Three phase permanent magnet synchronous motor (PMSM) is a strong coupling and complex nonlinear system. After the coordinate transformation of PMSM model, the static decoupling can be realized between the direct axis and the quadrature axis. However, there are still cross coupling problems in the dynamic regulation process, and the higher the speed, the more serious the coupling. In order to solve the above problems, a current cross coupling compensation controller is added to the current decoupling control of three-phase permanent magnet synchronous motor. The simulation results show that the control strategy has good control effect and can realize the stable operation of three-phase permanent magnet synchronous motor under certain load disturbance.

In the present study, the current control method of the model predictive control is applied to the field-oriented control induction motor. The augmentation model of the motor is initially established based on the stator current equation, which performs the current predictive control and formulates the new cost function by means of tracking error. Then, the influence of parameter error on the current control stability in the prediction model is analysed, and the current static error is corrected according to the correlation between the input and feedback. Finally, a simple and effective three-vector control strategy is proposed. Moreover, three adjacent basic voltage vectors are utilized, and then six candidate voltage vectors are synthesized in each sector to replace eight basic voltage vectors in the conventional model predictive control (MPC). The obtained results show that synthesized vectors, which have arbitrary amplitude and direction, significantly expand the coverage of the system’s control set, reduce the torque and flux pulsation in the conventional MPC, and improve the steady-state performance of the system. Finally, the dSPACE platform is employed to validate the performed experiment. It is concluded that the proposed method can reduce the torque and flux pulse, perform the induction motor current control, and improve the steady-state performance of the system.

In view of the problem that the electrical parameters in the operation of permanent magnetic synchronous motor (PMSM) are more easily affected by conditions such as magnetic path saturation and external temperature changes, resulting in a decrease in operational reliability, a model reference adaptive system (MRAS) parameter identification method based on Popov hyperstability theory is studied. First of all, the mathematical model of PMSM is established, and then, the establishment of a suitable reference model and adjustable model, the use of Popov hyperstability theory design parameter adaptive law, so that the difference between the adjustable model and the reference model output finally converges to 0, to achieve parameter identification of PMSM, effectively identify PMSM inductance, permanent magnet magnetic chain, stabilizer resistance and other major electrical parameters. Finally, the validity of this research method is verified by simulation.

The speed identification method in the vector control system of asynchronous motor without speed sensor is a hot topic in the current research, in which MRAS has been widely used in AC speed control system because of its simple principle and practicality. Due to the change of motor fixed rotor parameters, the estimation of speed by using the general rotor magnetic chain equation will not accurately reflect the real index of the motor. In this paper, a vector control model based on MRAS asynchronous motor speed-less sensor is constructed by reference and adjustable model of integral rotor magnetic chain, Firstly, the mathematical model of asynchronous motor is constructed, the principles of vector control and MRAS related are introduced, and finally the relevant model is constructed according to the super-stability theory to simulate and verify it in simulink environment. The simulation results show that the control strategy is well controlled and can achieve the steady operation of the sensor-less motor under large load disturbance.

In order to improve the accuracy of the BP neural network prediction model to predict the transmission synchronizer shift fault, a BP neural network prediction method based on genetic algorithm optimization is proposed. The characteristics and defects of BP neural network and genetic algorithm are introduced. Further study the relevant technology combining BP neural net-work and genetic algorithm. The genetic algorithm is used to optimize the weight and threshold of BP neural network, and train the BP neural network prediction model to obtain the optimal solution. The advantages of the local search ability of BP-neural network and global search ability of genetic algorithm are fully displayed. The simulation results show that the method has higher accuracy and better nonlinear fitting ability for transmission synchronizer shift fault.

Finite control set-model predictive torque control (FCS-MPTC) depends on the system parameters and the weight coefficients setting. At the same time, since the actual load disturbance is unavoidable, the model parameters are not matched, and there is a torque tracking error. In traditional FCS-MPTC, the outer loopthat is, the speed loopadopts a classic Proportional Integral (PI) controller, abbreviated as PI-MPTC. The pole placement of the PI controller is usually designed by a plunge-and-test, and it is difficult to achieve optimal dynamic performance and optimal suppression of concentrated disturbances at the same time. Aiming at squirrel cage induction motors, this paper first proposes an outer-loop F-ETFC-MPTC control strategy based on a feed-forward factor for electromagnetic torque feedback compensation (F-ETFC). The electromagnetic torque was imported to the input of the current regulator, which is used as the control input signal of feedback compensation of the speed loop; therefore, the capacity of an anti-load-torque-disturbance of the speed loop was improved. The given speed is quantified by a feed-forward factor into the input of the current regulator, which is used as the feed-forward adjustment control input of the speed controller to improve the dynamic response of the speed loop. The range of the feed-forward factor and feed-back compensation coefficient can be obtained according to the structural analysis of the system, which simplifies the process of parameter design adjustment. At the same time, the multi-objective optimization based on the sorting method replaces the single cost function in traditional control, so that the selection of the voltage vector works without the weight coefficient and can solve complicated calculation problems in traditional control. Finally, according to the relationship between the voltage vector and the switch state, the virtual six groups of three vector voltages can be adjusted in both the direction and amplitude, thereby effectively improving the control performance and reducing the flow rate and torque ripple. The experiment is based on the dSPACE platform, and experimental results verify the feasibility of the proposed F-ETFC-MPTC. Compared with traditional PI-MPTC, the feed-forward factor can effectively improve the stability time of the system by more than 10 percent, electromagnetic torque feedback compensation can improve the anti-load torque disturbance ability of the system by more than 60 percent, and the three-vector voltage method can effectively reduce the disturbance.

In recent years, researchers in relevant fields in China and abroad have been attaching more and more importance to the research of SMC (soft magnetic composite) permanent magnet motor, which has greatly improved in volume, deadweight and torque density compared with traditional motor, and more and more about the design and research of this kind of permanent magnet motor. This review summarized and summarized the latest research status and research results of SMC materials at home and abroad, introduced the superiority of SMC material on the motor, the design of the permanent magnet motor and the corresponding iron consumption analysis, and finally summarized the prospect of SMC material in the motor.

In order to settle the questions of the asynchronous motor in the traditional PI control strategy, the parameters are fixed and easy to overshoot, and the poor robustness to the parameter change in the speed sensor-less is not available, this paper studies a vector control scheme of asynchronous motor speed sensor-less based on backward propagation (back propagation) BP neural network control and sliding mode observer. Sliding mode observer based on the relationship between stator flux and stator current of asynchronous motor, a mathematical state equation is deduced, and an observer model is built on the basis of sliding mode adaptive theory, thus realizing the speed estimation. The outer loop PI of motor speed is tuned by BP iterative optimization, compared with the traditional control scheme, this method is easy to realize, which can effectively improve the control accuracy, suppress the disturbance, and save the sensor cost. The correctness and feasibility of the control scheme are verified by the simulation experiment, the observer can realize the observation of stator flux and rotational speed, and the sliding mode observer is robust in the case of load disturbance and a given speed changes.

This paper studies the main indexes of vehicle dynamic performance, and analyzes the requirements of vehicle dynamic Performance Index to drive motor system parameters. In this paper, the various types of driving motors used in electric vehicles are briefly described, and the structural features, application ranges advantages and disadvantages of various driving motors are analyzed. Finally, the development trend and possible new technology of electric vehicle in the future are forecasted.

In twenty-first Century, people's living demand is higher and higher, the SCM application is more and more widespread, and the residents' equipment is constantly intelligent, in which the baby automatic rocking sleep device is a manifestation.For understanding the modern city infant care needs, combined with the development situation both at home and abroad, this paper puts forward a design of intelligent nursing device for baby, analysis device is feasible in theory, through the analysis of the process of care and infant care personnel needs, will demand into the design language, so as to establish the functional framework of infant nursing device, MCU minimum system as the basis, structures of each module, design a baby care device model, so as to assist the care function, ease the pressure on the role of guardian care of infants.The main purpose of this design is to study the diversification of the baby bed, and design a control unit based on single chip microcomputer.The baby bed takes the smallest system of STC89C51 as the main control unit.The external temperature and humidity detection module, the voice sensor detects the baby's crying, and uses the buzzer to play music.

with the accident of Asphyxiation and death in the children's car in recent years, the demand for this kind of dangerous alarm devices.The vehicle dangerous alarm device has both temperature and oxygen concentration monitoring and alarm function .As the core of the main measurement and control system of the vehicle dangerous alarm device, STC89C52 is used to collect, process and display the data of the data .The function of alarm and other functions, The temperature monitoring module uses DS18B20 digital temperature sensor, output signal is all digital; The Oxygen concentration monitoring module uses the potentiometer to replace, through the ADC0809 conversion, carry on the LCD digital display.In this paper, design based on single chip microcomputer on-board danger alarm device structure is simple, the design is unique the research has some significance.

This paper aims at discussing the development process and application of permanent magnet brushless DC motor. By referring to the related literatures, this thesis gives an overview of several common non-position sensor detection technologies, analyzing their strengths and weaknesses as well as a number of new and improved methods in practical applications. Besides, The application situation of the electric door with sensorless permanent magnet brushless DC motor was illustrated.

Because the car headlamp light intensity is too large and it leads to accidents, This paper is based on the initiative to reduce the light intensity of their vehicles according headlights glare or close the high beam and open the lamp method, to achieve the purpose of the glare. The system is AT89C51 microcontroller as the core control, use of photodiode sensor to induction opposite the car headlights light intensity , when opposite car headlights light intensity up to a certain value, photodiode get a signal to the microcontroller ,and then microcontroller sends a signal, to control buzzer sound or not. When the buzzer sounded, using DAC0832 chip to control the brightness of the light emitting diode or control the light on and off and low beam enabled. When enabled for dipped beam, has been more than the antiglare range; after the scope enabled high beam, in order to achieve the anti-dazzle cycle. Through practice, the system has reached the anti-dazzle purpose and has practical value .

The primary principle of anti-vibration on vehicle is introduced.Based on the laboratory bench for vehicle braking-suspension anti-vibration efficiency,the vibration curve of suspension from test car is obtained.The system parameters such as characteristic frequency and damp rate are calculated with the vibration curve.The actual data of experiment is used as sample and the system parameters are identified.The results show that the neural network can provide effectively research for the anti-vibration efficiency of vehicle front suspension.