Collaborative Control with Nonlinear Observer for the Stability of Electric Vehicles

2020 ◽  
Author(s):  
Yan Ma ◽  
Jian Chen ◽  
Junmin Wang ◽  
Deepak Narang
Keyword(s):  
Electric Vehicles ◽  
Nonlinear Observer ◽  
Collaborative Control ◽  
The Stability

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.

scholarly journals Desain dan analisis pengaruh parameter PI dan variasi kecepatan pada respon sistem kontrol arah hadap prototype kendaraan listrik

2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Afif Caesar Distara ◽  
Fatkhur Rohman
Keyword(s):  
Control System ◽  
Steady State ◽  
Electric Vehicles ◽  
Rise Time ◽  
Small Error ◽  
Settling Time ◽  
System Stability ◽  
Prototype System ◽  
Stability Parameters ◽  
The Stability

Electric vehicles are alternative vehicles that carry energy efficient. At this time the dominant vehicle uses ordinary wheels so that it will become an obstacle in the maneuver function that requires movement in various directions. With mechanum wheels the vehicle can move in various directions by adjusting the direction of rotation of each wheel. The problem is choosing the right control system for the control system needed by the vehicle. The purpose of this study is to determine and analyze the effect of variations in the value of PI (Proportional Integral) and speed of the vehicle to the stability response of the system to control the direction of prototype electric vehicles. This study method is an experiment that is by giving a treatment, then evaluating the effects caused by the research object. The results of this study can be concluded that the variation of PI constant values and speed variations have an effect on the stability parameters of the system, namely rise time, settling time, overshot, and steady state error. To get the best system stability response results can use the constant value PI Kp = 2; and Ki = 17; where the stability response of the system for direction control at each speed condition has a fairly good value with a fast rise time, fast settling time, small overshot and a small error steady state compared to other PI constant values in this study.Keywords: mechanum wheel, PI control, direction, prototype, system stability

scholarly journals Nonlinear Position Control Using Only Position Feedback under Position Errors and Yaw Constraints for Air Bearing Planar Motors

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1354
Author(s):  
Wonhee Kim ◽  
Donghoon Shin ◽  
Youngwoo Lee
Keyword(s):  
Position Control ◽  
Position Error ◽  
Nonlinear Observer ◽  
Closed Loop System ◽  
Tracking Errors ◽  
Position Errors ◽  
Full State ◽  
Position Feedback ◽  
Position Controller ◽  
The Stability

In this paper, we propose a nonlinear position control using only position feedback to guarantee the tolerances for position tracking errors and yaw. In the proposed method, both mechanical and electrical dynamics are considered. The proposed method consists of the nonlinear position controller and nonlinear observer. The nonlinear position controller is designed by a backstepping procedure using the barrier Lyapunov function to satisfy the constraints of position error and yaw. The nonlinear observer is developed to estimate full state using only position feedback. The stability of the closed-loop system is proven using Lyapunov and input-to-state stabilities. Consequently, the proposed method satisfies the constraints of position error and yaw using only position feedback for the planar motor.

scholarly journals Development of a Kernel Extreme Learning Machine Model for Capacity Selection of Distributed Generation Considering the Characteristics of Electric Vehicles

2019 ◽  
Vol 9 (12) ◽  
pp. 2401
Author(s):  
Zhongdong Yin ◽  
Jingjing Tu ◽  
Yonghai Xu
Keyword(s):  
Extreme Learning Machine ◽  
Distributed Generation ◽  
Electric Vehicles ◽  
Distribution Network ◽  
Support Vector ◽  
Kernel Extreme Learning Machine ◽  
Learning Machine ◽  
The Stability ◽  
Capacity Selection ◽  
Selection Of

The large-scale access of distributed generation (DG) and the continuous increase in the demand of electric vehicle (EV) charging will result in fundamental changes in the planning and operating characteristics of the distribution network. Therefore, studying the capacity selection of the distributed generation, such as wind and photovoltaic (PV), and considering the charging characteristic of electric vehicles, is of great significance to the stability and economic operation of the distribution network. By using the network node voltage, the distributed generation output and the electric vehicles’ charging power as training data, we propose a capacity selection model based on the kernel extreme learning machine (KELM). The model accuracy is evaluated by using the root mean square error (RMSE). The stability of the network is evaluated by voltage stability evaluation index (Ivse). The IEEE33 node distributed system is used as simulation example, and gives results calculated by the kernel extreme learning machine that satisfy the minimum network loss and total investment cost. Finally, the results are compared with support vector machine (SVM), particle swarm optimization algorithm (PSO) and genetic algorithm (GA), to verify the feasibility and effectiveness of the proposed model and method.

scholarly journals Optimal Charging Navigation Strategy Design for Rapid Charging Electric Vehicles

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 962 ◽  
Author(s):  
Wangyi Mo ◽  
Chao Yang ◽  
Xin Chen ◽  
Kangjie Lin ◽  
Shuaiqi Duan
Keyword(s):  
Electric Vehicles ◽  
Power Grid ◽  
Harmonic Distortion ◽  
Traffic Information ◽  
Local Power ◽  
Real Time Traffic ◽  
Regulation Scheme ◽  
Navigation Strategy ◽  
The Stability ◽  
Grid Operation

Electric vehicles (EVs) have become an efficient solution to making a transportation system environmentally friendly. However, as the number of EVs grows, the power demand from charging vehicles increases greatly. An unordered charging strategy for huge EVs affects the stability of a local power grid, especially during peak times. It becomes serious under the rapid charging mode, in which the EVs will be charged fully within a shorter time. In contrast to regular charging, the power quality (e.g.,voltages deviation, harmonic distortion) is affected when multiple EVs perform rapid charging at the same station simultaneously. To reduce the impacts on a power grid system caused by rapid charging, we propose an optimal EV rapid charging navigation strategy based on the internet of things network. The rapid charging price is designed based on the charging power regulation scheme. Both power grid operation and real-time traffic information are considered. The formulated objective of the navigation strategy is proposed to minimize the synthetic costs of EVs, including the traveling time and the charging costs. Simulation results demonstrate the effectiveness of the proposed strategy.

LAG SYNCHRONIZATION OF THE FRACTIONAL-ORDER SYSTEM VIA NONLINEAR OBSERVER

2011 ◽  
Vol 25 (29) ◽  
pp. 3951-3964 ◽  
Author(s):  
HAO ZHU ◽  
ZHONGSHI HE ◽  
SHANGBO ZHOU
Keyword(s):  
Numerical Simulation ◽  
Fractional Order ◽  
Stability Theorem ◽  
Nonlinear Observer ◽  
Order System ◽  
Fractional Order Systems ◽  
Lag Synchronization ◽  
Systematic Method ◽  
Fractional System ◽  
The Stability

In this paper, based on the idea of nonlinear observer, lag synchronization of chaotic fractional system with commensurate and incommensurate order is studied by the stability theorem of linear fractional-order systems. The theoretical analysis of fractional-order systems in this paper is a systematic method. This technique is applied to achieve the lag synchronization of fractional-order Rössler's system, verified by numerical simulation.

Adaptive coordinated leader–follower control of autonomous over-actuated electric vehicles

2016 ◽  
Vol 39 (12) ◽  
pp. 1798-1810 ◽  
Author(s):  
Jinghua Guo ◽  
Yugong Luo ◽  
Keqiang Li
Keyword(s):  
Control System ◽  
Electric Vehicles ◽  
Formation Control ◽  
Level Control ◽  
Inverse Control ◽  
Level Control System ◽  
Actuation System ◽  
Uniform Ultimate Boundedness ◽  
The Stability ◽  
High Level

In this paper, the leader–follower formation control problem of autonomous over-actuated electric vehicles on a highway is studied. As the autonomous over-actuated electric vehicles have the characteristics of non-linearities, external disturbances and strong coupling, a novel coordinated three-level control system is constructed to supervise the longitudinal and lateral motions of autonomous electric vehicles. Firstly, an adaptive terminal sliding high-level control algorithm is designed to compute a vector of total forces and torque of vehicles, and the stability of the high-level control system is proven via Lyapunov analysis where uniform ultimate boundedness of the closed-loop signals is guaranteed. Then, a pseudo-inverse control allocation algorithm, which can achieve fault tolerance and reconfiguration of the redundant tyre actuation system, is presented to generate the desired longitudinal and lateral tyre forces. Then, a separate low-level controller consisting of an inverse tyre model and two inner loops for each wheel is designed to achieve its desired forces. Finally, simulation results demonstrate that the proposed control system not only enhance the tracking performance, but also improve the stability and riding comfort of autonomous over-actuated electric vehicles in a platoon.

scholarly journals A comparative study of nonlinear circle criterion based observer and H∞ observer for induction motor drive

2019 ◽  
Vol 10 (3) ◽  
pp. 1229
Author(s):  
Farid Berrezzek ◽  
Wafa Bourbia ◽  
Bachir Bensaker
Keyword(s):  
Comparative Study ◽  
Induction Motor ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Optimization Approach ◽  
Lmi Optimization ◽  
Circle Criterion ◽  
True State ◽  
The Stability

<span lang="EN-US">This paper deals with a comparative study of circle criterion based nonlinear observer<em> </em>and <em>H<sub>∞</sub></em> observer for induction motor (IM) drive. The  advantage of the circle criterion approach for nonlinear observer design is that it directly handles the nonlinearities of the system with less restriction  conditions in contrast of the other methods which attempt to eliminate them. However the <em>H<sub>∞</sub></em> observer guaranteed the stability taking into account disturbance and noise attenuation. Linear matrix inequality (LMI) optimization approach is used to compute the gains matrices for the two observers. The simulation results show the superiority of <em>H<sub>∞</sub></em> observer in the sense that it can achieve convergence to the true state, despite the nonlinearity of model and the presence of disturbance.</span>

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