Torque Ripple Reduction of Predictive Torque Control for PMSM Drives With Parameter Mismatch

Siami, Mohsen; Khaburi, Davood Arab; Rodríguez, José

doi:10.1109/tpel.2016.2630274

Cited by 130 publications

(49 citation statements)

References 29 publications

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“…Thus, it is concluded that the second term is the flux error [28]. This is rewritten as D r = T ripp + λ ripp (22) where T ripp = abs( T e / T const ) and λ ripp = abs( λ s / λ const ). Here, T const is the torque constant, and λ const is the flux constant.…”

Section: Torque Minimization Strategymentioning

confidence: 99%

“…In a motor drive system, according to different control objectives, the FCS-MPC method can be classified into model predictive current control [19] and model predictive torque control (MPTC) [20]. This strategy utilizes a control target model to achieve the state variables [21], [22] and uses a correct cost function for each control and conditions defined through reference values and feedback state values to anticipate the output state. Thus, the MPTC strategy uses optimized states as a control input to obtain a minimized cost function for each control period.…”

Section: Introductionmentioning

confidence: 99%

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Predictive Torque Control With Simple Duty-Ratio Regulator of PMSM for Minimizing Torque and Flux Ripples

2020

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In this paper, a new method for reducing the ripples of torque and flux is proposed for the predictive torque control (PTC) of permanent magnet synchronous motors. The conventional PTC uses equations to analyze the relationship between the electrical torque and voltage with a fixed magnitude of reference voltage. Consequently, flux and torque ripples increase significantly at low-speed operation. This paper proposes an improved PTC algorithm using a simple duty-ratio regulator. The proposed method will minimize the torque error by calculating an appropriate torque minimization function to mitigate the induced torque and flux ripple at low speed operation. This torque minimization function is synthesized into the space vector pulse-width modulation block to reduce the torque ripple induced owing to the fixed time duration. The proposed scheme considerably reduces the torque and flux ripples and establishes a fast-dynamic response of the torque in the transient state. Simulation and experimental results show that the proposed method achieves a more efficient steady-state performance and a faster step response compared with the conventional PTC.

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Section: Torque Minimization Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predictive Torque Control With Simple Duty-Ratio Regulator of PMSM for Minimizing Torque and Flux Ripples

2020

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“…Since FCS-MPC strategies use a machine model to predict the future behavior of the controlled variables, the accuracy of these predictions depends on the equivalent parameters of the machine [127]. As these parameters can vary for different operating conditions, any parameter mismatch will cause an error in the predictions of the FCS-MPC algorithm and will lead to a deteriorated performance of the drive [128,129]. For the case of six-phase IM drives, only Reference [130] has studied the parameter sensitivity of the S-PCC strategy, while the parameter sensitivity of FCS-MPC strategies for six-phase PMSM drives remains uncovered.…”

Section: Parameter Sensitivitymentioning

confidence: 99%

Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview

2019

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Recently, the control of multiphase electric drives has been a hot research topic due to the advantages of multiphase machines, namely the reduced phase ratings, improved fault tolerance and lesser torque harmonics. Finite control set model predictive control (FCS-MPC) is one of the most promising high performance control strategies due to its good dynamic behaviour and flexibility in the definition of control objectives. Although several FCS-MPC strategies have already been proposed for multiphase drives, a comparative study that assembles all these strategies in a single reference is still missing. Hence, this paper aims to provide an overview and a critical comparison of all available FCS-MPC techniques for electric drives based on six-phase machines, focusing mainly on predictive current control (PCC) and predictive torque control (PTC) strategies. The performance of an asymmetrical six-phase permanent magnet synchronous machine is compared side-by-side for a total of thirteen PCC and five PTC strategies, with the aid of simulation and experimental results. Finally, in order to determine the best and the worst performing control strategies, each strategy is evaluated according to distinct features, such as ease of implementation, minimization of current harmonics, tuning requirements, computational burden, among others.

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“…The phases are energized over the entire region of rising inductance and the active current limiting from the controller at low speeds. SRMDs are only depending on the variation of inductance is rising or falling due to angular position (non-linear) but it does not dependent on the direction of the current [6,7]. So, for an optimal excitation sequence, the control structure requires rotor position.…”

Section: Introductionmentioning

confidence: 99%

Torque Ripple Minimization in Switch Reluctance Motor Drives: an ANFACO Based Control

Chaple¹,

Bodkhe²,

Daigavane³

2018

IJIES

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Abstract:In this paper, the torque ripples in the switched reluctance motor (SRM) is constrained by utilizing an Ant Colony Optimization and an Adaptive Neuro Fuzzy Inference System (ANFACO). The control scheme is utilized for the simultaneous control of the speed and current of the SRM which fuses two controlling loops of PI controller. The external loop is governed for speed control and the internal loops is governed for current control despite the ideal decision of the turn on and turn off switching angles. With respect to, for instance, speed, current, inductance and torque, the dynamic behavior of the SRM is examined to control the speed and current which restrict the torque ripple. The gain parameters of the PI controller are ideally made as the dataset by the ant colony optimization (ACO) algorithm. The created dataset is passed to the adaptive neuro fuzzy inference system (ANFIS) for the error prediction. By then, the proposed framework is executed in the MATLAB/Simulink working stage. The execution of the proposed method is affirmed by differentiating and the current systems like ant lion optimization (ALO), non dominating sorting search algorithm (NSGA-II) and combined moth flame optimization and genetic algorithm with recurrent neural network (CMFG-RNN) procedures.

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Torque Ripple Reduction of Predictive Torque Control for PMSM Drives With Parameter Mismatch

Cited by 130 publications

References 29 publications

Predictive Torque Control With Simple Duty-Ratio Regulator of PMSM for Minimizing Torque and Flux Ripples

Predictive Torque Control With Simple Duty-Ratio Regulator of PMSM for Minimizing Torque and Flux Ripples

Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview

Torque Ripple Minimization in Switch Reluctance Motor Drives: an ANFACO Based Control

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