For Four-wheel Independently Actuated Research Articles

Estimation of Longitudinal Force, Sideslip Angle and Yaw Rate for Four-Wheel Independent Actuated Autonomous Vehicles Based on PWA Tire Model.

This article introduces an efficient and high-precision estimation framework for four-wheel independently actuated (FWIA) autonomous vehicles based on a novel tire model and adaptive square-root cubature Kalman filter (SCKF) estimation strategy. Firstly, a reliable and concise tire model that considers the tire’s nonlinear mechanics characteristics under combined conditions through the piecewise affine (PWA) identification method is established to improve the accuracy of the lateral dynamics model of FWIA autonomous vehicles. On this basis, the longitudinal relaxation length of each tire is integrated into the lateral dynamics modeling of FWIA autonomous vehicle. A novel nonlinear state function, including the PWA tire model, is proposed in this paper. To reduce the impact of the uncertainty of noise statistics on the estimation accuracy, an adaptive SCKF estimation algorithm based on the maximum a posteriori (MAP) criterion is proposed in the estimation framework. Finally, the estimation accuracy and stability of the adaptive SCKF algorithm are verified by the co-simulation of CarSim and Simulink. The simulation results show that when the statistical characteristics of noise are unknown and the target state changes suddenly under critical maneuvers, the estimation framework proposed in this paper still maintains high accuracy and stability.

Adaptive complementary filter-based post-impact control for independently-actuated and differentially-steered autonomous vehicles

This paper investigates a post-impact control (PIC) method for four-wheel independently actuated (FWIA) electric autonomous vehicles (EAVs) after an initial impact. Differential steering angles actuated by differential torques generated from the left and right wheels have been utilized as an inherent redundant control strategy when the steering motor totally fails, to realize the PIC and secondary collision mitigation. To this end, a vehicle state estimation-based PIC strategy is developed in this work, and three contributions have been made as follows: 1) A novel cascaded estimation approach using the adaptive complementary filters (ACF) is proposed to estimate the longitudinal and lateral velocities with low-cost measurement; 2) Experiments on a scaled FWIA EAV with differential steering mechanism have been conducted to verify the proposed ACF approach, indicating that ACF can accurately estimate the longitudinal and lateral velocities; 3) The vehicle velocity estimation-based path planning and following with model predictive control (MPC) strategy are proposed for PIC and for FWIA EAVs, both for the first time. Finally, the verifiable simulation based on the high-fidelity CarSim-Simulink conjoint platform with the experimentally identified vehicle parameters has been conducted, which has verified the proposed ACF-based PIC strategy can effectively avoid the secondary collision and guarantee vehicle stability and control performance.

Robust Adaptive Fault-Tolerant Control of Four-Wheel Independently Actuated Electric Vehicles

In this paper, the tracking control problem for four-wheel independently actuated (FWIA) electric vehicles (EVs) system with actuator fault and unmatched disturbance is investigated. An adaptive fast terminal sliding mode fault-tolerant control (AFTSMFTC) scheme is proposed. First of all, the FWIA electric vehicle (EV) system with actuator fault and unmatched disturbance model is established. Then, a novel composite observer is designed to estimate the state and disturbance of the EV system simultaneously; by introducing an updating law, the fault efficiency factor is reconstructed. Furthermore, in accordance with the estimated information, an AFTSMFTC strategy is proposed based on the tracking error and its derivative information. In the AFTSMFTC scheme, on one hand, two adaptive expressions are contained to realize a self-adapting adjustment to the controller parameters, such that a faster convergence can be guaranteed; on the other hand, the estimated disturbance value is utilized to design the scheme in order to improve the robustness of the tracking performance. Finally, three cases are given to illustrate the effectiveness of the proposed method.

Robust H∞ dynamic output-feedback control for four-wheel independently actuated electric ground vehicles through integrated AFS/DYC

This paper simultaneously addresses the parameter/state uncertainties, external disturbances, input saturations, and actuator faults in the handling and stability control for four-wheel independently actuated (FWIA) electric ground vehicles (EGVs). Considering the high cost of the available sensors for vehicle lateral velocity measurement, a robust H∞ dynamic output-feedback controller is designed to control the vehicle motion without using the lateral velocity information. The investigated parameter/state uncertainties include the tire cornering stiffness, vehicle mass, and vehicle longitudinal velocity. The unmodeled terms in the vehicle lateral dynamics model are dealt as the external disturbances. Faults of the active steering system and in-wheel motors can cause dangerous consequences for driving, and are considered in the control design. Input saturation issues for the tire forces can deteriorate the control effects, and are handled by the proposed strategy. Integrated control with active front steering (AFS) and direct yaw moment (DYC) is adopted to control the vehicle yaw rate and sideslip angle simultaneously. Simulation results based on a high-fidelity and full-car model via CarSim-Simulink show the effectiveness of the proposed control approach.

Integral Sliding Mode-Based Composite Nonlinear Feedback Control for Path Following of Four-Wheel Independently Actuated Autonomous Vehicles

This paper presents an accurate, fast, and robust path-following control approach for four-wheel independently actuated (FWIA) autonomous vehicles via integrated control of the active front-wheel steering (AFS) and direct yaw-moment control (DYC). The path following is realized through simultaneously converging the yaw rate and lateral velocity to their respective desired values which are generated according to the path-following demand. A novel integral sliding mode (ISM)-based composite nonlinear feedback (CNF) control technique considering the multi-input multi-output and the time-varying tracking reference is proposed, which has combined the advantages of CNF control in improving the transient performance and ISM control in guaranteeing good robustness. Chattering is avoided using a continuous ISM controller instead of generally adopted discontinuous ones based on a multivariable super-twisting algorithm (STA). System uncertainties, tire fore saturations, and variation of the desired-path curvature are compositively considered in the ISM-CNF controller design, with the stability of the overall system proved using Lyapunov method. CarSim–Simulink simulations have verified the effectiveness of the proposed controller in improving the transient path-following performance, inhibiting the overshoots, eliminating the steady-state errors, and rejecting the lumped disturbance considering the tire forces saturations and the varying path curvature.

Robust Lateral Motion Control of Electric Ground Vehicles With Random Network-Induced Delays

This paper presents a lateral motion control strategy for four-wheel independently actuated (FWIA) electric ground vehicles that use the controller area network as a communication medium. The proposed controller design aims to guarantee vehicle stability while tracking the desired yaw rate, in spite of random network-induced delays that exist in both the feedback and forward channels. By modeling the random network-induced delays in both channels as two homogenous Markov chains, statistic information of these delays is incorporated in the mode-dependent tracking controller design. The control law consists of state feedback control and integral control. To fully compensate for the network-induced delays, a delay-free stochastic closed-loop system is first obtained in a discrete-time framework by using a system augmentation technique. Then, a robust linear quadratic regulator-based $\boldsymbol{H}_{\infty}$ controller is developed to achieve the tradeoff between the tracking error and the control input while also attenuating the effect of external disturbance. Considering the physical limitation of in-wheel motors, the eigenvalue positions of the state matrix are constrained in a predefined area to further balance the control inputs and transient responses by using pole placement. Finally, an iterative linear matrix inequality algorithm is adopted to obtain the delay-dependent feedback control gains. Simulation results based on a high-fidelity, CarSim, full-vehicle model show the effectiveness of the proposed lateral motion control approach.

Robust control for four wheel independently-actuated electric ground vehicles by external yaw-moment generation

This paper presents a robust controller for four wheel independently-actuated (FWIA) electric ground vehicles to preserve vehicle stability and improve vehicle handling performance. Thanks to the actuation flexibility of FWIA electric ground vehicles, an external yaw moment, which is usually employed to regulate the vehicle yaw and lateral motions, can be easily generated with the torque differences between the left and right side motors. A μ-synthesis control method which can deal with unmodeled dynamics and parametric uncertainties is proposed by taking the external yaw moment as the control input. Simulations with a high-fidelity, CarSim®, full-vehicle model are carried out to demonstrate the effectiveness of the proposed control system. Simulation results in various driving scenarios with vehicle payload variations show the robustness of the proposed controller.w

A Yaw Stability Control Algorithm for Four-Wheel Independently Actuated Electric Ground Vehicles considering Control Boundaries

A hierarchical control algorithm of direct yaw moment control for four-wheel independently actuated (FWIA) electric ground vehicles is presented. Sliding mode control is adopted to yield the desired yaw moment in the higher layer of the algorithm due to the possible modeling inaccuracies and parametric uncertainties. The conditional integrator approach is employed to overcome the chattering issue, which enables a smooth transition to a proportional + integral-like controller, with antiwindup, when the system is entering the boundary layer. The lower level of the algorithm is given to allocate the desired yaw moment to four wheels by means of slip ratio distribution and control for a better grasp of control boundaries. Simulation results, obtained with a vehicle dynamics simulator, Carsim, and the Matlab/Simulink, show the effectiveness of the control algorithm.

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.

Actuator-Redundancy-Based Fault Diagnosis for Four-Wheel Independently Actuated Electric Vehicles

This paper presents a real-time actuator-redundancy-based fault diagnosis approach for four-wheel independently actuated (FWIA) in-wheel motor electric ground vehicles. The tire-road friction coefficient (TRFC), which is usually unknown, needs to be accurately estimated to calculate the in-wheel motor torque and evaluate the fault in real time. An observer is applied to each of the in-wheel motors to generate a TRFC estimate from the respective wheel. The individual estimates of the TRFC are merged using a voting scheme, which can reject the erroneous estimate from the faulty motor. Then, the resulting accurate TRFC estimate is adopted to calculate the residual for each of the in-wheel motors and to detect the possible actuator fault. Experimental results from a prototype FWIA electric ground vehicle are given to show the effectiveness of the proposed fault diagnosis method.

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.