Finite Control Set Model-Free Predictive Current Control of PMSM With Two Voltage Vectors Based on Ultralocal Model

Sun, Zheng; Deng, Yongting; Wang, Jianli; Yang, Tian; Wei, Zongen; Cao, Haiyang

doi:10.1109/tpel.2022.3198990

Cited by 43 publications

(11 citation statements)

References 35 publications

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“…Such ways are feasible theoretically but lead to additional computations unavoidably. Another way is to remove the model parameters from the controller, called model-free predictive control (MFPC) [34], [35]. The MFPC method is actually data-driven but not model-based, which implies that this method is hard to work if the sampling frequency is low or the sampling accuracy is deficient.…”

Section: Robustness Analysismentioning

confidence: 99%

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A Novel Model Predictive Current Control for Asymmetrical Six-Phase PMSM Drives With an Optimum Duty-Cycle Calculation Scheme

Zhang¹,

2023

IEEE Access

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This paper presents a novel model predictive current control (MPCC) with an optimum duty-cycle calculation scheme for asymmetrical six-phase permanent magnet synchronous machine (ASPMSM) drives. The proposed method takes advantages of the steady-state performance improvement and the weighting factor elimination. Both merits are owing to the optimum duty-cycle calculation scheme. On the one hand, for the α-β subspace, the optimal voltage vector set (VVS) is chosen from twelve ones and the corresponding optimal duty cycles are calculated using the proposed scheme. On the other hand, for the x-y subspace, the VVS can be determined according to that of α-β subspace and the optimal duty cycles are deduced using the same scheme. The voltage vector references in two subspaces are then obtained, and they are transformed to six-phase voltages for controlling the six-phase inverter. The proposed method is verified by experimental results based on a 2 kW ASPMSM prototype.INDEX TERMS Model predictive current control (MPCC), asymmetrical six-phase permanent magnet synchronous machine (ASPMSM), steady-state performance, weighting factor, duty-cycle calculation.

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Section: Robustness Analysismentioning

confidence: 99%

“…where η is the drive system efficiency; P m is the outputted mechanical power, which can be estimated using (35); P dc is the input power, which can be read from the control panel of the dc power supply. The drive system efficiency comparison is shown in Fig.…”

Section: E Computation Burden and Efficiencymentioning

confidence: 99%

A Novel Model Predictive Current Control for Asymmetrical Six-Phase PMSM Drives With an Optimum Duty-Cycle Calculation Scheme

Zhang¹,

2023

IEEE Access

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“…where i re f d and i re f q are the dq-axis reference currents, respectively; u * d (k + 1) and u * q (k + 1) are the dq-axis reference voltage vectors, respectively; as designed in [28], Fd (k + 1) and Fq (k + 1) will be observed by a sliding mode observer (SMO), respectively. The block diagram of the SMO can be found in Figure 3.…”

Section: Space Vector Selectionmentioning

confidence: 99%

Robust three‐voltage‐vector‐based model‐free predictive current control for permanent magnet synchronous motor with ultra‐local model

Sun,

Deng,

Wang

et al. 2023

IET Power Electronics

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A large current ripple may arise in the finite control set model‐free predictive current control (FCS‐MFPCC) strategy because only one voltage vector can be applied during the whole control period. Therefore, an improved three‐vector‐based model‐free predictive current control (MFPCC) strategy to improve the current tracking performance is proposed by increasing the number of the applied voltage vector. Based on the extreme existence theorem for the function of two variables, the optimal voltage vector can be synthesized. Compared with the one‐vector‐based FCS‐model‐based predicted current control (FCS‐MBPCC) and two‐vector‐based FCS‐MBPCC in the time and frequency domains, the maximum tracking error is decreased by 42.17% and 48.58%, and the total harmonic distortion is decreased by 40.97% and 37.56%, respectively. Besides, compared with the previous three‐vector‐based strategy, the computational time of the proposed strategy is reduced from 57.6 to 45.89 , which is reduced by 20.33%. Furthermore, the switching frequency of the proposed method can be decreased by 70.3% compared with the deadbeat MFPCC. The experimental results in the time and frequency domains demonstrate that the proposed three‐vector‐based MFPCC can not only improve the current tracking performance but also improve robustness against parameter mismatches.

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“…Model predictive control (MPC) based on a finite control set has caught the eye of scholars in recent years because of its quick transient ability and simple structure [2], [3]. In MPC, the voltage vectors in the control set are the dominant keys for the control performance.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Current Control for Asymmetric Six-phase Permanent Magnet Motors With Less Computation and Optimized Voltage Vector Magnitude

Sun

Chen

2023

J. Phys.: Conf. Ser.

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For the sake of the fixed magnitude of candidate control sets, the conventional model predictive current control (MPCC) for asymmetric six-phase permanent magnet motors suffers from huge harmonic currents. This article designs a novel MPCC that aims to improve operational performance. First, virtual-voltage vector (VV) sets are synthesized as the new candidate vectors to restrain harmonic currents. Then, a simplified method for evaluating voltage vectors is used to alleviate the computation in the enumeration process. Moreover, the duty cycle modulation with the deadbeat solution is introduced to optimize the magnitude of the VV. The modulation range can be expanded by utilizing null vectors, which will significantly reduce the torque fluctuations and flux ripples. The experiments are conducted to verify the designed control strategy.

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Finite Control Set Model-Free Predictive Current Control of PMSM With Two Voltage Vectors Based on Ultralocal Model

Cited by 43 publications

References 35 publications

A Novel Model Predictive Current Control for Asymmetrical Six-Phase PMSM Drives With an Optimum Duty-Cycle Calculation Scheme

A Novel Model Predictive Current Control for Asymmetrical Six-Phase PMSM Drives With an Optimum Duty-Cycle Calculation Scheme

Robust three‐voltage‐vector‐based model‐free predictive current control for permanent magnet synchronous motor with ultra‐local model

Model Predictive Current Control for Asymmetric Six-phase Permanent Magnet Motors With Less Computation and Optimized Voltage Vector Magnitude

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