Model Order Reduction for Simulation and Control of Synchronous Machines

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School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2019-05-28
Degree programme
92 + app. 34
Aalto University publication series DOCTORAL DISSERTATIONS, 35/2019
Model order reduction approaches aim at reducing the computational complexity of numericalmodels. The reduction is achieved by lowering the dimension of the state space or the numberof degrees of freedom in the original high-order model, which in return generates a reducedorder model. This reduced order model is an appropriate substitution for the original model inthe applications with restricted computational resources or a demanding large number of simulations. This thesis proposes a novel method, named the orthogonal interpolation method, to reducethe computational burden of numerical models, which makes the models suitable for real-timeexecution. This method is applied to a 2-D finite element model of a 2.2 kW interior permanentmagnet synchronous motor. According to the simulation results, the resulting reducedmodel accurately imitates the behaviour of the finite element model of the machine, and successfully lowers the computational time and memory requirements. Furthermore, the proposedmethod grants a more significant reduction in the computational complexity comparedto other model order reduction techniques, such as proper orthogonal decomposition coupledwith a discrete empirical interpolation method. As an application, the proposed reduced model is employed in a control system for real-timecontrol of the motor. The high computational efficiency of the reduced model allows direct implementation of the resulting control system in the embedded processor of the drive. Moreover,the simulation and the experimental results show the capability of the developed controlsystem in considering the magnetic cross-coupling and saturation phenomena of the motor,and therefore produces higher torque and output power.
Supervising professor
Belahcen, Anouar, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
Thesis advisor
Martin, Floran, Dr., Aalto University, Department of Electrical Engineering and Automation, Finland
Rasilo, Paavo, Asst. Prof., Tampere University of Technology, Finland
finite element model, model order reduction, real-time control, synchronous machine
Other note
  • [Publication 1]: Mehrnaz Farzam Far, Anouar Belahcen, Paavo Rasilo, Stéphane Clénet, Antoine Pierquin. Model Order Reduction of Electrical Machines with Multiple Inputs. IEEE Transactions on Industry Applications, 2017, volume 53, issue 4, pp. 3355-3360.
    DOI: 10.1109/TIA.2017.2681967 View at publisher
  • [Publication 2]: Mehrnaz Farzam Far, Floran Martin, Anouar Belahcen, Laurent Montier, Thomas Henneron. Orthogonal Interpolation Method for Order Reduction of a Synchronous Machine Model. IEEE Transactions on Magnetics, 2018, volume 54, issue 2, pp. 1-6.
    DOI: 10.1109/TMAG.2017.2768328 View at publisher
  • [Publication 3]: Victor Mukherjee, Mehrnaz Farzam Far, Floran Martin, Anouar Belahcen. Constrained Algorithm for the Selection of Uneven Snapshots in Model Order Reduction of a Bearingless Motor. IEEE Transactions on Magnetics, 2017, volume 53, issue 6, pp. 1-4, June 2017.
    DOI: 10.1109/TMAG.2017.2664505 View at publisher
  • [Publication 4]: Mehrnaz Farzam Far, Floran Martin, Anouar Belahcen, Paavo Rasilo, Hafiz Asad Ali Awan. Real-Time Control of an Electrical Machine Using Model Order Reduction. Submitted, November 2018.
  • [Errata file]: Errata of P1