks in a driver-assist system. The yaw stability-enhancing steering controller is designed in the parameter space to satisfy a frequency-domain mixed sensitivity constraint. To evaluate the resulting controller design, a real-time hardware-in-the-loop simulator is developed. Steering tests with and without the controller in this hardware-in-the-loop setup allow the driver to see the effect of the proposed controller to improve vehicle-handling quality. The hardware-in-the-loop simulation setup can also be used for real-time driver-in-the-loop simulation of other vehicle control systems.      

Yaw stability control of a steer-by-wire equipped vehicle via active front wheel steering

A novel yaw stability control algorithm with active front wheel steering control of a vehicle equipped with a steer-by-wire system is presented in this paper. The proposed algorithm achieves the decoupling of the lateral and yaw motion of a vehicle and the vehicle’s yaw damping simultaneously by the feedback of both yaw rate and front steering angle. A trade-off is then made between the robust decoupling and yaw rate damping through the adjustment of the feedback gains with respect to vehicle speed. With this trade-off, the gain scheduled steering controller provides the desired yaw rate damping while keeping the yaw-lateral motion decoupled. The robustness of the yaw-lateral decoupling is achievable when arbitrary yaw damping is not required. The proposed control system is implemented on a steer-by-wire vehicle, and the experimental results are presented illustrating the benefits.     

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.     

An adaptive hierarchical control approach of vehicle handling stability improvement based on Steer-by-Wire Systems

This paper proposes a novel adaptive hierarchical control approach for Steer-by-Wire (SbW) vehicles to improve the handling stability. The high-level stability control scheme contains a variable steering ratio (VSR) strategy based on the adaptive-network-based fuzzy inference system (ANFIS) and an active front steering (AFS) controller designed with the integral sliding mode method by tracking the expected yaw rate, in which the desired front wheel angle is generated to enhance the cornering stability performance. Besides, an adaptive tracking controller (ATC) for the SbW system is designed by using the adaptive sliding mode control method to achieve desired steering performance in the lower level. The proposed adaptive control strategy is validated with different driving circles from ISO standards in simulation tests and hardware-in-the-loop (HiL) experiments. The results demonstrate that the designed control approach improve the vehicle handling stability significantly, even in some extreme driving conditions.     

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.     

Unified Chassis Control for Rollover Prevention and Lateral Stability

This paper describes a unified chassis control (UCC) strategy to prevent vehicle rollover and improve vehicle lateral stability. A rollover index (RI), which indicates impending rollover, and a model-based roll state estimator are introduced to detect potential rollover. An RI/lateral stability-based rollover mitigation (ROM) controller is designed to reduce the danger of rollover without loss of vehicle lateral stability by integrating electronic stability control (ESC) and continuous damping control (CDC). Simulation results indicate that significant improvement in vehicle rollover prevention and lateral stability can be expected from the proposed UCC system.      

基于Kalman预测的四轮转向状态估计算法

针对车辆运动状态测量存在的成本高、难度大问题,提出了一种基于Kalman预测技术的车辆状态估计算法,该估计算法以线性二自由度的车辆模型为基础,对四轮转向过程中车辆横摆角速度、车辆侧向加速度分别进行估计,并与实测结果对比分析,结果表明,Kalman预测算法能准确估计四轮转向时车辆的横摆角速度、侧向加速度,并结合车速信息对4WS转向车辆采用低速时,前后轮采用反向转向、高速时前后轮采用同向转向的控制策略,以实现汽车低速行驶的机动性和高速行驶的操作稳定性。