Conventional Model Predictive Torque Control Research Articles

Three-Stage Duty Cycle-Based Deadbeat Predictive Torque Control for Three-Phase SPMSMs With CMV Reduction

Model Predictive Torque Control (MPTC) is highly regarded for its simple structure, rapid dynamic response, and optimized control performance when applied to actual motor driving systems. However, conventional MPTC techniques often lead to undesirable effects in three-phase inverter-based surface-mounted permanent magnet synchronous motors (SPMSMs), such as high electromagnetic torque, stator flux ripples, and significant current harmonic distortion. Notably, the generalized MPTC approach generates a substantial common mode voltage (CMV) that can cause damage to the motor bearing and winding insulation in SPMSMs. To address these issues, this paper proposes a three-stage duty cycle-based deadbeat predictive torque control (DCDPTC) technique for SPMSMs. The proposed technique leverages the volt-second equilibrium theorem by aligning the duty cycles with the predicted electromagnetic torque, stator flux, and their respective target values while accounting for extreme cases, accordingly electromagnetic torque and stator flux ripples as well as the total harmonic distortion (THD) of the stator current are minimized. In order to improve the system robustness, the duty cycle is limited to avoid the overmodulation. Furthermore, optimized switching sequences are meticulously arranged to ensure the CMV is lowered and the minimum number of switching transitions is maintained while utilizing a fixed switching frequency. The proposed technique is simplified. Its resultant performance is validated by experimental results.

Model predictive torque control for permanent magnet synchronous motor with hybrid mode duty cycle optimization

AbstractDue to the application of only one voltage vector in a control period, conventional model predictive torque control (MPTC) suffers from relatively large steady‐state ripples. The‐state‐of‐the‐art double‐vector‐based MPTC (DVMPTC) was proposed to improve steady‐state performance. However, its duty cycle optimization method significantly affects the control performances. Thus, MPTC with hybrid mode duty cycle optimization is proposed, which realizes better performance than the universal DVMPTC, and obtains the appropriate average switching frequency, especially at high‐speed domain. The proposed method utilises the universal DVMPTC method, while it equips duty cycle optimization with discrete space vector modulation (DSVM) scheme as the additional constraint for further reducing the reference voltage tracking error that exists in DVMPTC. What's more, rotation module and pre‐selection strategies are involved in simplifying the design of vector selection methods. Comparative simulations and experiments verify the effectiveness of the proposed method.

Modulated Model Predictive Torque Control for Fault-Tolerant Inverter-Fed Induction Motor Drives With Single DC-Link Voltage Sensor

Four-switch three-phase inverter (FSTPI) is widely used as a cost-effective fault-tolerant topology of six-switch three-phase inverter with an open-phase fault. To solve the inherent dc-link capacitor voltage offset (CVO) issue of FSTPI, two dc-link capacitor voltage sensors are required in conventional model predictive torque control (MPTC) strategies. To improve the reliability and reduce the cost of induction motor (IM) drives, a modulated MPTC (M-MPTC) for FSTPI-fed IM with single dc-link voltage sensor is proposed in this article. Therein, the relationship of the CVO and the load current is established to obtain the fundamental component of CVO. The two capacitor voltages are reconstructed by single dc-link voltage sensor and the fundamental component of CVO. To suppress the CVO, a cost function that only contains the output voltage vector is designed. The inner relationship between the proposed M-MPTC with single dc-link voltage sensor and the conventional M-MPTC with two dc-link voltage sensors is derived. To retain the load current within the allowed range, a current constraint scheme is proposed and integrated into the M-MPTC. Various simulation and experimental studies are carried out to verify the effectiveness of the proposed strategy.

An Improved Model Predictive Torque Control for PMSM Drives Based on Discrete Space Vector Modulation

In this paper, an improved model predictive torque control (MPTC) method based on discrete space vector modulation (DSVM) is proposed for permanent magnet synchronous motor (PMSM) drives. Aiming at solving the two problems of large torque ripples and high computational complexity in conventional MPTC, the proposed method adopts a second optimization and a new simplified search strategy. The key idea of second optimization is to make the output voltage vector closer to the actual optimal solution. In this case, a more suitable voltage vector is applied in each sampling period. The simplified search strategy reduces the calculation time by cutting down the number of candidate voltage vectors without affecting drives performance. Compared to the conventional MPTC without DSVM and with DSVM, the proposed method can produce superior steady-state performance and lower computational complexity. Simulation and experimental results are presented to validate the effectiveness and feasibility of the proposed method.

An Improved Model Predictive Torque Control for Switched Reluctance Motors With Candidate Voltage Vectors Optimization

This paper proposes an improved model predictive torque control (MPTC) strategy for switched reluctance motor (SRM) drives with candidate voltage vectors (CVVs) optimization, which can suppress the torque ripple effectively and enhance the system efficiency. This MPTC method is improved by three aspects. Firstly, the flux linkage calculation is removed compared to conventional MPTC. Secondly, the electric cycle of SRM is divided into six sectors based on the ideal torque contribution profile and the commutation region of the motor is redefined. Finally, CVVs of each sector are adopted based on phase torque characteristics and the total number of CVVs is reduced to 2 or 3 at each control period. The cost function is designed for the torque ripple suppression and copper loss minimization by selecting the optimal voltage vector from CVVs. This improved MPTC method avoids mass useless computation compared to conventional MPTC and no longer relies on hysteresis control loops compared to DTC method. In the simulation and experimental verification on a three-phase 12/8 SRM, the proposed MPTC method effectively reduces the torque ripple, improves the torque–ampere ratio and system efficiency, and improves dynamic response compared to DTC method.

A look-up table-based model predictive torque control of IPMSM drives with duty cycle optimization

Model Predictive Control (MPC) is an effective method of driving motors and power converters due to its quick response, integrity, and multivariable control adaptability. A model-predictive torque control (MPTC) technique for permanent magnet synchronous motors (IPMSMs), which is computationally efficient and of low complexity, is presented in this paper. The proposed technique designs a lookup table that is independent of flux angle and torque deviation. For each control instant, this technique has to evaluate four voltage space vectors (VSV) from the lookup table, resulting in a substantial reduction in switching frequency and computational burden without compromising the performance. A maximum torque per ampere (MTPA) technique generates reference currents. The controller’s complexity is minimized by eliminating the flux weighting factor from the cost function, saving time on offline weighting factor adjustments. Moreover, duty cycle optimization is performed using the mean torque control technique to minimize torque and flux ripples. The proposed method has been experimentally validated using a real-time simulator hardware in loop (HIL) with a TMS320F28335 floating-point digital signal processor on a prototype IPMSM drive. Furthermore, the proposed MPTC scheme is compared to conventional MPTC and direct torque control (DTC).

Model Predictive Torque Control for a Dual Three-phase PMSM Using Modified Dual Virtual Vector Modulation Method

Single voltage vectors applied in the conventional model predictive torque control (MPTC) for multiphase motors do not only suffer from serious torque and stator flux ripples but also cause the large harmonic current. To address the aforementioned challenges, an MPTC using a modified dual virtual vector modulation method is proposed to improve the operational performance of a dual three-phase permanent magnet synchronous motor. Virtual voltage vectors are synthesized as the candidate control set to restrain the harmonic current. A transformation method is introduced to consider both the stator flux and torque in the duty cycle modulation. The torque and stator flux ripples are simultaneously reduced by addressing the limitations of nonuniform units. Furthermore, the null voltage vector is then inserted to expand the modulation range and improve the steady-state performance. Moreover, the sawtooth carrier is adopted to address the challenge of the asymmetric switch sequence caused by the modified modulation. Finally, the experimental results are presented to verify the effectiveness and superiority of the proposed MPTC method.

Improve Performance of Induction Motor Drive using Weighting Factor approach-based Gravitational Search Algorithm

ABSTRACT The weighting factor adjustment limits the extensive application of conventional model predictive torque control in practice. In this paper, a model predictive torque control strategy with gravitational search algorithm (GSA) is proposed. The detail of an adaptive torque variable is introduced to control the flux linkage of the induction motor, and a modified value function is constructed by using electromagnetic torque and image torque. The proposed model uses two control variables to replace the torque and flux variables in the conventional model predictive torque control and improve the control efficiency. The simulation and experimental results show that the proposed method achieves a fast dynamic performance compared to the conventional model and reduces the average switching frequency. Besides, the system has high response speed, high accuracy, stability, and a certain application value.

Model Predictive Torque Control of Five-Phase PMSM by Using Double Virtual Voltage Vectors Based on Geometric Principle

The conventional model predictive torque control (MPTC) suffers from the heavy computation burden and the uncertainty of the weighting factor. This article proposed a new MPTC scheme for a five-phase permanent magnet synchronous motor by using double virtual voltage vectors (VVVs), in which no weighting factor is required. The VVVs that can restrain the harmonics work as the candidate vectors. The deadbeat principle is adopted to predict the reference voltage, which can be used to select the optimal VVV directly in avoid of testing all candidate VVVs, and hence, the computation burden is reduced. The geometric principle is applied to select the second voltage vector and calculate the vector duration. The second vector can be a VVV or null vector. Therefore, double VVVs or a VVV and a null vector can be synthesized for the next period. It should be noted that no weighting factor is required because of the introduced geometric principle. Due to the selection of the second voltage vector, the torque and flux ripples are reduced and the steady-state performance is improved. The proposed MPTC has the same fast dynamic response with the conventional MPTC. The experiments are presented to verify the proposed MPTC scheme.

A Low-Complexity Three-Vector-Based Model Predictive Torque Control for SPMSM

In conventional model predictive torque control (MPTC), only one voltage vector (VV) is applied during a whole control period, thus causing a large torque ripple. To improve the steady-state performance, some two-vector-based control schemes have been proposed. However, the selection of the optimal VV pair is complex as well as has a large computational burden, and the improvement of performance is still limited by the direction and amplitude of the output VV. This article proposes a low-complexity three-vector-based MPTC for SPMSM drives, which can precisely determine the appropriate active voltage vectors (AVVs) with the predicted torque error. Then, a modified switching table is developed to directly select the AVVs, thus greatly reducing the complexity and computational burden of the algorithm. To obtain a better steady-state performance, a duty cycle calculation method based on torque and stator flux difference parameters is newly proposed to achieve the deadbeat control of torque and stator flux. And then, the experimental comparisons with the double-vector-based MPTC are conducted. The results show that the proposed MPTC can effectively reduce the steady-state torque ripple while maintaining a good dynamic performance as well as almost a fixed switching frequency for all speed ranges.

Two-Stage Series Model Predictive Torque Control for PMSM Drives

A two-stage series model predictive torque control for permanent magnet synchronous motor drives is proposed in this article. First, the control of torque and flux linkage is converted to double-torque control (i.e., the control of active torque and reactive torque) based on the instantaneous power theory to eliminate the weighting factor in conventional model predictive torque control. Then, the double-torque prediction trajectory and double-torque reference are extrapolated to two control periods. The concept of two-stage series predictive control is proposed in this article, in which the cost functions of two prediction instants are designed to form series control structure. In the proposed method, the first-stage prediction is used to select candidate voltage vectors and the second-stage prediction is used to evaluate the optimal voltage vector. Since the cost function of two control periods in the future is considered when selecting the voltage vectors, the possibility that the same voltage vector is applied to adjacent control periods increases, thereby reducing the switching frequency of the system. Finally, the effectiveness of the proposed method is verified by experiments.

Duty VV-MPTC for Post-Fault Eight Switch Three-Phase Inverter Fed Induction Motor Drives With Reduced Neutral Point Voltage Fluctuation

This article proposes a novel duty ratio regulated virtual voltage vector (VV) model predictive torque control (MPTC) strategy for post-fault eight switch three-phase inverter fed induction motor drive with reduced neutral point (NP) voltage fluctuation. The proposed method contributes to substantially improve the steady-state torque control performance under post-fault conditions. Furthermore, compared with the conventional MPTC, it reduces the torque ripples as well as the NP voltage fluctuations. The mathematical model of eight-switch three-phase post-fault inverter fed induction motor is presented. Based on this, the synthesis of virtual VV is analyzed. Simulation and experimental results are presented to validate the effectiveness of the proposed method.

Robust Sensorless Model-Predictive Torque Flux Control for High-Performance Induction Motor Drives

This paper introduces a novel sensorless model-predictive torque-flux control (MPTFC) for two-level inverter-fed induction motor (IM) drives to overcome the high torque ripples issue, which is evidently presented in model-predictive torque control (MPTC). The suggested control approach will be based on a novel modification for the adaptive full-order-observer (AFOO). Moreover, the motor is modeled considering core losses and a compensation term of core loss applied to the suggested observer. In order to mitigate the machine losses, particularly at low speed and light load operations, the loss minimization criterion (LMC) is suggested. A comprehensive comparative analysis between the performance of IM drive under conventional MPTC, and those of the proposed MPTFC approaches (without and with consideration of the LMC) has been carried out to confirm the efficiency of the proposed MPTFC drive. Based on MATLAB® and Simulink® from MathWorks® (2018a, Natick, MA 01760-2098 USA) simulation results, the suggested sensorless system can operate at very low speeds and has the better dynamic and steady-state performance. Moreover, a comparison in detail of MPTC and the proposed MPTFC techniques regarding torque, current, and fluxes ripples is performed. The stability of the modified adaptive closed-loop observer for speed, flux and parameters estimation methodology is proven for a wide range of speeds via Lyapunov’s theorem.

Predictive torque control of SMPMSM drive system based on extended control set and double gradient descent method

Model predictive torque control (MPTC) has become an effective control method for the permanent magnet synchronous machine (PMSM) drive system in recent years. However, large torque and flux ripples due to the limited numbers of inverter voltage vector deteriorate the steady-state performance. In this paper, a novel model predictive torque control based on extended control set (ECS-MPTC) is proposed. First, an innovative extended control set is generated by the proposed partition method of quasi longitude and latitude lines, in which, many virtual voltage vectors are generated. Then, based on the characteristic of cost function without weighting factor, the optimal inverter voltage vector can be selected quickly by using the double gradient descent methods, and the invalid enumeration can be avoided. Thus, the computation burden can be kept in a low level. Finally, the simulation results of conventional MPTC and proposed ECS-MPTC validate that the proposed control can achieve excellent steady-state performance of PMSM drive system and low computation burden simultaneously.

Adaptive Sliding-Mode-Based Speed Control in Finite Control Set Model Predictive Torque Control for Induction Motors

The conventional model predictive torque control (MPTC) for induction motor drives evaluates the electromagnetic torque and stator flux linkage in the cost function. However, in the speed outer loop design, the torque reference in the cost function generally utilizes a classic proportional-integral (PI) controller, which is not only dependent on motor parameters but also sensitive to the change of the load torque. In this article, an adaptive sliding-mode-control-based MPTC (ASMC-MPTC) method is proposed to improve the robustness of the finite control set model predictive control (FCS-MPC). First, the influence of the mismatched parameters for FCS-MPTC is introduced and the shortcoming of the PI-based MPTC (PI-MPTC) is analyzed. Then, a sliding-mode-control-based MPTC (SMC-MPTC) is studied, in which the exponential reaching law is introduced to control the trajectories of the state variables. To further improve the control performance of SMC-MPTC, the exponential reaching law is optimized to adjust the switching gain adaptively, thus the ASMC-MPTC is proposed. The PI-MPTC, SMC-MPTC, and ASMC-MPTC are compared theoretically and experimentally, and the results show that the proposed ASMC-MPTC has the best disturbance rejection ability and robustness against motor parameters variation and load torque change.

Improved Model Predictive Torque Control for PMSM Drives Based on Duty Cycle Optimization

This article proposes an optimal scheme for an interior permanent-magnet synchronous motor (IPMSM) in electric vehicle drive system using novel model predictive torque control (MPTC) algorithm. A single optimal voltage space vector (VSV) is applied with a two-level voltage source inverter in the conventional MPTC. An improved MPTC is presented to reduce the drawbacks with satisfied torque reaction performance without adding the sampling time. First, set switching table to alleviate the calculated complexity which decreasing the selection of the appropriate VSVs. Second, optimize the duty cycle to restrain the torque ripple. Finally, the conventional MPTC and the proposed MPTC are compared in the aspects of torque and flux ripples, current harmonics, and computational level in the experiment using dSPACE.

Model Predictive Full-Torque Control for the Open-Winding PMSM System Driven by Dual Inverter With a Common DC Bus

To eliminate the weighting factor, suppress the zero-sequence current, and reduce the computation burden in the conventional model predictive torque control (MPTC) of the open-winding permanent magnet synchronous motor (OW-PMSM) system with a common dc bus, a vector partition selection-based full-torque control is proposed. The instantaneous power theory is introduced to make the control of the torque, the flux linkage, and the zero-sequence current, which is equivalent to the control of the real torque, the virtual torque, and the zero torque. Then, the full-torque-based cost function is designed to avoid the weighting factor in the proposed method. In addition, to reduce the calculation burden caused by the large number of candidate voltage vectors, a vector partition selection strategy in 3-D space is presented. Then, the candidate vectors are reduced from 27 to 6 or 7 in every control period. Finally, the experimental results verify the effectiveness of the proposed method.

MPTC of NP‐clamped three‐level inverter‐fed permanent‐magnet synchronous motor system for NP potential imbalance suppression

For neutral point (NP)-clamped three-level inverter-fed permanent-magnet synchronous motor system, the tuning process of weighting factors in the cost function of conventional model-predictive torque control (MPTC) is complex. Also, large imbalance of NP potential can cause the deteriorated performance of flux and torque. To solve these problems, an improved MPTC is proposed. This algorithm first uses the deadbeat principle to unify the dimension of torque and flux. Then, the NP potential term in the conventional cost function can be eliminated by introducing the partition control of NP potential imbalance, which also eliminates the whole process of tuning weighting factors. After that, under the large NP potential imbalance, sectors are dynamically divided by modifying the magnitude and phase angle of medium and small vectors to improve the performance of torque and flux linkage. The experimental results show that compared with conventional MPTC, the improved MPTC can achieve fast suppression of NP potential imbalance with reducing the fluctuation of torque, flux linkage and current when NP potential imbalance is large.

Integral Super Twisting Sliding Mode Based Sensorless Predictive Torque Control of Induction Motor

In the direct torque control (DTC) of induction motor (IM) drive systems utilizing model predictive torque control (MPTC) in the inner loop and classical proportional integral (PI) control in the outer loop is prone to weaknesses, such as uncertainties, external disturbances, parameter variations, and nonlinear dynamics. A high-performance control system for speed and torque is required to guarantee a smooth and robust control architecture that can withstand such unpredictable effects. In this study, we propose an integral super twisting sliding mode control (ISTSMC) to address the shortcomings of the classical PI used in the outer loop of DTC drive systems. A sliding mode speed observer is also designed and utilized to overcome problems associated with mechanical sensors. The robustness of the proposed control strategy and fast dynamic speed response are compared favorably with a benchmark PI controller and conventional sliding mode control (SMC). The ability of the proposed system to regulate both speed and torque was evaluated through simulations, under various fault perturbations, parameter variations, and load disturbances, conducted in MATLAB/ Simulink. Various performance indices were used to demonstrate the superior performance of the proposed strategy compared to a benchmark PI system and conventional SMC-based MPTC approaches.

Enhanced Model Predictive Torque Control of Fault-Tolerant Five-Phase Permanent Magnet Synchronous Motor With Harmonic Restraint and Voltage Preselection

This article investigates an enhanced model predictive torque control (MPTC) strategy to improve the fault-tolerant capability of a five-phase permanent magnet synchronous motor drive under open-circuit fault operation. The conventional fault-tolerant MPTC is focused on the control of the stator flux amplitude and the torque in the fundamental subspace, suffering from the influences of the unregulated harmonic subspace and the large computational burden. Hence, an MPTC strategy considering the control of both fundamental and harmonic subspaces is proposed. Apart from the stator flux and the torque, the harmonic current in the x-y subspace is also selected and controlled in this strategy. In addition, to mitigate the workload of the proposed MPTC, the voltage vectors are preselected according to the stator flux error. With the proposed MPTC, the regulation of both subspaces is realized. Furthermore, the computational burden is significantly alleviated. Finally, comparative experiments are conducted to validate the effectiveness of the proposed control strategy.