Switched-capacitor based multilevel inverters (SC MLIs) have received a great deal of interest that reduces the dc source requirement and improves the power quality. However, multiple dc sources and requirement of a large number of switches to generate a high-quality boost output are the fundamental issues in the SC MLIs. This paper presents a step-up 17-level SC MLI using reduced number of switches, three capacitors and a single dc source. The steady-state voltage across the capacitors is maintained in the ratio 1:2:0.5 that contributes to quadruple boosting ability without using any auxiliary capacitor voltage balancing circuit. Besides, lower switch count in the conduction path and operation of 50 % of the switches at fundamental frequency ensures total power loss reduction in the proposed circuit. A comparative assessment with recently developed 17-level MLIs in terms of the number of components, gain, stress and cost factor elucidates the advantages of the proposed MLI. After a detailed circuit analysis and loss evaluation, simulations are performed to verify the step-up and inherent balancing features of the proposed MLI. Further, using both the fundamental frequency and high-frequency switching techniques, extensive experimental test results are presented under different transient conditions to validate the operational feasibility of the 17-level prototype.

Joomla! - the dynamic portal engine and content management system

Spontaneous self-excitation in induction generators is a fascinating phenomenon triggered by the instability of a zero equilibrium state. Prediction of this condition for various values of free parameters requires many computations of the eigenvalues of a 6 × 6 matrix over a large space. The paper uses a novel approach to derive analytic conditions and predict precisely when instabilities occur. The formulas give the values of the minimum load resistance, the range of capacitor values, and the range of speeds for which spontaneous self-excitation appears. The paper concludes with an illustration of the theoretical results on an example.

The application of electrical drives in the control of centrifugal fans and pumps is a well-established area that leads to substantial energy savings. It requires electrical and automation engineers to have some knowledge relevant to drives about fan and pump modelling since ignoring or oversimplifying fan/pump modelling for the intended drive design compromises the required control quality. This paper improves the existing dynamical models of fans and pumps integrated with induction motors via neural network estimation of overall fan/pump efficiency; this estimation is based on the voltage frequency of the driving induction motor, pressure, and flow rate, followed by the separation of the fan’s or pump’s own efficiency for the motor load torque computation, enhancing the accuracy due to the correct reflection of the power balance. The model is developed with a view to being convenient for control design applications. For the first time for dynamical models, it is verified experimentally, justifying the necessity of the first-order nonlinear differential equation for the flow rate. The validation includes a direct approach based on analysis of transient behaviour caused by a small-step perturbation of the frequency of the motor voltages and an indirect approach based on the introduced concept of the dynamical flow rate and pressure estimators.

This study proposes a novel pressure control strategy for a centrifugal fan driven by an induction motor, using a two-degree-of-freedom (2-DOF) proportional-integral (PI) controller optimized via the fungal growth optimizer (FGO). Built upon a validated nonlinear model, the FGO algorithm tunes the controller parameters to minimize a cost function reflecting overshoot and tracking error. Comparative evaluations are performed against genetic algorithm (GA), L-SHADE, and the Newton-Raphson-based optimizer (NRBO), as well as classical methods such as Cohen-Coon and Rovira techniques. The FGO-based controller demonstrates superior dynamic response, robustness, and noise immunity. Statistical validation using the Wilcoxon signed-rank test confirms the performance improvements. These results highlight the effectiveness of FGO in real-world pressure regulation and establish a benchmark for modern industrial fan control systems.

Energy saving control algorithms of centrifugal fans/pumps are based on the use of the frequency-controlled induction motor drives and pressure or flow rate sensors, the costs of which are comparable to the cost of the fans/pumps for low-power applications. The paper develops a new and simple estimation approach of the pressure and flow rate, utilising the measured Root Mean Square (RMS) value of the stator current, estimated motor’s input active power, reference stator voltage frequency and feed-forward backpropagation artificial neural network. The error percentage for both flow rate and pressure in experimental and estimated data is within the range of ±5%, which conforms to the ISO 13348 standard. A test rig for the rapid control prototyping of the fan is designed, and necessary design and test procedures are developed. The estimation approach is verified experimentally and demonstrates better estimation accuracy compared to the existing and possible similar simple approaches. The developed algorithm can be easily embedded into the industrial variable frequency drives without any hardware changes.