Self-Commissioning of AC Motor Drives

In modern motion control and power conversion applications, the use of inverter-fed electrical machines is fast growing with continuous development in the field of power electronics and drives. The Variable Voltage Variable Frequency (VVVF) supply for electrical machines gives superior performance in terms of speed control, efficiency and dynamics compared to the machines operated directly from the mains. In one of the most basic configurations, a drive system consists of a closed loop speed control that has a current controller inside the loop. For effective and stable current control, the controller gains need to be set according to the parameters of the machine at hand. Besides, accurate parameter information is helpful in ensuring better machine exploitation as well as maintaining higher efficiency in various operating modes and conditions. The traditional methods of determining machine parameters consist of extensive machine testing under prescribed supply and ambient conditions. These methods become impracticable when the machine cannot be isolated from its load or the test equipment cannot be made available. Under such conditions, the alternatives are needed that use only the available hardware included in a standard drive to completely define the machine parameters. Self-commissioning thus comes into play in such situations. The automatic determination of machine electrical parameters before the drive is put in continuous operation is called self-commissioning of the drive system. In this thesis, self-commissioning of AC electric motors is studied, analyzed and results are presented for the implementation of different self-commissioning methods either proposed in the literature or developed in the course of this research. By far the commonest control strategy of AC machines is the vector control that allows dc machine like decoupled control of machine flux and torque. The separation of flux and torque producing current components depends heavily on the parameters of the machine at hand. In case the parameters fed to the controller do not match the actual machine parameters, the control performance deteriorates both in terms of accuracy and efficiency. For synchronous machines using permanent magnets, the magnetic model of the machine is important both for flux estimation accuracy at low speeds and for deriving maximum torque out of machine per ampere of input stator current. The identification of the magnetic model of permanent magnet synchronous machines requires special tests in a laboratory environment by loading the machine. A number of machine parameter identification methods have been studied in the past and proposed in the literature. As the power amplifier implied is almost always an inverter, the estimation of machine parameters at start-up by generating special test signals through the inverter have been researched in depth and are investigated in this thesis. These techniques are termed as offline parameter identification strategies. Other methods that focus on parameter updating during routine machine operation are called online parameter estimation methods. In this thesis, only the offline identification schemes are studied and explored further. With continuous improvements in power semiconductor devices' switching speeds and more powerful microprocessors being used for the control of electric drives, generating a host of test signals has been made possible. Analysing the machine response to the injected test signals using enhanced computational power onboard is relatively easier. These conditions favour the use of even more complex test strategies and algorithms for self-commissioning and to reduce the time required for conducting these tests. Moreover, the universal design of electric drives renders the self commissioning algorithms easily adaptable for different machine types used in industry. Among a number of AC machines available on the market, the most widely used in industrial drives are considered for study here. These include AC induction and permanent magnet synchronous machines. Induction machines still play a major part in industrial processes due, largely, to their ruggedness and maintenance-freeness; however, the permanent magnet machines are fast replacing them as competitive alternatives because of their low volume-to-power, weight-to-power ratios and higher efficiency. Their relatively light weight makes these machines a preferred choice in traction and propeller applications over their asynchronous counterpart

A Novel Repetitive Controller Assisted Phase-Locked Loop with Self-Learning Disturbance Rejection Capability for Three-Phase Grids

The synchronization between the power grid and distributed power sources is a crucial issue in the concept of smart grids. For tracking the real-time frequency and phase of three-phase grids, phase-locked loop (PLL) technology is commonly used. Many existing PLLs with enhanced disturbance/harmonic rejection capabilities, either fail to maintain fast response or are not adaptive to grid frequency variations or have high computational complexity. This article, therefore, proposes a low computational burden repetitive controller (RC) assisted PLL (RCA-PLL) that is not only effective on harmonic rejection but also has remarkable steady-state performance while maintaining fast dynamic. Moreover, the proposed PLL is adaptive to variable frequency conditions and can self-learn the harmonics to be canceled. The disturbance/harmonic rejection capabilities together with dynamic and steady-state performances of the RCA-PLL have been highlighted in this article. The proposed approach is also experimentally compared to the synchronous rotation frame PLL (SRF-PLL) and the steady-state linear Kalman filter PLL (SSLKF-PLL), considering the effect of harmonics from the grid-connected converters, unbalances, sensor scaling errors, dc offsets, grid frequency variations, and phase jumps. The computational burden of the RCA-PLL is also minimized, achieving an experimental execution time of only 12 μs

An accurate self-commissioning technique for matrix converters applied to sensorless control of synchronous reluctance motor drives

The compensation of converters’ nonlinear voltage error is crucial in encoder-less control of ac motor drives. In this paper, a new self-commissioning and compensation method is proposed for matrix converters (MC). Similar to what done in the past for voltage source inverters, the MC voltage error is identified before the drive start and stored in a look-up table (LUT), later used for error compensation and accurate voltage estimate. Different from what observed in the past, the effect of parasitic capacitors on nonlinear voltage error of MCs in four-step current based commutation is observed and studied. Eventually, this method is applied to the sensorless control of a synchronous reluctance (SyR) motor drive, using the direct flux vector control (DFVC) concept. Experimental results are presented to validate the effectiveness of proposed self-commissioning in improving the performance of sensorless control at standstill and low speed

Modulated model predictive control with optimized overmodulation

Finite Set Model Predictive Control (FS-MPC) has many advantages, such as a fast dynamic response and an intuitive implementation. For these reasons, it has been thoroughly researched during the last decade. However, the wave form produced by FS-MPC has a switching component whose spread spectrum remains a major disadvantage of the strategy. This paper discusses a modulated model predictive control that guarantees a spectrum switching frequency in the linear modulation range and extends its optimized response to the overmodulation region. Due to the equivalent high gain of the predictive control, and to the limit on the voltage actuation of the power converter, it is expected that the actuation voltage will enter the overmodulation region during large reference changes or in response to load impacts. An optimized overmodulation strategy that converges towards FS-MPC’s response for large tracking errors is proposed for this situation. This technique seamlessly combines PWM’s good steadystate switching performance with FS-MPC’s high dynamic response during large transients. The constant switching frequency is achieved by incorporating modulation of the predicted current vectors in the model predictive control of the currents in a similar fashion as conventional Space-Vector Pulse Width Modulation (SV-PWM) is used to synthesize an arbitrary voltage reference. Experimental results showing the proposed strategy’s good steady-state switching performance, its FS-MPC-like transient response and the seamless transition between modes of operation are presented for a permanent magnet synchronous machine drive

A New Position and Speed Estimation Scheme for Position Control of PMSM Drives Using Low-Resolution Position Sensors

A new position control method for permanent magnet synchronous motor (PMSM) drive with a low-resolution encoder is proposed in this paper. Three binary Hall position sensors are utilized to realize a moderate-performance position control system for the consideration of economy and simplicity in servo application. Compared with sensorless control, the usage of binary Hall position sensors is a guarantee of both control performance and low cost. However, the low resolution of the Hall sensor will heavily deteriorate the accuracy of the position and speed calculation. Such drawback can be effectively minimized by using appropriate position and speed estimation schemes. With the help of polynomial fitting and state observer techniques, a solution is provided to realize semi-closed loop control by treating the position and speed estimators as separate systems. The performance can be improved (1) by proposing a polynomial fitting scheme with least squares method, high-resolution rotor-position predictor can be derived by fitting the predefined position data from binary Hall position sensors in a linear or quadratic manner; (2) by adopting the dual-sampling-rate observer, instantaneous speed can be estimated at each control cycle and the estimation error is corrected once a new measurement form the Hall arrives. Furthermore, a nonlinear position control algorithm is introduced to increase standstill stability. Extensive experimental results are given to demonstrate the feasibility of the proposed method and its superiority over conventional methods

High dynamic performance power quality conditioner for AC microgrids

This paper deals with power quality problems encountered in weak AC microgrids and solutions for mitigation. A power electronic converter can be used as an effective power quality conditioner to compensate non-idealities in currents drawn from the grid. A power quality conditioner consisting of three power converters connected to a common DC link is analysed. One of these converters acts as an active power filter for removing unwanted harmonics in grid currents feeding a non-linear load. The other two converters instead remove the harmonics from the voltage at the terminals of a sensitive load. The control of the shunt converter is designed to be fast enough for power quality servicing but also has a fast disturbance rejection capability. Simulation and experimental results validating the concept are provided along with obtained total harmonic distortion improvements

Direct Model Predictive Control of Synchronous Reluctance Motor Drives

This paper investigates a finite-control set model-predictive control (FCS-MPC) algorithm to enhance the performance of a synchronous reluctance machine drive. Particular emphasis is placed on the definition of the cost function enabling a computationally light implementation while targeting good transient and steady-state performance. In particular, this work proposes the inclusion of an integral term into the cost function to ensure zero steady-state errors thus compensating for any model inaccuracies. A control effort term is also considered in the formulation of the cost function to achieve a high ratio between the sampling frequency and the average switching frequency. After a comprehensive simulation study showing the advantages of the proposed approach over the conventional FCS-MPC for a wide range of operating conditions, several experimental test results are reported. The effectiveness of the proposed control approach, including a detailed analysis of the effect of the load and speed variations, is thus fully verified providing useful guidelines for the design of a direct model predictive controller of synchronous reluctance motor drives

Integrated Motor Drive: Mass and Volume Optimization of the Motor with an Integrated Filter Inductor

The present trend of aerospace industries is being shifted towards a “More Electric Aircraft” system which needs to be high power dense. For this purpose, the integration technologies have gained massive interest, providing the benefits of reduced losses, weight, volume and cost. In this article, the integration concept of a passive filter inductor is presented for a permanent magnet synchronous motor. The integrated motor eliminates the need of an external inductor, thus, eliminates the added inductor losses, mass, volume and cost associated with it. The motor utilizes its’s inherent inductance to use it as a filter inductor instead of implementing a discrete inductor that is commonly placed between inverter and the motor terminals. Optimization study is carried out, where the filter branch windings are tapped, in terms of improving mass and volume and performance parameters such as power losses and torque ripple. From the optimization study, the motor with minimum weight and volume is experimentally validated at the rated conditions, in order to prove the concept feasibility. Total system weight and volume of integrated and traditional motor drives are compared, which gives the minimum weight of 2.26 kg and 3.14 kg respectively, and the minimum volume of 0.54 L and 1.1 L respectively