Model Predictive Current Control of Multilevel Inverter in Traction System

Hassan, Mannan; Atif, Rao; Ge, Xinglai; Teklu, Woldegiorgis Abebe; Munir, Hafiz Mudassir; Amjad, Muhammad

doi:10.1109/icecce47252.2019.8940746

Cited by 6 publications

(6 citation statements)

References 23 publications

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“…The finite control-set model predictive control (FCS-MPC) has grown quickly in the last decade, covering many fields, such as UPS, renewable energy systems, electric grids, multi-level converters, electric drives, etc. [31][32][33][34][35].…”

Section: Motivation and Incitementmentioning

confidence: 99%

Simplified Model Predictive Current Control of Four-Level Nested Neutral Point Clamped Converter

et al. 2023

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Model predictive control (MPC) is an efficient and growing approach to power converter control. This paper proposes an improved and simplified model predictive current control (MPCC) technique for a four-level nested neutral point clamped (4L-NNPC) converter. Conventional MPCC exhibits better performances as compared to the conventional linear control system such as fast dynamic response, consideration of the system constraints, and nonlinearities. However, the application of the conventional model predictive current control (MPCC) approach on complex systems provokes a significant number of calculations, which is the main hurdle to its practical implementation. To fix this flaw, this paper proposes an effective algorithm to shorten the execution time of the conventional MPCC. In this proposed technique, 216 current predictions of the conventional MPCC are skipped and converted into one required voltage vector (RVV) prediction. With this equivalent reference voltage transformation, the calculation burden of MPCC is significantly reduced, while the output performance is not influenced. The results of the simplified MPCC for the 4L-NNPC converter are analyzed and compared with the conventional MPCC. The computational time is reduced by 19.56% using the simplified MPCC, while keeping an approximately similar error of output currents. The switching frequency and total harmonic distortion (THD) of the proposed method are reduced by 8.16% and 0.07%, respectively, as compared to the conventional technique. These results demonstrate the fact that that the performance of a conventional MPCC is enhanced with the proposed MPCC. The proposed algorithm can be applied to several inverter topologies.

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Section: Motivation and Incitementmentioning

confidence: 99%

Simplified Model Predictive Current Control of Four-Level Nested Neutral Point Clamped Converter

et al. 2023

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“…In addition, it reduces the capacitor's voltage ripples and THD magnitudes. In contrast, a classical PWM control technique for SC-MLIs uses two or more PI controllers for current control and balancing the voltage of the capacitors, which makes the control hard and complex [38], [39]. In addition, industrial applications need several operational amplifiers (OpAmp) to tune the control objectives, which increases the final cost of massive production.…”

Section: Comparison Fcs-mpc and Classical Pwm Techniques For Sc-mlismentioning

confidence: 99%

Model Predictive Control for Single-Phase Switched-Capacitor Multilevel Inverters

Hosseinzadeh

Sarebanzadeh

Kennel

et al. 2023

IEEE Open J. Power Electron.

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“…This method has the advantage of less calculation burden than the conventional MPCC technique by reducing the voltage vector from eight to three by dividing the control plane into six sectors and each sector having three VV. The angle of reference voltages can be calculated using Equation (19). As shown in Figure 1, six sectors of VV are introduced, and the location of the reference voltage angle can be found in the given sectors.…”

Section: Determining Three Optimal Voltage Vectorsmentioning

confidence: 99%

“…An appropriate modulation technique is required in this control system. The second one is finite control set (FCS) MPC [17][18][19]. In this approach, the need for a modulator is eliminated and incorporates only the finite number of the output state of the power converter.…”

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confidence: 99%

Computational efficient model predictive current control for interior permanent magnet synchronous motor drives

Hassan

Atif

et al. 2022

IET Power Electronics

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The standard model predictive control (MPC) of three‐phase motors requires heavy calculation efforts for evaluating all voltage vectors (VV) in addition to the variable switching frequency, large current harmonics, and torque ripples. To deal with these problems, a computational efficient model predictive current control (MPCC) is proposed for a three‐phase interior permanent magnet synchronous motor (IPMSM). Initially, to avoid the protracted enumeration process, the reference voltage vector (RVV) is directly calculated by using the reference current generated by the maximum torque per ampere technique (MTPA), which is an additional control objective. The position of the RVV is utilized to define three candidate voltage vectors to be examined using the cost function, which determines the optimal vector. Secondly, an optimal duty cycle (ODC) is designed to minimize the error between the optimal vector and the reference vector reducing the current ripples. Furthermore, the proposed scheme is compared with the conventional MPCC techniques using MATLAB simulation and hardware in loop (HIL) with TMS320F28335 digital signal processor (DSP) experiments. A comprehensive analysis of the results for different operating conditions shows the effectiveness and robustness of the proposed method.

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Model Predictive Current Control of Multilevel Inverter in Traction System

Cited by 6 publications

References 23 publications

Simplified Model Predictive Current Control of Four-Level Nested Neutral Point Clamped Converter

Simplified Model Predictive Current Control of Four-Level Nested Neutral Point Clamped Converter

Model Predictive Control for Single-Phase Switched-Capacitor Multilevel Inverters

Computational efficient model predictive current control for interior permanent magnet synchronous motor drives

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