Mod­el Pre­dict­ive Con­trol of Multi-Phase Thyris­tor Mat­rix Con­vert­ers

Project acronym: DFG-MPCMC
Funding period: 3 years with extension (2013-2018)
Project partner: German Research Foundation (DFG)


Turbine generator sets for generation of electric energy with power ratings of several 100 MW are typically connected directly to the electric grid. Thus, the turbine is operated at fixed speed, resulting in a drop of efficiency at partial load. If the turbine speed could be adjusted at partial load, the gain of efficiency would be up to 25 %. Matrix or cyclo converters can provide frequency-elastic coupling and would allow speed-variable operation of the turbine. Due to high robustness and small losses, thyristor converters are favoured particularly in the range of very high-power rating. Unfortunately, the standard three-phase cyclo converter can only be used up to frequency ratios up to 1:3 between generator and mains which is not given here. However, if the number of phases is increased (e.g. up to N = 27), the distortions would be within an acceptable level. The state-of-the-art control method for such a multi-phase cyclo converter is derived from that of the standard cyclo converter and operates the converter with a rather high commutation frequency, which contradicts the goal of efficiency improvement. A proposal in order to reduce the commutation frequency has been presented, but this includes other drawbacks as larger total harmonic distortions.

Project goals

Goal of this project is to improve the control of this converter concept to operate the converter with a small number of commutations in order to minimize losses as well as to consider other optimization targets as the total harmonic distortion (THD) and the converter voltage utilization.

Methodological approach is the employment of space vector modulation which so far has not been applied to such converters, likely because of the large number of states to be handled (with N = 27 phases, N³ = 19683 states result), which are furthermore varying in time, and also because the commutations cannot be triggered arbitrarily with externally commutated converters. The implementation of a Direct Current Control in a rotor-fixed reference frame by means of Model Predictive Control (MPC) is a promising way to solve this complex task. Model Predictive Control will select the best switching state with help of an objective function that considers the control error, the rate of change of the predicted control variable (which is approximately proportional to THD) and the commutation voltage. In that way, the switching losses are expected to be reduced by about a factor of two.



M. Leuer, A. Rüting, J. Böcker
Efciency-Optimized Model Predictive Torque Control for IPMSM
IEEE International Energy Conference (Energycon 2014), Dubrovnik, Croatia, 2014


M. Leuer, J. Böcker
Real-Time Implementation of an Online Model Predictive Control for IPMSM Using Parallel Computing on FPGA
International Power Electronics Conference (IPEC Asia), Hiroshima, Japan, 2014


M. Leuer, J. Böcker
Voltage Utilization in Model Predictive Control for IPMSM
IEEE International conference on Power Electronics, Drives and Energy Systems (PEDES), Mumbai, India, 2014


M. Leuer, J. Böcker
Self-Optimized Model Predictive Direct Torque Control for Electrical Drives
24th IEEE International Syposium in Industrial Electronics (ISIE 2015), Rio de Janeiro, Brazil, 2015


M. Leuer, M. Lönneker, J. Böcker
Direct Model Predictive Control Strategy for Multi-Phase Thyristor Matrix Converters
IEEE 3rd International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE 2015), Valparaíso, Chile, 2015

[6] M. Leuer, J. Böcker, M. Lönneker
Model Predictive Control Strategy for Multi-Phase Thyristor Matrix Converters - Advantages, Problems and Solutions
18th European Conference on Power Electronics and Applications (EPE 2016), Karlsruhe, Germany, 2016


Dr.-Ing. Oliver Wallscheid

Dr.-Ing. Oliver Wallscheid

Power Electronics and Electrical Drives

Chief Engineer - Former - Teamleader Electrical Drives & Smart Energy Systems

+49 5251 60-3653
Fax (External):
+49 5251 60-3443
Office hours:


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33098 Paderborn
Further workspaces


Latest Publications

Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning

S. Peitz, J. Stenner, V. Chidananda, O. Wallscheid, S.L. Brunton, K. Taira, Physica D: Nonlinear Phenomena 461 (2024) 134096.

Insights and Challenges of Co-Simulation-Based Optimal Pulse Pattern Evaluation for Electric Drives

L. Hölsch, A. Brosch, R. Steckel, T. Braun, S. Wendel, J. Böcker, O. Wallscheid, IEEE Transactions on Energy Conversion (2024) 1–12.

Time-Optimal Model Predictive Control of Permanent Magnet Synchronous Motors Considering Current and Torque Constraints

A. Brosch, O. Wallscheid, J. Böcker, IEEE Transactions on Power Electronics (2023) 1–14.

Finite Set Sensorless Control With Minimum a Priori Knowledge and Tuning Effort for Interior Permanent Magnet Synchronous Motors

A. Brosch, F. Tinazzi, O. Wallscheid, M. Zigliotto, J. Böcker, IEEE Transactions on Power Electronics (2023).

ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids

O. Wallscheid, S. Peitz, J. Stenner, D. Weber, S. Boshoff, M. Meyer, V. Chidananda, O. Schweins, Journal of Open Source Software 8 (2023).

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