International Journal of Power Electronics and Drive Systems (IJPEDS)
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Supervised learning for fast inverse motor control mapping: a comparative study on SRM and BLDC motors
Get PDFThis paper investigates the application of machine learning (ML) models, specifically artificial neural networks (ANN) and XGBoost, for real-time motor control, focusing on switched reluctance motors (SRM) and brushless DC motors (BLDC). Traditional inverse dynamics mapping for motor control is compared with ML approaches to highlight advantages in speed, accuracy, and deployment efficiency. Datasets simulating the input-output behavior of both motor types are used to train and test the models. Key performance metrics such as mean squared error (MSE), R² score, training time, and latency are evaluated, with the goal of replacing traditional control methods in real-time applications. Results indicate that ML models outperform traditional methods in terms of prediction accuracy and deployment speed, suggesting a promising path toward more efficient and adaptive motor control systems. The novelty of this work lies in applying supervised learning directly for inverse motor control mapping, thereby eliminating the need for explicit analytical models and enabling a unified, data-driven benchmarking framework across SRM and BLDC
Comparison of the discounted costs of controlled asynchronous electric drives with matrix and with DC link frequency converters
Get PDFA quality criterion based on discounted costs is proposed, which demonstrates a significant advantage of the variable frequency asynchronous motor drive with a matrix converter over the drive with a voltage source inverter, which contains a DC link. A MATLAB software simulation was conducted to ascertain the control characteristics. In light of the control range afforded by both drives, a criterion for discounted costs is proposed that is calculated as a mid-range within a specific rotational speed control range, or is determined based on a given tachogram. The aforementioned costs include the expense of the drive, the cost of losses, maintenance costs, amortization charges, and the cost of reactive power compensation due to phase shifts of the main harmonic current and voltage. In this study, we put forth a novel proposal for the incorporation of the cost of distortion power compensation resulting from the presence of harmonic components of the input current. The latter costs characterize the electromagnetic compatibility of the drive with the network. For the first time, a quality criterion for a regulated electric drive is proposed, which has a cost component that takes into account the electromagnetic compatibility of the drive with the network. A significant reduction in this component in a drive with a matrix converter compared to a drive with a DC link predetermines a reduction in discounted costs. For a given payback period and annual inflation rate, it was determined that the mid-range discounted costs were reduced by more than 11 times and the tachogram based discounted costs were reduced by more than 10 times for a drive with a matrix converter in comparison to a drive with a DC link
Modelling and analysis of linear DC motor with constant thrust characteristics
Get PDFThis paper introduces a portable and user-friendly innovation in food processing by replacing traditional molding methods with a linear DC motor (LDM). Traditional methods, which involve manual pressing, are energy-intensive and time-consuming, reducing productivity. The proposed LDM offers a simple, cost-effective, and robust solution capable of producing constant thrust, unlike conventional LDMs that require complex and expensive control methods and are limited to short displacements. The research focuses on modelling and analyzing an LDM with constant thrust characteristics for food processing applications. The primary objective is to model the thrust using the permeance analysis method (PAM), ensuring constant thrust capability. Verification was conducted using the finite element method (FEM) and measurement results, showing a percentage difference of 1.7% and 6.5%, respectively, between PAM and the other methods. The study provides valuable guidance for designing LDMs with constant thrust capabilities, enhancing the efficiency and practicality of food processing devices
Dynamic modelling and small-signal analysis of an efficient bridge-type multi-input DC converter for hybrid low-power systems
Get PDFThis paper presents the dynamic modelling and small-signal analysis of a bridge-type multi-input DC converter designed for hybrid low-power systems. The converter architecture supports the integration of multiple energy sources such as fuel cells and photovoltaic (PV) arrays, enabling enhanced flexibility and reliability. A CUK-based configuration is employed to achieve continuous input current and reduced voltage stress across the switches. The dynamic behavior of the converter is analyzed through average large-signal and small-signal state-space modelling. Stability is assessed using the Routh-Hurwitz criterion, and steady-state analysis is carried out to support performance evaluation. Experimental results obtained from a 250 W prototype confirm the validity of the developed models and demonstrate the efficiency and suitability of the proposed converter for hybrid renewable energy systems
Performance placement of BESS in the Sulawesi-Southern interconnected power system
Get PDFFrequency regulation and active power loss management are crucial aspects of power system operations. Battery energy storage systems (BESS) have emerged as an innovative solution to enhance grid performance, especially in addressing frequency fluctuations and reducing power losses. This study explores the role of BESS in optimizing frequency regulation and managing active power losses in the power system through several BESS integration scenarios. In this study, a BESS with a capacity of 8.437 MW was used and analyzed using symmetric steady-state simulations in DigSILENT PowerFactory software. The simulations aim to test the effectiveness of BESS in frequency regulation and minimizing active power losses in the Sulbagsel system. The analysis results show that implementing BESS can respond effectively to both over-frequency and under-frequency conditions in the Sulbagsel system. In the discharge scenario, BESS can reduce the system's average frequency by 0.02 Hz and decrease active power losses by up to 1.09 MW. Conversely, in the charge scenario, active power losses increase by 1.22 MW when the BESS is installed on Bus Tonasa. This study provides valuable insights for developing BESS-based frequency regulation strategies that contribute to the stability and efficiency of the power system
Adaptive fuzzy logic controller based BLDC motor to improve the dynamic performance for electric tractor application
Get PDFPermanent magnet brushless DC (PMBLDC) motors are widely used in a variety of industrial applications due to their high-power density and ease of regulation. The three-phase power semiconductors bridge is the standard way for controlling these motors. In order to initiate the inverter bridge and switch on the power devices, rotor position sensors must be provided with the correct commutation sequence. The power devices commutate progressively 60 degrees, depending on the location of the rotor. The right speed controllers are necessary for the motor to run as efficiently as possible. PI controllers are commonly employed with permanent magnet motors to achieve speed control in simple manner. Nevertheless, these controllers provide challenges in managing control complexity, including nonlinearity, parametric fluctuations, and load disturbances. PI controllers need accurate linear mathematical models. To overcome this, in this paper adaptive fuzzy logic controller (FLC) for controlling the speed of a BLDC motor is presented. When the motor drive system uses the adaptive FLC technology for speed control, it exhibits better dynamic behavior and is more resistant to changes in parameters and load disturbances. The main objectives of this work are to analyze and appraise the functioning of an electric tractor driven by a PMBLDC motor drive using adaptive FLC. The PMBLDC motor drive controllers are simulated using MATLAB/Simulink software
ANN-based MPPT for photovoltaic systems: performance analysis and comparison with nonlinear and classical control techniques
Get PDFIn photovoltaic energy systems, maximum power point tracking (MPPT) techniques are essential for optimizing power output under changing climatic conditions. Several techniques have been proposed in the literature, including classical techniques such as perturb and observe (P&O) and incremental conductance (INC), nonlinear controllers such as backstepping, and artificial intelligence-based techniques like fuzzy logic. This study compares the performance of an artificial neural network (ANN)-based MPPT approach with these nonlinear and classical MPPT techniques. It analyses the advantages and limitations of the various techniques to evaluate their performance in terms of efficiency, accuracy, and output power stability under changing climatic conditions. The study aims to help researchers select the most effective technique to improve the efficiency of photovoltaic systems. The simulation was carried out using MATLAB/Simulink. The simulation results indicated that the artificial neural network achieved better performance than the other techniques in terms of tracking speed, with an efficiency of up to 99.94%, while maintaining stable output power under changing climatic conditions. The backstepping controller also showed stable output power compared to traditional techniques. Fuzzy logic had a lower efficiency than both the artificial neural network and backstepping. Perturbation and observe and incremental conductance are easy to implement, but they showed oscillations around the maximum power point, which reduces the overall efficiency of the system
Control strategy comparison of the 8/6 switched reluctance motor in several inverter topologies
Get PDFThis paper proposes a control strategy for switched reluctance motors (SRMs) using the asymmetric half-bridge (AHB), shared switch, and Miller converter based on MATLAB/Simulink and TMS320F28379D. The control strategy implemented in this study involves the application of proportional-integral (PI) speed control with a pulse width modulation (PWM) switching method for each topology. By employing this control strategy, the system aims to regulate the speed of the motor and achieve the desired performance while ensuring efficient power utilization. The PI controller is utilized to adjust the motor's speed based on the error between the desired and actual speeds, enabling precise control. Additionally, the PWM switching method is employed to modulate the motor voltage, allowing for smooth and continuous speed adjustments. A thorough method for maximizing each topology's performance and raising the overall system efficiency is provided by this combination of control techniques. The detailed analysis and operation of each converter are presented in this paper. Simulation and experiment results show that AHB and shared switch have better performance than Miller. But the Miller converter needs the least number of switching components. Although the performance of the shared switch is equal to that of AHB, uses of this topology are limited to SRM with an even number of phases
Review on multi-input DC-DC converters topologies for electric vehicle charging application
Get PDFThe evolving fast-charging technology ends the hindrances of electric vehicle (EV) usage by integrating renewable energy sources and hybrid energy storage systems to increase the range and reliability of the vehicle. Nowadays, the development of the smart grid hosts bi-directional operation for improving the power quality by sending power from EV to the grid. For that, the multi-input (MI) converters are the breakthrough with the bidirectional conduction operation, which supports the power flow from vehicle to grid, vehicle, and building operation (V2X). Another important criterion for EV chargers is the high-power density with less losses by zero voltage and current switching and less circulating current, which can be achieved with resonant converters. All existing reviews missed out on focusing on resonant converters for bi-directional MI converters. This paper reviews the bi-directional converter topologies with multiple inputs suitable for V2X operation based on high and low voltage, frequency, control, and switching components
Hybrid energy storage system for dynamic power management in grid-connected microgrid
Get PDFThis paper presents an adaptive rule-based approach for dynamic power management in grid-connected microgrids. Solar photovoltaics (PV) and a battery-ultracapacitor hybrid energy storage system form the DC subsystem. Initially, the reference power is processed through a low-pass filter, diverting high-frequency power variations to the ultracapacitor, thereby safeguarding the battery. Then, a power allocation factor proportional to the battery state of charge manages the average power distribution between the battery and the grid. Finally, a microgrid power management system (MPMS) establishes rules to regulate power sharing among sources and loads. In the proposed method, the battery handles long-term energy requirements, the ultracapacitor meets short-term power demands, and the grid is adjusted to align with the system’s requirements. The main benefits involve effective power distribution among sources and loads, DC bus voltage stabilization, smooth transitions between different operating modes, and enhanced grid power quality. Additionally, safety protocols prevent overcharging/deep discharging, thus reducing the risk of premature degradation and resulting in longer lifespan of storage devices. MATLAB/Simulink is used to implement and validate the method