Model Predictive Control of Six-Phase Induction Motor Drives Using Two Virtual Voltage Vectors

Aciego, Juan J.; González-Prieto, Ignacio; Durán, Mario J.

doi:10.1109/jestpe.2018.2883359

Cited by 81 publications

(43 citation statements)

References 36 publications

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“…To solve the aforementioned disadvantage, [20,21] proposed the implementation of virtual voltage vectors for MPC strategies. The VVs are created taking advantage of the special localization of the available six-phase IM voltage vectors.…”

Section: Vv-mpc With Natural Fault Tolerancementioning

confidence: 99%

“…With the application of these VV, the control of x-y currents is performed in open-loop mode, with no inclusion of these components into the control strategy. This simplification results in a reduced predictive model that skip the x-y equations [20,21]. Consequently, the number of weighting factors can be reduced compared to standard MPC and the x-y term can be eliminated from the cost function as follows: Figure 4 shows the VV-MPC scheme where the main differences with the standard MPC ( Figure 3) have been colored in magenta.…”

Section: Vv-mpc With Natural Fault Tolerancementioning

confidence: 99%

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Efficient Model Predictive Control with Natural Fault-Tolerance in Asymmetrical Six-Phase Induction Machines

et al. 2019

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Multiphase machines allow enhancing the performance of wind energy conversion systems from the point of view of reliability and efficiency. The enhanced robustness has been traditionally achieved with a mandatory post-fault control reconfiguration. Nevertheless, when the regulation of x-y currents in multiphase drives is done in open-loop mode, the reconfiguration can be avoided. As a consequence, the reliability of the system increases because fault detection errors or delays have no impact on the post-fault performance. This capability has been recently defined as natural fault tolerance. From the point of view of the efficiency, multiphase machines present a better power density than three-phase machines and lower per-phase currents for the same voltage rating. Moreover, the implementation of control strategies based on a variable flux level can further reduce the system losses. Targeting higher reliability and efficiency for multiphase wind energy conversion systems, this work proposes the implementation of an efficient model predictive control using virtual voltage vectors for six-phase induction machines. The use of virtual voltage vectors allows regulation of the x-y currents in open-loop mode and achieving the desired natural fault tolerance. Then, a higher efficiency can be achieved with a simple and universal cost function, which is valid both in pre- and post-fault situations. Experimental results confirm the viability and goodness of the proposal.

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Section: Vv-mpc With Natural Fault Tolerancementioning

confidence: 99%

Section: Vv-mpc With Natural Fault Tolerancementioning

confidence: 99%

Efficient Model Predictive Control with Natural Fault-Tolerance in Asymmetrical Six-Phase Induction Machines

et al. 2019

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“…In the IM system, the torque difference on the motor shaft can be simplified as an integral link after the Laplace transformation has been obtained: Js T r =  (10) where J is the moment of inertia, and The speed loop structure of the induction motor speed control system is shown in Figure 1: Where ω * r is the speed setting, i * st is the torque current setting, i st is the armature current which is proportional to torque, and T f is the time constant, which is the delay time of the Pulse Width Modulation (PWM) device. According to Figure 1, suppose the current loop is completely tracked, where G(s) = 1 T f s+1 = 1.…”

Section: Analysis Of Speed Closed-loop Pi Controllermentioning

confidence: 99%

“…MPC can be divided into continuous control set-model predictive control (CCS-MPC) [7] and finite control set-model predictive control (FCS-MPC) [8]. In the motor drive system, according to the different control objectives, the finite control set model predictive control method can be divided into Model Predictive Current Control (MPCC) [9,10] and Model Predictive Torque Control (MPTC) [11]. MPTC takes stator flux and electromagnetic torque as control objectives.…”

mentioning

confidence: 99%

Three Vectors Model Predictive Torque Control Without Weighting Factor Based on Electromagnetic Torque Feedback Compensation

Jican

2019

Energies

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Finite control set-model predictive torque control (FCS-MPTC) depends on the system parameters and the weight coefficients setting. At the same time, since the actual load disturbance is unavoidable, the model parameters are not matched, and there is a torque tracking error. In traditional FCS-MPTC, the outer loop—that is, the speed loop—adopts a classic Proportional Integral (PI) controller, abbreviated as PI-MPTC. The pole placement of the PI controller is usually designed by a plunge-and-test, and it is difficult to achieve optimal dynamic performance and optimal suppression of concentrated disturbances at the same time. Aiming at squirrel cage induction motors, this paper first proposes an outer-loop F-ETFC-MPTC control strategy based on a feed-forward factor for electromagnetic torque feedback compensation (F-ETFC). The electromagnetic torque was imported to the input of the current regulator, which is used as the control input signal of feedback compensation of the speed loop; therefore, the capacity of an anti-load-torque-disturbance of the speed loop was improved. The given speed is quantified by a feed-forward factor into the input of the current regulator, which is used as the feed-forward adjustment control input of the speed controller to improve the dynamic response of the speed loop. The range of the feed-forward factor and feed-back compensation coefficient can be obtained according to the structural analysis of the system, which simplifies the process of parameter design adjustment. At the same time, the multi-objective optimization based on the sorting method replaces the single cost function in traditional control, so that the selection of the voltage vector works without the weight coefficient and can solve complicated calculation problems in traditional control. Finally, according to the relationship between the voltage vector and the switch state, the virtual six groups of three vector voltages can be adjusted in both the direction and amplitude, thereby effectively improving the control performance and reducing the flow rate and torque ripple. The experiment is based on the dSPACE platform, and experimental results verify the feasibility of the proposed F-ETFC-MPTC. Compared with traditional PI-MPTC, the feed-forward factor can effectively improve the stability time of the system by more than 10 percent, electromagnetic torque feedback compensation can improve the anti-load torque disturbance ability of the system by more than 60 percent, and the three-vector voltage method can effectively reduce the disturbance.

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“…There are two common types of modeling methods for the power converter, the switching function-based method and the controlled source-based method. In the former one, the arms of power converters are simplified as switching functions [14][15][16][17]. Different kinds of command signals correspond to different switching function values.…”

Section: Introductionmentioning

confidence: 99%

Open-Circuit Fault Analysis and Modeling for Power Converter Based on Single Arm Model

et al. 2019

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This paper proposes a new modeling method for power converter based on single arm model. The objective of this paper is twofold: (1) One is to present the single arm model with good portability. The single arm model can be used to build the models of power converters which have several arms with the same structure; (2) the other is that the converter model built by the single arm model can represent the power converter when open-circuit faults happened in power devices and clamping diodes. First of all, the inputs and outputs of single arm are redefined. Then, the open-circuit faults occurring in different power devices and clamping diodes are analyzed. Furthermore the single arm model is built. Finally, the model of power converter is established based on the single arm model, which can express the power converter with open-circuit fault. The effectiveness and accuracy of the proposed model have been verified by simulation and experiment results.

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Model Predictive Control of Six-Phase Induction Motor Drives Using Two Virtual Voltage Vectors

Cited by 81 publications

References 36 publications

Efficient Model Predictive Control with Natural Fault-Tolerance in Asymmetrical Six-Phase Induction Machines

Efficient Model Predictive Control with Natural Fault-Tolerance in Asymmetrical Six-Phase Induction Machines

Three Vectors Model Predictive Torque Control Without Weighting Factor Based on Electromagnetic Torque Feedback Compensation

Open-Circuit Fault Analysis and Modeling for Power Converter Based on Single Arm Model

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