Tire Force Saturation Research Articles

Two-stage auxiliary drifting path tracking control for distributed driving three-axle commercial vehicles

When maneuvering corners at high speeds, commercial vehicles experience significant sideslip angles and tire force saturation, which can lead to severe traffic accidents. Incorporating intelligent driving technology to develop a controllable scheme that surpasses stability constraints and maintains the vehicle in a drift state is crucial for enhancing driving safety. Therefore, based on the model characteristics of distributed drive three-axle(DDTA) commercial vehicles, a two-stage auxiliary drift controller is proposed. In the auxiliary drift stage, time-varying model predictive control (MPC) is employed to track the desired states and achieve steady-state drift path tracking under extreme working conditions. A two-stage controller switching strategy is implemented based on road information. In the yaw stability control stage, an advanced auxiliary system facilitates cooperative control to smoothly restore tire attachment and vehicle yaw. Simulation results demonstrate that the control strategy ensures consistent path tracking performance even when adhesion of the middle and rear axle saturates and peak vehicle sideslip angle reaches 32.09°. After completing the drifting, vehicle yaw successfully returns to a stable state. Subsequently, miniaturized vehicle tests qualitatively analyze relevant conclusions by elucidating transient instability evolution in vehicles subjected to steering and distributed drive. The controllable stability boundary of the vehicle is thus expanded, thereby enhancing the engineering feasibility of drift technology.

Estimating Modeling Errors in Vehicle Dynamics for Timely Detection of Tire Force Saturation

Estimating Modeling Errors in Vehicle Dynamics for Timely Detection of Tire Force Saturation

Event-Triggered Control with Intermittent Communications over Erasure Channels for Leader–Follower Problems with the Combined-Slip Effect

In this article, we investigate the vehicle path-following problem for a vehicle-to-vehicle (V2V)–enabled leader–follower scenario and propose an integrated control policy for the following vehicle to accurately follow the leader’s path. We propose a control strategy for the follower vehicle to maintain a velocity-dependent distance relative to the leader vehicle while stabilizing its longitudinal and lateral dynamics considering the combined-slip effect and tire force saturation. In light of reducing wireless communication errors and efficient usage of battery power and resources, we propose an intermittent V2V communication in which transmissions are scheduled based on an event-triggered law. An event is triggered and a transmission is scheduled in subsequent sample time if some of the well-defined path-following error functions (relative distance error and lateral error) exceed given tolerance bounds. Considering that the V2V communication channel might be erroneous or a transmission fails due to, e.g., vehicles’ distance or low battery power, we consider data loss in the V2V channel. Our proposed control law consists of two components: a receding horizon feedback controller with state constraints based on a safe operation envelop and a feedforward controller that generates complementary control inputs when the leader’s states are successfully communicated to the follower. To mitigate the effects of data loss on the follower’s path-following performance, we design a remote estimator for the follower to predict the leader’s state using its on-board sensor equipment when an event is triggered but the corresponding state information is not received by the follower due to a packet loss. Incorporating this estimator allows the follower to apply cautionary control inputs knowing that the path-following error had exceeded a tolerance bound. We show that while the feedback controller stabilizes the follower’s dynamics, the feedforward component improves the safety margins and reduces the path-following errors even in the presence of data loss. High-fidelity simulations are performed using CarSim to validate the effectiveness of our proposed control architecture specifically in harsh maneuvers and high-slip scenarios on various road surface conditions.

Cooperative Strategy of Trajectory Tracking and Stability Control for 4WID Autonomous Vehicles Under Extreme Conditions

Trajectory tracking and stability control are two essential functions of autonomous vehicles, and there is inevitable mutual interference between them, especially under extreme conditions. Towards addressing this challenge, this paper proposes a novel cooperative strategy of trajectory tracking and stability control for four-wheel independent drive (4WID) autonomous vehicles. An adaptive trajectory tracking controller is designed based on the model predictive control (MPC) theory, in which the tire cornering stiffness is modified in real-time leverages the lateral force estimated by the square-root cubature Kalman filter (SCKF). Then, the vehicle stability controller is designed based on the sliding mode control (SMC), in which the tire force saturation constraint and the relative weight of yaw rate and sideslip angle are considered. Furthermore, a weight adaptive criterion with normalized stability index is defined to develop the cooperative strategy of trajectory tracking and stability control. The feasibility and adaptability of the proposed method to different extreme conditions are verified by hardware-in-the-loop (HIL) test and CarSim-Simulink co-simulation. Finally, an experimental case is presented to demonstrate the realizability of the proposed method.

Handling Enhancement of Autonomous Emergency Steering for Reduced Road Friction Using Steering and Differential Braking

Steering has more potential than braking to prevent rear-end collisions at higher relative velocities. A path tracking controller based on multi-input multi-output (MIMO) model predictive control (MPC) is proposed to enhance the handling performance of autonomous emergency steering in this paper. A six-state MIMO bicycle model including actuator dynamics of steering and differential braking is used for model prediction. Two control inputs are front wheel steering angle and direct yaw moment. Two model outputs are lateral displacement and heading angle. According to the work load ratios at four wheels, control allocation is used to determine the optimal braking force distribution to prevent tire force saturation. The performance of a single-input single-output (SISO) MPC that uses only steering angle control to track the lateral displacement of the desired path is employed to benchmark the performance of the proposed algorithm. Simulation results show that both SISO MPC and MIMO MPC can track the path on nominal road surface with high road friction coefficient of 0.9. For a road surface with medium road friction coefficient of 0.7, the SISO MPC is unable to track the path and loses directional stability. However, the MIMO MPC can still track the path and demonstrate robust path tracking and handling enhancement against model uncertainty due to reduced road friction.

Urgent Collision Avoidance Control by Using of Braking and Steering with Consideration for Tire Force Saturation

Urgent Collision Avoidance Control by Using of Braking and Steering with Consideration for Tire Force Saturation

Torque Distribution Algorithm for Stability Control of Electric Vehicle Driven by Four In-Wheel Motors Under Emergency Conditions

With the rapid development of intelligent transportation system, the research on vehicle stability can be a theoretical basis for realizing autonomous driving technology. The previous stability control strategies have not taken into account the tire force saturation factor, the slip rate, and the robustness of the control system sufficiency. According to the characteristic that the torque of each wheel can be distributed independently, a torque distribution algorithm under emergency conditions is proposed. The proposed torque distribution algorithm is constructed using three hierarchical controllers. The upper controller attempts to judge whether the vehicle is in stable state using the phase plane method. Also, it judges whether the wheels are slipping. The middle controller aims to calculate the demands for the desired traction force and yaw moment, whereas the lower controller is designed to translate those virtual signals into actual actuator commands. When designing the middle controller, a sliding mode control method is utilized to guarantee system stability and robustness by taking into account various factors, including lateral wind, and sensor noise. For the lower controller, the control allocation optimization method is utilized to determine an appropriate control input for each in-wheel motor by considering the road conditions, adhesion utilization, and maximum output torque of the motor. The numerical simulation studies are conducted to evaluate the performance of the torque distribution algorithm. Comparison results indicate that the proposed algorithm presents better performance to distribute the appropriate torque for each wheel and ensure the stability of the vehicle under emergency conditions.

Differential Steering Based Yaw Stabilization Using ISMC for Independently Actuated Electric Vehicles

Differential drive assistance steering (DDAS) is an emerging assisted steering mechanism in in-wheel-motor driven (IWMD) electric vehicles, yielded by the differential moment of the front tires in the steering system. DDAS can steer the front wheels when there is no steering power from the steering motor, and thus can be used as a redundant steering mechanism. To realize the yaw control when the active front steering entirely breaks down and guarantee the transient control performance therein, this paper proposes an integral sliding mode control (ISMC) approach for IWMD electric vehicles steered by DDAS. Two contributions are made in this paper: 1) An improved disturbance observer based ISMC strategy is designed to cope with the unknown mismatched disturbances, and the composite nonlinear feedback technique is employed to design the nominal part of the controller to restrain overshoots and remove steady-state errors considering the tire force saturations; 2) An adaptive super-twisting control approach is proposed to deal with the disturbances with unknown boundaries using a continuous controller while eliminating the chattering effect. The system stability and robustness are proved via Lyapunov approach. CarSim-Simulink simulation has verified the effectiveness of the proposed control approach in the case of the steering fault.

Robust Composite Nonlinear Feedback Path-Following Control for Independently Actuated Autonomous Vehicles With Differential Steering

This paper investigates utilizing the front-wheel differential drive-assisted steering (DDAS) to achieve the path-following control for independently actuated (IA) electric autonomous ground vehicles (AGVs), in the case of the complete failure of the active front-wheel steering system. DDAS, which is generated by the differential torque between the left and right wheels of IA electric vehicles, can be utilized to actuate the front wheels as the sole steering power when the regular steering system fails, and thus avoids dangerous consequences for AGVs. As an inherent emergency measure and an active safety control method for the steering system of electric vehicles, DDAS strategy is a valuable fault-tolerant control approach against active steering system failure. To improve the transient performance of the fault-tolerant control with the DDAS, a novel multiple-disturbance observer-based composite nonlinear feedback (CNF) approach is proposed to realize the path-following control for IA AGVs considering the tire force saturations. The disturbance observer is designed to estimate the external multiple disturbances with unknown bounds. CarSim–Simulink joint simulation results indicate that the proposed controller can effectively achieve the fault-tolerant control and improve the transient performance for path following in the faulted-steering situation.

Robust output-feedback based vehicle lateral motion control considering network-induced delay and tire force saturation

This paper presents a robust H∞ output-feedback vehicle lateral motion control strategy considering network-induced delay and tire force saturation. The unavoidable time delay in the in-vehicle networks degrades the control performance, and even deteriorates the system stability. In addition, the tire lateral force suffers saturation phenomenon, which also deteriorates the control effect in extreme driving conditions. To handle the network-induced control delay and tire force saturation, a robust H∞ controller is presented to regulate the vehicle lateral motion. An output-feedback control schema, which does not need the vehicle lateral velocity, is designed to achieve the desired control performance and reduce the cost of control system. The tire cornering stiffness uncertainty and external disturbances are also considered in the controller design to improve the robustness of the proposed controller. The comparative simulation results based on Carsim-Simulink joint simulation verify the effectiveness and robustness of the proposed control strategy.

Composite Nonlinear Feedback Control for Path Following of Four-Wheel Independently Actuated Autonomous Ground Vehicles

This paper investigates the path-following control problem for four-wheel independently actuated autonomous ground vehicles through integrated control of active front-wheel steering and direct yaw-moment control. A modified composite nonlinear feedback strategy is proposed to improve the transient performance and eliminate the steady-state errors in path-following control considering the tire force saturations, in the presence of the time-varying road curvature for the desired path. Path following is achieved through vehicle lateral and yaw control, i.e., the lateral velocity and yaw rate are simultaneously controlled to track their respective desired values, where the desired yaw rate is generated according to the path-following demand. CarSim–Simulink joint simulation results indicate that the proposed controller can effectively improve the transient response performance, inhibit the overshoots, and eliminate the steady-state errors in path following within the tire force saturation limits.

Robust lateral motion control of four-wheel independently actuated electric vehicles with tire force saturation consideration

The paper presents a vehicle lateral-plane motion stability control approach for four-wheel independently actuated (FWIA) electric ground vehicles considering the tire force saturations. In order to deal with the possible modeling inaccuracies and parametric uncertainties, a linear parameter-varying (LPV) based robust H∞ controller is designed to yield the desired external yaw moment. The lower-level controller operates the four in-wheel (or hub) motors such as the required control efforts can be satisfied. An analytical method without using the numerical-optimization based control allocation algorithms is given to distribute the higher-level control efforts. The tire force constraints are also explicitly considered in the control allocation design. Simulation results based on a high-fidelity, CarSim, full-vehicle model show the effectiveness of the control approach.

LMI Design of a Direct Yaw Moment Robust Controller Based on Adaptive Body Slip Angle Observer for Electric Vehicles

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 (β) observer. In the design strategy of the fuzzy observer, the vehicle dynamics are represented by local models. Initially, local equivalent vehicle models have been built using linear approximations of vehicle dynamics respectively for low and high lateral acceleration operating regimes. The optimal β observer is then designed for each local model using Kalman filter theory. Finally, local observers are combined to form the overall controlled system by using fuzzy rules. These fuzzy rules consequently 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 has been introduced within the fuzzy design and incorporated to improve the accuracy and performance of the controlled system. The controller can then be robustly synthesized based on Linear Matrix Inequalities and using the deviation states model. The controller-observer pair gives good performances in term of stability and presents convincing advantages regarding the real-time implementation issues. The effectiveness of this design approach has been demonstrated in simulations and using real-time experimental data.

Motion Control of Four-Wheel Independently Actuated Electric Ground Vehicles considering Tire Force Saturations

A vehicle stability control approach for four-wheel independently actuated (FWIA) electric vehicles is presented. The proposed control method consists of a higher-level controller and a lower-level controller. An adaptive control-based higher-level controller is designed to yield the vehicle virtual control efforts to track the desired vehicle motions due to the possible modeling inaccuracies and parametric uncertainties. The lower-level controller considering tire force saturation is given to allocate the required control efforts to the four in-wheel motors for providing the desired tire forces. An analytic method is given to distribute the high-level control efforts, without using the numerical-optimization-based control allocation algorithms. Simulations based on a high-fidelity, CarSim, and full-vehicle model show the effectiveness of the control approach.

Electric Vehicle Lateral Dynamics Control based on Instantaneous Cornering Stiffness Estimation and an Efficient Allocation Scheme

AbstractBeyond the establishment of a polution free mobility, electric vehicles show attractive features as far as vehicle motion control is concerned. In this work an electric vehicle equipped with four independent In-Wheel-Motors and active front and rear steering system is considered. The 6 actuators should be controlled in a way to guarantee safe, comfortable and low energy consumption drive. Generally, Linear Time Invariant (LTI) vehicle models are appropriate if the motion of the vehicle does not approach the physical limits of the tire force saturation and road conditions remain constant. Otherwise, they fail to predict the vehicle dynamics. On the other hand the control design approach based on LTI models is straightforward. The approach taken in this contribution is the following: use a robust sliding mode controller based on a slowly linear time varying model, together with an efficient estimation scheme for the instantaneous cornering stiffness in order to prevent the vehice to reach lateral tire force saturation by restricting the possible actuator outputs in a control allocation scheme. Computer simulation runs with the professional vehicle dynamics environment CarSim show good performance of the control scheme. Further work will be the validation with real vehicle experiments and modelling of consumed energy for consideration of energy efficency in the control scheme.

Vehicle Dynamics Control of In-wheel Electric Motor Drive Vehicles Based on Averaging of Tire Force Usage

For in-wheel electric motor drive vehicles, a new vehicle dynamics control which is based on the tire force usage rate is proposed. The new controller adopts non-linear optimal control could manage the interference between direct yaw-moment control and the tire force usage rate. The new control is considered total longitudinal and transverse tire force. Therefore the controller can prevent tire force saturation near tire force limit during cornering. Simulations and test runs by the custom made four wheel drive in-wheel motor electric vehicle show that higher driving stability performance compared to the performance of the same vehicle without control.

Vehicle Yaw Control Using an Active Front Steering System with Measurements of Lateral Tire Forces

We have proposed a design method of an active front wheel steering controller that guarantees closed-loop stability under lateral tire force saturation. The controller uses lateral tire force information to counteract destabilization caused by such saturation. The controller suppresses slip angle magnitude while lateral tire force is saturated. Numerical simulation results confirmed the effectiveness of the proposed method.

603 タイヤ摩擦力制限を考慮した直接ヨーモーメント制御系の設計(機械力学・計測制御I)

603 タイヤ摩擦力制限を考慮した直接ヨーモーメント制御系の設計(機械力学・計測制御I)

Vehicle Yaw Control Using an Active Front Steering System with Measurements of Lateral Tire Forces

We propose a design method of an active front wheel steering controller that guarantees closed-loop stability under the lateral tire forces saturation. The proposed controller utilizes the information on the lateral tire forces to counteract the destabilizing effects caused by the lateral tire force saturation. The controller can suppress the magnitude of the slip angle while the lateral tire forces are in the saturated region. The effectiveness of the proposed method is shown through numerical simulation results.

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.