Microgrids (MGs) have become more prominent because of their ability to integrate renewable energy resources effectively. However, MGs face challenges in maintaining power quality due to the intermittent nature of renewable sources and the inherent time delay associated with feedback control loops, particularly in inverter-dominated systems with parallel distributed generators. This article proposes an enhanced multistep finite control set-based model-predictive controller (MSFCS-MPC) designed for AC MGs to effectively mitigate time delay. The considered AC MG design constitutes parallel inverter-fed DGs with intermittent source and load dynamics, where the photovoltaic with a boost converter and the battery with a bidirectional DC–DC converter are modeled to capture the realistic behavior of DC-link voltage instead of ideal DC conditions. The proposed model-predictive control framework incorporates a multistep algorithm to mitigate the effect of time delay and to enhance the dynamic performance of the system. The robustness of the proposed model is evaluated under load disturbances for different delay values and compared with the existing conventional control strategies. The proposed MSFCS-MPC achieves faster active and reactive power settling time of 0.18–0.24 and 0.20–0.27 s, respectively, compared to 0.22–0.28 and 0.26–0.30 s for the conventional finite control set-based model-predictive controller (FCS-MPC) and 0.40–0.45 and 0.45–0.50 s for the proportional–integral (PI) controller. Furthermore, the proposed approach improves waveform quality by maintaining voltage total harmonic distortion (THD) below 2% and reducing current THD to approximately 2%, even for delay values up to 50 μs, whereas the conventional FCS-MPC and the PI controller exhibit voltage and current distortions. The efficacy of the proposed model is further validated through real-time simulations, utilizing OPAL-RT OP4510.

This paper proposes a Z source inverter assisted electromagnetic energy harvesting system. Electrical and mechanical components in an energy harvesting system produces electrical energy when tuned optimally. Adjustment of damping and resonant frequency is a crucial parameter in operating an energy harvesting system. This paper proposes a Z source inverter assisted system, where the independent control free-dom of Z source inverter has been utilized to regulate the output power. The two key components, damping and resonant frequency, have been regulated and therefore, an improved performance of the energy harvesting system has been achieved. The simulation based validation establishes the effectiveness of proposed architecture and control under operating conditions of varying frequency and varying amplitude.

A unified secondary controller based on finite control set-model predictive controller (FCS-MPC) approach is proposed for frequency control and voltage restoration of islanded-based AC Microgrid. The considered microgrid system consists of two distributed generation (DG) units with parallel inverters connected to photovoltaic (PV) and battery energy storage systems. The errors generated by the droop controller are eliminated using a secondary controller, which introduces corrective offsets to restore frequency and voltage to their nominal values. Unlike conventional approaches that employ traditional MPC and PI-based secondary control, the proposed method utilizes FCS-MPC in both primary and secondary control layers, establishing a unified predictive framework. An FCS-MPC is also used to control the bidirectional DC-DC converter and PV boost converter to ensure a stable DC-link voltage. A delay-compensated multi-step prediction mechanism is incorporated in the primary control layer to mitigate the effects of computational delays. The effectiveness of the proposed control strategy is investigated under load disturbances and delay conditions. Furthermore, the performance is compared with a traditional MPC and PI-based secondary controller using the OPAL-RT OP4510 platform, demonstrating enhanced dynamic response and robustness.

In this paper, a quadral-duty digital pulse width modulation (QDPWM) control-based hardware accelerator for the auxiliary permanent magnet brushed DC (PMDC) motors of electric three-wheelers (E3Ws) is proposed. The proposed accelerator involves a precise motor speed calculation circuit, including a buffer to hold the position encoder signal for a predefined number of clock cycles to eliminate encoder signal noise. The proposed hardware accelerator is described with supporting mathematical models and is implemented on field-programmable gate array (FPGA) as well as application-specific integrated circuit (ASIC) platforms using SCL 180 nm CMOS technology library. The ASIC implementation at 12.5 MHz shows that the proposed design has significantly less area and power consumption than the conventional PI-PWM controller-based architecture and is comparable to the dual-duty digital pulse width modulation (DDPWM) controller. The proposed FPGA prototype-driven motor attains a wider speed range with low-speed ripple than DDPWM controller-based architecture. The position signal buffer circuit also enables the accelerator to tolerate noise or glitches in the position encoder signal, which makes the speed calculation precise and reliable. The proposed hardware accelerator-based PMDC drive performance has been validated regarding settling time, speed tracking ability, tolerance to dynamic speed, and load variations on a laboratory test setup.

This paper presents an internal model control (IMC) strategy for an inverter-based autonomous microgrid (MG) considering time delay. The system is modeled with two parallel inverters connected with multiple linear loads and incorporates communication delay associated with measurement blocks. The IMC controller is properly tuned with the help of a filter. parameter and utilized to control active and reactive power sharing. Furthermore, the time delay is modeled using Pade. approximation and the test system is investigated with uniform and non-uniform delay. The key performance indicators, like Overshoot, steady-state accuracy, and settling time demonstrate that the IMC controller provides better mitigation of high-frequency oscillations under both uniform and non-uniform delay. The proposed model efficacy is compared with a conventional controller, and the results indicate that IMC application in distributed energy systems mitigates high-frequency oscillations associated with inherent time-delays.

Lithium-ion batteries are essential to modern electric vehicles, yet managing them safely and efficiently requires accurate real-time estimation of the State of Charge (SoC) and State of Health (SoH). Traditional estimation methods face significant limitations under dynamic conditions. This paper presents a hybrid estimation framework for combined SoC and SoH estimation using a second-order equivalent circuit (2RC) model and error correction via an Extended Kalman Filter (EKF). MATLAB-based simulations validate the model, demonstrating accurate SoC and SoH predictions under real-world conditions. The proposed method shows high precision, achieving R2 values of 0.997 and 0.999 for SoC and SoH estimates, respectively. The standard error deviations are also low, confirming its reliability. These findings indicate that the proposed framework significantly enhances the accuracy and robustness of battery monitoring, making it well-suited for integration into advanced battery management systems (BMS) in electric vehicles.

Smoke detection is essential for safety and fire protection systems, and incorporating machine learning (ML) algorithms significantly improves its precision and effectiveness. The ML techniques for binary classification are investigated and assessed in this work by utilizing different algorithms such as: Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RT), and Support Vector Machine (SVM). The smoke detection dataset chosen for this study contains around 62,630 with 14 features instances where 44,757 instances have been identified as fire, whereas 17,873 instances have been classed as no fire. Moreover, these cases are determined to be unbalanced. The data pre-processing techniques utilized for training and performance evaluation are SMOTE-Tomek, the removal of unnecessary features, and the correlation matrix for dimensionality feature selection. The efficacy of the fire and smoke detection model is then compared with the following metrics such as: computational time, accuracy, precision, recall, and F1-score.

Power and frequency instability pose significant challenges in microgrid operation, which restricts load sharing and degrades dynamic performance. Existing control methods often involve trade-offs between stability and power sharing. Conventional power system stabilizers (PSS) utilize lead-lag compensators with parameters selected arbitrarily, resulting in less than optimal performance during disturbances. This research paper presents a novel, generalized PSS designed for inverter-based microgrids. It incorporates an adaptive Honey Bee Optimization (HBO) algorithm for dynamic tuning of the lead compensator parameters T1, T2, and gain K. Unlike traditional methods, the proposed HBO-PSS improves the damping of low-frequency oscillations and enhances power sharing accuracy, while maintaining stable output voltage. The time-domain simulation results indicate that the adaptive HBO-PSS demonstrates superior performance compares to existing methodologies. The proposed PSS facilitates faster and more equitable power sharing, while also enhancing stability significantly, even in the presence of switching disturbances and higher droop coefficients. This work simplifies the implementation and analysis of PSS while facilitating future research into decentralized control strategies for distributed energy systems.

This paper proposes a novel hybrid control strategy integrating a Finite Control Set Model Predictive Controller (FCS-MPC) with a universal droop controller (UDC) for effective load power sharing in inverter-fed microgrids. Traditional droop-based methods, though widely adopted for their simplicity and decentralized nature, suffer from limitations such as steady-state inaccuracies and poor transient response, particularly under mismatched impedance conditions. To overcome these drawbacks, the proposed scheme incorporates detailed modeling of inverter and source dynamics within the predictive controller to enhance accuracy, stability, and response speed. The UDC complements the predictive framework by ensuring coordination among inverters with different impedance characteristics. Simulation results under various load disturbances demonstrate that the proposed approach significantly outperforms conventional PI-based droop control in terms of voltage and frequency regulation, transient stability, and balanced power sharing. The performance is further validated through real-time simulations, affirming the scheme’s potential for practical deployment in dynamic microgrid environments.

In this paper, A new customized multi-level inverter (MLI) configuration is proposed for induction motor drive, aiming to lower the requirement of DC bus voltage magnitude. This method utilizes pole pair winding coils separately to generate multi-level voltage waveform across the total stator phase windings. As the inverter requires lower input voltage it eliminates the requirement of boost converters when it is used in the EV applications. The inherent advantages of this topology significantly reduce control complexity in the battery systems by reducing the number of series-connected battery cells. The conventional Level-Shifted Sine Triangle PWM technique proficiently shifts low-frequency harmonics to the carrier frequency, enhancing power quality and minimizing electromagnetic interference. Through MATLAB simulation, this new customized multi-level inverter-fed open-end stator winding Induction motor is simulated and results are presented to validate the proposed concept. Ultimately, our research aims to contribute to advancing electric vehicle technology by operating the induction motor with minimal input DC source voltage, and substantial output gain.

Numerous reviews are available in the literature on PV inverter topologies. These reviews have intensively investigated the available PV inverter topologies from their modulation techniques, control strategies, cost, and performance aspects. However, their compliance with industrial standards has not been investigated in detail so far in the literature. There are various standards such as North American standards (UL1741, IEEE1547, and CSA 22.2) and Australian and European safety standards and grid codes, which include IEC 62109 and VDE. These standards provide detailed guidelines and expectations to be fulfilled by a PV inverter topology. Adherence to these standards is essential and crucial for the successful operation of PV inverters, be it a standalone or grid-tied mode of operation. This paper investigates different PV inverter topologies from the aspect of their adherence to different standards. Both standalone and grid-tied mode of operation-linked conditions have been checked for different topologies. This investigation will help power engineers in selecting suitable PV inverter topology for their specific applications.

Boost converters often face challenges such as sluggish dynamic behavior, inadequate voltage regulation, and variations in input voltage and load current. These issues necessitate the need for closed-loop operation. Nature-inspired optimization algorithms (NIOA) have demonstrated their effectiveness in delivering enhanced solutions for various engineering problems. Several studies have been conducted on the use of proportional-integral-derivative (PID) controllers for controlling boost converters, as documented in the literature. Some studies have shown that using fractional order PID (FO-PID) controllers can lead to better performance than traditional PID controllers. Nevertheless, implementing FO-PID can be quite complex. Considering the widespread use of commercial PID controllers in industrial settings, this study focuses on finding the best tuning for these controllers in DC-DC boost converters. The approach used is particle swarm optimization (PSO) based on integral performance criteria. Simulation results indicate that the proposed controller achieves superior performance, evidenced by the lowest settling time, overshoot, integral absolute error (IAE), and integral squared error (ISE) values under varying input voltage and load current conditions, compared to both PID and FO-PID controllers. These findings have been confirmed through hardware implementation, which demonstrates the effectiveness of the proposed controller.

This work presents the power factor correction (PFC) buck-boost converter for on-board electric vehicle (EV) charging applications. The PFC buck-boost converter is designed to operate in discontinuous current conduction mode (DCCM), thus achieving natural PFC for the universal input voltage range. In addition, DCCM operation does not require input voltage or current sensors; as a result, the control is more reliable and economical than continuous current conduction mode (CCCM). Furthermore, the buck-boost converter switch operates in zero current switching (ZCS) which results in reduced switching losses and improves the efficiency. The detailed steady-state analysis, operating modes, and design analysis for DCCM operation are presented. To validate the theoretical studies, a closed-loop voltage mode control of the PFC buck-boost converter is developed and tested in a PSIM software environment. The simulation results uphold the converter analysis and achieve a high power factor and low total harmonic distortion (THD) for the universal input range.

In this paper, a customized multi-level inverter configuration designed for driving an induction motor with multiple pole pairs is introduced. Within the induction motor, each pole pair winding coil spaced 360° (electrically) apart maintains the same voltage profile. In our case, two windings in a four-pole induction motor are deliberately disconnected. A dual two-level inverter is used to power each half of the winding, so two such inverters are used to feed the entire stator winding of the induction motor as pole pair windings are disconnected. The single DC source used to power these inverters has a magnitude of Vdc/4, or 25% of input voltage DC bus voltage needed to power a typical Neutral Point Clamped five-level inverter. This new Pulse Width Modulation approach is used to cancel the harmonics at first center band while controlling the inverter output voltage. This method successfully lowers torque ripple by reducing current ripple. Furthermore, power balancing problems are eliminated because the single DC source is supplying the entire topology. The capacitor voltage balancing problems are also resolved because this design is derived using only two-level inverters. Very few changes to the design are needed for the suggested topology; the main change is to disconnect winding coils with the same voltage profile. The efficacy of the proposed inverter employing the innovative PWM technique in the linear modulation region is demonstrated by simulation results utilizing a 5-hp four-pole induction motor in MATLAB (Simulink).

The equivalent circuit of a voltage source inverter (VSI) fed brushless DC (BLDC) motor is similar to a buck converter supplied brushed DC motor. This analogy derives a linear relationship between the duty ratio and motor speed for continuous current conduction mode (CCCM). However, this relationship is not linear for discontinuous current conduction mode (DCCM), which is not generally considered in literature while controllers are designed. The DCCM of the BLDC motor driven by unipolar pulse width modulation (PWM) controlled voltage source inverter is analyzed, and corresponding quasi-steady-state model is derived in this paper. The motor speed can be precisely determined by simple computations with the proposed DCCM model, which can lead to complexity reduction in controller design. The effectiveness of the proposed model has been validated by the simulation and experimental analysis.

The wide integration of power electronics-fed systems presents new challenges to modern grids in terms of stability and power-quality. The various time constants associated with power electronic devices and their corresponding feedback control loop leads to dynamic frequency-couplings in a wide range of time-scale. This paper presents a comprehensive state-space model to examine the stability of an inverter-fed microgrids (IFMGs) using internal model controller (IMC) considering the digital time delay into account. The impact of control parameters along with power-droop coefficients and digital time-delay on system stability for analysing the cause of low-and-high-frequency instability phenomenon is evaluated through eigenvalue analysis. The delay effect on the significant parameters of the considered microgrid (MG) model is established and corresponding stability margins are investigated. Moreover, the states contributing to the oscillation modes are revealed through participation factor analysis. Finally, the real-time simulation results using OPAL-RT OP4510 are presented for validating the theoretical analysis and the efficacy of the proposed model is compared with well established traditional PI-based controller.

This paper examines the impact of polarization and gravity on piezoelectric actuators operating in various modes (d13 and d33). These modes are responsible for two different types of actuations like compressive and tensile. The Finite element analysis (FEA) of unimorph actuator is presented using 3D 20 node coupled element. The two different axial polarization effects are analyzed considering the effect of gravity. The displacement and stress field are studied for PZT-5H (Lead Zirconate Titanate) material. The variation of displacement and stress is presented with respect to thickness of piezoelectric actuator. In addition, the displacement field analysis of bimorph under voltaic gravity loading environment is presented.

The distributed generations (DGs) of an islanded microgrids (MGs) comprises of interconnecting primary and secondary control layers. The interactions among these controllers may yield new oscillatory modes with low damping, which decrease the stability margins. As the distribution network is dynamic in nature, the maintenance of system stability is of great concern, mainly while operating in autonomous mode. This paper proposes the optimal internal model control (IMC)-based droop control scheme to improve the small-signal stability and transient-response of an inverter-based MGs (IMGs) under different operating conditions. The proposed optimal scheme is achieved with the following approach: (a) first, comprehensive small signal model is prepared for the study system, and the interaction of the control parameters which influence the system stability are investigated through eigenvalue analysis, (b) the critical values of the significant parameters of the IMC and droop controllers are sorted out, and their corresponding stability domain is formulated, (c) based on the stability domain, PSO optimization technique is employed to generate optimal values, which delivers effective coordination among the crucial control parameters to improve the stability, (d) the developed optimal control scheme is cross-validated by comparing with the existing methods from the literature. The effectiveness of the proposed optimal scheme is subsequently assessed quantitatively with the help of time-domain specifications.

Microgrid comprises of several distributed generations (DGs), which are typically integrated through power electronic inverters. The existence of low inertial devices combined with the dynamic nature of the load challenges the stability of a microgrid and the effectiveness of the controller, mainly when operated in islanded mode. It is essential to optimize the parameters of the controller to enhance its efficacy under various operating conditions. In this paper, parameter optimization of universal droop and internal model control (IMC) is proposed based on an accurate small-signal model for an inverter dominated microgrid. In order to achieve robust control performance under different load conditions, a four-step approach is proposed: 1) an accurate small-signal model of a parallel multi-inverter system is prepared, which operates with the universal droop and internal model controller. The developed small-signal model is more accurate because it considers the dynamics of filter and phase-locked loop; 2) an investigation of critical control parameters of universal droop and internal model controller influencing the system stability is carried out, and their corresponding stability domain is identified through eigenvalue analysis; 3) particle swarm optimization (PSO) is used to optimize the critical parameters; and 4) the obtained result is validated under different load disturbances. Following the above approach, the time domain simulation is performed, which establishes that the proposed scheme improves the dynamic response of the DGs, counteracts the disturbances effectively and simultaneously improves the power-sharing. The proposed model is also compared with the well-established conventional PI-based droop controller, which demonstrates the efficacy of the proposed scheme.

In this paper, the internal model controller (IMC)-based universal droop controller is proposed to improve the dynamic response of parallel operated inverters as compared to conventional droop controller when there is a mismatch in line impedance. The proposed controller is demonstrated on two converters, 3-bus system, and results are compared with proportional integral (PI)-based conventional droop controller. The effectiveness of the proposed controller is verified from the dynamic response of the system. Also, the voltage and frequency of the system can be maintained within an acceptable range with the proposed controller.

The microgrid is an integrated form of distributed energy resources (DERs), which are typically interfaced with load and utility grid by power electronic converters. Stability analysis plays an important role in planning the microgrid system. In this paper, the analysis of stability and power sharing is carried out for an islanded microgrid with a universal droop controller. For a small signal stability assessment, state space model is developed for the microgrid system considering the linearized model of inverters and its associated feedback controllers. The different frequency modes of the complete model are identified and an eigen value analysis is done to determine the critical values of the controller gains. The system stability is tested on a microgrid framework with three inverters functioning as DERs. The effectiveness of the model is validated and verified with time domain simulations.

In this paper, an internal model control (IMC)-based universal droop controller is proposed in order to improve the accuracy of the small signal model and subsequently the transient behaviour of the system. The universal droop control technique utilized for power sharing among the parallel operated inverters is based upon the droop phenomenon of voltage and frequency. An IMC-based controller is designed to maintain the system frequency and voltage within permissible limits. The non-linear differential and algebraic equations of the system are derived by including network, load, phase locked loop (PLL) and filter dynamics along with the proposed controller. These equations are linearised around operating points to form a state-space model of the microgrid system. An eigenvalue analysis is carried out using the linearised model to ascertain the small-signal stability of the system. The critical values of the controller gains are identified and the effectiveness of the proposed model is validated with time domain simulations. Also, the improvement in power sharing of the inverters is observed with the proposed model.

This paper presents the small signal modelling and stability analysis of an inverter based microgrids with internal model control (IMC)-based robust droop controller. The robust droop control technique used for power sharing among the parallel operated inverters is without communication and is based on voltage and frequency droops respectively. An IMC based voltage and current controller is designed to maintain the system voltage and frequency within permissible limits. The dynamic equations of the microgrid system are developed and linearised around operating points. Subsequently, these equations are used to form a state space model of the considered microgrid system. The state space models of each inverter and its corresponding feedback controllers along with network and load are considered. Eigenvalue analysis is carried out to identify different frequency modes of the complete model and to determine the critical values of controller gains. The consequences of droop coefficients and gain on stability margins is studied in detail with the help of eigenvalue analysis. Further, this analysis and the effectiveness of the model is verified with time-domain simulation in MATLAB/SIMULINK. Results show that the IMC based robust droop controller improves the power-sharing and transient behaviour of the considered microgrid system.