rss_2.0Power Electronics and Drives FeedSciendo RSS Feed for Power Electronics and Driveshttps://sciendo.com/journal/PEADhttps://www.sciendo.comPower Electronics and Drives Feedhttps://sciendo-parsed.s3.eu-central-1.amazonaws.com/64727010215d2f6c89dc7e8a/cover-image.jpghttps://sciendo.com/journal/PEAD140216An Experimental Set-up Involving Low-cost Digital Controller to Study the Magnetizing Inrush Current in a Transformer using Point-on-Wave Switching Techniquehttps://sciendo.com/article/10.2478/pead-2024-0019<abstract> <title style='display:none'>Abstract</title> <p>Generally in under-graduate studies, magnetizing inrush current (MIC) is discussed theoretically without giving much practical exposure. This paper presents the development of a low cost experimental set-up using a digital controller to study the MIC and the different parameters which can affect the same. This also helps to show how the inrush current can be minimized. This set-up also provides a hands-on experience of MIC and its control in under-graduate study, which can help an upcoming practitioner in industry as well as in further research. This paper presents a brief description of MIC, followed by a short analysis. Here, a pair of anti-parallel thyristors are connected in series with the primary winding of a single-phase power transformer. The turningon instant of this switch, with respect to the zero-crossing instant of the input supply voltage, may be adjusted through a firmware, in a PIC18F4620 from Microchip Technology microcontroller development board from Microchip Technology to control the transformer energisation instant. The firmware is developed in MPLABX-IDE from Microchip Technology, and the scheme is verified via simulations in Proteus simulation software. A suitable circuit to support the microcontroller development board to achieve the above function is designed and fabricated.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00192024-05-10T00:00:00.000+00:00Capacitor-Based Active Cell Balancing for Electric Vehicle Battery Systems: Insights from Simulationshttps://sciendo.com/article/10.2478/pead-2024-0020<abstract> <title style='display:none'>Abstract</title> <p>Cell balancing, a critical aspect of battery management in electric vehicles (EVs) and other applications, ensures a uniform state of charge (SOC) distribution among individual cells within a battery pack, enhancing performance and longevity while mitigating safety risks. This paper examines the effectiveness of capacitor-based active cell-balancing techniques using simulations under dynamic loading conditions. Utilising MATLAB and Simulink, various circuit topologies are evaluated, considering real-world cell parameters and open-circuit voltage (OCV) curve modelling. Results indicate that advanced configurations, such as double-tiered switched-capacitor balancing, offer improved balancing speed and efficiency compared to conventional methods. However, challenges such as transient events during charging and discharging phases underscore the need for further research. By leveraging simulations and experimental data, researchers can refine cell-balancing strategies, contributing to the development of safer, more efficient battery systems for EVs and beyond. This study underscores the importance of systematic analysis and optimisation in advancing cell-balancing technology for future energy-storage applications.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00202024-05-10T00:00:00.000+00:00Quasi-Z-Source Three-Phase Voltage Source Inverter with Virtual Space Vector Modulation to Increase the Voltage Gain and for the Reduction of Common Mode Voltagehttps://sciendo.com/article/10.2478/pead-2024-0018<abstract> <title style='display:none'>Abstract</title> <p>A quasi-Z-source network is used to boost the DC bus voltage of a voltage source two-level H-bridge inverter to increase the voltage gain. With the increase in the DC bus voltage, the common mode voltage (CMV) also increases. The CMV is reduced using virtual space vector pulse width modulation (SVPWM). Due to the presence of a quasi-Z-source network, the expression of the CMV changes significantly with respect to the conventional voltage source two-level H-bridge inverter fed from a pure DC supply. In this paper, a detailed analysis of the origin of the CMV for the quasi-Z-source two-level H-bridge inverter is presented. Additionally, it is shown how the CMV is affected for a DC input supply taken from a three-phase diode bridge rectifier. The work also details the scheme for suitable placement of shoot-through time intervals required for boosting within the non-active time intervals in virtual SVPWM. The simulation and experimental results show the scheme is effective in increasing the voltage gain and reducing the CMV arising at the third harmonic of the desired output frequency by at least 33.33%.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00182024-04-29T00:00:00.000+00:00Excitation Control of Brushless Induction Excited Synchronous Motor with Induction Machine Operating in Deep-Plugging Modehttps://sciendo.com/article/10.2478/pead-2024-0017<abstract> <title style='display:none'>Abstract</title> <p>The popularity of electrified transportation is rising at a sharp pace due to environmental concerns over internal combustion (IC) engines. Researchers are nowadays looking for a brushless and permanent magnet (PM)-less solution for electric vehicle (EV) motors. Wound-field synchronous motor (WFSM) is a potential solution for EVs and is being used in Renault Zoe EV and BMW iX3 e-Drive models. A Brushless Induction excited Synchronous Motor (BINSYM) is a WFSM where the exciter, an induction machine (IM), is embedded inside the synchronous machine (SM) frame. Two machines (SM and IM) are configured for different numbers of poles to achieve magnetic decoupling, which facilitates independent control of both machines. The purpose of IM is to maintain the excitation requirement of SM. The IM is controlled in deep-plugging mode at a constant slip frequency over the entire speed range to minimise its reactive power demand. The maximum torque per ampere (MTPA) and root mean square (rms) current minimisation algorithms are used to control the SM. Simulation of the BINSYM-based system under dynamic conditions (MTPA with varying field current and load transient) has been carried out in MATLAB/Simulink to validate the control strategies. Experimental findings from the laboratory prototype machine closely match the simulation results.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00172024-04-16T00:00:00.000+00:00Real-time Neural Sliding Mode Linearization Control for a Doubly Fed Induction Generator under Disturbanceshttps://sciendo.com/article/10.2478/pead-2024-0016<abstract> <title style='display:none'>Abstract</title> <p>This paper presents an experimental implementation of a Neural Sliding Mode Linearization approach for the control of a double-fed induction generator connected to an infinite bus via transmission lines. The rotor windings are connected to the grid via a back-to-back converter, while the stator windings are directly coupled to the network. The chosen control scheme is applied to obtain the required stator power trajectories by controlling the rotor currents and to track the desired values of the DC-link output voltage and the grid power factor. This controller is based on a neural identifier trained online using an Extended Kalman Filter. Based on such identifier, an adequate model is obtained, which is used for synthesizing the required controllers. The proposed control scheme is experimentally verified on 1/4 HP DFIG prototype considering normal and abnormal grid conditions. In addition, maximum power extraction from a random wind profile is tested in the presence of different grid scenarios. Moreover, a comparison with conventional control schemes is performed. The obtained results illustrate the capability of the proposed control scheme to achieve active power, reactive power, and DC voltage desired trajectories tracking and to operate the wind power system even in the presence of parameter variation and grid disturbances, which helps to ensure the stability of the system and improve generated power quality.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00162024-04-13T00:00:00.000+00:00A Simulation Analysis of Grid-Connected DSTATCOM with PWM Voltage Control and Hysteresis Current Control for Power Quality Improvementhttps://sciendo.com/article/10.2478/pead-2024-0015<abstract> <title style='display:none'>Abstract</title> <p>The DTSTACOM is a power quality compensator that can be used in the distribution grid to compensate the demand of reactive power, which can be produced by different linear and non-linear loads. In this process, the control method of DSTATCOM is one of the key factors influencing the performance of DSTATCOM. This study aims to analyse the effect of two modulation schemes, Pulse Width Modulation (PWM) and Hysteresis Current Control (HCC), under several conditions. The proposed modelling approach and Synchronous Reference Frame (SRF) theory are used to verify reactive power compensation and total harmonic distortion (THD). Further, PWM and Hysteresis Current Control (HCC) with proportional-integral (PI) controller simulated in MATLAB for different cases, and percentage THD was calculated to prove the effectiveness of the proposed method for the control of reactive power and THD with grid-connected DSTATCOM. The results presented here justify that the HCC controller can be better than the PWM method to generate the PWM pulses for reduction of harmonics under various conditions of DTSTACOM to compensate the reactive power. Additionally, the simulation was performed to check the efficacy of the projected method to reduce THD by varying the current control band of HCC.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00152024-04-12T00:00:00.000+00:00A Novel Proportional Multi-Resonant Current Controller Strategy for Reduced DC Voltage fed D-STATCOM with Internal LCL Resonance Dampinghttps://sciendo.com/article/10.2478/pead-2024-0008<abstract><title style='display:none'>Abstract</title> <p>This work focuses on a new topology-control-based D-STATCOM solution with reduced DC bus voltage requirement and with an excellent grid side performance. The proposed solution consists of a main inverter and auxiliary inverter along with a transformer and LCL filter network to achieve the required DC bus reduction. A new controller structure with two proportional-multi resonant controller for the converters with only one of the inductors current as a controlled variable ensures the active damping of the LCL resonance. The power circuit configuration assists the controller to generate a difference in the modulation signal due to non-equal gains in two controllers and helps to achieve the resonance damping without capacitor current sensor. Hence, the corresponding capacitor current sensor can be eliminated. The converter operates for any point of common coupling (PCC) loading conditions and the performance of the controller is immune to the grid impedance variation. A detailed stability study is carried out for the proposed controller. The proposed controller can achieve a very fast dynamic response with an excellent stability margin. The proposed solution is verified through simulation studies and through a scaled-down experimental prototype.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00082024-03-26T00:00:00.000+00:00Minimisation of AC Grid Side Input Power Factor Angle for Three-phase AC to Three-phase AC Matrix Converter under Varying Loadhttps://sciendo.com/article/10.2478/pead-2024-0014<abstract><title style='display:none'>Abstract</title> <p>Minimisation of AC grid side input power factor angle for a ‘matrix converter (MC)’ improves the efficiency of the grid. Input volt-ampere requirement is minimum if the current drawn by the ‘MC’ is sinusoidal and input displacement power factor (IDPF) is unity. A MC is inherently capable of maintaining a unity displacement power factor (UDPF) angle at its input terminals. However, the input currents drawn from the grid are not sinusoidal. The high-frequency ripples are suppressed by input current filters (ICFs).These filters additionally introduce a leading phase angle for the current which varies with the loading. This phase lead can be compensated by adjusting the angle between the input current space vector and the input voltage space vector of the MC. The computation of this adjustment angle depends on the estimation of power losses in the switching devices. A simple method is proposed in this paper to estimate the switching losses without measuring device voltages and currents using the perturbation technique. The perturbation logic depends on input current, instantaneous active and reactive power computed at regular intervals of time. The proposed method effectively minimises the IDPF angle very close to zero. The experimental results are included for validation,</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00142024-03-26T00:00:00.000+00:00An Impact of Switching Frequency and Model Accuracy on Model Predictive Current Control Performance for Reluctance Synchronous Motorshttps://sciendo.com/article/10.2478/pead-2024-0012<abstract> <title style='display:none'>Abstract</title> <p>The present paper investigates the feasibility of utilizing the simplified prediction model for finite control set model predictive current control (FCS-MPCC) applied to reluctance synchronous motors (RSMs). The FCS-MPCC exhibits torque and current ripples, and a crucial consideration is the reduction of these ripples by increasing the switching frequency. The algorithm’s computational complexity is tied to the accuracy of the adopted model. Two approaches with varying levels of accuracy in predicting current dependencies concerning changes in the inductance of the RSM are investigated. The findings highlight the potential of employing simplified fixed inductance values for efficient control in drive systems, particularly those amenable to high switching frequencies.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00122024-03-05T00:00:00.000+00:00Real-Time Implementation of a Hybrid ESC Approach for Maximising the Extracted Photovoltaic Power Under Partial Shading Conditionshttps://sciendo.com/article/10.2478/pead-2024-0013<abstract> <title style='display:none'>Abstract</title> <p>Solar energy, an available and renewable resource, can be efficiently transformed into electrical energy through the use of photovoltaic (PV) cells. The primary emphasis lies in the significance of maximising power output for economic considerations. In terms of optimising power generation, the implementation of maximum power point tracking (MPPT) techniques is imperative. A range of approaches, such as super twisting (ST) control and modified extremum seeking control (ESC-mod), are explored for their potential in enhancing the efficiency of power-generation systems. The novelty is a combination of these methods; the modified ESC has the role of finding the optimum voltage value of the global maximum power point (MPP) during the partial shading, while the super-twisting improves the performance of the system. The efficacy of the MPPT algorithm is assessed across diverse conditions, encompassing scenarios with load variations and fluctuating irradiances (uniform and non-uniform). The experimental setup involves essential components such as a PV generator, a boost converter and a resistive load. This comprehensive testing aims to evaluate the algorithm’s performance under varying circumstances, providing insights into its adaptability and effectiveness across different operational conditions. The system is modelled, simulated using Matlab–Simulink and implemented using a dSPACE 1104 card. Simulation results indicate that ST control is faster in reaching the permanent regime, but ESC-mod provides smoother performance in the permanent regime. The integration of both ST control and ESC-mod methods proves advantageous by diminishing the response time in the seeking process while concurrently ensuring a consistent and smooth operation in the permanent regime. This combined approach has undergone practical implementation and testing across diverse conditions, encompassing both optimal, healthy states and shaded environments. The results affirm the method’s ability to deliver efficient and stable performance across a spectrum of operating conditions.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00132024-03-05T00:00:00.000+00:00A Study on Various Causes of Low Frequency Components in Common Mode Voltage of a Space Vector Pulse Width Modulated Three– Phase Quasi–Z–Source H–Bridge Inverter Fed from a Three–Phase Diode Bridge Rectifierhttps://sciendo.com/article/10.2478/pead-2024-0009<abstract> <title style='display:none'>Abstract</title> <p>The presence of low frequency components in the common mode voltage can cause harmful electromagnetic interference. A critical study on various causes of low frequency components in the common mode voltage of a space vector pulse width modulated Quasi–Z– source three–phase H–bridge voltage source inverter fed from a three–phase diode bridge rectifier is presented in this paper. The Quasi–Z–source network is utilized in boosting the rectified dc voltage which increases the overall voltage gain. The study considers the effect of boosting on the low frequency components. The input three-phase diode bridge rectifier has its influence in modulating the instantaneous common mode voltage and contributes low frequency components. The unbalanced three-phase supply can contribute additionally ac supply frequency component in the common mode voltage. The major contribution of this paper is the analytical, simulated and experiment-based study on various causes of the low frequency common mode voltages due to the combined action of the input non-ideal three phase grid, the front-end diode bridge rectifier as well as the load-end Z-source H-bridge three-phase inverter feeding a three-phase inductive load, while operated through a space vector pulse width modulation strategy.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00092024-03-05T00:00:00.000+00:00Fault Tolerant Control of a Dual Star Induction Machine Drive System using Hybrid Fractional Controllerhttps://sciendo.com/article/10.2478/pead-2024-0010<abstract> <title style='display:none'>Abstract</title> <p>This paper presents a novel fault tolerant control (FTC) strategy for a dual star induction machine (DSIM) based on the combination of two types of robust controllers, namely a proportional resonant (PR) controller for current regulation and a fractional order PI (FOPI) for speed regulation. This FTC is associated with an indirect rotor indirect rotor field-oriented control (IRFOC) strategy. Fault feedforward compensation of the current components is introduced using the residual signal generated by the calculations passing through the PR controller. The fractional-order PI controller is applied as a feedforward fractional-order perturbation observer to the speed control loop, which attempts to minimise the error induced by the fault. In this context, a fault-tolerant control scheme is achieved. The performance characteristics of the proposed fault tolerant control for a dual star induction machine drive are compared with the fault tolerant control based on the conventional integer order IP (IOPI) to verify the effectiveness of the proposed FTC scheme under various conditions, by examining the robustness of the control in the presence of faults. To evaluate the performance of the proposed technique, simulation results are obtained using the Matlab/Simulink environment. According to the obtained simulation results, the proposed FTC system achieves significantly better responses than the conventional IRFOC system in terms of harmonics in the stator currents, and low oscillations in the electromagnetic torque response.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00102024-03-02T00:00:00.000+00:00Condition Monitoring and Fault Diagnosis of Permanent Magnet Synchronous Motor Stator Winding Using the Continuous Wavelet Transform and Machine Learninghttps://sciendo.com/article/10.2478/pead-2024-0007<abstract> <title style='display:none'>Abstract</title> <p>Applying the condition monitoring technology to industrial processes can help detect faults in time, minimise their impact and reduce the cost of unplanned downtime. Since the introduction of the Industry 4.0 paradigm, many companies have been investing in the development of such technology for drive systems. Permanent magnet synchronous motors (PMSMs) have recently been used in many industries. Therefore, the issues of condition monitoring of PMSM drives are important. This study proposes and compares diagnostic schemes based on the stator phase currents (SPCSCs) signal for condition monitoring and fault diagnosis of PMSM stator winding faults. The continuous wavelet transform (CWT) is used for the extraction of the symptoms of interturn short circuits in PMSM stator winding. Machine learning algorithms are applied to automate the detection and classification of the faults. The concept for an original and intelligent PMSM stator winding condition monitoring system is proposed.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00072024-02-24T00:00:00.000+00:00A Comparative Study of PSO, GWO, and HOA Algorithms for Maximum Power Point Tracking in Partially Shaded Photovoltaic Systemshttps://sciendo.com/article/10.2478/pead-2024-0006<abstract> <title style='display:none'>Abstract</title> <p>Solar energy harnessed through photovoltaic technology plays a crucial role in generating electrical energy. Maximising the power output of solar modules requires optimal solar radiation. However, challenges arise due to obstacles such as stationary objects, buildings, and sand-laden winds, resulting in multiple points of maximum power on the P–V curve. This problem requires the use of maximum power point tracking algorithms, especially in unstable climatic conditions and partial shading scenarios. In this study, we propose a comparative analysis of three MPPT methods: particle swarm optimisation (PSO), grey wolf optimisation (GWO) and Horse Herd Optimization Algorithm (HOA) under dynamic partial shading conditions. We evaluate the accuracy of these methods using Matlab / Simulink simulations. The results show that all three methods solve partial shading problems effectively and with high precision. Furthermore, the Horse Herd Optimization approach has superior tracking accuracy and faster convergence compared with the other proposed methods.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00062024-02-15T00:00:00.000+00:00Novel Speed Sensorless DTC Design for a Five-Phase Induction Motor with an Intelligent Fractional Order Controller Based-MRAS Estimatorhttps://sciendo.com/article/10.2478/pead-2024-0005<abstract> <title style='display:none'>Abstract</title> <p>This paper presents a fractional-order adaptive mechanism-based model reference adaptive system (MRAS) configuration for speed estimation of sensorless direct torque control (DTC) of a five-phase induction motor. In effect, the fractional-order proportional-integral (FOPI) controller parameters are obtained by the particle swarm optimisation (PSO) algorithm to enhance the MRAS observer response. Thus, the developed algorithm in the speed loop control of the DTC strategy to increase its robustness against disturbances. Moreover, a comparative study has been done of the proposed MRAS-PSO/FOPI speed estimator with the conventional MRAS-proportional-integral (PI) and the PSO-based MRAS-PI. Simulation results have carried out of the different controllers used in the adaptation mechanism of the MRAS estimator, to show the performance and robustness of the proposed MRAS-PSO/FOPI algorithm in use.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00052024-02-15T00:00:00.000+00:00Hybrid Flatness-Based Control of Dual Star Induction Machine Drive System for More Electrical Aircrafthttps://sciendo.com/article/10.2478/pead-2024-0004<abstract> <title style='display:none'>Abstract</title> <p>This paper develops a precise method control system for tracking control of a power drive system based on a multi-phase machine under motor parameter and load torque variations. By adding a simple feedforward term based on the flatness theory, a conventional flux oriented control (FOC) can be enforced to have a perfect tracking performance under model parameter and load torque variations. Hence, a hybrid flatness-based control (HFBC) technique is applied to the control of a dual star induction machine (DSIM) and compared to a classical vector control strategy regarding tracking behaviour, robustness, and perturbations rejection. Finally, the simulation and experimental results are provided to verify the effectiveness of the proposed HFBC under uncertainties such as motor parameter and load torque variations. Furthermore, an enhancement of the drive system’s control performances is demonstrated by the improvement of the technique of separation of the objectives of tracking and disturbance rejection. The simulation and experimental results are presented, demonstrating the superiority of the HFBC.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00042024-01-20T00:00:00.000+00:00Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approacheshttps://sciendo.com/article/10.2478/pead-2024-0003<abstract> <title style='display:none'>Abstract</title> <p>Optimisation, or optimal design, has become a fundamental aspect of engineering across various domains, including power devices, power systems, and industrial systems. Engineers and academics have been actively involved in optimising these systems to achieve better performance, efficiency, and cost-effectiveness. Optimising electrical machines, including permanent magnet motors, is a complex task. It often involves solving intricate problems with various parameters and constraints. Engineers use different optimisation methods to tackle these challenges. Depending on the specific requirements and goals of a design project, engineers may employ either single-objective or multi-objective optimisation approaches. Single-objective optimisation focuses on optimising a single objective, while multi-objective optimisation considers multiple conflicting objectives. In optimisation, objective functions are mathematical representations of what needs to be optimised. In this case, optimising the efficiency of the motor, reducing cogging torque, and minimising the total weight of active materials are defined as possible objective functions. Genetic algorithms are nature based algorithms that are commonly used in engineering to find optimal solutions to complex problems, including those with multiple objectives. In this paper, after conducting optimisations using different objective functions and methods, a comparative analysis of the results is performed. This helps in understanding the trade-offs and benefits of different design choices. Finite element analysis (FEA) is a computational method used to analyse the physical properties and behaviours of complex structures and systems. In this case, FEA is used to validate and analyse selected optimisation solutions to ensure they meet the desired characteristics and parameters. Overall, this work demonstrates the interdisciplinary nature of engineering, where mathematics, computer science (for optimisation algorithms), and physics (for FEA) converge to improve the performance and efficiency of electrical machines. It also underscores the importance of considering multiple objectives in design processes to find optimal solutions that strike a balance between competing goals.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00032024-01-20T00:00:00.000+00:00Analysis of PMSM Short-Circuit Detection Systems Using Transfer Learning of Deep Convolutional Networkshttps://sciendo.com/article/10.2478/pead-2024-0002<abstract> <title style='display:none'>Abstract</title> <p>Modern permanent magnet synchronous motor (PMSM) diagnostic systems are now combined with advanced artificial intelligence techniques, such as deep neural networks. However, the design of such systems is mainly focussed on a selected type of damage or motor type with a limited range of rated parameters. The application of the idea of transfer learning (TL) allows the fully automatic extraction of universal fault symptoms, which can be used for various diagnostic tasks. In the research, the possibility of using the TL idea in the implementation of PMSM stator windings fault-detection systems was considered. The method is based on the characteristic symptoms of stator defects determined for another type of motor or mathematical model in the target diagnostic application of PMSM. This paper presents a comparison of PMSM motor inter-turn short circuit fault detection systems using TL of a deep convolutional network. Due to the use of direct phase current signal analysis by the convolutional neural network (CNN), it was possible to ensure high accuracy of fault detection with simultaneously short reaction time to occurring fault. The technique used was based on the use of a weight coefficient matrix of a pre-trained structure, the adaptation of which was carried out for different sources of diagnostic information.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00022024-01-20T00:00:00.000+00:00Nonlinear Optimal Control for the Nine-Phase Permanent Magnet Synchronous Motorhttps://sciendo.com/article/10.2478/pead-2023-0022<abstract> <title style='display:none'>Abstract</title> <p>Multi-phase electric motors and in particular nine-phase permanent magnet synchronous motors (9-phase PMSMs) find use in electric actuation, traction and propulsion systems. They exhibit advantages comparing to three-phase motors because of achieving high power and torque rates under moderate variations of voltage and currents in their phases, while also exhibiting fault tolerance. In this article a novel nonlinear optimal control method is developed for the dynamic model of nine-phase PMSMs. First it is proven that the dynamic model of these motors is differentially flat. Next, to apply the proposed nonlinear optimal control, the state-space model of the nine-phase PMSM undergoes an approximate linearization process at each sampling instance. The linearisation procedure is based on first-order Taylor-series expansion and on the computation of the system’s Jacobian matrices. It takes place at each sampling interval around a temporary operating point which is defined by the present value of the system’s state vector and by the last sampled value of the control inputs vector. For the linearized model of the system an H-infinity feedback controller is designed. To compute the feedback gains of this controller an algebraic Riccati equation is repetitively solved at each time-step of the control algorithm. The global stability properties of the control scheme are proven through Lyapunov analysis. First it is demonstrated that the H-infinity tracking performance criterion is satisfied, which signifies robustness of the control scheme against model uncertainty and perturbations. Moreover, under mild assumptions it is also proven that the control loop is globally asymptotically stable. Additionally it is experimentally confirmed through simulation tests, that the nonlinear optimal control method achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs. Finally, to apply state estimation-based control without the need to measure the entire state vector of the nine-phase PMSM, the H-infinity Kalman Filter is used as a robust state estimator.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2023-00222023-12-12T00:00:00.000+00:00Enhancing PV Systems with Intelligent MPPT and Improved control strategy of Z-Source Inverterhttps://sciendo.com/article/10.2478/pead-2024-0001<abstract> <title style='display:none'>Abstract</title> <p>The Improved Z-Source Inverter (IZSI) has gained attention in the photovoltaic industry for its ability to boost PV voltage with a single-stage topology, simplifying system design and reducing costs. However, research on integrating IZSI into PV systems, particularly regarding the Maximum Power Point Tracker (MPPT) and IZSI control strategy, is limited. This study proposes an Intelligent Improved Particle Swarm Optimization (IPSO) algorithm as an MPPT method for PV systems under constant and varying irradiance conditions. The IPSO algorithm is compared to the FPA, CSA, and traditional MPPT algorithm (PSO), and the results demonstrate that IPSO outperforms all algorithms in terms of speed, efficiency, and convergence in finding the Maximum Power Point (MPP). Two methods, Simple Boost Control (SBC) and Maximum Constant Boost Control with Third Harmonic Injection (THIMCBC), are employed to control IZSI. Simulation results using MATLAB-Simulink show that both strategies successfully find and track the MPP, but THIMCBC exhibits superior voltage-boosting performance compared to SBC. Overall, the proposed IZSI topology with the IPSO MPPT method and THIMCBC IZSI control strategy offers several advantages, including improved voltage boost ability, reduced z-source capacitor voltage stress, inherent inrush current limitation, and cost-effectiveness. These advantages make the proposed system a promising solution for photovoltaic systems.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/pead-2024-00012023-12-12T00:00:00.000+00:00en-us-1