Boris Reznikov, Alexander Ruderman and Valentina Galanina
The paper considers a discrete state-space model for transients in a three-level flying capacitor DC–DC converter. A transition matrix is obtained for a pulse width modulation (PWM) period. The matrix elements are expanded into a power series using a selected small parameter. The matrix eigenvalues that determine the natural balancing dynamics transients are presented in the form of power series as well. Four separate transients are constructed based on four possible PWM period initial states (topologies). Inductor current and capacitor voltage transients are found for the voltage source power-up as the arithmetic average of the four separate transients. The discrete solutions are replaced by continuous ones. The resulting transients that are elementary functions of the circuit parameters, PWM period, and voltage reference demonstrate good agreement with the simulation results.
The paper presents the possibility of using neural networks in the detection of stator and rotor electrical faults of induction motors. Fault detection and identification are based on the analysis of symptoms obtained from the fast Fourier transform of the voltage induced by an axial flux in a measurement coil. Neural network teaching and testing were performed in a MATLAB–Simulink environment. The effectiveness of various neural network structures to detect damage, its type (rotor or stator damage) and damage levels (number of rotor bars cracked or stator winding shorted circuits) is presented.
Rao Anand, Nihal Vishnu Vantagodi, Kartik A Shanbhag and M Mahesh
Material handling and logistics management that involve transportation of work pieces on production floor are important aspects to manufacturing that affect productivity and efficiency. Tow vehicles that are manually driven are currently used for this purpose. These processes can be better performed through automation. Automated guided vehicle (AGV) is an apt solution. AGVs are unmanned autonomous vehicles that can be programmed to perform versatile tasks. AGVs available in market are imported and hence have high capital cost and increased lead time for spare parts. Proposed AGV is built with a capital cost that is less than half of the existing AGVs. Its design is made indigenously, with most of its parts locally sourced. It can achieve a speed of 0.83 m/s, with a pulling capacity of 1,300 kg. Its rechargeable batteries sustain four hours of continuous operation for one complete discharge. It has been tested and found to effectively replace tow vehicles.
Pulse width modulation (PWM) of inverter output voltage causes the waveforms of motor phase currents to consist of distinctive ripples. In order to provide suitable feedback for the motor current controllers, the mean value must be extracted from the currents’ waveforms in every PWM cycle. A common solution to derive the mean phase currents is to sample their value at the midpoint of a symmetrical PWM cycle. Using an assumption of linear current changes in steady PWM subintervals, this midpoint sample corresponds to the mean current in the PWM cycle. This way no hardware filtering or high-rate current sampling is required. Nevertheless, the assumption of linear current changes has been recently reported as over simplistic in permanent magnet synchronous motor (PMSM) drives operating with low switching-to-fundamental frequency ratio (SFFR). This, in turn, causes substantial errors in the representation of the mean phase currents by the midpoint sample. This paper proposes a solution for deriving mean phase currents in low SFFR PMSM drives, which does not rely on the linear current change assumption. The method is based on sampling the currents at the start point of a PWM cycle and correcting the sampled value using a model-based formula that reproduces the current waveforms. Effectiveness of the method is verified by simulation for an exemplary setup of high-speed PMSM drive. The results show that the proposed method decreases the error of determining the mean phase currents approximately 10 times when compared to the classical midpoint sampling technique.
M. Abdallah Eissa, R. R. Darwish and A. M. Bassiuny
Industrial systems serve us in all areas of life. Faults may result in economic loss and wasting energy. Detecting the onset of faults, and determining their location are important engineering tasks. An important class of fault detection (FD) and diagnosis methods utilizes the mathematical model of the monitored system. But, the parameters required for mathematical modelling are limited or unavailable for the most real industrial engineering applications. Observer-based FD is one of the main approaches to FD and identification. At the same time, the traditional observer’s gain calculation required system model parameters. So, this article presents the design of a novel observer for FD purposes using the input–output measurements of the system with unknown parameters. This proposed observer’s design considers observer’s gain tuning, regardless of the mathematical representation of the plant. This the new feature that distinction our observer will facilitate the implementation of FD systems for many unknown parameters industrial systems. The effectiveness of the proposed observer is verified by experimental application to BLDC motor and compared with classical Luenberger observer. The experimental and comparison results prove feasibility and effectiveness of the proposed observer for FD purposes.
To improve the reliability of motor system, this paper investigates the sensor fault diagnosis methods for T-type inverter-fed dual three-phase permanent magnet synchronous motor (PMSM) drives. Generally, a T-type three-level inverter-fed dual three-phase motor drive utilizes four phase-current sensors, two direct current (DC)-link voltage sensors and one speed sensor. A series of diagnostic methods have been comprehensively proposed for the three types of sensor faults. Both the sudden error change and gradual error change of sensor faults are considered. Firstly, the diagnosis of speed sensor fault was achieved by monitoring the error between the rotating speed of stator flux and the value from speed sensor. Secondly, the large high-frequency voltage ripple of voltage difference between the estimated voltage and the reference voltage was used to identify the voltage sensor faults, and the faulty voltage sensor was determined according to the deviation of voltage difference. Thirdly, the abnormal current amplitude on harmonic subspace was adopted to identify the current sensor faults, and the faulty current sensor was located by distinguishing the current trajectory on harmonic subspace. The experiments have been taken on a laboratory prototype to verify the effectiveness of the proposed fault diagnosis schemes.
Mariusz Malinowski, Emil Levi and Teresa Orlowska-Kowalska
This article constitutes an introductory part of the special section on Intelligent Fault Monitoring and Fault-Tolerant Control in Power Electronics, Drives and Renewable Energy Systems. In the current issue of the journal, the first part of this section is published. Accepted articles are focussed mainly on the sensor-fault diagnosis methods for T-type inverter-fed dual-three phase PMSM drives, partial demagnetization, faults of the permanent magnet synchronous generator (PMSG) and online open phase fault detection (FD) in the sensorless five-phase induction motor drive implemented with an inverter output LC filter and third harmonic injection. Also, neural networks (NN) application in the detection of stator and rotor electrical faults of induction motors has been proposed in one of the papers, and the observer-based FD concept for unknown systems using input–output measurements was applied to a brushless direct current motor drive with unknown parameters.
Synchronous reluctance motor drives are one of the most attractive alternatives of permanent magnet synchronous motor drives and induction motor drives in the field of conventional industrial and household applications. This tendency is expected to be continued in the case of motion control applications as well. This article investigates two torque-control algorithms that are possible candidates for motion control synchronous reluctance motor applications. The examined torque-control algorithms are direct torque control (DTC) and hysteresis current vector control (HCVC).
This paper proposes a multiobjective improved particle swarm optimisation (IPSO) for placing and sizing the series modular multilevel converter-based unified power flow controller (MMC-UPFC) FACTS devices to manage the transmission congestion and voltage profile in deregulated electricity markets. The proposed multiobjective IPSO algorithm is perfect for accomplishing the close ideal distributed generation (DG) sizes while conveying smooth assembly qualities contrasted with another existing algorithm. It tends to be reasoned that voltage profile and genuine power misfortunes have generous upgrades along ideal speculation on DGs in both the test frameworks. The proposed system eliminates the congestion and the power system can be easily used to solve complex and non-linear optimisation problems in a real-time manner.
Grzegorz Iwański, Paweł Maciejewski and Tomasz Łuszczyk
One of the currently investigated problems in power electronics-based electrical energy conversion is proper operation of electronic converters during grid voltage imbalance and harmonics. In classic control methods, it introduces oscillations of variables, resulting in the necessity to improve control systems with signals filtration and usually by application of resonant terms as part of current controllers. The paper presents a new approach to grid-connected inverter control based on transformation to a non-Cartesian frame, the parameters of which are correlated with grid voltage asymmetry. The proposed method results in resignation from resonant terms used as controllers and their replacement with proportional–integral terms for which anti-wind-up structures are significantly simpler than for oscillatory terms. The paper presents new transformation principles, features and some simulation results showing the waveforms of signals transformed to the new non-Cartesian frame.