Robust control for four-wheel-independent-steering electric vehicle with steer-by-wire system

A four-wheel-independent-steering (4WIS) electric vehicle (EV) with steer-by-wire (SBW) system is proposed in this paper. The fast terminal sliding mode controller (FTSMC) is designed for the SBW system to suppress external disturbances. Taking unstructured and structured uncertainties into consideration, a robust controller is designed for the 4WIS EV utilizing μ synthesis approach and the controller order reduction is implemented based on Hankel-Norm approximation. Since sideslip angle is the feedback signal of robust controller and it is hard to measure, the extended Kalman filter (EKF) is employed to estimate sideslip angle. To evaluate the vehicle performance with the designed control system, step and sinusoidal steering maneuvers are simulated and analyzed. Simulation results show that the designed control system have good tracking ability, strong robust stability and good robust performance to improve vehicle stability and handing performance.     

On the experimental analysis of single input single output control of yaw rate and sideslip angle

Electric vehicles with individually controlled drivetrains allow torque-vectoring, which improves vehicle safety and drivability. This paper investigates a new approach to the concurrent control of yaw rate and sideslip angle. The proposed controller is a simple single input single output (SISO) yaw rate controller, in which the reference yaw rate depends on the vehicle handling requirements, and the actual sideslip angle. The sideslip contribution enhances safety, as it provides a corrective action in critical situations, e.g., in case of oversteer during extreme cornering on a low friction surface. The proposed controller is experimentally assessed on an electric vehicle demonstrator along two maneuvers on surfaces with significantly varying tire-road friction coefficient. Different longitudinal locations of the sideslip angle used as control variable are compared during the experiments. Results show that: i) the proposed SISO approach provides significant improvements with respect to the vehicle without torque-vectoring, and the controlled vehicle with a reference yaw rate solely based on the handling requirements for high-friction maneuvering; and ii) the control of the rear axle sideslip angle provides better performance than the control of the sideslip angle at the center of gravity.     

Cooperative lateral vehicle control for autonomous valet parking

This paper presents a lateral vehicle control algorithm for autonomous valet parking (AVP). Under the assumption that the position and heading angle are provided via vehicle-to-infrastructure (V2I) communication, the lateral controller aims to conduct two different driving maneuvers, i.e., forward driving and backward parking, and to control various types of vehicles in a unified approach. Therefore, it is necessary for the lateral controller to be robust enough to track the desired trajectories for different driving maneuvers, as well as to compensate for the uncertainty caused by the need to consider various vehicle types. With the assumption of operating conditions such as a low speed and small slip angle, a nonlinear kinematic model with kinematic constraints is used for the design of the lateral control. Based on this nonlinear model, a nonlinear control technique called dynamic surface control (DSC) is applied to design the lateral controller, and its stability is analyzed in the framework of linear differential inclusion. Finally, the proposed lateral control algorithm is validated through vehicle simulations and field tests.     

Sideslip angle estimation considering short-duration longitudinal velocity variation

The accurate estimation of sideslip angle is necessary for many vehicle control systems. The detection of sliding and skidding is especially critical in emergency situations. In this paper, a sideslip angle estimation method is proposed that considers severe longitudinal velocity variation over the short period of time during which a vehicle may lose stability due to sliding or spinning. An extended Kalman filter (EKF) based on a kinematic model of a vehicle is used without initialization of the inertial measurement unit to estimate vehicle longitudinal velocity. A dynamic compensation method that compensates for the difference in the locations of the vehicle velocity sensor and the IMU in on-road vehicle tests is proposed. Evaluations with a CarSim™ 27-degree-of-freedom (DOF) model for various vehicle test scenarios and with on-road tests using a real vehicle show that the proposed sideslip angle estimation method can accurately predict sideslip angle, even when vehicle longitudinal velocity changes significantly.     

Disturbance Observer-Based Sideslip Angle Control for Improving Cornering Characteristics of In-Wheel Motor Electric Vehicles

In this paper, a robust sideslip angle controller based on the direct yaw moment control (DYC) is proposed for in-wheel motor electric vehicles. Many studies have demonstrated that the DYC is one of the effective methods to improve vehicle maneuverability and stability. Previous approaches to achieve the DYC used differential braking and active steering system. Not only that, the conventional control systems were commonly dependent on the feedback of the yaw rate. In contrast to the traditional control schemes, however, this paper proposes a novel approach based on sideslip angle feedback without controlling the yaw rate. This is mainly because if the vehicle sideslip angle is controlled properly, the intended sideslip angle helps the vehicle to pass through the corner even at high speed. On the other hand, the vehicle may become unstable because of the too large sideslip caused by unexpected yaw disturbances and model uncertainties of time-varying parameters. From this aspect, disturbance observer (DOB) is employed to assure robust performance of the controller. The proposed controller was realized in CarSim model described actual electric vehicle and verified through computer simulations.     

MPC-BASED steering control for backward-driving vehicle using stereo vision

We propose a steering control algorithm for autonomous backward driving in a narrow corridor. Passable spaces are detected using a stereo camera, and the steering angle is controlled by a model predictive controller (MPC). For passable space detection, an UV-disparity map is calculated from the original disparity map. Information regarding passable spaces collected by the stereo camera is used in steering control. Backward driving requires the driver’s preemptive actions, which can be learned by experience because of the non-intuitive responses (the initial motion of the vehicle is opposite to the driver’s steering angle input). This occurs because a backward-driving vehicle is a non-minimum phase system. One of the most popular steering control algorithms is Stanley method, which is based on the feedback of lateral displacement error and heading angle error. The method is very intuitive and works well for forward driving, but it exhibits significant undershoot for backward driving cases. Furthermore, the method does not explicitly consider any constraints on control inputs and states. We designed a steering controller based on the MPC technique that requires future information but can handle constraints explicitly. Because we have near-future information from the stereo camera under limited passable spaces, MPC can be effectively implemented. We performed several simulations and experiments to show the performance and superiority of the suggested method over a simple feedback-based control algorithm.     

Optimal preview game theory approach to vehicle stability controller design

Dynamic game theory brings together different features that are keys to many situations in control design: optimisation behaviour, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degrees-of-freedom vehicle-handling performance model is put into discrete form to develop the game equations of motion. To evaluate the developed control algorithm, CarSim with its built-in nonlinear vehicle model along with the Pacejka tire model is used. The control algorithm is evaluated for a lane change manoeuvre, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. Simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity, yaw rate, and roll angle, which all contribute to enhancing vehicle stability.     

基于模型预测控制的智能车轨迹跟踪控制研究

为了完成智能车的轨迹跟踪,提出一种基于模型预测控制的轨迹跟踪方法,利用将运动学模型这个非线性系统线性化的方案,来获得必须的线性时变系统,采取模型预测控制的三要素来设计控制器。并且基于MPC在控制过程中能增加多种约束的优点,建立基于车辆运动学模型的约束做轨迹跟踪仿真实验,最后,基于山东理工大学智能车平台上GPS提供的定位信息,在校园中采集路线并对前提规划好的的轨迹进行实车验证。实验结果表明:基于MPC算法所设计的控制器能快速且稳定地跟踪期望轨迹。     

基于驾驶人转向意图的双电机驱动电动汽车稳定性控制策略

为了使双电机驱动电动车在车辆稳定性控制过程中能够精确解读驾驶意图,使车辆实际行驶状态与驾驶意图期望的车辆行驶状态尽可能相符合,提出一种基于驾驶人意图辨识的稳定性控制策略.利用基于支持向量机递归特征消除(SVM-RFE)得到的特征参数构建基于长短期记忆(LSTM)模型的驾驶人转向意图辨识模型;基于转向意图识别结果,以方向...     

A new flatness-based control of lateral vehicle dynamics

This paper presents a new concept for vehicle dynamics control (VDC). The control of the longitudinal vehicle dynamics is not discussed, since we are assuming that it is much slower and weakly coupled to the lateral and yawing dynamics. The actuators are considered to be the traction and the braking torques of the individual wheels and only the standard sensors of the common VDC system are used. A modular interface to the subordinate wheel control system is provided by choosing the yaw torque as a fictitious control input. The VDC system is designed by means of a two degrees-of-freedom control scheme. It comprises a flatness-based feedforward part and a stabilising feedback part. The reference trajectory generation is introduced for the flat output which is given by the lateral velocity of the vehicle. Thus an advantageous kind of body side-slip angle control is provided with the standard VDC system hardware. Extensive simulation studies show excellent performance of the designed control concept.     

Using µ Feedforward for Vehicle Stability Enhancement

A differential braking control strategy using yaw rate feedback, coupled with µ feedforward is introduced for a vehicle cornering on different µ roads. A nonlinear 4-wheel car model is developed. A desired yaw rate is calculated from the reference model based on the driver steering input. It is shown that knowledge of µ offers significant improvement of the vehicle desired trajectory over that of a yaw rate controller alone. Uncertainties and time delay in estimating µ are shown to still yield a system that is superior to using no µ information at all.     

Using µ Feedforward for Vehicle Stability Enhancement

A differential braking control strategy using yaw rate feedback, coupled with µ feedforward is introduced for a vehicle cornering on different µ roads. A nonlinear 4-wheel car model is developed. A desired yaw rate is calculated from the reference model based on the driver steering input. It is shown that knowledge of µ offers significant improvement of the vehicle desired trajectory over that of a yaw rate controller alone. Uncertainties and time delay in estimating µ are shown to still yield a system that is superior to using no µ information at all.     

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.     

智能汽车轨迹跟踪与横摆稳定性协同控制

为了提高四轮独立驱动智能电动汽车在变曲率弯道下的轨迹跟踪精度和横摆稳定性,提出了一种模型预测控制与直接横摆力矩控制协同的综合控制方法。建立了横纵向耦合的车辆动力学模型,采用2阶龙格库塔离散法保证了离散模型的精度,并基于简化的2自由度动力学模型推导了车辆横摆稳定性约束,设计了非线性模型预测控制器;利用直接横摆力矩控制能够改变车辆横摆角速度和航向角的特点,考虑模型预测控制器的预测状态、控制量以及跟踪误差,设计了协同控制规则。仿真结果表明,协同控制方法解决了考虑横摆稳定性约束的模型预测控制器中存在的稳定性约束与控制精度相矛盾的问题,并补偿了模型预测控制器没有可行解时对横摆稳定性的约束,同时提高了智能汽车的轨迹跟踪精度和横摆稳定性。     

Multi-axle vehicle dynamics stability control algorithm with all independent drive wheel

The stability driving characteristic and the tire wear of 8-axle vehicle with 16-independent driving wheels are discussed in this paper. The lateral stability of 8-axle vehicle can be improved by the direct yaw moment which is generated by the 16 independent driving wheels. The hierarchical controller is designed to determine the required yaw torque and driving force of each wheel. The upper level controller uses feed-forward and feed-backward control theory to obtain the required yaw torque. The fuzzification weight ratio of two control objective is built in the upper level controller to regulate the vehicle yaw and lateral motions. The rule-based yaw moment distribution strategy and the driving force adjustment based on the safety of vehicle are proposed in the lower level controller. The influence of rear steering angle is considered in the distribution of driving force of the wheel. Simulation results of a vehicle double lane change show the stability of 8-axle vehicle under the proposed control algorithm. The wear rate of tire is calculated by the interaction force between the tire and ground. The wear of tire is different from each other for the vehicle with the stability controller or not.     

Yaw rate and side-slip control considering vehicle longitudinal dynamics

Most conventional vehicle stability controllers operate on the basis of many simplifying assumptions, such as a small steering wheel angle, constant longitudinal velocity and a small side-slip angle. This paper presents a new approach for controlling the yaw rate and side-slip of a vehicle without neglecting its longitudinal dynamics and without making simplifying assumptions about its motion. A sliding-mode controller is used to develop a differential braking controller for tracking a desired vehicle yaw rate for a given steering wheel angle, while keeping the vehicle’s side-slip angle as small as possible. The trade-off that exists between yaw rate and side-slip control is described. Conventional and proposed algorithms are presented, and the effectiveness of the proposed controller is investigated using a seven-degree-of-freedom vehicle dynamics model. The simulation results demonstrate that the proposed controller is more effective than the conventional one.     

基于扰动观测的客车ESC自适应神经网络滑模控制

为了提高客车电子稳定性控制系统(ESC)的控制精度,针对实际车辆系统建模中存在各种非线性扰动项以及传统滑模控制(Sliding Mode Control,SMC)中抖振较大的问题,提出一种自适应神经网络滑模控制算法.基于2自由度车辆模型,首先设计一个二阶滑模(Second-order Sliding Mode,SOSM...     

Design of a feedback-feedforward steering controller for accurate path tracking and stability at the limits of handling

This paper presents a feedback-feedforward steering controller that simultaneously maintains vehicle stability at the limits of handling while minimising lateral path tracking deviation. The design begins by considering the performance of a baseline controller with a lookahead feedback scheme and a feedforward algorithm based on a nonlinear vehicle handling diagram. While this initial design exhibits desirable stability properties at the limits of handling, the steady-state path deviation increases significantly at highway speeds. Results from both linear and nonlinear analyses indicate that lateral path tracking deviations are minimised when vehicle sideslip is held tangent to the desired path at all times. Analytical results show that directly incorporating this sideslip tangency condition into the steering feedback dramatically improves lateral path tracking, but at the expense of poor closed-loop stability margins. However, incorporating the desired sideslip behaviour into the feedforward loop creates a robust steering controller capable of accurate path tracking and oversteer correction at the physical limits of tyre friction. Experimental data collected from an Audi TTS test vehicle driving at the handling limits on a full length race circuit demonstrates the improved performance of the final controller design.     

基于变权重系数的分布式驱动无人车轨迹跟踪

为了提高分布式无人车轨迹跟踪的精度，提出了基于自主与差动协调转向控制的轨迹跟踪方法。首先，在车辆三自由度模型基础上，基于模型预测控制（MPC）实时计算前轮转角以控制车辆进行自主转向轨迹跟踪。在此过程中，为了提高自主转向下车辆的轨迹跟踪精度与行驶的稳定性，考虑多种因素，利用经验公式及神经网络控制对MPC的预瞄步数和预瞄步长进行多参数调整，实现预瞄时间的自适应控制。其次，在恒转矩需求的情况下，以轨迹偏差为PID控制器的输入及左右轮毂电机转矩为输出进行差动转向控制，实现了差动转向下的轨迹跟踪控制。然后，通过设置权重系数的方法将自主与差动转向相结合。考虑到车辆横纵向动力学因素，采用模糊控制及经验公式对权重系数进行了调整，从而在提高车辆转向灵活性与轨迹跟踪效果的同时保证车辆行驶的稳定性。CarSim与Simulink联合仿真以及实车试验结果表明：与自主转向轨迹跟踪相比，采用变权重系数的协调控制可以在不同的工况下提高车辆的转向灵活性与轨迹跟踪的精度，轨迹跟踪偏差的均方根值改善率达到了11%。所提出的协调转向控制方法可为分布式驱动车辆转向灵活性的提高及轨迹跟踪精度的改善提供一种新的思路。     

Nonlinear adaptive sliding mode control for vehicle handling improvement via steer-by-wire

This paper proposes a nonlinear adaptive sliding mode control that aims to improve vehicle handling through a Steer-By-Wire system. The designed sliding mode control, which is insensitive to system uncertainties, offers an adaptive sliding gain to eliminate the precise determination of the bound of uncertainties. The sliding gain value is calculated using a simple adaptation algorithm that does not require extensive computational load. Achieving the improved handling characteristics requires both accurate state estimation and well-controlled steering inputs from the Steer-By-Wire system. A second order sliding mode observer provides accurate estimation of lateral and longitudinal velocities while the driver steering angle and yaw rate are available from the automotive sensors. A complete stability analysis based on Lyapunov theory has been presented to guarantee closed loop stability. The simulation results confirmed that the proposed adaptive robust controller not only improves vehicle handling performance but also reduces the chattering problem in the presence of uncertainties in tire cornering stiffness.