Voltage Vector Research Articles

Enhanced Output Performance of Two-Level Voltage Source Inverters Using Simplified Model Predictive Control with Multi-Virtual-Voltage Vectors

Interest in electric propulsion ships has garnered attention to reduce ship exhaust emissions. This has sparked extensive research on inverters. While two-level voltage source inverters are commonly utilized in small- and medium-sized ships owing to their simple structure and cost-effectiveness, they have limitations, such as high switching losses and reduced output performance. To address these issues, a model predictive control technique based on virtual voltage vectors is proposed in this study. Conventional two-level voltage source inverters are restricted to using only eight voltage vectors, which limits their output performance. By incorporating virtual voltage vectors, similar performance to multilevel converters can be achieved. The proposed technique involves a pre-voltage selection method that enhances output performance without increasing computational load. Through simulation and experiments, improved output current THD and current error were observed under various load conditions. This showcases the potential for enhancing the efficiency and performance of electric propulsion ships.

Predictive Torque Control With Reduced Voltage Vectors for Voltage Source Inverter Driven Induction Motor Drives

Predictive Torque Control With Reduced Voltage Vectors for Voltage Source Inverter Driven Induction Motor Drives

Minimization of Flux and Torque Ripples of FPOEW Induction Motor with FCS-MPTC using Synthetic Voltage Vectors

Minimization of Flux and Torque Ripples of FPOEW Induction Motor with FCS-MPTC using Synthetic Voltage Vectors

Modeling of Liquefied Natural Gas Cold Power Generation for Access to the Distribution Grid

Cold energy generation is an important part of liquefied natural gas (LNG) cold energy cascade utilization, and existing studies lack a specific descriptive model for LNG cold energy transmission to the AC subgrid. Therefore, this paper proposes a descriptive model for the grid-connected process of cold energy generation at LNG stations. First, the expansion kinetic energy transfer of the intermediate work mass is derived and analyzed in the LNG unipolar Rankine cycle structure, the mathematical relationship between the turbine output mechanical power and the variation in the work mass flow rate and pressure is established, and the variations in the LNG heat exchanger temperature difference, seawater flow rate, and the turbine temperature difference in the cycle system are investigated. Secondly, based on the fifth-order equation of state of the synchronous generator, the expressions of its electromagnetic power, output AC frequency, and voltage were analyzed. Finally, the average equivalent models of the machine-side and grid-side converters are established using a direct-fed grid-connected structure, thus forming a descriptive model of the overall drive process. The ORC model is built in Aspen HYSIS to obtain the time series expression of the torque output of the turbine; based on the ORC output torque, the permanent magnet synchronous generator (PMGSG) as well as the direct-fed grid-connected structure are built in MATLAB/Simulink, and the active power and current outputs of the grid-following-type voltage vector control method and the grid-forming-type power-angle synchronous control method are also verified.

Model Predictive Current Control for Six-Phase PMSM with Steady-State Performance Improvement

The application of finite control set model predictive control (FCS-MPC) in six-phase permanent magnet synchronous motors (PMSMs) often faces a trade-off between computational burden and accurate voltage vector selection, as well as challenges related to harmonic components and torque generation. This paper introduces an improved model predictive current control (MPCC) method to address these problems. Firstly, 12 virtual voltage vectors are synthesized to improve torque output performance while suppressing harmonic currents. Then, to generate symmetrical switching signals and reduce switching loss, the largest basic vector used to synthesize the virtual vector is replaced by two medium vectors. Secondly, to solve the problem of the increased computational burden caused by the increase in discrete virtual vectors, a two-step vector selection method is proposed. In this method, each part is divided into several parts according to N, and the traditional cost function is also replaced by two-step functions. Different control performances can be achieved according to different values of N. Experimental results show that the proposed control scheme not only achieves stable current quality but also significantly improves steady-state performance throughout the entire speed range.

Research on an improved deadbeat model predictive current control of double three-phase open-winding permanent magnet motor

Model predictive current control has high control accuracy and good control performance, and has been widely applied in the control strategy of dual three-phase permanent magnet synchronous motors. This article proposes an improved deadbeat model predictive current control (DMPCC) method by analyzing the mathematical model of a dual three-phase open-winding permanent magnet synchronous motor. One inverter predicts and calculates the optimal voltage vector through the deadbeat model, while the other inverter calculates the optimal voltage vector through the value function rolling optimization. This method reduces the computational workload of the controller, avoids the delay problem of the traditional model predictive current control (MPCC) method, improves the system's response speed, effectively suppresses the current in the harmonic sub-plane, and reduces torque ripple. The simulation results have verified the accuracy and speed of the above control method.

Dynamic overmodulation strategy based on torque and flux optimal tracking for DTC‐SVM of surface‐mounted PMSM drives

AbstractDirect torque control with space vector modulation has been increasingly attracting emphasis for permanent‐magnet synchronous machine control, benefiting from a high dynamic response and low torque ripple. However, the rapid tracking performance of torque and stator flux linkage is gradually deteriorating as the machine enters the overmodulation region because of the output‐voltage limitation of the inverter. Therefore, to enhance the system tracking performance in the overmodulation region, an innovative overmodulation method based on torque and flux optimal tracking is proposed. In contrast to the conventional overmodulation method where only one of the torque and stator flux linkage tracking is considered, the proposed strategy first constructs the weightless cost function to achieve a trade‐off control between the torque and stator flux linkage. Then, by using an equivalent geometric path to intuitively express the weightless cost function, the minimum cost function can be easily solved and the optimal output voltage vector can be determined correspondingly, to achieve the fast‐tracking of both the torque and stator flux linkage. Additionally, the voltage utilization of different overmodulation schemes is also analysed. Finally, the experimental results demonstrate the efficiency and practicality of the proposed strategy.

Research on Decoupling Duty Cycle Optimization Control Method of a Multiport Converter for Dual-Port Direct Drive Wave Power Generation System

Dual-port direct drive wave energy power generation systems (DP-DDWEPGS) have received widespread attention due to their smooth and zero-free output power, compared to single-port direct drive wave energy power generation systems (SP-DDWEPGS) which have the disadvantage of large out-put power fluctuations. To further enhance the performance of the DP-DDWEPGS, optimal power capture control is proposed to achieve maximum power point tracking. Meanwhile, a multiport converter is applied to the DP-DDWEPGS to solve the problem caused by an excessive number of switching devices in the overall system converter. The multiport converter fulfills all the functional requirements of the DP-DDWEPGS while reducing the number of switching devices. However, switch multiplexing of the multiport converter also introduces coupling relationships between each port and the wave force exhibits time-varying characteristics, necessitating advanced control methods with superior fast-tracking capability. Therefore, in this paper, a decoupling duty cycle optimization model predictive control for DP-DDWEPGS is proposed. Based on the characteristics of switching multiplexing, NSC finite control set model predictive control (FCS-MPC) decouples the current prediction and the cost function, reduces the number of candidate voltage vectors in each operation, and shortens the operation time by 70%. To address the issues of high ripple value and increased error due to decoupling in FCS-MPC, duty cycle optimization control is added, greatly reducing the fluctuations in electromagnetic force and power of the permanent magnet linear generator (PMLG). Based on the established simulation model, the feasibility and superiority of the multiport converter and decoupling duty cycle optimization model predictive current control method are verified.

Active damping control based bus voltage resonance suppression in electrolytic capacitorless PMSM application

Abstract The structure of electrolytic capacitorless in automotive electronic applications has the advantages of lower cost and better reliability. However, motor drive systems using this structure may experience unstable bus voltage. To this end, this paper proposes an active damping control strategy based on virtual impedance. By modelling the electric drive system and conducting stability analysis, the cause of bus voltage resonance due to the use of small capacitors is revealed. Based on the extracted DC bus voltage harmonic signal, additional voltage vectors are added in the d-axis and q-axis voltage vectors, eliminating the impedance mismatch problem in the drive system caused by the reduction of bus capacitance, effectively suppressing the voltage oscillation on the machine side of the drive system. Simulation data shows that under the condition of using small-capacity ceramic capacitors, the method proposed in this paper achieves a harmonic suppression capability similar to that of large-capacity electrolytic capacitors, effectively ensuring the application safety of automotive drivers with electrolytic capacitorless architecture.

An improved finite set model predictive control of SRM drive based on a voltage vectors strategy for low torque ripple

The robust rotor structure and fault-tolerance characteristics of the Switched Reluctance Motors (SRMs) are the best choice for next-generation Electric Vehicle (EV) applications. This machine has few restraints like high torque and flux ripples. However, the existing Model Predictive Control (MPC) using multiple control objectives and maximum sectors in the switching table results in high torque ripples due to the improper sector partition, Voltage Vectors (VVs) and weight factor (K1) selection. This paper proposes a Finite Set-Model Predictive Control (FS-MPC) for an analytical model of a non-linearity SRM machine to analyze the torque ripple performance. The proposed VVs are derived using sector partition based on the rotor position. The control is designed as a single cost function with the weighting factor contributing to smooth torque by selecting optimal control signals. Simulation studies and experiments with a four-phase 8/6 SRM drive verifies the enhanced FS-MPC for real-time implementation. The dynamic speed and ripple values of SRM Drives are measured using a mixed signal oscilloscope and the sensor probes. The laboratory outcomes calculate the analytical equations to validate the findings. The calculated value of torque ripple is 9 % through this FS-MPC. The study reveals that the proposed method is well suited for torque ripple reduction than flux ripples.

Sliding mode-based direct power control of unified power quality conditioner

The Unified Power Quality Conditioner (UPQC) is a promising solution for mitigating multiple Power Quality(PQ) issues in distribution systems, including harmonics, poor power factor, voltage sag/swell and voltage imbalance. The conventional Sliding Mode Controller (SMC) in UPQCs suffers from wide switching frequency variations, chattering problems, and inherent active and reactive power coupling. This study proposes a nonlinear control method, Sliding Mode-based Direct Power Control (SMC-DPC), for the simultaneous regulation of the shunt and series compensators in a UPQC. By optimizing voltage vector selection based on real-time power errors, the proposed method effectively mitigates chattering, and reduces switching frequency variations, and ensures precise tracking of instantaneous active and reactive powers even in the presence of coupling effects. The proposed approach simplifies the system design and improves steady state and dynamic power tracking. The simulation results in MATLAB Simulink® on a 20 kVA system demonstrate that the proposed method achieves a source current THD of 1.52%, compared to 2.31% for conventional SMC and 5.11% for linear controller. Furthermore, the method is robust to grid parameter variations and demonstrates satisfactory performance in both strong and weak grids. In weak grids, the proposed method reduces the line losses by 13.71% and 14.54% compared to SMC and linear controller respectively. The reported results comply with international standards such as IEEE-519 and IEC 61000-3-12, confirming effectiveness of SMC-DPC for enhancing PQ in distribution system.

A Reduced Voltage Vector Strategy-Based PTC of OEW-PMSM Drives

A Reduced Voltage Vector Strategy-Based PTC of OEW-PMSM Drives

Weightless Model Predictive Control for Permanent Magnet Synchronous Motors with Extended State Observer

Traditional model predictive torque control (MPTC) predicts the torque and flux values for the next time step and selects the voltage vector that minimizes the cost function as the optimal vector to apply to the inverter. This control approach is straightforward and allows for multi-objective control, but it has some issues in terms of the dynamic steady-state performance and parameter robustness. Therefore, this paper proposes a weightless model predictive control method based on an extended state observer (ESO). By designing an improved ESO to observe and compensate for motor parameter disturbances in real time, and employing a novel 2-D switching table and voltage vector sector selection diagram, the method evaluates three out of eight voltage vectors based on the torque and stator flux error signals. This reduces the computational load while increasing the number of candidate voltage vectors. Finally, a cost function without weighting factors is designed to lower the computational complexity. The simulation results show that the proposed new control method effectively reduces the torque and flux ripple and improves the current waveform compared to traditional MPTC.

ENHANCED MODEL-FREE PREDICTIVE CONTROL FOR VOLTAGE SOURCE INVERTERS USING AN ADAPTIVE OBSERVER

In this paper, a free model predictive control based on the active vector execution time (AVET-MFPC) using an adaptive observer is proposed for two-level voltage source inverters. The traditional model-free predictive control (MFPC) uses the sampling period to select one voltage vector for all candidate vectors according to the minimizing cost function principle. With the proposed control, two vectors are selected at one sampling period. The first vector is an active vector that uses the execution time of the active vector to select it, while the second one is a zero vector as it is applied after the active vector. The execution time is calculated using the ultra-local model (ULM) equation. In the traditional MFPC, the factor in the ULM is chosen with approximate values ranging between ±50 % of the nominal value. This paper proposes an adaptive sliding mode observer (ASMO) with an improved design to observe the variation of this factor, especially in case of mismatch parameters and during a step change in the reference signal. Combining the proposed ASMO observer and the AVET-MFPC controller gives faster system response, good tracking results, and less computational burden. Finally, the effectiveness of the proposed control model is approved and confirmed under various conditions, as well as the simulations carried out and the results obtained.

MPTC for Dual Three-Phase PMSM Based on Novel Virtual Voltage Vector

MPTC for Dual Three-Phase PMSM Based on Novel Virtual Voltage Vector

Modified load angle direct torque control for dual star motor using fuzzy logic

Space Vector Modulation (SVM) has emerged as a prominent alternative for motor control, particularly within the framework of Direct Torque Control (DTC-SVM). SVM leverages variations in the load angle, which result from changes in motor torque, to generate the appropriate voltage vectors. The conventional approach to this method involves a single Proportional-Integral (PI) regulator, which is characterized by a constant switching frequency and the capability to reduce ripples in torque, flux, and current. Despite these advantages, the PI regulator may face challenges in maintaining optimal performance under varying load conditions. This study seeks to enhance the performance of the DTC-SVM strategy by integrating Fuzzy Logic into the PI regulator. The primary objective is to improve the accuracy and responsiveness of the load angle control, thereby optimizing the motor's operational efficiency. The proposed SVM-Fuzzy control scheme is designed to address the limitations of the traditional PI regulator, offering a more adaptive and robust solution for motor control. To evaluate the effectiveness of the proposed approach, extensive simulations were conducted using Matlab Simulink. The SVM-Fuzzy strategy was compared against the conventional SVM-PI approach to assess its performance in terms of torque, flux, and current regulation. The SVM-Fuzzy control scheme significantly enhances efficiency, stability, and load angle precision, particularly in Double Star Induction Motors (DSIM). It also ensures the durability and reliability of the motor control system under different operating conditions.

Comparative analysis of uncontrollable angles in direct torque and stator flux control and rotor flux control strategies: A numerical and experimental study

AbstractThe uncontrollable angles (UAs) in direct torque control (DTC) algorithm is an important issue through which the effects of voltage vectors (VEs) on the magnetic flux and the torque are accurately determined. In this paper, a unique analysis of UAs is performed at different operating conditions, including parameters variations in two different strategies: Direct torque and stator flux control (DTC_SC) and (DTC_RC). Values of Those angles were accurately determined for wide speed, stator and rotor variations, and load changes. In addition, a detailed numerical comparison was performed in terms of these angles in the two strategies mentioned above for each operating condition. The comprehensive comparison showed the superiority of the DTC_RC strategy over its DTC_SC counterpart, being the maximum values of UAs in DTC_RC were 8°, 33°, and 21° versus 15°, 45°, and 38° in DTC_RC strategy for the following operations: Variable speed with variable stator resistance, variable speed with variable stator and rotor resistances, variable speed with variable load, respectively. MATLAB/Simulink results of the contributed analysis and comparisons were accomplished and validated. In addition, DS1103‐based experimental tests supported and verified the theoretical analysis.

A Novel Finite-Set Ultra-Local Model-Based Predictive Current Control for AC/DC Converters of Direct-Driven Wind Power Generation with Enhanced Steady-State Performance

Compared with the standard finite-set model-based predictive current control (FS-MPCC), the finite-set ultra-local model-based predictive current control (FS-ULMPCC) removes the use of actual system parameters and thus has some advantages like good robustness and easy implementation. However, the steady-state performance of FS-ULMPCC is relatively weak. In this paper, a novel FS-ULMPCC method is proposed and applied to the AC/DC converter of a direct-driven wind power generation system. The proposed method is designed based on a linear-extended state observer (LESO). In particular, a new control set reconstruction strategy is proposed to improve the steady-state performance. Only three options are included in the reconstructed control set, and each one is associated with two independent, active voltage vectors and their durations. The proposed FS-ULMPCC method is compared with the traditional one through experiments. The proposed method includes enhanced steady-state performance and reduced computational burden.

Improved weighting factor selection method of predictive torque control for PMSM

AbstractIn the traditional predictive torque control strategy, the cost function considers two different control objectives: stator flux and torque. Therefore, it is necessary to reasonably set the weighting factor to ensure that the optimal voltage vector is accurately selected during the control process, thereby achieving better torque and flux control performance. In view of the complex tuning process caused by traditional predictive torque control setting method of weighting factor, a new weighting factor selection method for permanent magnet synchronous motor control system is proposed in this paper. The derivation process is based on the equivalent transformation between the torque–flux prediction and the voltage vector prediction. If both the cost functions of the torque–flux and voltage vector reach their minimum values, the same output voltage vector will be selected. Compared with previous studies, the algorithm proposed in this paper can find the precise location of the optimal weighting factor without changing the form of the cost function, which simplifies the parameter tuning process. Experimental results are also provided to validate the effectiveness of the proposed algorithm.

Expanded virtual vector-based model forecastable control strategy for three-phase two-level inverters

Abstract A three-phase, two-level inverter based on model forecastable control has good transient performance but poor steady-state performance. Considering the limitation of a limited number of discrete voltage vectors in a two-level inverter topology, this paper proposes a virtual vector model prediction method based on the analysis of a time-stepped forecasting model for a three-phase grid-connected inverter. First, three fixed virtual voltage vectors are constructed in each sector, and the action time of the required fundamental vector is found. Then, the cost function is constructed, and the optimum is selected among the virtual and fundamental voltage vectors in each sector. Finally, a hardware-in-the-loop experiment was carried out based on the PE-Expert4 experimental platform developed by Myway Co., LTD. The results show that the proposed virtual vector model forecastable control strategy can effectively improve the transient and steady-state performance of three-phase two-level inverters.