Phase Portrait Trajectory of a 3DOF Vehicular Dynamic Model

This article formulates a front-wheel-drive three-degree-of-freedom (3DOF) four-wheel planar vehicle model with the Magic Formula tire model. The state variables' evolutions of the model, i.e., trajectories of the model under acceleration and deacceleration conditions, are analyzed. The process of evolution is divided into desirable and undesirable phases based on the response characteristics of the vehicle to the driver input during the process. The trajectories are categorized as unsaturated trajectories and saturated trajectories by the existence of saturated tires during these phases. The response of state variables to driver input under acceleration conditions during undesirable phases are zero or even opposite, while the response of undesirable phases under the deacceleration condition is partially positive. Besides, the existing yaw rate safety envelope is recalibrated by using a longitudinal and lateral tire force coupling model. A more accurate yaw rate safety envelope is obtained from the given driver input. Furthermore, a longitudinal speed safety envelope is proposed according to the relationships among slip angle, yaw rate, and longitudinal speed. These safety envelopes are determined by driver input, tire properties, and grip condition. After overlaying yaw rate and longitudinal speed safety envelopes in the state space, the feasibility of using the safety envelope as trajectory classification criteria is discussed.

Trajectory Tracking Control of Intelligent Electric Vehicles Based on the Adaptive Spiral Sliding Mode

Aiming at the multi-objective control problem of the tracking effect and vehicle stability in the process of intelligent vehicle trajectory tracking, a coordinated control strategy of the trajectory tracking and stability of intelligent electric vehicles is proposed based on the hierarchical control theory. The vehicle dynamics model and trajectory tracking model are established. In order to tackle the chattering problem in the traditional sliding mode controller, an Adaptive Spiral Sliding Mode controller is designed by taking the derivative of the controller as the upper controller, which is intended to reduce the heading deviation and lateral deviation in the trajectory tracking process whilst ensuring the stability of the vehicle itself. In the lower controller, a four-wheel tire force optimal distribution method is designed. According to the requirements of the upper controller, combined with the yaw stability of the vehicle, the directional control distribution of the four-wheel tire force is realized. A joint simulation model was built based on CarSim and Simulink, and simulation experiments were performed. The results show that the proposed control strategy can effectively control the heading deviation and lateral deviation in the vehicle trajectory tracking while ensuring the lateral stability of the vehicle.

An observation algorithm for key motion states of skid-steered wheeled unmanned vehicle

With the increasing demand of military and civilian in the intelligent vehicles, the skid-steering theory has been widely used in unmanned ground vehicles, especially in unmanned military vehicles and unmanned surveillance platforms. Due to its driving environment complex and variable, which requires stricter dynamic control system. In order to improve the active safety performance of the skid-steering unmanned vehicle and develop the key technologies such as behavior decision planning technology, path tracking, and dynamic control technology, it is necessary to develop the dynamic state parameter observation system based on skid-steering theory. In this paper, an observation using Strong Track External Kalman Filter theory with noise matrix adaptive is designed to estimate vehicle kinematic parameters based on a 6 × 6 skid-steered unmanned vehicle. First, kinematic and dynamic model is built to analyze the characters of a skid-steered wheeled vehicle. Then a tire force estimation method based on dynamic model is presented to observe the tire longitude and vertical force. The tire force data is also used by Dugoff nonlinear model. Then an External Kalman Filter theory is designed to estimate vehicle kinematic parameters. To increase the accuracy and the robustness of the observer, the Strong Tracking EKF (STEKF) and noise adaptive adjustment is designed. Finally, a combined simulation using TruckSim and Simulink and the experiment using a 6 × 6 skid-steered unmanned vehicle verifies the efficiency of the observer. Results show that the observer is able to estimate the skid-steered wheeled vehicle states, and it also shows that the yaw rate result in the slip angle difference between each tire.

A Universal Approach to Tire Forces Estimation by Accelerometer-Based Intelligent Tire: Analytical Model and Experimental Validation

ABSTRACT Efforts to improve the performance and safety of vehicles include placing active sensing components (e.g., embedded microsensors) within tires result in intelligent tires. One application of intelligent tire is tire force estimation based on accelerometers. However, its development is limited due to the difficulty of relating the tire force to kinematical information by model-based theory. In this manuscript, a universal approach to tire forces estimation by the accelerometer-based intelligent tire is formulated and experimentally validated. First, a microelectromechanical system accelerometer-based intelligent tire prototype is established with the function of on-board monitoring of tire forces. Then, a theoretical rolling kinematics model is proposed for illustrating the mechanisms of acceleration fields, resulting from the coupling effect of rigid body motion and elastic deformation. An analytical model is formulated to estimate the vertical force in real time. Furthermore, the beam model is adopted to describe lateral deformations of the tire belt, directly linking lateral acceleration and lateral force. Finally, the lateral force can be estimated by lateral acceleration and vertical force already estimated. Based on a universal analytical model, the lateral force estimation method realizes high accuracy under different circumstances, even with unified coefficients, by clarifying and eliminating the influence of ply steer. A field test and two bench experiments have been conducted to fully validate the developed model. It can be concluded that the theoretical-analysis-based estimation model realizes an encouraging tire force estimation application with an intelligent tire hardware system.

Path Tracking Control of Autonomous Vehicle Based on Nonlinear Tire Model

The tire forces of vehicles will fall into the non-linear region under extreme handling conditions, which cause poor path tracking performance. In this paper, a model predictive controller based on a nonlinear tire model is designed. The tire forces are characterized with nonlinear composite functions of the magic formula instead of a simple linear relation model. Taylor expansion is used to linearize the controller, the first-order difference quotient method is used for discretization, and the partial derivative of the composite function is used for matrix transformation. Constant velocity and variable velocity conditions are selected to compare the designed controller with the conventional controller in Carsim/Simulink. The results show that when the tire forces fall in the nonlinear region, two controllers have good stability, and the tracking accuracy of the controller designed in this paper is slightly better. However, after the tire forces become nonlinear, the controller with linear tire force becomes worse, the tracking accuracy is far worse than the controller with the nonlinear tire model, and the vehicle stability is also degraded. In addition, an active steering test platform based on LabVIEW-RT is established, and hardware-in-the-loop tests are carried out. The effectiveness of the designed controller is verified.

Identifying Vehicle Model Parameters Using Remote Mounted Motion Sensor

The recent developments on advanced driver assistance system(ADAS) have extended the capability of sensor systems from surrounding perception to motion estimation. The motion estima?tion provides tri-axial velocity and pose measurements, which open potential benefits for control and state estimation through sensor fusion with the vehicle dynamics model. In this paper we propose an identification method for the vehicle single track model parameters including the relative distance between the vehicle center of gravity and the motion sensor. A linearized tire force model and simplified single track vehicle model are constructed with the corresponding sensor kinematics model. We demonstrate the efficacy of iden?tification performance of the proposed method and confirm the feasibility of the usage of ADAS sensor in vehicle dynamics and vice versa

Identifying Vehicle Model Parameters Using Remote Mounted Motion Sensor

The recent developments on advanced driver assistance system(ADAS) have extended the capability of sensor systems from surrounding perception to motion estimation. The motion estima?tion provides tri-axial velocity and pose measurements, which open potential benefits for control and state estimation through sensor fusion with the vehicle dynamics model. In this paper we propose an identification method for the vehicle single track model parameters including the relative distance between the vehicle center of gravity and the motion sensor. A linearized tire force model and simplified single track vehicle model are constructed with the corresponding sensor kinematics model. We demonstrate the efficacy of iden?tification performance of the proposed method and confirm the feasibility of the usage of ADAS sensor in vehicle dynamics and vice versa

Application of Transient- and Steady-State Acceleration Signals in Intelligent Tires

ABSTRACT The accelerometer-based intelligent tire has gained focus in recent years for its ability to obtain both kinematics and dynamics-related information of the tire. This paper extends the previous steady-state applications of acceleration signals, which mainly estimate tire force, sideslip, and friction coefficient from the steady-state features of acceleration waveforms, to transient acceleration applications. By using the proposed tire mixed Euler–Lagrange rolling model, it is analytically demonstrated that tire rolling acceleration can be decomposed into steady-state and transient-state components from the perspective of kinematics. It is hard to analyze the transient-state component theoretically or split it from the measured signals on real road surfaces; thus, a learning-based algorithm is developed to automatically extract discriminative features without any physical models. With this method, essential information associated with tire transient acceleration could be inferred to help improve driving safety and performance. As the application, tire wear identification with an artificial neural network is validated to be feasible based on complete acceleration signals. The prediction accuracy reaches 98.2% under different test conditions. The proposed acceleration formation mechanism is proved to be effective in explaining tire rolling acceleration as well as guiding to acquire vital information about the tire to improve vehicle safety and performance.

Unified Chassis Control of Electric Vehicles Considering Wheel Vertical Vibrations

In the process of vehicle chassis electrification, different active actuators and systems have been developed and commercialized for improved vehicle dynamic performances. For a vehicle system with actuation redundancy, the integration of individual chassis control systems can provide additional benefits compared to a single ABS/ESC system. This paper describes a Unified Chassis Control (UCC) strategy for enhancing vehicle stability and ride comfort by the coordination of four In-Wheel Drive (IWD), 4-Wheel Independent Steering (4WIS), and Active Suspension Systems (ASS). Desired chassis motion is determined by generalized forces/moment calculated through a high-level sliding mode controller. Based on tire force constraints subject to allocated normal forces, the generalized forces/moment are distributed to the slip and slip angle of each tire by a fixed-point control allocation algorithm. Regarding the uneven road, H∞ robust controllers are proposed based on a modified quarter-car model. Evaluation of the overall system was accomplished by simulation testing with a full-vehicle CarSim model under different scenarios. The conclusion shows that the vertical vibration of the four wheels plays a detrimental role in vehicle stability, and the proposed method can effectively realize the tire force distribution to control the vehicle body attitude and driving stability even in high-demanding scenarios.