scholarly journals A driver model–based direct yaw moment controller for in-wheel motor electric vehicles

2019 ◽  
Vol 11 (9) ◽  
pp. 168781401987731
Author(s):  
Qiguang Wang ◽  
Ye Zhuang ◽  
Jiannan Wei ◽  
Konghui Guo
Keyword(s):  
Driving Simulator ◽  
Sliding Mode ◽  
Driver Model ◽  
Torque Distribution ◽  
Yaw Rate ◽  
Model Based ◽  
Control Set ◽  
The Difference ◽  
Driver’S Intention ◽  
Yaw Moment

In this article, a driver model–based direct yaw moment controller, selected as the upper controller, is developed, of which the control target is determined through a reference driver model in accordance with the driver’s intention. The sliding surface is chosen by the difference between the desired yaw rate and the real output yaw rate. Then, the desired yaw moment is calculated by the sliding mode control. In the lower controller, a novel control torque distribution strategy is designed based on the analysis of the tire characteristics. In addition, an admissible control set of the control torques is calculated in real time through an embedded tire model “UniTire.” Finally, a driver-in-the-loop experiment, via the driving simulator, is conducted to verify the proposed direct yaw moment controller.

Vehicle Direct Yaw Moment Control with Longitudinal Forces Distribution

2014 ◽  
Vol 709 ◽  
pp. 331-334
Author(s):  
Man Hong Huang ◽  
Huan Shen ◽  
Yun Sheng Tan
Keyword(s):  
Control System ◽  
Reference Model ◽  
Sliding Mode ◽  
Stability Control ◽  
Yaw Rate ◽  
Vehicle Stability Control ◽  
Braking Torque ◽  
Stability Control System ◽  
Yaw Moment Control ◽  
Yaw Moment

In this paper, a vehicle stability control system is proposed to improve vehicle comfort, handling and stability. The control system includes reference model, DYC controller and Distributer. Reference model is used to obtain the desired yaw rate. DYC controller determines the desired yaw moment by means of sliding-mode technique. Distributer, based on maneuverability and comfort, distributes driving torque or braking torque according to the desired yaw rate. Simulation result shows that the proposed control algorithm can improve vehicle handling and stability effectively.

scholarly journals Direct Yaw Moment Control for Enhancing Handling Quality of Lightweight Electric Vehicles with Large Load-To-Curb Weight Ratio

2019 ◽  
Vol 9 (6) ◽  
pp. 1151 ◽  
Author(s):  
Pongsathorn Raksincharoensak ◽  
Sato Daisuke ◽  
Mathias Lidberg
Keyword(s):  
Experimental Study ◽  
Vehicle Dynamics ◽  
Driving Simulator ◽  
Feedback Gain ◽  
Lane Change ◽  
Vehicle Handling ◽  
Feed Forward ◽  
Yaw Rate ◽  
Rate Feedback ◽  
Yaw Moment

In this paper a vehicle dynamics control system is designed to compensate the change in vehicle handling dynamics of lightweight vehicles due to variation in loading conditions and the effectiveness of the proposed design is verified by simulations and an experimental study using a fixed-base driving simulator. Considering the electrification of future mobility, the target vehicle of this research is a lightweight vehicle equipped with in-wheel motors that can generate an additional direct yaw moment by transverse distribution of traction forces to control vehicle yawing as well as side slip motions. Previously, the change in vehicle handling dynamics for various loading conditions have been analyzed by using a linear two-wheel vehicle model in planar motion and a control law of the DYC system based on feed-forward of front steering angular velocity and feedback of vehicle yaw rate. The feed-forward controller is derived based on the model following control with approximation of the vehicle dynamics to 1st-order transfer function. To make the determination of the yaw rate feedback gain model-based and adaptable to various vehicle velocity conditions, this paper selects a method where the yaw rate feedback gain in the DYC system is determined in a way that the steady-state yaw rate gain of the controlled loaded vehicle matches the gain of the unloaded vehicle. The DYC system is simulated in a single lane change maneuver to confirm the improved responsiveness of the vehicle while simulations of a double-lane change maneuver with a driver steering model confirms the effectiveness of the DYC system to support tracking control. Finally, the effectiveness of the proposed DYC system is also verified in an experimental study with ten human drivers using a fix-based driving simulator.

Torque vectoring control system for distributed drive electric bus under complicated driving conditions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Liang Su ◽  
Zhenpo Wang ◽  
Chao Chen
Keyword(s):  
Control System ◽  
Feedback Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Steering Wheel ◽  
Content Type ◽  
Yaw Rate ◽  
Torque Vectoring ◽  
Driving Conditions ◽  
Yaw Moment

Purpose The purpose of this study is to propose a torque vectoring control system for improving the handling stability of distributed drive electric buses under complicated driving conditions. Energy crisis and environment pollution are two key pressing issues faced by mankind. Pure electric buses are recognized as the effective method to solve the problems. Distributed drive electric buses (DDEBs) as an emerging mode of pure electric buses are attracting intense research interests around the world. Compared with the central driven electric buses, DDEB is able to control the driving and braking torque of each wheel individually and accurately to significantly enhance the handling stability. Therefore, the torque vectoring control (TVC) system is proposed to allocate the driving torque among four wheels reasonably to improve the handling stability of DDEBs. Design/methodology/approach The proposed TVC system is designed based on hierarchical control. The upper layer is direct yaw moment controller based on feedforward and feedback control. The feedforward control algorithm is designed to calculate the desired steady-state yaw moment based on the steering wheel angle and the longitudinal velocity. The feedback control is anti-windup sliding mode control algorithm, which takes the errors between actual and reference yaw rate as the control variables. The lower layer is torque allocation controller, including economical torque allocation control algorithm and optimal torque allocation control algorithm. Findings The steady static circular test has been carried out to demonstrate the effectiveness and control effort of the proposed TVC system. Compared with the field experiment results of tested bus with TVC system and without TVC system, the slip angle of tested bus with TVC system is much less than without TVC. And the actual yaw rate of tested bus with TVC system is able to track the reference yaw rate completely. The experiment results demonstrate that the TVC system has a remarkable performance in the real practice and improve the handling stability effectively. Originality/value In view of the large load transfer, the strong coupling characteristics of tire , the suspension and the steering system during coach corning, the vehicle reference steering characteristics is defined considering vehicle nonlinear characteristics and the feedforward term of torque vectoring control at different steering angles and speeds is designed. Meanwhile, in order to improve the robustness of controller, an anti-integral saturation sliding mode variable structure control algorithm is proposed as the feedback term of torque vectoring control.

Torque vectoring system design for hybrid electric–all wheel drive vehicle

2020 ◽  
Vol 234 (10-11) ◽  
pp. 2680-2692
Author(s):  
Jeongmin Cho ◽  
Kunsoo Huh
Keyword(s):  
Sliding Mode ◽  
Combustion Engine ◽  
Traction Force ◽  
Torque Distribution ◽  
Handling Performance ◽  
Tire Force ◽  
Wheel Drive ◽  
Torque Vectoring ◽  
Hybrid Electric ◽  
Driver’S Intention

A torque vectoring system is designed for the hybrid electric–all wheel drive vehicle where the front and rear wheels are powered by the combustion engine and electric motors, respectively. The vehicle provides enhanced handling performance by a twin motor drive unit that can distribute the driving and regenerative braking torques to the rear-left and rear-right wheels independently. Based on the driver’s intention, a sliding mode controller is designed to calculate the desired traction force and yaw moment for the vehicle. The force distribution between the front and rear axles is investigated considering the principle of the friction circle, and characteristics of the engine and drive motors. The vertical tire force is estimated using the random walk Kalman filter for the proportional distribution between the front and rear longitudinal forces. For the torque distribution between the rear-left and rear-right wheels, an optimization problem is formulated by considering the constraints of the friction circle and motor characteristics. The proposed algorithm is evaluated in a simulation environment first by reflecting the characteristics of the hybrid electric–all wheel drive modules. Then, the test vehicle is utilized to validate the handling performance experimentally and to compare with the uncontrolled cases.

scholarly journals Lane Departure Avoidance Control for Electric Vehicle Using Torque Allocation

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Yiwan Wu ◽  
Zhengqiang Chen ◽  
Rong Liu ◽  
Fan Li
Keyword(s):  
Electric Vehicle ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Lower Layer ◽  
Yaw Rate ◽  
Lane Departure ◽  
Dangerous Driving ◽  
Braking Torque ◽  
Avoidance Control ◽  
Yaw Moment

This paper focuses on the lane departure avoidance system for a four in-wheel motors’ drive electric vehicle, aiming at preventing lane departure under dangerous driving conditions. The control architecture for the lane departure avoidance system is hierarchical. In the upper controller, the desired yaw rate was calculated with the consideration of vehicle-lane deviation, vehicle dynamic, and the limitation of road adhesion. In the middle controller, a sliding mode controller (SMC) was designed to control the additional yaw moment. In the lower layer, the yaw moment was produced by the optimal distribution of driving/braking torque between four wheels. Lane departure avoidance was carried out by tracking desired yaw response. Simulations were performed to study the effectiveness of the control algorithm in Carsim®/Simulink® cosimulation. Simulation results show that the proposed methods can effectively confine the vehicle in lane and prevent lane departure accidents.

Torque Distribution Control for Multi-Wheeled Combat Vehicle

2014 ◽  
Author(s):  
Hossam Ragheb ◽  
Moustafa El-Gindy ◽  
Hossam Kishawy
Keyword(s):  
Lateral Acceleration ◽  
Pid Controllers ◽  
Torque Distribution ◽  
Yaw Rate ◽  
Bicycle Model ◽  
Torque Vectoring ◽  
Combat Vehicle ◽  
Simulation Results ◽  
Driving Torque ◽  
Yaw Moment

Multi-wheeled combat vehicles behavior depends not only on the available total driving torque but also on its distribution among the drive axles/wheels. In turn, this distribution is largely regulated by the drivetrain layout and its torque distribution devices. In this paper, a multi-wheeled (8×4) combat vehicle bicycle model has been developed and used to obtain the desired yaw rate and lateral acceleration to become reference for the design of the controllers. PID controllers were designed as upper and lower layers of the controllers. The upper controller develops the corrective yaw moment, which is the input to the lower controller to manage the independent torque distribution (torque vectoring) among the driving wheels. Several simulation maneuvers have been performed at different vehicle speeds using Matlab/Simulink-TruckSim to investigate the proposed torque vectoring control strategy. The simulation results with the proposed controller showed a significant improvement over conventional driveline, especially at severe maneuvers.

Helicopter Motion Control Using Model-Based Sliding Mode Controller

2008 ◽  
Vol 12 (4) ◽  
pp. 342-347 ◽  
Author(s):  
Gesang Nugroho ◽  
◽  
Zahari Taha
Keyword(s):  
Motion Control ◽  
Rate Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Longitudinal Velocity ◽  
Control Law ◽  
Sliding Mode Controller ◽  
Lateral Velocity ◽  
Yaw Rate ◽  
Model Based

This paper describes a model-based controller design for helicopter using the sliding mode approach. The controller design assumes that only measured output are available and uses sliding mode observer to estimate all states of the system. The estimated states are then used to construct a model reference sliding mode control law. Simulation shows good performance for lateral velocity, longitudinal velocity, vertical velocity and yaw rate control.

Torque Vectoring Control for Handling Improvement of 4WD EV

2013 ◽  
Vol 765-767 ◽  
pp. 1893-1898
Author(s):  
Xia Xu ◽  
Lu Xiong ◽  
Yuan Feng
Keyword(s):  
Sliding Mode ◽  
Control Level ◽  
Control Law ◽  
Yaw Rate ◽  
Bicycle Model ◽  
Torque Vectoring ◽  
Parameter Variations ◽  
Upper Level ◽  
Traction Distribution ◽  
Yaw Moment

Exploiting the structural merit that electric motors can be controlled precisely in speed und torque, this paper investigates the use of Torque Vectoring Control (TVC) for improving handling of electric vehicles. The strategy consists of two control levels. The upper level controller layer achieves reference yaw rate tracking, by using the 2-DOF planar bicycle model with a linear tire model to calculate the desired yaw rate. Then with sliding mode control law the desired yaw moment is determined. The lower control level determines control inputs for four driving motors by means of optimum traction distribution. Simulations are carried out by using the co-simulation of vehicle dynamics software CarSim and Simulink to verify the effectiveness of this control system and the effects of parameter variations (friction coefficient and throttle).

scholarly journals Sliding Mode Integrated Control for Vehicle Systems Based on AFS and DYC

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Chao Lu ◽  
Jing Yuan ◽  
Genlong Zha
Keyword(s):  
Sliding Mode ◽  
Integrated Control ◽  
Sideslip Angle ◽  
Yaw Rate ◽  
Direct Yaw Moment Control ◽  
Vehicle Systems ◽  
Yaw Moment Control ◽  
Moment Control ◽  
Two Degree Of Freedom ◽  
Yaw Moment

This paper has investigated an integrated control of active front steering (AFS) and direct yaw-moment control (DYC) for vehicle systems. First of all, the desired yaw rate and sideslip angle are estimated by using a two-degree-of-freedom (2-DOF) model of the vehicle system. On this basis, the actual sideslip angle is estimated by means of an observer. Then, the sliding mode control (SMC) is developed for AFS and DYC, respectively, to guarantee that the actual yaw rate and the sideslip angle track their reference signals. Additionally, the disturbance observer (DOB) technique is introduced to further improve the control performance. Finally, the simulation results validate the superiority of the AFS and DYC integrated control by using CarSim software during the following conditions: double lane change and side wind disturbance.

scholarly journals Research on Steering Stability Control Strategy of Four-wheel Independent Electric Drive Special Vehicles

2021 ◽  
Vol 248 ◽  
pp. 02041
Author(s):  
Liao Zili ◽  
Shu Xin ◽  
Cai Lichun ◽  
Zhang Linyun
Keyword(s):  
Driving Force ◽  
Sliding Mode ◽  
Stability Control ◽  
Utilization Rate ◽  
Force Distribution ◽  
Sideslip Angle ◽  
Distribution Method ◽  
Yaw Rate ◽  
Optimization Function ◽  
Yaw Moment

In order to solve the steering stability problem of a special four-wheel independent electric vehicle, a dynamic model of the vehicle was established to analyze the cause of vehicle instability. A steering stability controller was designed, which included the upper yaw moment controller and the lower driving force distribution controller. Based on the sliding mode control algorithm, the yaw moment controller determines the yaw moment required while the vehicle is moving by controlling the yaw rate and sideslip angle. Based on the safety distribution method, the driving force distribution controller selects the sum of tire utilization rate as the optimization function to realize the optimal distribution of yaw moment. Software of MATLAB/Simulink and CarSim were used to build a co-simulation platform, and the designed steering stability controller was analyzed and verified. The simulation results show that the steering stability controller is helpful to improve the steering ability and handling stability of the vehicle in the extreme working conditions.

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