Litcius/Paper detail

Flux Linkage-Based Direct Model Predictive Current Control for Synchronous Machines

Sebastian Wendel, Πέτρος Καραμανάκος, Philipp Gebhardt, Armin Dietz, Ralph Kennel

2021IEEE Transactions on Power Electronics19 citationsDOI

Abstract

This article presents a flux linkage-based direct model predictive current control approach that achieves favorable performance both during steady-state and transient operation. The former is achieved by computing the optimal time instants at which a new switch position is applied to the converter. To this end, the future current behavior is not computed based on the machine inductances or inductance look-up tables; instead, flux linkage maps are utilized to predict the trajectory of the magnetic flux linkage, and subsequently of the current. This is advantageous for electric drives with noticeable magnetic nonlinearity in terms of saturation and/or cross-coupling effects. Hence, by using flux linkage maps in the prediction process, the evolution of the stator current can be calculated more accurately, enabling the controller to make better switching decisions. Moreover, the discussed predictive controller exhibits excellent dynamic performance owing to its direct control nature, i.e., the control and modulation tasks are performed in one computational stage rendering a dedicated modulation stage redundant. Three different drive systems based on permanent magnet synchronous motors are examined to demonstrate the effectiveness of the presented control approach.

Topics & Concepts

Flux linkageControl theory (sociology)InductanceModel predictive controlStatorSynchronous motorComputer scienceMagnetic fluxMachine controlTransient (computer programming)Direct torque controlEngineeringControl engineeringPhysicsVoltageInduction motorControl (management)Magnetic fieldArtificial intelligenceElectrical engineeringQuantum mechanicsOperating systemMultilevel Inverters and ConvertersMicrogrid Control and OptimizationAdvanced DC-DC Converters