CarSim-Simulink Co-simulation Research Articles

Research on Active Obstacle Avoidance Control Strategy for Intelligent Vehicle Based on Active Safety Collaborative Control

Aiming at the issue of active obstacle avoidance control for intelligent vehicles under emergency, an active safety collaborative control system integrated with adaptive cruise control (ACC), rear steering control (RSC), and rollover braking control (RBC) is developed. The proposed novel control architecture consists of a supervisor, an upper controller, and a lower controller. The supervisor decides which control mode to be used based on multi-sensors information of the driving vehicle. Active rear wheel steering based on lateral acceleration feedback and active braking control strategies based on fuzzy PID are added into the control model to enhance driving stability. To make the vehicle motion control model suitable for highway path tracking with obstacle avoidance under emergency, a priority is given to the RBC controller even though the vehicle speed is lower than the expected speed when the rollover index exceeds the safety threshold. A nonlinear vehicle simulation model is established to validate the proposed control scheme based on Carsim. Finally, a Carsim-Simulink co-simulation model is constructed, and simulation results show that the proposed integrated control strategy based on active safety collaborative control has good performance in both path tracking and driving stability, and has better stability of rollover under emergency.

Influence of vehicle parameters on handling characteristics and its control using torque vectoring

Handling characteristics of any vehicle refer to its directional control and stability for given steering input. The vehicle parameters such as mass, mass moment of inertia and location of C.G. play a vital role and decide handling response of vehicle under different scenarios. Safe drive is ensured by vehicle’s responses such as yaw rate, roll rate and vehicle lateral acceleration. This paper presents steady state and transient state simulation of XUV 500 model in accordance with ISO 4138 and ISO 3888 test standards using CarSim-Simulink Co-simulation. Influence of changes in above mentioned parameters on Vehicle response during both tests is investigated. Further, control of power train output using torque vectoring is implemented in both tests and its effect on vehicle response is evaluated. The results show that understeer tendency of the vehicle is reduced in steady state test (Constant radius test: ISO 4138). Critical vehicle responses of yaw rate, roll rate, lateral acceleration and path tracking showed improvement during the DLC manoeuvre (ISO 3888) hence, improving stability at higher lateral accelerations.

Integrated yaw and rollover control based on differential braking for off-road vehicles with mechanical elastic wheel

Aiming at the issue of yaw and rollover stability control for off-road vehicles with non-pneumatic mechanical elastic wheel (MEW), an integrated control system based on fuzzy differential braking is developed. By simplifying the structure of the MEW, a corresponding fitting brush tire model is constructed and its longitudinal and lateral tire force expressions are set up, respectively. Then, a nonlinear vehicle simulation model with MEW is established to validate the proposed control scheme based on Carsim. The designed yaw and rollover control system is a two-level structure with the upper additional moment controller, which utilizes a predictive load transfer ratio (PLTR) as the rollover index. In order to design the upper integrated control algorithm, fuzzy proportional-integral-derivative (PID) is adopted to coordinate the yaw and rollover control, simultaneously. And the lower control allocator realizes the additional moment to the vehicle by differential braking. Finally, a Carsim-simulink co-simulation model is constructed, and simulation results show that the integrated control system could improve the vehicle yaw and roll stability, and prevent rollover happening.

Sideslip Angle Fusion Estimation Method of an Autonomous Electric Vehicle Based on Robust Cubature Kalman Filter with Redundant Measurement Information

Accurate and reliable estimation information of sideslip angle is very important for intelligent motion control and active safety control of an autonomous vehicle. To solve the problem of sideslip angle estimation of an autonomous vehicle, a sideslip angle fusion estimation method based on robust cubature Kalman filter and wheel-speed coupling relationship is proposed in this paper. The vehicle dynamics model, tire model, and wheel speed coupling model are established and discretized, and a robust cubature Kalman filter is designed for vehicle running state estimation according to the discrete vehicle model. An adaptive measurement-update solution of the robust cubature Kalman filter is presented to improve the robustness of estimation, and then, the wheel-speed coupling relationship is introduced to the measurement update equation of the robust cubature Kalman filter and an adaptive sideslip angle fusion estimation method is designed. The simulations in the CarSim-Simulink co-simulation platform and the actual vehicle road test are carried out, and the effectiveness of the proposed estimation method is validated by corresponding comparative analysis results.

Passive actuator-fault-tolerant path following control of autonomous ground electric vehicle with in-wheel motors

This paper investigates the fault-tolerant path following control problem of autonomous ground electric vehicles with in-wheel motors through hierarchical control strategy. The sliding mode observer with boundary layer is designed to estimate the vehicle state, and the time-delay estimation method is used to compute the actuator fault. Considering the actuator fault, the fault-tolerant path following control strategy is proposed, in which the upper layer controller is developed to achieve path following control and guarantee vehicle stability simultaneously by sliding mode control method, and the lower layer controller is presented to achieve the control efforts of upper layer controller by adaptive orientated tire force allocation method. The simulations are implemented in the CarSim-Simulink co-simulation platform, and the simulation results have verified the effectiveness of proposed fault-tolerant path following control method.

Vehicle Velocity Estimation Fusion with Kinematic Integral and Empirical Correction on Multi-Timescales

Accurate and reliable vehicle velocity estimation is greatly motivated by the increasing demands of high-precision motion control for autonomous vehicles and the decreasing cost of the required multi-axis IMU sensors. A practical estimation method for the longitudinal and lateral velocities of electric vehicles is proposed. Two reliable driving empirical judgements about the velocities are extracted from the signals of the ordinary onboard vehicle sensors, which correct the integral errors of the corresponding kinematic equations on a long timescale. Meanwhile, the additive biases of the measured accelerations are estimated recursively by comparing the integral of the measured accelerations with the difference of the estimated velocities between the adjacent strong empirical correction instants, which further compensates the kinematic integral error on short timescale. The algorithm is verified by both the CarSim-Simulink co-simulation and the controller-in-the-loop test under the CarMaker-RoadBox environment. The results show that the velocities can be accurately and reliably estimated under a wide range of driving conditions without prior knowledge of the tire-model and other unavailable signals or frequently changeable model parameters. The relative estimation error of the longitudinal velocity and the absolute estimation error of the lateral velocity are kept within 2% and 0.5 km/h, respectively.

A path and velocity planning method for lane changing collision avoidance of intelligent vehicle based on cubic 3-D Bezier curve

A novel path and velocity planning method for lane changing collision avoidance of intelligent vehicle based on cubic 3-D Bezier curve is proposed in this paper to enhance the flexibility of path and guarantee the conformity to the realistic lane changing maneuver. Owing to the characteristic of 3-D Bezier curve, the velocity information is appended to the path to establish a real-time correspondence between them. In the XY plane, the integrated path is divided into a collision avoidance path and a lane changing path, which is combined with two asymmetrical Bezier curves. And the velocity planning of two paths is implemented by the same curve in the Z axis. The objective functions and dynamic constraints are formulated to solve the optimal problems of the path and velocity planning for satisfying different traffic situations. The simulations are performed in the CarSim-Simulink co-simulation platform and the results show the performance and effectiveness of the proposed approach.

Passive fault-tolerant path following control of autonomous distributed drive electric vehicle considering steering system fault

Abstract In the path following process, once vehicle steering system fails, the common path following control system will not work properly, and even worse, the vehicle will be seriously deviated from the ideal path and the risk of vehicle instability will also increase. Reliable fault-tolerant control strategy can promote the autonomous vehicle to maintain stability and path following accuracy in case of failure. In this paper, a passive fault-tolerant path following control method of autonomous distributed drive electric vehicle is presented considering the vehicle steering system fault. The reduced-order Kalman filter is applied to estimate the vehicle sideslip angle and the vehicle steering system fault. The hierarchical control strategy was developed, and in the upper layer controller, the adaptive sliding mode control method is proposed to facilitate the fault-tolerant path following controller and used to improve the lateral stability and anti-roll performance of vehicle and ensure path following accuracy at the same time, using the estimated sideslip angle and steering system fault as inputs. In the lower layer controller, a novel adaptive orientated tire force allocation method is proposed to execute the control efforts of upper layer controller. The simulations are implemented in the CarSim-Simulink co-simulation platform, and the effectiveness of proposed fault-tolerant path following control method is verified.

Design of Vehicle Running States-Fused Estimation Strategy Using Kalman Filters and Tire Force Compensation Method

Accurate and reliable vehicle state estimation results are very significant to the active safety, energy optimization, and the intelligent control of vehicles. In this paper, to improve the accuracy and adaptability of vehicle running state estimation, the vehicle running states fused estimation strategy is presented for in-wheel motor drive electric vehicle using the Kalman filters and tire force compensation method. The concept of electric drive wheel model (EDWM) is developed and deduced, and then, considering that the EDWM is a nonlinear model with an unknown input, the design concept of high-order sliding mode observer is used to construct the state space equation of longitudinal force. To improve the accuracy and the reliability of vehicle state estimation, an overall estimation strategy with information fusion and tire force compensation is designed, in which a weighted square-root cubature Kalman filter with an adaptive covariance matrix of measurement noise is developed for observer design. Finally, the simulations in CarSim-Simulink co-simulation model and experiments are carried out, and the effectiveness of the designed estimation strategy is validated.

Simultaneous path following and lateral stability control of 4WD-4WS autonomous electric vehicles with actuator saturation

A simultaneous path following and lateral stability control method was presented for four-wheel independent drive and four-wheel independent steering (4WD-4WS) autonomous electric vehicles based on Hamilton energy function with the actuator saturation being considered in this paper. The hierarchical control strategy including upper layer controller and lower layer controller is used for simultaneous path following and lateral stability control. In the upper layer controller, the vehicle motion controller is designed using Hamilton energy function control theory and the convergence and stability of controller was proved, the control demand of simultaneous path following and lateral stability was obtained and messaged to the lower layer controller. In the lower layer controller, the orientated tire force allocation method was used to execute the control demand by real-time tire force allocation control of four wheels. The simulations are performed in the CarSim-Simulink co-simulation platform, and the effectiveness of proposed control method was verified.

Estimation of maximum road friction coefficient based on Lyapunov method

With the real time and accurate information of motor torque and rotation speed of the four-in-wheel-motordrive electric vehicles, a slip based algorithm for estimating maximum road friction coefficient is designed using Lyapunov stability theory. Modified Burckhardt tire model is used to describe longitudinal slip property of the tire. By introducing a new state variable, a nonlinear estimator is proposed to estimate the longitudinal tire force and the maximum road friction coefficient simultaneously. With the appropriate selection of estimation gain, the convergence of the estimation error of the tire longitudinal force and maximum road friction coefficient is proved through Lyapunov stability analysis. In addition, the error is exponentially stable near the origin. Finally the method is validated with Carsim-Simulink co-simulation and real vehicle tests under multi working conditions in acceleration situation which demonstrate high computational efficiency and accuracy of this method.