A New Approach of Position Sensorless Control for Brushless DC Motor

2020 ◽  
Vol 15 (1) ◽  
pp. 65-76
Author(s):  
N. Hemalatha ◽  
S. Nageswari
Keyword(s):  
Permanent Magnets ◽  
Sensorless Control ◽  
Control Technique ◽  
Bldc Motor ◽  
Zero Crossing ◽  
Brushless Dc ◽  
Detection Circuit ◽  
Field Programmable ◽  
Artificial Neural Network Ann ◽  
Position Sensorless

Background: Position sensorless control technique for Permanent Magnets-Brush Less Direct Current (PM-BLDC) motor drive is considered in this paper. Materials and Methods: A new estimation based on sensorless technique is proposed for PMBLDC motor. Artificial Neural Network (ANN) is aided for the purpose. Results: The inputs to the ANN are the voltages of PM-BLDC motor and it estimates the sample signals to feed Zero Crossing Point (ZCP) detection circuit. The ZCP detection circuit provides ZCP signals for commutation logic which gives the commutation sequence to power switches. In order to provide the correct sample signal to ZCP detection circuit, the ANN is well trained by Genetic Algorithm (GA). The proposed sensor less control model is implemented in MATLAB/SIMULINK working platform. Conclusion: Field Programmable Gate Array (FPGA) is used to implement the proposed method. Experimental results verify the analysis and demonstrate the advantages of the proposed method.

scholarly journals Sensorless Control of BLDC Motor using Flux Linkage Based Algorithm

2019 ◽  
Vol 8 (6) ◽  
pp. 1549-1556
Keyword(s):  
Sensorless Control ◽  
Digital Signal ◽  
Open Loop ◽  
Control Technique ◽  
Bldc Motor ◽  
Zero Crossing ◽  
Detection Techniques ◽  
Rotor Position ◽  
Low Speeds ◽  
Hall Sensors

The performance of Conventional sensorless back-emf detection techniques for BLDC Motor is poor at low speeds, since at zero and low speeds the magnitude of back-emf is very less. This causes failure of zero crossing instant detection. This paper presents a new Sensorless Control Technique for BLDC motor drive to estimate the rotor position accurately even at zero and low speeds. A new algorithm has been developed to estimate the rotor position based on the prediction of stator flux linkages. The main advantage of the proposed technique is that the flux linkages are independent of the speed. For starting of the motor an open loop starting method was adopted. By implementing this technique the Meta heuristic digital signal control systems like PWM/ADC, PLL are avoided in order to make motor control easy and economical. To verify the accuracy of the proposed technique it is compared with existing hall sensors controlled BLDC drive operation. The validity of proposed scheme is verified through Simulation.

Modeling and Simulation of Sensorless Control of BLDC Motor Based on Submersible Pump

2013 ◽  
Vol 312 ◽  
pp. 786-790
Author(s):  
Zi Kuan Zhang
Keyword(s):  
Sensorless Control ◽  
Hall Sensor ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Submersible Pump ◽  
Work Condition ◽  
Zero Crossing ◽  
Brushless Dc ◽  
Motor Control System ◽  
Permanent Magnet Brushless Dc

In this paper, modeling selects sensorless control of permanent magnet brushless DC motor in terms of work condition of submersible pump under water. Motor reduced by Hall sensor so that maintenance. Motor was controlled by state space and back EMF zero-crossing in Matlab/Simulink, and constitute total simulation system along with the other modules. Eventually, motor character was estimated in accordance with waveforms of simulation, which offers foundation for the design of actual motor control system.

scholarly journals Development of a high-quality brushless dc electric drive systems model

Vestnik IGEU ◽  
2020 ◽  
pp. 31-45
Author(s):  
T.H. Abuziarov ◽  
A.S. Plehov ◽  
A.B. Dar’enkov ◽  
A.I. Ermolaev
Keyword(s):  
Electric Drive ◽  
Electric Motor ◽  
Permanent Magnets ◽  
Structural Features ◽  
Bldc Motor ◽  
Electric Drives ◽  
Brushless Dc ◽  
Systems Model ◽  
Semiconductor Converter ◽  
Torque Pulsations

When designing electric drives based on brushless DC motors with permanent magnets (BLDC), which have low level torque pulsations, the problem of modelling non-standard topological solutions appears. The known models of BLDC motors are either based on the assumptions about the symmetry of the stator pa-rameters of the electric motor and/or the ideal form of the phase back-EMF waveform, which reduce the accuracy of evaluating the effectiveness of the proposed solutions or prove unusable for modelling an operation of the electric motor with a non-standard semiconductor converter. It is necessary to develop a mathematical model of the BLDC motor-based electric drive that takes into account the structural features of the electric motor and allows for semiconductor converter configuration variability. The model is designed in the Matlab Simulink environment. The verification is carried out by comparing the modelling results with experimental data obtained previously by other researchers. The proposed method for generating phase back-EMF in the BLDC motor model provides the possibility for the user to set the EMF form templates independent for each phase. The proposed method for stator circuit simulating provides the user with access to each of the stator windings leads as well as with the possibility of asymmetric determination of each parameter of the electric motor. Upon verification, it has been shown that the difference in the control points between the simulated and experimental speed-torque curves does not exceed 3,5 %. The developed model allows analyzing the static and dynamic characteristics of operation modes of non-standard topology BLDC motor-based electric drives taking into account the stator pa-rameters asymmetry and the real phase back-EMF waveform. The specified features of the model allow exploring the operation of the designed electric drive, taking into account the BLDC motor and converter design. The model can be applied when checking atypical design decisions and when changing the set parameters of the electric drive and restrictions on working conditions and target functions to refine the control system algorithms and automate the search for optimal parameters of the motor and the semiconductor converter.

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