Yaw Stability Control Research Articles

Rollover Control of AGV Combined with Differential Drive, Active Steering, and Centroid Adjustment under Slope Driving Condition

The centroid of the Automated Guided Vehicle (AGV) equipped with the load platform is high, and it is prone to rollover when driving sideways on a slope. To solve this problem, this study proposes an anti-rollover cooperative control strategy combining differential drive, active steering, and load platform. According to the characteristics of AGV, the dynamic coupling of each subsystem is analyzed. The expected yaw stability control torque is calculated based on optimal control. The active steering controller is designed based on the model predictive control. The expected roll control torque is solved by the proposed sliding mode variable structure control method to dynamically adjust the centroid. Evaluation of the overall control system is accomplished by simulations and experiments under different load conditions of the AGV in the lateral driving condition on a slope. Compared with the PI controller, the sideslip angle decreases by 14.62% and 18.24%, and the roll angle decreases by 12.38% and 14.93% under high and low load conditions, respectively. The error between the experimental and simulation results is within 7.8%. It shows that the proposed cooperative control strategy can improve the stability of AGV under different load conditions and reduce the rollover probability when the AGV is driving sideways on a slope. This research provides a theoretical and experimental basis for active safety control of AGVs.

Multidirectional motion coupling based extreme motion control of distributed drive autonomous vehicle

To improve the multidirectional motion control accuracy and driving stability of Distributed Drive Autonomous Vehicles (DDAVs) under extreme conditions, the extreme speed estimation method based on dynamic boundary and the multidirectional motion coupling control law design method based on multi degrees of freedom vehicle dynamic model are proposed. The extreme speed estimation method identifies the stable state of DDAVs by the dynamic boundary composed of yaw rate, sideslip angle and roll angle, and then estimates the extreme speed of the vehicle. The design method of multidirectional motion coupling control law adopts eight-degrees-of-freedom (8-DOF) vehicle dynamic model to design path tracking control law, speed tracking control law, yaw stability control law, and active suspension control law at the same time, so as to realize multidirectional motion coupling control. Based on the above method, the Multidirectional Motion Coupling Control System (MMCCS) of DDAVs is designed. The effectiveness of the proposed method is verified by double-line-shifting and serpentine driving simulations under different road adhesion conditions. The superiority of the method is proved by comparing the existing integrated control method.

Yaw stability control for steer-by-wire vehicle based on radial basis network and terminal sliding mode theory

To further improve the handling and steering performance of steer-by-wire vehicles, a layered control strategy is proposed for the steer-by-wire system, which includes the upper and lower controllers. In the upper control, considering the vehicle sideslip angle and yaw rate, an adaptive sliding mode control strategy is designed for the vehicle lateral stability. Due to the measurement difficulty of the sideslip angle, a robust sliding mode observer is designed to estimate the sideslip angle. In the lower control, a new adaptive global fast terminal sliding mode is proposed to ensure the tracking accuracy of the front wheel angle, considering the dynamic uncertainty characteristics of the steering-by-wire system. The adaptive part of the lower control adopts a radial basis function network, and the adaptive law is designed in Lyapunov sense to make the network approximate the unknown dynamics of the steering-by-wire system, thus the parameters of the steering-by-wire are not required to be completely known. Finally, the joint simulation of MATLAB/Simulink and Carsim verifies that the proposed layered controller has excellent control performance.

Coordinated yaw stability control for extreme path tracking of 4WIDEVs based on predictive control

To improve safety and stability of four-wheel independent drive electric vehicles (4WIDEVs) in extreme path tracking maneuvers, a hierarchical yaw stability control scheme based on predictive control is proposed in this work. The upper-level stability control strategy coordinates active front steering (AFS) and direct yaw moment control (DYC), yielding desired front steering angle and longitudinal force of each tire. The control task is formulated into a finite horizon optimal control problem, which is solved by hybrid model predictive control (hMPC) algorithm. The lower-level slip ratio control strategy calculates and tracks the optimal longitudinal slip ratio of each tire for implementation of the longitudinal tire force distributions in a wide range of road friction coefficient. Based on a qualified piecewise affine (PWA) approximation of lateral tire force models, the stable regions of vehicle states under multiple varying inputs are obtained by analyzing trajectories of fixed points. Furthermore, the control modes of the upper-level control strategy with different control inputs and state constraints are determined by judging bifurcation point of system. Finally, the proposed control approach is verified and compared through the dSPACE-based hardware-in-the-loop (HIL) experiments. The results indicate that the proposed yaw stability control strategy can improve yaw stability performance and reduce the tracking error significantly in extreme situations.

Integration sliding mode control for vehicle yaw and rollover stability based on nonlinear observation

An active rear steering and direct yaw moment (ARS-DYC) coordination control is conducted on the basis of nonlinear fuzzy observation to improve yaw and roll stability control of vehicles under extreme conditions. First, a Takagi–Sugeno (T-S) model of yaw and roll motion is established, and tire nonlinearity at emergency steering is approximated with sector domain. A nonlinear fuzzy observation model is established on the basis of the extended Kalman filter (EKF) to observe the sideslip angle, yaw rate, and roll state accurately under extreme conditions in real time. Second, an improved ideal yaw reference model under the T-S framework is constructed in accordance with the effect of yaw rate on roll stability, and the feedforward control of roll stability is achieved through yaw motion tracking. A fuzzy sliding mode controller is designed on the basis of nonlinear fuzzy observation considering tire sideslip stiffness and actuator constraints, and the coordinated control strategy of layered sliding mode surface for yaw and roll is constructed. Finally, the parameters of sub-sliding mode surface are adjusted with the 4-wire phase plane stability domain, the main sliding mode surface parameters are adjusted following the roll stability index, and the stability of the fuzzy sliding mode controller is proven in the Lyapunov framework. A hardware-in-loop simulation test is established with Carsim-Labview software, and results show that the proposed controller significantly enhances the yaw and roll stability of vehicles under the extreme steering process, due to the accuracy of nonlinear dynamic observation and the flexibility of layered sliding surface coordinated control.

Coordinated control strategy of roll-yaw stability and path tracking for centralized drive electric vehicles

Previous anti-rollover studies only focused on reducing the risk of vehicle rollover, which could not guarantee yaw stability and ignored path tracking problems. This paper presents an integrated control scheme for centralized drive electric vehicles to prevent rollover, enhance the yaw stability, and ensure path tracking capability. The integration of stability control is implemented by switching among several control modes which include four control modes: yaw stability control, roll stability control, roll-yaw stability control, and rollover prevention. A differential drive based on direct yaw moment control (DYC) is employed to improve yaw stability, and the roll stability is improved via longitudinal speed control. Then, the DYC-based single-wheel braking is utilized to prevent rollover. Moreover, a model predictive control (MPC) algorithm is adopted to design the path tracking controller, and then the coordinated control scheme is proposed to realize a trade-off between stability control and path following. Simulation results show that the proposed scheme can realize the rollover prevention function while satisfying the path tracking target and yaw stability.

Integrated Yaw Stability Control of Electric Vehicle Equipped with Front/Rear Steer-by-Wire Systems and Four In-Wheel Motors

This paper presents the integrated motion control method for an electric vehicle (EV) equipped with a front/rear steer-by-wire (SbW) system and four in-wheel motor (IWM). The proposed integrated motion control method aims to maintain stable cornering. To maintain vehicle agility and stability, the lateral force and yaw rate commands of the vehicle are generated by referring to the neutral steering characteristics. The driver’s driving force command, the lateral force command based on the bicycle model, and the yaw moment generated by the high-level controller are distributed into the driving force of each wheel and the lateral force of the front and rear wheels by the yaw moment distribution. Finally, the distributed forces are directly controlled by a low-level controller. To directly control the forces, a driving force observer and a lateral force observer were introduced via driving force estimation in the IWMs and rack force estimation in the SbW system. The control performance is verified through computer simulations.

Yaw stability control of single-trailer truck using steerable wheel at middle axle: hardware-in-the-loop simulation

Yaw stability control of single-trailer truck using steerable wheel at middle axle: hardware-in-the-loop simulation

Coordination control method of autonomous ground electric vehicle for simultaneous trajectory tracking and yaw stability control

A hierarchical trajectory tracking and yaw stability combined control strategy of autonomous ground vehicle within-wheel motor is proposed in this paper to achieve simultaneous and accurate trajectory tracking and vehicle yaw stability control. A trajectory-tracking controller is designed on the basis of model predictive control algorithm, and the ideal front-wheel steering angle requirement is calculated to follow the referenced trajectory. In order to improve the accuracy of vehicle steering control, a vehicle steering controller is designed based on high-order sliding mode control method, in which the control demand of front-wheel steering angle is satisfied by real-time torque control of vehicle steering motor. Simultaneously, a double power reaching rate-based sliding mode control method is applied to design the vehicle yaw stability controller, in which the yaw moment control requirement is met by an optimal oriented tire force allocation algorithm. The simulation and experiment results show that the presented control method can improve the accuracy and real-time performance of trajectory tracking control while ensuring vehicle yaw stability.

Vehicle yaw stability control with a two-layered learning MPC

This paper proposes a novel framework to address the model-vehicle mismatch (MVM) challenge of yaw stability control, which introduces the Gaussian Process-based Model Predictive Control into the classical two-layer structure. In the upper layer, the supervisor controller calculates the compensation torque required for vehicle turning. Gaussian Process regression is employed to compensate model mismatch and unmodelled dynamics. The chance constraints on sideslip angle are converted into double half-space constraints by the normal distribution quantile function. In the lower layer, the subordinate controller utilises the nonlinear slip rate model to distribute torque to the wheels in the form of braking torque. A new assignment rule of braking torque weight is proposed according to the yaw torque analysis. The stability of the two-layered learning MPC is ensured through proof and simulation. In the Simulink and Carsim co-simulation environment, the superiority of the proposed method is verified in the task of rapid double-lane change. Compared with the traditional MPC-based yaw stability controller, the proposed method has increased the stability tracking index and energy consumption index by around 13% and 8%.

Distributed Drive Electric Bus Handling Stability Control Based on Lyapunov Theory and Sliding Mode Control

To improve the handling stability of distributed drive electric buses, a vehicle stability control system based on direct yaw moment control (DYC) with a hierarchical control structure was designed. Considering that the vehicle dynamics system is highly nonlinear, a nonlinear controller based on Lyapunov stability theory was designed to calculate the required additional yaw moment of the vehicle in the upper controller. In the lower controller, the additional yaw moment is distributed to four wheel-side motors according to the equal proportion torque distribution method, and the direction of wheel-side motor output torque is determined based on the steering state of the vehicle. A co-simulation based on Simulink and Trucksim was conducted to verify the designed controller under two extreme conditions. Simulation results indicate that the proposed method performs feasibly and effectively in the handling stability of vehicles. Compared with traditional sliding mode control (SMC), the proposed control strategy can significantly reduce the chattering of the system, which provides a theoretical basis for the application of this yaw stability control method in engineering practice.

Yaw and lateral stability control based on predicted trend of stable state of the vehicle

This study proposes an approach to the yaw and lateral stability of the vehicle that considers their steady-state trend. This study designs a new linear time-varying model predictive control (LTV-MPC) method based on the 2DOF vehicle model. The tire model curve of the magic formula is simplified into two straight lines to replace the nonlinear characteristic of tires and reduce the solution time of the controller under the premise of a good tracking effect. The lateral stiffness of tires is selected according to the predicted trend of stable state of the vehicle. Simulation results show that, under extreme conditions, the proposed method can effectively track the reference vehicle sideslip angle and yaw rate. The real-time performance of the controller is substantially improved compared with NMPC.

Vehicle yaw stability control: literature review

Vehicle yaw stability control: literature review

Vehicle yaw stability control: literature review

Vehicle yaw stability control: literature review

Research on Yaw Stability Control of Multi-axle Electric Vehicle with In-Wheel Motors Based on Fuzzy Sliding Mode Control

Research on Yaw Stability Control of Multi-axle Electric Vehicle with In-Wheel Motors Based on Fuzzy Sliding Mode Control

Yaw stability control of automated guided vehicle under the condition of centroid variation

The centroid of an automated guided vehicle (AGV) changes due to the irregular position and uneven weight of the cargo on the load platform, which affects the completion of the handling task between stations in intelligent factories. This paper presents a hierarchical control strategy to improve yaw stability considering centroid variation. Firstly, the vehicle body and hub motor models are established based on dynamics. Secondly a hierarchical controller is designed by using the method of extension theory, model predictive control and sliding mode control. Then based on CarSim and Simulink, the low-speed step co-simulation condition of the AGV is carried out. Compared to the uncontrolled condition, the maximum deviation of the yaw rate is reduced from 0.58 to 0.52 rad/s, and the difference with the theoretical value is reduced from 16 to 4%; the maximum deviation of the centroid sideslip angle is reduced from − 0.84 rad to − 0.77 rad, and the difference with the theoretical value is reduced from 12 to 3%. Finally, a four-wheel drive and four-wheel steering AGV are manufactured to carry out inter station steering experiments in simulated factory environment on different road adhesion coefficients. The difference between simulation and experiment is less than 5%. The results show that the designed controller is effective, and the research can provide theoretical and experimental basis for the low-speed steering control stability of AGV.

Dynamic-boundary-based lateral motion synergistic control of distributed drive autonomous vehicle

To improve the path tracking accuracy and yaw stability of distributed drive autonomous vehicles (DDAVs) under extreme working conditions, a cooperative lateral motion control method based on the dynamic boundary is proposed to prevent different road adhesion conditions from affecting the motion stability of DDAVs. Based on the analysis of the DDAV lateral dynamics system coordination mechanism, a dynamic boundary considering the pavement adhesion coefficient is proposed, and the Lateral Motion Synergistic Control System (LMSCS) is designed. The LMSCS is divided into the coordination, control, and executive layers. The coordination layer divides the control domain into the stable, quasi-stable, and unstable domains by the dynamic boundary, and coordinates the control strength of the path following control and yaw stability control. In the control layer, the path following control and yaw stability control laws are designed based on the global fast terminal sliding mode. The executive layer estimates the expected steering wheel angle and expected additional wheel torque. Joint simulations under double line shifting conditions confirmed that LMSCS reflects the impact of the road attachment conditions and improves the path tracking accuracy and vehicle yaw stability. The LMSCS has better overall performance than existing lateral motion control methods.

Modelling and experimental validation of an EV torque distribution strategy towards active safety and energy efficiency

Electric vehicles (EVs) have promisingly contributed to the decarbonization of the transportation sector. Torque distribution in energy management is vital to enhance EV safety and efficiency; however, its nonlinearity and real-time executability have not been extensively researched. This paper proposes an integrated torque distribution strategy that simultaneously considers vehicle security and dynamic power allocation. In the upper active safety layer, the yaw stability control and active front steering control are coupled to maintain vehicle stability. Additionally, a linear time-varying model predictive controller is developed to address the system nonlinearity and online executability problems. In the lower energy distribution layer, the motor efficiency and dynamic tire-slip power are simultaneously optimized to maintain EV energy conservation. Numerical simulations and hardware experiments are conducted in this study. The results demonstrate that the proposed integrated strategy is superior to other typical torque distribution strategies in terms of reducing the risk of emergent accidents. Moreover, the energy consumption of the powertrain is reduced by 13.4% and 14.2% under the steering and straight driving conditions, respectively. Overall, our study further promotes the practical application of EVs in the future automotive market and lays a solid foundation for intelligent torque distribution in autonomous EVs.

An Adaptive Nonsingular Fast Terminal Sliding Mode Control for Yaw Stability Control of Bus Based on STI Tire Model

Due to the bus characteristics of large quality, high center of gravity and narrow wheelbase, the research of its yaw stability control (YSC) system has become the focus in the field of vehicle system dynamics. However, the tire nonlinear mechanical properties and the effectiveness of the YSC control system are not considered carefully in the current research. In this paper, a novel adaptive nonsingular fast terminal sliding mode (ANFTSM) control scheme for YSC is proposed to improve the bus curve driving stability and safety on slippery roads. Firstly, the STI (Systems Technologies Inc.) tire model, which can effectively reflect the nonlinear coupling relationship between the tire longitudinal force and lateral force, is established based on experimental data and firstly adopted in the bus YSC system design. On this basis, a more accurate bus lateral dynamics model is built and a novel YSC strategy based on ANFTSM, which has the merits of fast transient response, finite time convergence and high robustness against uncertainties and external disturbances, is designed. Thirdly, to solve the optimal allocation problem of the tire forces, whose objective is to achieve the desired direct yaw moment through the effective distribution of the brake force of each tire, the robust least-squares allocation method is adopted. To verify the feasibility, effectiveness and practicality of the proposed bus YSC approach, the TruckSim-Simulink co-simulation results are finally provided. The co-simulation results show that the lateral stability of bus under special driving conditions has been significantly improved. This research proposes a more effective design method for bus YSC system based on a more accurate tire model.

Observation of Dynamic State Parameters and Yaw Stability Control of Four-Wheel-Independent-Drive EV

Vehicle yaw stability control is an important part of the active safety of electric vehicles. In order to realize the yaw stability control of vehicles, this paper takes 4-WID electric vehicles as the research object, studies the nonlinear estimation of the state parameters of the lateral stability dynamic system and the yaw stability control strategy. The vehicle state parameter estimation strategy, based on the unscented Kalman filter (UKF) algorithm and the model predictive control algorithm, are designed to control the vehicle yaw stability, which realizes the safe and stable driving of the vehicle. Through CarSim–Simulink joint simulation and hardware-in-the-loop (HIL) experiments based on MicroAutoBox, the effectiveness and real-time performance of the designed control strategy are fully verified, which accelerate the development process of the vehicle controller, and realizes the safe and stable driving of the vehicle.