Low Complexity Dual-Vector Model Predictive Current Control for Surface-Mounted Permanent Magnet Synchronous Motor Drives

Chen, Junshuo; Qin, Yi; Bozorgi, Amir Masoud; Farasat, Mehdi

doi:10.1109/jestpe.2019.2917865

Cited by 38 publications

(45 citation statements)

References 24 publications

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“…In this case, negative voltage vectors with positive duty cycles are selected when there is a negative duty cycle. The average switching frequency is greater than that of the method in [14].…”

Section: Introductionmentioning

confidence: 74%

“…Because the switching state is determined directly based on the cost function value, the switching frequency can vary, and the produced currents contain a broad spectrum of harmonics [12]. A fast sampling rate is generally required in singlevector MPCC [13], [14] to achieve the acceptable steadystate performance. Current distortion can be reduced by using a short time for the voltage vector application.…”

Section: Introductionmentioning

confidence: 99%

“…In [14], the duty cycle of an active voltage vector is calculated based on the projection of the current error vector onto the active voltage vector, which minimizes the cost function. In the paper, the computational burden is significantly reduced for two main reasons.…”

Section: Introductionmentioning

confidence: 99%

“…Although the methods in [13], [14], and [23] result in reduced current distortion, nonetheless they are either highly complex and/or less efficient. The reduced efficiencies in [13] and [23] are due to the increased average switching frequency.…”

Section: Introductionmentioning

confidence: 99%

“…The reduced efficiencies in [13] and [23] are due to the increased average switching frequency. The performance of the low complexity method in [14] could be improved further.…”

Section: Introductionmentioning

confidence: 99%

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Dual-Vector Model Predictive Current Control of Permanent Magnet Synchronous Motor Drives With the Segment Golden Search Method

Chen

Zhang

2020

IEEE Access

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Dual vector model predictive current control (DVMPCC) has been receiving plenty of concern due to its excellent static and dynamic performance. However, the application time of each selected voltage vector may not be optimal value because the calculation of duty cycle for each voltage vector is independent of the cost function. Here, to overcome the drawbacks of the current calculation methods, the paper introduces a novel approach to calculate the duty cycles for the two voltage vectors in one sampling time by combining the duty cycle calculation into the cost function. In this algorithm, the segment golden search method is used to find the optimal duty cycles for any pair of two voltage vectors. The cost function compares the available pairs of voltage vectors based on the obtained optimal duty cycles of each pair of voltage vectors to select the optimal pair of voltage vectors and duty cycles. In addition, to reduce the complexity of the algorithm, the redundant pairs of voltage vectors are eliminated and the available pairs of the voltage vectors is limit to five. Furthermore, a novel switching pattern is introduced to reduce the average switching frequency. When the inverter adopts the proposed MPCC, the optimal switching time and optimal voltage vector pair are both obtained at the same time, and the result duty cycle is always a reasonable number within the sampling interval. Comparative studies between the proposed method and a recently introduced duty cycle-based MPCC are carried out. The performance of a permanent magnet synchronous motor drive under the proposed MPCC confirms superiority in terms of average switching frequency, better quality currents, and electromagnetic torque ripple. INDEX TERMS Model predictive control, segment golden search method, permanent magnet synchronous motor, dual-vector MPCC.

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Section: Introductionmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The reduced efficiencies in [13] and [23] are due to the increased average switching frequency. The performance of the low complexity method in [14] could be improved further.…”

Section: Introductionmentioning

confidence: 99%

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Dual-Vector Model Predictive Current Control of Permanent Magnet Synchronous Motor Drives With the Segment Golden Search Method

Chen

Zhang

2020

IEEE Access

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An enhanced predictive current control technique for interior permanent magnet synchronous motor drives with extended voltage space vectors for electric vehicles

Kumar,

Praveen Kumar

2024

Circuit Theory & Apps

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SummaryPermanent magnet synchronous motors (PMSM) are widely employed in the application of electric vehicles (EVs) due to their simplicity of operation. Model predictive current control (MPCC) is an advanced technique used to control the PMSM owing advantages like multi‐variable cost function and good dynamic performance. Cost function of predictive current control (PCC) does not require the flux weighting factor; hence, it is simple in the selection of suitable voltage vector (VV). The conventional PCC (C‐PCC) applied to interior PMSM (IPMSM) contains more torque and flux ripples as it includes only one set of voltage vectors for all speed ranges. In proposed PCC (P‐PCC), the magnitude and location of voltage vectors is to be selected as large and small VVs to reduce torque ripples. The P‐PCC in this article utilizes two set of extended voltage vectors (large and small VVs) based on the applied speed change in dynamic conditions and hence reduces the ripple content. Incorporating maximum torque per ampere (MTPA) control in this article serves the purpose of optimizing the machine performance. By adding MTPA to the proposed method, it is aimed to enhance the machine performance with less ripples and improved torque response. Simulation results are presented for conventional and P‐PCC to highlight the effectiveness and efficacy of the P‐PCC. The P‐PCC is experimentally verified with 3.7 kW PMSM using d‐SPACE controller.

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Minimization of torque ripples in PMSM drive using PI- resonant controller-based model predictive control

et al. 2022

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Low Complexity Dual-Vector Model Predictive Current Control for Surface-Mounted Permanent Magnet Synchronous Motor Drives

Cited by 38 publications

References 24 publications

Dual-Vector Model Predictive Current Control of Permanent Magnet Synchronous Motor Drives With the Segment Golden Search Method

Dual-Vector Model Predictive Current Control of Permanent Magnet Synchronous Motor Drives With the Segment Golden Search Method

An enhanced predictive current control technique for interior permanent magnet synchronous motor drives with extended voltage space vectors for electric vehicles

Minimization of torque ripples in PMSM drive using PI- resonant controller-based model predictive control

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