scholarly journals Differential Steering Control of Four-Wheel Independent-Drive Electric Vehicles

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2892 ◽  
Author(s):  
Jie Tian ◽  
Jun Tong ◽  
Shi Luo
Keyword(s):  
Electric Vehicles ◽  
Dynamic Models ◽  
Reference Model ◽  
Sliding Mode ◽  
Variable Structure ◽  
Front Wheel ◽  
Steering Control ◽  
Sideslip Angle ◽  
Differential Steering ◽  
Skid Steering

This paper investigates the skid steering of four-wheel independent-drive (4WID) electric vehicles (EV) and a differential steering of a 4WID EV with a steer-by-wire (SBW) system in case of steering failure. The dynamic models of skid steering vehicle (SSV) and differential steering vehicle (DSV) are established and the traditional front-wheel steering vehicle with neutral steering characteristics is selected as the reference model. On this basis, sideslip angle observer and two different sliding mode variable structure controllers for SSV and DSV are designed respectively. Co-simulation results of CarSim and Simulink show that the designed controller for DSV not only controls the yaw rate and sideslip angle of DSV to track those of the reference model exactly, but also ensures the robustness of the controlled system compared with the designed controller for SSV. And the differential driving torque needed to realize the differential steering is much smaller than that for skid steering, which indicates the possibility of the differential steering in case of steering failure.

Differential steering-based electric vehicle lateral dynamics control with rollover consideration

2019 ◽  
Vol 234 (3) ◽  
pp. 338-348
Author(s):  
Hui Jing ◽  
Rongrong Wang ◽  
Cong Li ◽  
Jinxiang Wang
Keyword(s):  
Electric Vehicles ◽  
Measurement Problem ◽  
Low Cost ◽  
Steering System ◽  
Front Wheel ◽  
Steering Control ◽  
Lateral Velocity ◽  
Lateral Dynamics ◽  
Vehicle Rollover ◽  
Differential Steering

This article investigates the differential steering-based schema to control the lateral and rollover motions of the in-wheel motor-driven electric vehicles. Generated from the different torque of the front two wheels, the differential steering control schema will be activated to function the driver’s request when the regular steering system is in failure, thus avoiding dangerous consequences for in-wheel motor electric vehicles. On the contrary, when the vehicle is approaching rollover, the torque difference between the front two wheels will be decreased rapidly, resulting in failure of differential steering. Then, the vehicle rollover characteristic is also considered in the control system to enhance the efficiency of the differential steering. In addition, to handle the low cost measurement problem of the reference of front wheel steering angle and the lateral velocity, an [Formula: see text] observer-based control schema is presented to regulate the vehicle stability and handling performance, simultaneously. Finally, the simulation is performed based on the CarSim–Simulink platform, and the results validate the effectiveness of the proposed control schema.

scholarly journals Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Jinghua Guo ◽  
Keqiang Li ◽  
Jingjing Fan ◽  
Yugong Luo ◽  
Jingyao Wang
Keyword(s):  
Electric Vehicles ◽  
Sliding Mode ◽  
Variable Structure ◽  
Control Law ◽  
Time Varying ◽  
Steering Control ◽  
Structure Control ◽  
Adaptive Sliding Mode ◽  
Automatic Steering ◽  
Neural Fuzzy

AbstractThis paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters. Primarily, the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed, and in which the relationship between the look-ahead time and vehicle velocity is revealed. Then, in order to overcome the external disturbances, parametric uncertainties and time-varying features of vehicles, a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles, which includes an equivalent control law and an adaptive variable structure control law. In this novel automatic steering control system of vehicles, a neural network system is utilized for approximating the switching control gain of variable structure control law, and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time. The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory. Finally, the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

scholarly journals Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

2020 ◽  
Author(s):  
Jinghua Guo ◽  
Keqiang Li ◽  
Jinjin Fan ◽  
Yugong Luo ◽  
Jingyao Wang
Keyword(s):  
Electric Vehicles ◽  
Sliding Mode ◽  
Variable Structure ◽  
Control Law ◽  
Time Varying ◽  
Steering Control ◽  
Structure Control ◽  
Adaptive Sliding Mode ◽  
Automatic Steering ◽  
Neural Fuzzy

Abstract This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters. Primarily, the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed, and in which the relationship between the look-ahead time and vehicle velocity is revealed. Then, in order to overcome the external disturbances, parametric uncertainties and time-varying features of vehicles, a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to surprise the lateral dynamic behavior of unmanned electric vehicles, which includes an equivalent control law and an adaptive variable structure control law. In this novel automatic steering control system of vehicles, a neural network system is utilized for approximating the switching control gain of variable structure control law, and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time. The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory. Finally, The results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

scholarly journals Stability Control for Electric Vehicles with Four In-Wheel-Motors Based on Sideslip Angle

2021 ◽  
Vol 12 (1) ◽  
pp. 42
Author(s):  
Kun Yang ◽  
Danxiu Dong ◽  
Chao Ma ◽  
Zhaoxian Tian ◽  
Yile Chang ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Control Method ◽  
Sliding Mode ◽  
Stability Control ◽  
Torque Control ◽  
Wheel Load ◽  
Sideslip Angle ◽  
Distribution Method ◽  
Load Rate ◽  
The Stability

Tire longitudinal forces of electrics vehicle with four in-wheel-motors can be adjusted independently. This provides advantages for its stability control. In this paper, an electric vehicle with four in-wheel-motors is taken as the research object. Considering key factors such as vehicle velocity and road adhesion coefficient, the criterion of vehicle stability is studied, based on phase plane of sideslip angle and sideslip-angle rate. To solve the problem that the sideslip angle of vehicles is difficult to measure, an algorithm for estimating the sideslip angle based on extended Kalman filter is designed. The control method for vehicle yaw moment based on sliding-mode control and the distribution method for wheel driving/braking torque are proposed. The distribution method takes the minimum sum of the square for wheel load rate as the optimization objective. Based on Matlab/Simulink and Carsim, a cosimulation model for the stability control of electric vehicles with four in-wheel-motors is built. The accuracy of the proposed stability criterion, the algorithm for estimating the sideslip angle and the wheel torque control method are verified. The relevant research can provide some reference for the development of the stability control for electric vehicles with four in-wheel-motors.

Methods of Discontinuous Control for the Autonomous Underwater Vehicles

2013 ◽  
Vol 278-280 ◽  
pp. 1473-1476
Author(s):  
Alexander Lebedev
Keyword(s):  
Reference Model ◽  
Sliding Mode ◽  
Autonomous Underwater Vehicles ◽  
Variable Structure ◽  
Underwater Vehicles ◽  
Adjustment Process ◽  
Centralized Control ◽  
Reciprocal Effect ◽  
Discontinuous Control ◽  
Adjustment System

New methods of the synthesis of multi-dimensional robust and adaptive control systems for the centralized control of the spatial motion of autonomous underwater vehicles (AUV) is developed in this paper, such as variable structure system (VSS) and self-adjustment system with reference model. The conditions of the sliding mode existence and the self-adjustment process stability with the presence of essential dynamic reciprocal effect between all control channels are obtained and strictly proved. The application of synthesized discontinuous control provides the high control quality at any variations of the object parameters within the given ranges.

Study on Active Suspension with Variable Structure Control Based on the Fractional Order Exponential Reaching Law

2017 ◽  
Vol 872 ◽  
pp. 337-345
Author(s):  
Yan Dong Chen
Keyword(s):  
Fractional Order ◽  
Reference Model ◽  
Sliding Mode ◽  
Variable Structure Control ◽  
Variable Structure ◽  
Active Suspension ◽  
Mode Switching ◽  
Structure Control ◽  
Reaching Law ◽  
Exponential Reaching Law

Based on the dynamic model of 1/4 vehicle suspension, an active control system is designed using the fractional order exponential reaching law of model following variable structure control strategy. An active suspension with linear quadratic optimal control is used as the reference model. The sliding mode switching surface parameters is designed by pole placement method to ensure the stability of the system. At the same time, combined with the index reaching law proposed by Professor Gao Wei Bing and the definition and properties of fractional index, constructs a similar fractional order exponent reaching law to improve the dynamic quality of sliding mode motion. And in MATLAB, system modeling and controller design are implemented. By setting up experiments, the different suspensions are compared. The results show that compared with the passive suspension, the performance of the vehicle can be improved better, and the performance of the tracking reference model has good tracking performance. Moreover, compared with the integral exponential reaching law, the chattering can be more effectively weakened. Finally, before and after the change of vehicle parameters in the simulation, the results show that the system has good robustness.

The Control Strategy and Experimental Analysis of Electronic Differential Steering for Four Independent Drive Hub Motor Electric Vehicle

2014 ◽  
Vol 1030-1032 ◽  
pp. 1550-1553 ◽  
Author(s):  
Hao Pan ◽  
Run Sheng Song
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Future Development ◽  
Control Strategy ◽  
Experimental Analysis ◽  
Drive System ◽  
Experimental Results ◽  
Steering Control ◽  
Differential Steering ◽  
Differential Control

Wheel hub motor used in drive system of pure electric vehicle has become hot research and future development. Based on a four-wheel independent drive(4WID) electric vehicles with wheel hub motors, the paper has made the research on electronic differential steering control strategy by using Ackermann steering model conditions, and the experimental results have also been analyzed for the actual steering control effects under differential control strategy.

Sliding Mode Control Techniques in E-Learning Systems

2016 ◽  
pp. 78-95
Author(s):  
I. Boiko ◽  
H. Hussein ◽  
A. Al Durra
Keyword(s):  
Sliding Mode Control ◽  
Dynamic Models ◽  
Sliding Mode ◽  
Variable Structure ◽  
Optimal Level ◽  
Learning Systems ◽  
Variable Structure Systems ◽  
Control Techniques ◽  
Mode Control ◽  
E Learning

Perspectives of using sliding mode control in e-learning are discussed. The concepts of variable structure systems and sliding mode control are given. Analysis of convergence based on the second Lyapunov's method is presented. The analysis presented is based on the dynamic models of learning available in the literature. The suitability of the use of sliding mode to adaptation of level of challenge of the tasks in e-learning is demonstrated. It is shown that with frequent enough evaluation of tasks, optimal level of task challenge can be ensured.

Research on Vehicle Stability Based on DYC and AFS Integrated Controller

2013 ◽  
Vol 278-280 ◽  
pp. 1510-1515 ◽  
Author(s):  
Jie Tian ◽  
Ya Qin Wang ◽  
Ning Chen
Keyword(s):  
Control Method ◽  
Sliding Mode ◽  
Stability Control ◽  
Front Wheel ◽  
Vehicle Stability ◽  
Sideslip Angle ◽  
Stable Domain ◽  
Vehicle Stability Control ◽  
Integrated Controller ◽  
Yaw Moment

A new vehicle stability control method integrated direct yaw moment control (DYC) with active front wheel steering (AFS) was proposed. On the basis of the vehicle nonlinear model, vehicle stable domain was determined by the phase plane of sideslip angle and sideslip angular velocity. When the vehicle was outside the stable domain, DYC was firstly used to produce direct yaw moment, which can make vehicle inside the stable domain. Then AFS sliding mode control was used to make the sideslip angle and yaw rate track the reference vehicle model. The simulation results show that the integrated controller improves vehicle stability more effectively than using the AFS controller alone.

scholarly journals A Simple Soft Computing Structure for Modeling and Control

Machines ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 168
Author(s):  
Hemza Redjimi ◽  
József Kázmér Tar
Keyword(s):  
Dynamic Models ◽  
Sliding Mode ◽  
Variable Structure ◽  
Adaptive Controller ◽  
Activation Function ◽  
Approximate Model ◽  
Single Step ◽  
Van Der Pol Oscillator ◽  
Output State ◽  
Incremental Model

Using the interpolation/extrapolation skills of the core function of an iterative adaptive controller, a structurally simple single essential layer neural network-based topological structure is suggested with fast and explicit single-step teaching and data-retrieving abilities. Its operation does not assume massive parallelism, therefore it easily can be simulated by simple sequential program codes not needing sophisticated data synchronization mechanisms. It seems to be advantageous in approximate model-based common, robust, or adaptive controllers that can compensate for the effects of minor modeling imprecisions. In this structure a neuron can be in either a firing or a passive (i.e., producing zero output) state. In firing state its activation function realizes an abstract rotation that maps the desired kinematic data into the space of the necessary control forces. The activation function allows the use of a simple and fast incremental model modification for slowly varying dynamic models. Its operation is exemplified by numerical simulations for a van der Pol oscillator in free motion, and within a Computed Torque type control. To reveal the possibility for efficient model correction, a robust Variable Structure/Sliding Mode Controller is applied, too. The novel structure can be obtained by approximate experimental observations as e.g., the fuzzy models.

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