Research of parameter self-learning fuzzy control strategy in motor control system for electric vehicles

2009 ◽  
Author(s):  
Jian Zhang ◽  
Xuhui Wen ◽  
Lili Zeng
Keyword(s):  
Motor Control ◽  
Control System ◽  
Fuzzy Control ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Motor Control System ◽  
Fuzzy Control Strategy ◽  
Self Learning

Development of Experiment Platform of PMSM Control System in Electric Vehicles

2014 ◽  
Vol 635-637 ◽  
pp. 1241-1245
Author(s):  
Li Lin ◽  
Hong Zhi Cui ◽  
Hu Zhu
Keyword(s):  
Motor Control ◽  
Control System ◽  
Permanent Magnet ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Permanent Magnet Synchronous Motor ◽  
Strategy Study ◽  
Experiment Platform ◽  
Motor Control System ◽  
Vector Control System

In order to test the efficiency of motor control strategy, we developed a platform based on DSP2812,named permanent magnet synchronous motor control system which used in vehicle. The algorithm of vector control system is proved effective to modify parameters and debug. And the researches provide the experiment basis of motor control strategy study.

Simulation Study on ESP Fuzzy Control Based on Road Automatic Identification

2014 ◽  
Vol 1044-1045 ◽  
pp. 863-867
Author(s):  
Yan Rong Fu ◽  
Li Xian Ren ◽  
Guo Ye Wang ◽  
Hai Jing Hou
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Strategy ◽  
High Speed ◽  
Degrees Of Freedom ◽  
Integrated Control ◽  
Automatic Identification ◽  
Electronic Stability Program ◽  
Slip Ratio ◽  
Fuzzy Control Strategy

ESP (Electronic Stability Program) is a kind of active safety device which can comprehensively improve the brake, drive and high speed performance of the automobile. Mastering the key technologies of ESP control system plays an important role in improving the performance of ESP. Vehicle dynamic model and engine model with 9 degrees of freedom of one passenger car were established based on vehicle and tire force analysis. The ESP fuzzy control model based on slip ratio control was established. The optimal slip ratio under different pavements was confirmed by using road recognition method. ESP fuzzy control was realized under MATLAB/Simulink environment. And through the split road simulation prove the validity of the road recognition algorithm, and the effectiveness of the fuzzy control strategy. The simulation and the debugging results indicate that the ESP fuzzy control strategy based on road automatic identification works well, and obviously improves automobile stability under critical situations. And all of these make a good foundation for the further research and development for the ESP integrated control system.

Energy Control of HEV Based on Fuzzy Controller Optimized by Particle Swarm Optimization

2014 ◽  
Vol 936 ◽  
pp. 2155-2159 ◽  
Author(s):  
Li Yan Zhao ◽  
Niao Na Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Fuzzy Control ◽  
Optimization Algorithm ◽  
Control Strategy ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Energy Control ◽  
Swarm Optimization ◽  
Fuzzy Control Strategy ◽  
Self Learning

Energy control of HEV plays a very important role in the process of HEV design, which is directly related to the safety and feasibility. Considering the drive system of HEV is nonlinear and complex, a fuzzy control strategy which is combined with particle swarm optimization algorithm is designed to realize the energy control of HEV. Fuzzy control strategy does not need to built accuracy mathematics model and has good robustness, but it mostly depends on engineering experience and has poor ability of self-learning. So particle swarm optimization algorithm has been added to solve these disadvantages of fuzzy control strategy. In conclusion, this method can not only keep the advantage of fuzzy control strategy, but also has ability of self-learning and self-adapt because of particle swarm optimization added. And the simulation proves that this method is feasible and effective.

Research on Brushless DC Motor Control System for Electric Vehicle

2013 ◽  
Vol 850-851 ◽  
pp. 661-664
Author(s):  
Si Yang Liu ◽  
Dong Zhang
Keyword(s):  
Motor Control ◽  
Control System ◽  
Integrated Circuits ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Brushless Dc ◽  
Dc Motor Control ◽  
Motor Control System

In order to improve the controllability and safety of electric vehicle, the flexibility of the motor control system, and ensure the service life of the motor controller, a kind of brushless DC motor control system that used microcontroller with special integrated circuits is suggested in this paper. Introduced the control scheme and operational principle of the control system, given the main hardware circuit, and expounded the control strategy and software design of system. In this control system, the microcontroller is mainly used to control special integrated circuits, implement good man-machine conversation and control strategy, as well as the management of the lead-acid battery; Special integrated circuits main to control the motor, alleviate the pressure of microcontroller effectively, guarantee the microcontroller to complete other work better. The test result indicates that the control system have a simple structure, response quickly, good reliability.

Fuzzy Control Strategy of the Mixed Magnetic Levitation Bearing Rotor System

2012 ◽  
Vol 184-185 ◽  
pp. 1566-1569
Author(s):  
Xiao Bin Zhou ◽  
Li Zeng ◽  
Zheng Jie Xu ◽  
Dao Tian Hu ◽  
Yan Neng Yang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Strategy ◽  
Magnetic Levitation ◽  
Magnetic Suspension ◽  
Displacement Sensor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Fuzzy Control Strategy ◽  
Control Principle

This paper proposes a Fuzzy Control strategy of magnetic levitation bearing rotor according to the mixed magnetic levitation bearing. Combined with electromagnetic winding working principle, this paper uses the self-sensing displacement self-diagnosing system instead of the special displacement sensor, makes a no sensor self-diagnosing magnetic suspension control system, controls the system by the fuzzy PID (proportional, integral and differential) controller, and builds a mathematical model of the control system. Analyzing the fuzzy rules and fuzzy control principle of the fuzzy PID controller setting parameters, this paper has a fuzzy simulation for the system.

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