Current Tracking Accuracy Research Articles

Finite control set model predictive current control for three phase grid connected inverter with common mode voltage suppression

This research introduces an advanced finite control set model predictive current control (FCS-MPCC) specifically tailored for three-phase grid-connected inverters, with a primary focus on the suppression of common mode voltage (CMV). CMV is known for causing a range of issues, including leakage currents, electromagnetic interference (EMI), and accelerated system degradation. The proposed control strategy employs a system model that predicts the inverter’s future states, enabling the selection of optimal switching states from a finite set to achieve dual objectives: precise current control and effective CMV reduction, a meticulously designed cost function evaluates the potential switching states, balancing the accuracy of current tracking against the necessity to minimize CMV. The approach is grounded in a comprehensive mathematical model that captures the dynamics of CMV within the system, and it utilizes an optimization process that functions in real-time to determine the most suitable control action at each interval, Experimental validations of the proposed FCS-MPCC scheme have demonstrated its effectiveness in significantly improving the performance and durability of three-phase grid-connected inverters, Experimental validations of the proposed (MPC with CMV) scheme have demonstrated its effectiveness in significantly improving the performance and durability of three-phase grid-connected inverters. The proposed method achieved substantial reductions in CMV, notable improvements in current tracking accuracy, and extended system lifespan compared to conventional control methods.

Enhanced Adaptive Dynamic Surface Sliding Mode Control for Optimal Performance of Grid-Connected Photovoltaic Systems

This study presents an enhanced, adaptive, and dynamic surface sliding mode control (SMC), a cutting-edge method for improving grid-connected photovoltaic (PV) system performance. The suggested control approach uses dynamic SMC and adaptive approaches to enhance the robustness and efficiency of a system. Proportional–integral (PI) and SMC, two control systems for maximum power point tracking (MPPT) in PV systems, are compared in this paper. This study finds that the SMC system is a more effective and efficient MPPT approach for PV systems compared to the conventional PI control system. The SMC system’s unique feature is the capacity to stabilize grid voltage and attain a modulation index of less than one. An important component of power electronic system control is the index, which acts as a parameter representing the relationship between the output signal’s amplitude and the reference signal’s amplitude. The SMC method demonstrates improved robustness, efficiency, and stability, especially in dynamic operating settings with load and solar radiation changes. Compared to the PI control, the SMC exhibits a noteworthy 75% reduction in voltage fluctuations and an improvement in the power output of 5% to 10%. Regarding output power optimization, voltage stability, and accurate current tracking, the SMC system performs better than the PI control system. Furthermore, the SMC technique maintains a modulation index below one and guarantees grid voltage stability, both of which are essential for the efficiency and stability of power electrical systems.

High-performance finite-time adaptive control strategy for three-level T-type converters

Three-level T-type converters are necessary interfaces for distributed energy resources to interact with the public grid. Naturally, designing a control strategy, featuring superior dynamics and strong robustness, is a promising solution to guarantee the efficient operation of converters. This article presents an improved finite-time control (IFTC) strategy for three-level T-type converters to enhance the dynamic performance and anti-disturbance capacity. The IFTC strategy integrates a dual-loop structure to regulate the dc-link voltage and grid currents. Specifically, the voltage regulation loop employs a finite-time adaptive controller that can counteract load disturbances without relying on current sensors. In the current tracking loop, finite-time controllers combined with a command filter are constructed to obtain fast and accurate current tracking. In this loop, the command filter is utilized to avoid calculating the derivative of current references. Theoretical analysis and experimental results demonstrate the IFTC strategy’s effectiveness.

Predictive Current Control of Switched Reluctance Machine for Accurate Current Tracking to Enhance Torque Performance

Predictive Current Control of Switched Reluctance Machine for Accurate Current Tracking to Enhance Torque Performance

Adaptability enhancement of fractional‐order LLCL‐type grid‐connected inverter to weak grid based on grid voltage weighted feedforward scheme

SummaryGrid‐connected inverter with a novel fractional‐order LLCL filter has the advantage of high grid current tracking accuracy and low total harmonic distortion without passive or active dampers, and the grid voltage full feedforward scheme is an effective method to improve the quality of grid current. However, due to the digital control delay, the suppression of the grid current harmonics is weakened, and the inverter output impedance has an additional negative phase shift, which deteriorates the stability of grid‐connected systems under weak grid. In this paper, a weighted grid voltage fractional‐order feedforward control scheme is proposed based on a quasi‐proportional resonant (QPR) controller, which introduces two weighting factors in the full feedforward path of the grid voltage and compensates the phase lag of the output impedance by designing appropriate weighting factors. Then, an improved scheme combining the QPR controller with a phase compensator is presented. As a result, the suppression ability of grid current harmonics and the adaptability to grid impedance variations are enhanced. Simulation and experimental results verify the effectiveness of the proposed grid voltage fractional‐order weighted feedforward scheme.

Mode Predictive Direct Power Control Scheme with Fixed Operation Frequency for a Vienna Rectifier Based on Voltage‐Sensorless

Model predictive direct power control (MPDPC) is a suitable method for the highly nonlinear system of a three‐level Vienna rectifier. However, the traditional MPDPC suffers from irregular switching states, which can decrease current tracking accuracy and generate high current ripple and electromagnetic noise. Additionally, the use of sensors can increase system hardware costs and complexity. To enhance operational reliability and reduce the fault impact of AC voltage sensors, a double closed‐loop control strategy based on voltage‐sensorless MPDPC in the inner loop and sliding mode control (SMC) in the outer loop is proposed. First, the virtual flux model of the three‐phase Vienna rectifier is established in the two‐phase static coordinate system, and the second‐order low‐pass filter is used to improve the voltage observer to estimate the grid‐voltage. Meanwhile, an improved grid voltage observer based on the second‐order low‐pass filter is designed to improve the observation effect. Second, to solve the variable switching operation, current fluctuation and wide harmonic spectrum caused by the traditional MPDPC effectively, a double closed‐loop control strategy with constant switching frequency based on voltage‐sensorless MPDPC in the inner loop and SMC control in the outer loop is proposed. Based on the principle of SVPWM modulation, the modulation voltage of SVPWM is calculated directly, in order to verify the correctness of the theoretical analysis, extensive simulation and matching experimental is presented to verify the correctness of the theoretical analysis. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Hierarchical Coordinated Energy Management Strategy for Hybrid Energy Storage System in Electric Vehicles Considering the Battery’s SOC

This paper combines two types of energy storage components, the battery and supercapacitor (SC), to form a fully active hybrid energy storage system (HESS) as a power source for electric vehicles (EVs). At the same time, a hierarchical coordinated energy management strategy based on model predictive control (HCEMS-MPC) is presented. Firstly, the mathematical model of the fully active HESS is obtained based on Kirchhoff’s law and state-space modeling technology. Secondly, considering the state of charge (SOC) of the battery, a fuzzy-control-based upper-level energy management strategy (EMS) is proposed to optimize power allocation and to generate a reference current for a lower-level current controller. Then, a lower-level current predictive controller is designed to achieve accurate current tracking. Finally, a lower-level voltage sliding mode controller is designed to stabilize the bus voltage. Compared with previous works, the HCEMS-MPC strategy only needs to adjust the weight matrix and the reaching term to avoid the problem of excessive controller parameters. The simulation results, under different driving conditions, show that the HCEMS-MPC strategy has a better performance with respect to its fast response, error reduction, and robust stability. In addition, the SOC of the battery decreases more slowly, and the final SOC value significantly increases, thereby extending the single-discharge cycle time of the battery and improving the service life of the battery.

A Hierarchical Control Strategy Based on Dual-Vector Model Predictive Current Control for Railway Energy Router

The multiport and multidirectional energy flow of railway energy routers (RERs) poses a significant challenge when integrating photovoltaic (PV) systems and energy storage systems (ESSs). To address this issue, this paper proposes an improved hierarchical control strategy for RERs with a reference signal generation layer and an inverter control layer. In the reference signal generation layer, a time-segmentation energy allocation strategy based on a state machine is proposed to manage the multidirectional energy flow in RERs resulting from PV systems and ESSs while minimizing peak power demand. In the inverter control layer, a dual-vector model predictive current control (MPCC) strategy is designed for back-to-back inverters. The dual-vector MPCC strategy eliminates the need for individual PWM blocks, thereby enhancing RER current-tracking accuracy and efficiency. The prominent advantage of the dual-vector MPCC strategy is its ability to achieve high current-tracking accuracy while minimizing active power losses. Simulations and hardware-in-the-loop experiments are conducted to validate the feasibility and effectiveness of the proposed method.

Multivector Model Predictive Current Control for Paralleled Three-Level T-Type Inverters With Circulating Current Elimination

Paralleled three-level T-type inverters face the unavoidable pitfall of the zero-sequence circulating current (ZSCC). Although the conventional model predictive control (MPC) could eliminate the ZSCC, the control error occurs inevitably since only one vector is adopted in each sampling period, which decreases the current control performance. Thus, simultaneous ZSCC elimination and accurate current tracking become imperative to the inverter using MPC. This article proposed a multi-vector MPC to eliminate the ZSCC and reduce the current distortion without the weighting factor. As the common-mode voltage (CMV) and neutral point (NP) voltage are the main factors that induce the ZSCC, the virtual vector with zero-average CMV is constructed to eliminate the ZSCC. Meanwhile, the small vector is introduced to improve the NP voltage control capability. Additionally, to enhance the current accuracy and reduce the ZSCC ripple, three optimal vectors are adopted to synthesize desired voltage. Moreover, the multi-vector preselection algorithm is proposed to reduce the computational complexity of implementation process. Finally, the effectiveness of the proposed method is verified with comprehensive simulation and experimental results.

Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning

An improved fractional-order sliding mode control (FOSMC) for PMSM is presented in this study to set the unavoidable parameters and to improve permanent magnet synchronous motors (PMSMs) drive performance, such as current and speed tracking accuracy. To determine the optimal parameters of the FOSMC for control speed in a PMSM drive, a neural network algorithm with reinforcement learning (RLNNA) is proposed. The FOSMC parameters are set by the ANN algorithm and then adapted through reinforcement learning to enhance the results. The proposed controller using RLNNA based on fractional-order sliding mode control (RLNNA-FOSMC) can drive the motor speed to achieve the referred value in a finite period of time, leading to faster convergence and improved tracking accuracy. For a fair comparison and evaluation, the proposed RLNNA-FOSMC is compared with conventional FOSMC by applying the integral of time multiplied absolute error as an objective function. The most commonly used objective functions in the literature were also compared, including the integral time multiplied square error, integral square error, and integral absolute error. To validate the performance of the RLNNA-FOSMC speed controller, different scenarios with different speeds steps were carried out. The computational results are promising and demonstrate the effectiveness of the proposed controller. Overall, the proposed RLNNA-FOSMC controller for the PMSM speed control system performed better than conventional FOSMC in numerical simulations.

VOT and VFT-Based hybrid digital hysteresis control for UPS inverter

When the digital hysteresis current control (DHCC) strategy is applied to control the uninterruptible power supply (UPS) inverter, here are some issues such as large hysteresis tracking error caused by sampling interval and severe switching frequency swing caused by rapid change rate of inductor current. To address these issues, this paper presents a digital control strategy based on the hybrid digital hysteresis current control (HDHCC) of variable opening time (VOT) and variable falling time (VFT) for UPS inverter. Firstly, the HDHCC structure is established and the working principle of the inverter system is described in detail. Then, the tracking error and switching frequency error of the DHCC are derived. Based on the performance requirement of quasi-constant frequency control of UPS inverter, VOT and VFT control criteria without the dependency of circuit parameters are given. The experimental results demonstrate that the hybrid digital hysteresis control strategy based on VOT and VFT has the advantages of high current tracking accuracy, accurate switching frequency control, small output voltage waveform distortion, and simple implementation.

Brain Tumor Detection from MRI Images Using MATLAB Code

Cascaded H-bridge topology has been used in grid tied converters for battery energy storage system due to its modular structure. To fully utilize the converter’s modularity, this paper proposes a hierarchical distributed control architecture that consists of primary control, secondary control and battery state of charge (SOC) balancing control. Primary control ensures accurate current tracking while a distributed secondary control based on consensus algorithm is presented to regulate power sharing among modules and is proved to be stable theoretically. A distributed SOC balancing control is further introduced to improve energy efficiency of battery energy storage system. Finally, the hierarchical distributed control strategy is implemented using hardware controllers and a software platform. Besides, a carrier phase shift control is also implemented to achieve multilevel output voltage and harmonic reduction. The experimental results demonstrate the performance of the proposed control scheme effectively. Keywords—: Battery SOC balancing, cascaded H-bridge, consensus algorithm, distributed control.

Compensated Deadbeat Predictive Current Control Considering Disturbance and VSI Nonlinearity for In-Wheel PMSMs

In this article, a compensated deadbeat predictive current control (CDPCC) based on composite sliding mode disturbance observer (CSMDO) is proposed in response to the detrimental disturbance. Above all, the parameter variation and external load change are regarded as a lumped disturbance to build the PMSM mathematical model. Based on this model, a CSMDO is constructed to estimate the lumped disturbance in both speed and current loops. Then, the estimated disturbances are applied as compensations for the double loops to increase the speed robustness and current tracking accuracy. Furthermore, a voltage space vector compensation method is introduced to reduce the current distortion resulting from the added dead time in the three-phase full-bridge voltage source inverter. In the end, the effectiveness of the CDPCC method is validated by experiments through an in-wheel PMSM drive.

An improved data-driven based model predictive control for zero-sequence circulating current suppression in paralleled converters

To address the requirement of improved power capacity, reliability and operation, parallel converters have been widely applied in micro-grid. However, the connections between DC and AC sides of different parallel converters may lead to the surge of zero-sequence circulating current (ZSCC), which would result in the deterioration of system functionality. Regarding the stated problem above, this paper proposes an improved data-driven based model predictive control for parallel converters. Specifically, a model-free adaptive control (MFAC), which is based on the measured input/output data, is incorporated into the finite control-set model predictive control (FCS-MPC) framework with multi-objective constraints, thus allowing for the suppression of ZSCC and the improvement of robustness performance. Furthermore, to avoid the tuning of weighting factors, a novel cost function is constructed based on the multi-objective decision making method. The main contribution of the proposed methodology relies on the fact that no knowledge of any model parameters and weighting factors in whole control process are required, which leads to a significant enhancement in the robustness and reliability of the control system in the presence of parametric uncertainties. Furthermore, by this proposal, the accurate current tracking and ZSCC suppression can be achieved. Finally, the validity of the proposed FCS-MPC scheme is verified by comprehensive case studies.

A Parallel Topology Based Power-Stage PMSM Emulator With Accurate Ripple Current Reproduced

As a power hardware-in-the-loop (PHIL) technology, the power-stage motor emulator (ME) can be employed for the port characteristics emulation of motors. Meanwhile, the ripple current reproduction is one of the key technologies for achieving the high precision emulation of the port characteristics. Commonly, the high requirement for the hardware topology and the modulation strategy with rapid response and low harmonics are the main challenges. Aiming to obtain the precision ripple current, a ME scheme with dual-branch parallel topology is proposed in this paper, of which the equivalent switching frequency can be increased greatly by mean of interleaving switch. Furthermore, a new three-level space vector modulation strategy based on the idea of virtual transformation is presented. With the proposed strategy, the dual-branch parallel topology can be equivalently transformed into a specific three-phase three-level back-to-back topology. Finally, simulation and bench experiments have been conducted to validate the effectiveness of the proposed scheme. The results indicate that the proposed topology combined with the modulation strategy has a superior performance in improving the ripple current tracking accuracy of ME. Moreover, the proposed method can provide an excellent insight into improving the emulation accuracy of motor characteristics in practical applications.

Compensatory Model Predictive Current Control for Modular Multilevel Converter With Reduced Computational Complexity

Model predictive control (MPC) is widely used in modular multilevel converter (MMC) control because of its strong robustness, fast dynamic response, and strong stability. Traditional MPC must traverse several switch combinations to accurately regulate the output current and circulating current of the MMC. Therefore, as the number of sub-module (SM) grows, the controller’s computational complexity grows. This paper proposes a compensatory model predictive current control (CMPCC) for inner loop current control. It immediately estimates the number of SMs required by the bridge arm without scrolling optimization, reducing the amount of calculation of the system and improving the output current and circulating current tracking accuracy to the references. The objective function is established based on the system output current and internal circulation current by developing the discretization mathematical model of MMC. On the basis of minimizing the optimization scope, the compensation prediction is achieved through the volt-second balance, to achieve effective current control. Subsequently, an uneven bucket sorting algorithm is proposed to drastically eliminate the unnecessary sorting process. Finally, both a MATLAB/Simulink model and an experimental platform of MMC are built. To verify the practicality of the proposed control strategy, simulation and hardware experiments are provided.

Model predictive direct power control scheme for Vienna rectifier with constant switching frequency

Model predictive direct power control (MPDPC) has strong robustness and fast dynamic response, so it is widely applied in the control system of grid-connected converter. However, the traditional FCS-MPC bears with variable switching state, which will reduce the current tracking accuracy, accidentally produce current ripple and electromagnetic noise. Here, a double closed-loop control strategy with constant switching frequency based on optimal switching sequence synthesis of model predictive direct power control (MPDPC-CF) in the inner loop and SMC control in the outer loop is proposed for the non-linear system of Vienna rectifier. Firstly, the Vienna rectifier is modelled to obtain the predicted values of input power. Then, the given values of active power and reactive power are obtained through the outer loop. Three adjacent voltage vectors with the lowest cost function in the sector are selected to synthesize the optimal voltage vector, and the pulse time of the corresponding vector is calculated according to the cost function of the voltage vector. To verify the correctness of the theoretical analysis, the Vienna rectifier is taken as the research object, and the comparison with the traditional MPDPC shows that the proposed constant frequency model predictive control has good steadystate and dynamic performance.

An Improved Model Predictive Control Method for Three-Port Soft Open Point

Soft open point (SOP) is a key power electronic device to improve the flexibility and stability of the distribution network and is becoming a research hotspot. The traditional double closed-loop control of SOP has a complex structure, difficult process of parameter design, and poor output power quality. To solve these problems, finite control set model predictive control (FCS-MPC) has been adopted. Since FCS-MPC involves a large amount of calculation and experiences delay in current tracking, an improved FCS-MPC with delay compensation is proposed for three-port SOP in this paper to replace the inner loop current control strategy. Improved model predictive control combines the two-step prediction method based on the voltage vector and vector angle compensation method. The vector method is used to construct a mathematical model and a prediction model of three-port SOP. Based on FCS-MPC, the two-step prediction method that takes voltage as the target is used to compensate for the current delay problem, and the amount of calculation is reduced by converting the control target. Meanwhile, the vector angle compensation method is used to compensate the future reference value. Finally, a simulation model is built in MATLAB/Simulink. The simulation results under steady state and dynamic conditions show that the proposed strategy can effectively improve the current delay and reduce the amount of calculation. Furthermore, it has better current tracking accuracy and faster dynamic response speed.

Unified Control Scheme of Five-Phase Open-Winding Permanent-Magnet Synchronous Generator Systems for Aerospace Applications

In order to satisfy with the demand of high reliability in the aerospace field, a unified control scheme is proposed for five-phase open-winding permanent-magnet synchronous generator (FPOWPMSG) in this paper. Firstly, the mathematical model of FPOWPMSG in the phase coordinate system is established. Then, the proposed unified control scheme is presented in detail, which is mainly composed of the unified reference current generator, the current regulator, the synchronous electromotive force (EMF) compensator, and the piecewise nonlinear predictive compensator. In the unified reference current generator, normal operation, single-phase open-circuit, adjacent two-phase open-circuit, and non-adjacent two-phase open-circuit are taken into account by introducing a fault matrix. In the current regulator, the PI regulator is used. And the current tracking accuracy and the torque ripple are improved by both the synchronous EMF compensator and the piecewise nonlinear predictive compensator. Finally, the effectiveness of the proposed unified control scheme is validated by experimental results.

Stability Improvement of Pulse Power Supply With Dual-Inductance Active Storage Unit Using Hysteresis Current Control

The output power of the pulsed power supply (PPS) pulsates at the pulse repetition frequency (PRF) of pulse load. The pulsating power will result in a large bus voltage ripple. To balance the instantaneous power difference, a single or dual-inductance active storage unit (ASU) is usually connected in parallel with the output terminal of the PPS. Poor compensating current tracking accuracy of ASU will lead to the output current of PPS suffered from serious current spikes, which affects the stability of the bus voltage. A hysteresis current control (HCC) is proposed to achieve an excellent pulse current compensation performance. Compared with the current mode control (CMC), the small-signal modeling of dual-inductance with HCC is established to illustrate good compensation performance. Besides, a valley voltage loop is introduced to regulate the storage capacitor voltage in dual-inductance ASU to reduce the power loss at any pulse duty cycle. An experimental prototype is built to verify the spikes in output current can be eliminated effectively, the bus voltage keeps smooth and stable, and the output capacitor of the per-stage DC/DC converter is reduced significantly.