Speed sensorless model predictive current control with ability to start a free running induction motor

Yang, Haojin; Zhang, Yongchang; Walker, Paul; Liang, Jiejunyi; Zhang, Nong; Xia, Bo

doi:10.1049/iet-epa.2016.0481

Cited by 30 publications

(13 citation statements)

References 38 publications

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“…The intrusion level of this method is low, although it is slightly more intrusive than the nameplate method, because measuring the shaft speed might need a sensor, but there are sensorless real-time speed estimation methods [46,47]. Since the electric power and the motor speed can be measured in real-time, this method estimates the real-time response of IMs.…”

Section: Slip Methodsmentioning

confidence: 99%

Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring

et al. 2019

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Different methods have been developed to estimate the energy efficiency of induction motors. The accuracy of these methods vary with the load factor, the unbalanced voltage (UV) and harmonics. The feasibility of these methods for efficiency estimation in real-time were theoretically and experimentally assessed during the operation under different operational conditions (i.e. balanced sinusoidal voltage (BSV), harmonics, UV and harmonics with UV). Results show that for load factors over 80%, the air-gap method is applicable under any condition, while the slip method is only applicable under BSV or balanced harmonic voltage. Moreover, for load factors over 40%, the nameplate method is applicable under BSV. Other methods result in errors over 8% and optimization methods are not applicable for real-time monitoring. Electric systems generally operates with some degree of UV and harmonics, while induction motors mostly operate with load factors below 60%, limiting the use of these methods for real-time measurement.

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Section: Slip Methodsmentioning

confidence: 99%

Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring

et al. 2019

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“…In above equations, the parameters and signify the error or the disturbance imposed due to parametric differences or error. Mathematically, the disturbances are depicted in (37) and (38).…”

Section: A) Predictive Current Control (Pcc)mentioning

confidence: 99%

“…Considering the parametric mismatched or error in nonlinear IM condition to retrieve the disturbances and to predict the stator currents we derived an Observer unit using (37) and (38). Mathematically, the observer can be defined as (39) and (40).…”

Section: A) Predictive Current Control (Pcc)mentioning

confidence: 99%

“…Moreover, the inclusion of predictive current control and torque control as a combined solution can broaden the applicability of IMs in a non-liner environment. Considering the above-stated motives, in this research a novel strategic multi-phased effort has been made, where at first the focus is made on identifying optimal equivalent design parameters of the IM under predictive error condition or non-linear Sensorless environment [37]. In the subsequent research phase a novel Disturbance Observer assisted MPC control model is developed for IM vector field control.…”

Section: Introductionmentioning

confidence: 99%

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Disturbance Observer Assisted Error Sensitive Predictive Control for Induction Motors in Sensor less Environment: A Vector Field Control Model

Nayak*,

2020

IJRTE

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The exponentially rise within the demands of Induction Motors in several applications has revitalized academia-industries to develop more robust and efficient IM drives. Amongst the main classically available IM drives efforts are made either to regulate speed or torque. However, the problem inculcated due to parametric mismatch and resulting errors have much addressed. Though, predictive control based approaches are found potential to help current and torque control; however, ensuring optimal controllability under nonlinear condition remained a tedious task. Filter based approaches to impose delay that eventually impacts overall control performance. Realizing it as motivation, during this research a highly robust Disturbance Observer Assisted Error Sensitive Predictive Control Strategy for IM control is developed. Subsequently, a completely unique Disturbance Observer-based Model Predictive Control strategy is developed that performs predictive current control and torque-control during a non-linear environment. Our proposed model exploits the concept of Prediction-Error to realize transient controllability. Exploiting the error information our proposed model identified the optimal voltage vector value to be injected to the 3-∅ inverter connected to the PI-based Space Vector Pulse Width Modulation system to perform transient controllability. Structurally, our proposed system encompasses SQIM motor, 3-∅ inverter, PI controller SVPWM, Fluxobserver, Torque and Speed controllers, VSI units, etc. The MATLAB 2017a based simulation has revealed that the proposed model is able to do better current control, flux-torque control and torque-ripple suppression, which broadened its employability for varied applications demands fast-torque control during a noisy environment

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“…For power converters and motor drives, the inner current control loop plays an important role in achieving good performance of the whole control system. During the past decades, many methodologies have been investigated for high-performance current control, including proportional-integral (PI) control [1,2], hysteresis control [3,4], sliding-mode control (SMC) [5], and predictive control [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Deadbeat control based on a multipurpose disturbance observer for permanent magnet synchronous motors

Yang

Zhang

Liang

et al. 2018

IET Electric Power Applications

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Robustness against parameter mismatches and position-sensorless operation are two important research topics for permanent magnet synchronous motor (PMSM) drives. In this paper, a sliding mode disturbance observer (SMDO) is proposed to achieve either of two functions for different application environments: 1) if a position sensor is equipped, accurate current regulation can be achieved by deadbeat predictive current control (DBPC) despite mismatched motor parameters; 2) if the position sensor is not equipped but with a good estimation of motor parameters, the observer can serve as a back electromotive force (EMF) estimator. On this basis, the rotor position can be extracted for positionsensorless control. Usually, low-pass filter is required to suppress high frequency noises in conventional sliding mode observer. This inevitably leads to phase delay in the estimation, which cannot be directly used for disturbance compensation. While in the proposed method, a complex coefficient filter is inherently embedded, which can provide accurate estimation without phase or magnitude error. Experimental results obtained from a 2.4 kW PMSM drive platform indicate that high performance current control can be achieved with good robustness for position sensor based operation. And, rotor position can be accurately estimated with good steady and dynamic performance for position-sensorless operation.

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Speed sensorless model predictive current control with ability to start a free running induction motor

Cited by 30 publications

References 38 publications

Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring

Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring

Disturbance Observer Assisted Error Sensitive Predictive Control for Induction Motors in Sensor less Environment: A Vector Field Control Model

Deadbeat control based on a multipurpose disturbance observer for permanent magnet synchronous motors

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