Adaptive Robust Control for Driving and Regenerative Braking of Electric Vehicle

2013 ◽  
Vol 441 ◽  
pp. 887-891
Author(s):  
Long Xu ◽  
Jun Ping Wang ◽  
Yuan Bai ◽  
Gai Ling Hu
Keyword(s):  
Robust Control ◽  
Electric Vehicle ◽  
Adaptive Robust Control ◽  
Disturbance Attenuation ◽  
Regenerative Braking ◽  
Stability Robustness ◽  
Recovery System ◽  
And Performance ◽  
The Stability ◽  
Braking Energy Recovery

The driving and braking energy recovery system of electric vehicle faces a lot of uncertainties, including the system parameters and the running environment uncertainties. An adaptive robust control (ARC) is presented in this paper to treat the problems including disturbance and parameter variation in the design of driving and regenerative braking controller. It can enhance the stability robustness and performance robustness. A model of the driving and regenerative braking system is constructed and then the ARC controller is designed. The experiment results show that the controller based on ARC theory has better performance of stability, robustness, and disturbance attenuation than traditional PID controller.

Analysis of Hydraulic Regenerative Braking System for Electric Vehicle

2012 ◽  
Vol 490-495 ◽  
pp. 195-202 ◽  
Author(s):  
Xiao Bing Ning ◽  
Yao Ting Xu ◽  
Qiu Cheng Wang ◽  
Jue Jiang Chen
Keyword(s):  
Electric Vehicle ◽  
Pid Control ◽  
Energy Recovery ◽  
Dynamic Performance ◽  
Regenerative Braking ◽  
Energy Recovery System ◽  
Braking System ◽  
Recovery System ◽  
Driving Range ◽  
Braking Energy Recovery

In order to increase the regenerative braking energy recovery and the dynamic performance of vehicle start and acceleration in the stage of brake, the hydraulic braking energy recovery system was used with the storage battery braking energy recovery system after comparing kinds of regenerative braking recovery plan and energy storage method. The system was used to do simulation and analysis in vehicle dynamic performance and energy recovery efficiency under the PID control and ECE-15 cycle. The system simulation and analysis results show that using hydraulic regenerative braking system in pure electric vehicle can significantly improve the ability of vehicle’s start-acceleration and the increase in vehicle driving range of around 28%.

A computationally efficient adaptive robust control scheme for a quad-rotor transporting cable-suspended payloads

2021 ◽  
pp. 095441002110136
Author(s):  
Nasim Ullah ◽  
Irfan Sami ◽  
Wang Shaoping ◽  
Hamid Mukhtar ◽  
Xingjian Wang ◽  
...  
Keyword(s):  
Robust Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Adaptive Robust Control ◽  
Computationally Efficient ◽  
Control Scheme ◽  
Control Schemes ◽  
Adaptive Laws ◽  
Unknown Disturbances ◽  
The Stability

This article proposes a computationally efficient adaptive robust control scheme for a quad-rotor with cable-suspended payloads. Motion of payload introduces unknown disturbances that affect the performance of the quad-rotor controlled with conventional schemes, thus novel adaptive robust controllers with both integer- and fractional-order dynamics are proposed for the trajectory tracking of quad-rotor with cable-suspended payload. The disturbances acting on quad-rotor due to the payload motion are estimated by utilizing adaptive laws derived from integer- and fractional-order Lyapunov functions. The stability of the proposed control systems is guaranteed using integer- and fractional-order Lyapunov theorems. Overall, three variants of the control schemes, namely adaptive fractional-order sliding mode (AFSMC), adaptive sliding mode (ASMC), and classical Sliding mode controllers (SMC)s) are tested using processor in the loop experiments, and based on the two performance indicators, namely robustness and computational resource utilization, the best control scheme is evaluated. From the results presented, it is verified that ASMC scheme exhibits comparable robustness as of SMC and AFSMC, while it utilizes less sources as compared to AFSMC.

scholarly journals Research on braking energy recovery strategy of electric vehicle based on ECE regulation and I curve

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041987776 ◽  
Author(s):  
Shengqin Li ◽  
Bo Yu ◽  
Xinyuan Feng
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
State Of Charge ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Battery State Of Charge ◽  
Braking Force ◽  
Braking Control ◽  
Braking Energy Recovery

Electric vehicles can convert the kinetic energy of the vehicle into electric energy for recycling. A reasonable braking force distribution strategy is the key to ensure braking stability and the energy recovery rate. For an electric vehicle, based on the ECE regulation curve and ideal braking force distribution (I curve), the braking force distribution strategy of the front and rear axles is designed to study the braking energy recovery control strategy. The fuzzy control method is adopted while the charging power limit of the battery is considered to correct the regenerative braking torque of the motor, the ratio of the regenerative braking force of the motor to the front axle braking force is designed according to different braking strengths, then the braking force distribution and braking energy recovery control strategies for regenerative braking and friction braking are developed. The simulation model of combined vehicle and energy recovery control strategy is established by Simulink and Cruise software. The braking energy recovery control strategy of this article is verified under different braking conditions and New European Driving Cycle conditions. The results show that the control strategy proposed in this article meets the requirements of braking stability. Under the condition of initial state of charge of 75%, the variation of state of charge of braking control strategy in this article is reduced by 8.22%, and the state of charge of braking strategy based on I curve reduces by 9.12%. The braking force distribution curves of the front and rear axle are in line with the braking characteristics, can effectively recover the braking energy, and improve the battery state of charge. Taking the using range of 95%–5% of battery state of charge as calculation target, the cruising range of vehicle with braking control strategy of this article increases to 136.64 km, which showed that the braking control strategy in this article could increase the cruising range of the electric vehicle.

An adaptive robust control scheme for robot manipulators with unknown backlash nonlinearity in gears

2018 ◽  
Vol 41 (10) ◽  
pp. 2789-2802 ◽  
Author(s):  
Soheil Ahangarian Abhari ◽  
Farzad Hashemzadeh ◽  
Mahdi Baradarannia ◽  
Hamed Kharrati
Keyword(s):  
Robust Control ◽  
Controller Design ◽  
Robot Manipulators ◽  
Dead Zone ◽  
Main Idea ◽  
Adaptive Robust Control ◽  
Zone Model ◽  
Robot Trajectory ◽  
Zone Parameter ◽  
The Stability

This paper presents an adaptive robust control algorithm for the nonlinear dynamics of robot manipulators with unknown backlash in gears. The basic nonlinear model of a serial manipulator robot is used for the controller design, and this is combined with the nonlinear proposed dead zone model, based on the input and output torque. The main idea of providing this model is to achieve a dynamic model of the system considering the backlash of the robot joint gears, and having less complexity such that the developed controller does not need the inverse backlash model. The adaptive robust controller is developed, without using the inverse backlash model. The proposed controller is designed based on an unknown dead zone parameter and it guarantees the stability and path tracking of the robot trajectory with unknown dead zone parameter in the desired range. Numerical simulations are conducted to show the effectiveness of the proposed controller. Finally, the efficiency and capability of the proposed controller in dealing with the unknown backlash nonlinearities in gears of the manipulator are demonstrated by experimental results with a five-bar manipulator.

Uniform robust exact differentiator based adaptive robust control for a class of nonlinear systems

2017 ◽  
Vol 40 (9) ◽  
pp. 2901-2911 ◽  
Author(s):  
Zhangbao Xu ◽  
Dawei Ma ◽  
Jianyong Yao
Keyword(s):  
Robust Control ◽  
Nonlinear Systems ◽  
Closed Loop ◽  
Lyapunov Method ◽  
Adaptive Robust Control ◽  
Experimental Results ◽  
Closed Loop System ◽  
Robust Controller ◽  
Performance Simulation ◽  
The Stability

In this paper, an adaptive robust controller with uniform robust exact differentiator has been proposed for a class of nonlinear systems with structured and unstructured uncertainties. The adaptive robust controller is integrated with an uniform robust differentiator to handle the problem of the incalculable part of the derivative of virtual controls and the differential explosion happened in backstepping techniques. The stability of the closed loop system is demonstrated via Lyapunov method ensuring a prescribed transient and tracking performance. Simulation and experimental results are carried out to verify the advantages of the proposed method.

Study of a Method for Improving the Anti-Lock Brake System of Electric Vehicle

2012 ◽  
Vol 157-158 ◽  
pp. 542-545 ◽  
Author(s):  
Liang Chu ◽  
Liang Yao ◽  
Zi Liang Zhao ◽  
Wen Ruo Wei ◽  
Yong Sheng Zhang
Keyword(s):  
Electric Vehicle ◽  
Energy Recovery ◽  
Control Algorithm ◽  
System Structure ◽  
Regenerative Braking ◽  
Threshold Control ◽  
Braking System ◽  
Simulink Model ◽  
Braking Force ◽  
The Stability

The Anti-lock Braking System (ABS) of Electric Vehicle (EV) is improved in this paper. Based on the research of system structure and motor, a new method is proposed to adjust the threshold and coordinate the motor braking force with the friction braking force. So the traditional threshold control algorithm of ABS is improved for the EV. The simulation results based on the MATLAB/Simulink model indicate that the improved ABS can keep the wheels in the stability region and decrease the motor regenerative braking force as soon as possible. The balance between brake safety and energy recovery is achieved through this method.

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