PMSM was modeled in simulink with the help of model ..

Pmsm Phd Thesis pmsm phd thesis Sensorless Control of Permanent-Magnet Synchronous Motor ..

FPGA Based Sensorless Control of a Permanent Magnet Synchronous Motor

This thesis is a detailed study of how two error correction schemes affect the precision of shaft position estimation in state-observer techniques for sensorless control surface-mounted Permanent Magnet Synchronous Motors (PMSM), variance correction and variable PI regulation. A novel sensorless estimation technique based on Linear Kalman Filter (LKF) through constant variance correction is proposed and compared with the conventional Flux Linkage Observer (FLO) method and other state-estimation sensorless control techniques namely, Extended Kalman Filter (EKF), variable variance correction, Single Dimension Luenberger (SDL) observer and Full-Order Luenberger (FOLU) observer both through variable PI regulation. These five sensorless control techniques for PMSM are successfully implemented in the same lab-based hardware platform, i.e. full digital float-point-type DSP control inverter-fed PMSM system. Experiments are reported on each sensorless method covering position estimation, speed response, self-startup and load behaviour. Intensive analysis has also been carried out on the impact of error correction of estimated position on the steady/dynamic PMSM characteristics with different sensorless approaches. The experiment demonstrates that the novel Linear Kalman Filter can achieve the minimum average position estimation error throughout the electrical cycle of the five sensorless estimation techniques during no load operation at rated speed and also makes PMSM capable of self-startup for any initial rotor position except the dead area. A speed response experiment for LKF shows that individual speed estimation can be extracted directly from LKF state estimation for sensorless control PMSM. Experiments on the five sensorless methods proves that position error correction scheme is the dominating factor for state estimation sensorless control PMSM and better dynamic/steady control performance can be achieved using a variance correction scheme applied in EKF/LKF than with variable PI regulation applied in SDL/FOLU. The thesis also concludes that the novel Linear Kalman Filter is an optimised cost-effective sensorless estimation method for the PMSM drive industry compared with classic and Flux Linkage observers/Extended Kalman Filters.

Sensorless Control of Permanent-Magnet Synchronous Motor - VBN

Sensorless control of permanent magnet synchronous motor (PMSM)

This thesis analyzes saliency-based sensorless control methods for AC surface mounted permanent magnet machines (PMSM), because PMSMs have features that make them attractive for use in industrial drives: small size, high efficiency, low maintenance, high dynamics, and high power density. The thesis focuses on four different HF injection sensorless methods, which utilize resistance and inductance based saliencies for position estimation: the measurement axis method, the eddy current resistance based saliency tracking method, the eddy current inductance based saliency tracking method, and the PWM switching frequency injection method. The emphasis is in the comparison of the four HF saliency tracking methods under various conditions such as steady state, load impact, speed reversal, and zero and low speed operation. The amplitude and frequency of the injection signals are also compared to choose the best HF injection signal for the four saliency tracking methods. The best sensorless control method using eddy current resistance based saliency is introduced and the experimental results confirm the expected advantages for this sensorless application.

This thesis also describes the development and enhancement of current derivative measurement for saliency tracking methods, which uses the stator current transient response to the voltage vectors contained in the fundamental PWM sequence. Due to the HF switching oscillations caused by the switching of the IGBT and parasitic capacitance, the accuracy of the current measurement is reduced and requires a minimum vector time of approximately 6µs. A signal processing algorithm is proposed which uses current samples during the high frequency current oscillations, and can potentially reduce this minimum pulse time.

PMSM was modeled in simulink with the help of model adaptive reference system.

(2016)Sensorless And Independent Speed Control Of Dual-PMSM Drives Using Five-Leg Inverter (FLI). PhD thesis, Universiti Teknikal Malaysia Melaka.

The first one is the study of the PMSM mathematical modelling and the subsequent control method applied