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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) https://gepris.dfg.de/gepris/projekt/24515233

 Motivation

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.

References

[1]

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

[2]

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

[3]

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

[4]

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

[5]

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

Contact:

Dr.-Ing. Oliver Wallscheid

Contact
Publications
Dr.-Ing. Oliver Wallscheid

Power Electronics and Electrical Drives

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

Phone:
+49 5251 60-3653
Fax:
+49 5251 60-3443
Office:
E4.124
Office hours:

Terminvereinbarung

Web:
Visitor:
Pohlweg 55
33098 Paderborn
Further workspaces

Open list in Research Information System

2022

Data-Driven Adaptive Torque Oscillation Compensation for Multi-Motor Drive Systems

A. Brosch, J. Rauhaus, O. Wallscheid, J. Böcker, D. Zimmer, IEEE Open Journal of Industry Applications (2022)

DOI


Learning Thermal Properties and Temperature Models of Electric Motors with Neural Ordinary Differential Equations

W. Kirchgässner, O. Wallscheid, J. Böcker, in: 2022 International Power Electronics Conference (IPEC-Himeji 2022- ECCE Asia), IEEE, 2022

DOI


Long-Term Memory Recursive Least Squares Online Identification of Highly Utilized Permanent Magnet Synchronous Motors for Finite-Control-Set Model Predictive Control

A. Brosch, O. Wallscheid, J. Böcker, IEEE Transactions on Power Electronics (2022)

DOI



An Open-Source Transistor Database and Toolbox as an Unified Software Engineering Tool for Managing and Evaluating Power Transistors

N. Förster, P. Rehlaender, O. Wallscheid, F. Schafmeister, J. Böcker, in: Proc. 37th IEEE Applied Power Electronics Conference (APEC), IEEE, 2022


2021

Model Predictive Control of Permanent Magnet Synchronous Motors in the Overmodulation Region Including Six-Step Operation

A. Brosch, O. Wallscheid, J. Böcker, IEEE Open Journal of Industry Applications (2021), 2, pp. 47–63

DOI


Temperature estimation of electric machines using a hybrid model of feed-forward neural and low-order lumped-parameter thermal networks

E.G. Gedlu, O. Wallscheid, J. Böcker, in: 2021 IEEE International Electric Machines & Drives Conference (IEMDC), 2021, pp. 1–8

DOI


Transferring Online Reinforcement Learning for Electric Motor Control From Simulation to Real-World Experiments

G. Book, A. Traue, P. Balakrishna, A. Brosch, M. Schenke, S. Hanke, W. Kirchgässner, O. Wallscheid, IEEE Open Journal of Power Electronics (2021), pp. 187-201

DOI


Safe Bayesian Optimization for Data-Driven Power Electronics Control Design in Microgrids: From Simulations to Real-World Experiments

D. Weber, S. Heid, H. Bode, J. Lange, E. Hüllermeier, O. Wallscheid, IEEE Access (2021), 9, pp. 35654–35669

DOI


Accurate Torque Control for Induction Motors by Utilizing a Globally Optimized Flux Observer

M. Stender, O. Wallscheid, J. Böcker, IEEE Transactions on Power Electronics (2021), 36(11), pp. 13261-13274

DOI


Accurate Torque Estimation for Induction Motors by Utilizing a Hybrid Machine Learning Approach

M. Stender, O. Wallscheid, J. Böcker, in: 2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC), IEEE, 2021

DOI


Combined Electrical-Thermal Gray-Box Model and Parameter Identification of an Induction Motor

M. Stender, O. Wallscheid, J. Böcker, in: IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2021

DOI


Gray-Box Loss Model for Induction Motor Drives

M. Stender, O. Wallscheid, J. Böcker, in: 2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC), IEEE, 2021

DOI



Thermal Monitoring of Electric Motors: State-of-the-Art Review and Future Challenges

O. Wallscheid, IEEE Open Journal of Industry Applications (2021)


Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning: A Benchmark

W. Kirchgässner, O. Wallscheid, J. Böcker, IEEE Transactions on Energy Conversion (2021), 36(3), pp. 2059 - 2067

DOI


gym-electric-motor (GEM): A Python toolbox for the simulation of electric drive systems

P. Balakrishna, G. Book, W. Kirchgässner, M. Schenke, A. Traue, O. Wallscheid, Journal of Open Source Software (2021), 2498

DOI


A Deep Q-Learning Direct Torque Controller for Permanent Magnet Synchronous Motors

M. Schenke, O. Wallscheid, IEEE Open Journal of the Industrial Electronics Society (2021), pp. 388-400

DOI


Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning

M. Schenke, O. Wallscheid, arXiv preprint arXiv:2105.08990 (2021)


Thermal Neural Networks: Lumped-Parameter Thermal Modeling With State-Space Machine Learning

W. Kirchgässner, O. Wallscheid, J. Böcker, arXiv preprint arXiv:2103.16323 (2021)


Torque and Inductances Estimation for Finite Model Predictive Control of Highly Utilized Permanent Magnet Synchronous Motors

A. Brosch, O. Wallscheid, J. Böcker, IEEE Transactions on Industrial Informatics (2021)

DOI


2020

Toward a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control

A. Traue, G. Book, W. Kirchgässner, O. Wallscheid, IEEE Transactions on Neural Networks and Learning Systems (2020), pp. 1-10

DOI


Estimating Electric Motor Temperatures with Deep Residual Machine Learning

W. Kirchgässner, O. Wallscheid, J. Böcker, IEEE Transactions on Power Electronics (2020), 36(7), pp. 7480-7488

DOI


Data-Driven Recursive Least Squares Estimation for Model Predictive Current Control of Permanent Magnet Synchronous Motors

A. Brosch, S. Hanke, O. Wallscheid, J. Böcker, IEEE Transactions on Power Electronics (2020), pp. 2179-2190

DOI


Emulation of Microgrids for Research and Validation of Control and Operation Strategies

K.S.C. Stille, D. Weber, J. Lange, T. Vogt, O. Wallscheid, J. Böcker, in: 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), IEEE, 2020

DOI


Comparison of Gray-Box and Black-Box Two-Level Three-Phase Inverter Models for Electrical Drives

M. Stender, O. Wallscheid, J. Böcker, IEEE Transactions on Industrial Electronics (2020), 68(9), pp. 8646-8656

DOI


Accurate Torque Estimation for Induction Motors by Utilizing Globally Optimized Flux Observers

M. Stender, O. Wallscheid, J. Böcker, in: 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), IEEE, 2020

DOI


OMG: A scalable and flexible simulation and testing environment toolbox for intelligent microgrid control

S. Heid, D. Weber, H. Bode, E. Hüllermeier, O. Wallscheid, Journal of Open Source Software (2020), 5(54), pp. 2435


Towards a scalable and flexible simulation and testing environment toolbox for intelligent microgrid control

H. Bode, S. Heid, D. Weber, E. Hüllermeier, O. Wallscheid, arXiv preprint arXiv:2005.04869 (2020)


Permanent magnet synchronous machine temperature estimation using low-order lumped-parameter thermal network with extended iron loss model

E.G. Gedlu, O. Wallscheid, J. Böcker, in: The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020), 2020, pp. 937–942


Investigation of disturbance observers for model predictive current control in electric drives

O. Wallscheid, E.F.B. Ngoumtsa, IEEE Transactions on Power Electronics (2020), 35(12), pp. 13563–13572


Data Set Description: Identifying the Physics Behind an Electric Motor–Data-Driven Learning of the Electrical Behavior (Part II)

S. Hanke, O. Wallscheid, J. Böcker, arXiv preprint arXiv:2003.06268 (2020)


Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning

W. Kirchgässner, O. Wallscheid, J. Böcker, arXiv preprint arXiv:2001.06246 (2020)



2019

Controller Design for Electrical Drives by Deep Reinforcement Learning: A Proof of Concept

M. Schenke, W. Kirchgässner, O. Wallscheid, IEEE Transactions on Industrial Informatics (2019), pp. 4650-4658

DOI


Empirical Evaluation of Exponentially Weighted Moving Averages for Simple Linear Thermal Modeling of Permanent Magnet Synchronous Machines

W. Kirchgässner, O. Wallscheid, J. Böcker, in: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019

DOI


Deep Residual Convolutional and Recurrent Neural Networks for Temperature Estimation in Permanent Magnet Synchronous Motors

W. Kirchgässner, O. Wallscheid, J. Böcker, in: 2019 IEEE International Electric Machines & Drives Conference (IEMDC), 2019

DOI


Development of a Black-Box Two-Level IGBT Three-Phase Inverter Compensation Scheme for Electrical Drives

M. Stender, O. Wallscheid, J. Böcker, in: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), IEEE, 2019

DOI


Finite-control-set model predictive control for a permanent magnet synchronous motor application with online least squares system identification

S. Hanke, S. Peitz, O. Wallscheid, J. Böcker, M. Dellnitz, in: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE), 2019, pp. 1–6


Stator flux-based field-oriented position-sensorless control of permanent magnet synchronous motors with limited parameter knowledge

O. Wallscheid, M.S. Shafiq, J. Böcker, in: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019, pp. 402–407


Hierarchical model predictive speed and current control of an induction machine drive with moving-horizon load torque estimator

O. Wallscheid, E.F.B. Ngoumtsa, J. Böcker, in: 2019 IEEE International Electric Machines & Drives Conference (IEMDC), 2019, pp. 2188–2195


Continuous-control-set model predictive control with integrated modulator in permanent magnet synchronous motor applications

S. Hanke, O. Wallscheid, J. Böcker, in: 2019 IEEE International Electric Machines & Drives Conference (IEMDC), 2019, pp. 2210–2216


Improved Fusion of Permanent Magnet Temperature Estimation Techniques for Synchronous Motors Using a Kalman Filter

D.E.E. Gaona, O. Wallscheid, J. Böcker, IEEE Transactions on Industrial Electronics (2019)


2018

Energy Management for a Nano-CHP Unit and an Electrical Storage System in a Residential Application

D. Weber, K.S.C. Stille, O. Wallscheid, J. Böcker, in: 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), IEEE, 2018

DOI


Lifetime Extension of Photovoltaic Modules by Influencing the Module Temperature Using Phase Change Material

D. Weber, M.I. Rafsan Jani, M. Grabo, O. Wallscheid, T. Klaus, S. Krauter, J. Böcker, in: World Conference on Photovoltaic Energy Conversion (WCPEC-7), 45th IEEE PVSC, 28th PVSEC, 34th EU PVSEC., 2018

DOI


Improving torque and speed estimation accuracy by conjoint parameter identification and unscented Kalman filter design for induction machines

O. Wallscheid, M. Schenke, J. Böcker, in: 2018 21st International Conference on Electrical Machines and Systems (ICEMS), 2018, pp. 1181–1186


A combined approach to identify induction machine parameters and to design an extended kalman filter for speed and torque estimation

O. Wallscheid, M. Schenke, J. Böcker, in: 2018 IEEE 18th International Power Electronics and Motion Control Conference (PEMC), 2018, pp. 793–799


Koopman Operator-Based Finite-Control-Set Model Predictive Control for Electrical Drives

S. Hanke, S. Peitz, O. Wallscheid, S. Klus, J. Böcker, M. Dellnitz, arXiv preprint arXiv:1804.00854 (2018)


2017

Investigation of long short-term memory networks to temperature prediction for permanent magnet synchronous motors

O. Wallscheid, W. Kirchgässner, J. Böcker, in: 2017 International Joint Conference on Neural Networks (IJCNN), 2017

DOI


Glocal identification methods for low-order lumped parameter thermal networks used in permanent magnet synchronous motors

D. Gaona, O. Wallscheid, J. Böcker, in: 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS), 2017, pp. 1–126


Sensitivity analysis of a permanent magnet temperature observer for PM synchronous machines using the monte carlo method

D. Gaona, O. Wallscheid, J. Böcker, in: 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS), 2017, pp. 599–606


A direct model predictive torque control approach to meet torque and loss objectives simultaneously in permanent magnet synchronous motor applications

S. Hanke, O. Wallscheid, J. Böcker, in: 2017 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE), 2017, pp. 101–106


Observing the Permanent Magnet Temperature of Synchronous Motors Based on Electrical Fundamental Wave Model Quantities

O. Wallscheid, A. Specht, J. Böcker, IEEE Transactions on Industrial Electronics (2017), 64(5), pp. 3921–3929


Fusion of a lumped-parameter thermal network and speed-dependent flux observer for PM temperature estimation in synchronous machines

D. Gaona, O. Wallscheid, J. Böcker, in: 2017 IEEE Southern Power Electronics Conference (SPEC), 2017, pp. 1–6


Fusion of direct and indirect temperature estimation techniques for permanent magnet synchronous motors

O. Wallscheid, J. Böcker, in: 2017 IEEE International Electric Machines and Drives Conference (IEMDC), 2017, pp. 1–8


Derating of automotive drive systems using model predictive control

O. Wallscheid, J. Böcker, in: 2017 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE), 2017, pp. 31–36


Prediction of residual power peaks in industrial microgrids using artificial neural networks

T. Vogt, D. Weber, O. Wallscheid, J. Böcker, in: International Joint Conference on Neural Networks (IJCNN), 2017, pp. 3228–3235


Ein Beitrag zur thermischen Ausnutzung permanenterregter Synchronmotoren in automobilen Traktionsanwendungen

O. Wallscheid, Shaker Verlag, 2017

Essentielle Anforderungen an Antriebssysteme für (teil-)elektrisch angetriebene Fahrzeuge sind eine hohe Leistungs- und Drehmomentdichte. Hierbei determinieren insbesondere die zulässigen Temperaturen wichtiger Motorkomponenten das transient sowie dauerhaft erzielbare Leistungspotential. Für die in automobilen Anwendungen häufig eingesetzten permanenterregten Synchronmotoren ist die Temperaturverteilung innerhalb der Wicklung und der Permanentmagnete von besonderem Interesse. Um den thermischen Bauteilschutz zu gewährleisten, werden Motoren in der industriellen Praxis häufig überdimensioniert, was zusätzlichen Gewichts- und Bauraumbedarf sowie höhere Produktionskosten bedingt. Alternativ kann ein Derating eingesetzt werden, welches die zulässige Motorleistung in Abhängigkeit des thermischen Zustands regelt. Dies erlaubt, sowohl die thermischen Kapazitäten des Motors gezielt auszunutzen als auch die Leistungsaufnahme im thermisch stationären Betrieb zu maximieren. Substantielle Voraussetzung hierfür ist die Kenntnis wichtiger Temperaturen zur Laufzeit - eine vollständige messtechnische Erfassung dieser ist allerdings aus Kosten- und Ausfallsicherheitsgründen nicht möglich. Im Zuge dieser Arbeit wurden daher sowohl thermische Netzwerke mit konzentrierten Parametern als auch Beobachteransätze auf Basis des elektrischen Motormodells untersucht. Darauf aufbauend wurde eine virtuelle Sensorfusion mittels Kalman-Filter realisiert. Umfangreiche Kreuz-Validierungen belegen eine hochgenaue, echtzeitfähige Temperaturermittlung mit einer Schätzabweichung von kleiner 5 K. Abschließend wurde ein modellprädiktives Derating-Konzept erarbeitet, welches sowohl die maximale thermische Ausnutzung des Antriebs erlaubt als auch definierte Grenztemperaturen sicher einhält.


2016

A Critical Review of Techniques to Determine the Magnet Temperature of Permanent Magnet Synchronous Motors under Real-time Conditions

O. Wallscheid, T. Huber, W. Peters, J. Böcker, EPE Journal (2016)(25), pp. 1–10


Real-time capable model predictive control of permanent magnet synchronous motors using particle swarm optimisation

O. Wallscheid, U. Ammann, J. Böcker, in: PCIM Europe 2016; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, 2016, pp. 1–8


2015

Global Identification of a Low-Order Lumped-Parameter Thermal Network for Permanent Magnet Synchronous Motors

O. Wallscheid, J. Böcker, IEEE Transactions on Energy Conversion (2015), 31(1), pp. 354–365


An open-loop operation strategy for induction motors considering iron losses and saturation effects in automotive applications

O. Wallscheid, M. Meyer, J. Böcker, in: 2015 IEEE 11th International Conference on Power Electronics and Drive Systems, 2015, pp. 981–985



Design and Empirical Identification of a Lumped Parameter Thermal Network for Permanent Magnet Synchronous Motors with Physically Motivated Constraints

O. Wallscheid, J. Böcker, in: IEEE International Electric Machines and Drives Conference (IEMDC), 2015


Optimum Efficiency Control of Interior Permanent Magnet Synchronous Motors in Drive Trains of Electric and Hybrid Vehicles

W. Peters, O. Wallscheid, J. Böcker, in: European Conference on Power Electronics and Applications (EPE), 2015


2014

Real-time capable methods to determine the magnet temperature of permanent magnet synchronous motors—A review

O. Wallscheid, T. Huber, W. Peters, J. Böcker, in: IECON 2014-40th Annual Conference of the IEEE Industrial Electronics Society, 2014, pp. 811–818


Determination of rotor temperature for an interior permanent magnet synchronous machine using a precise flux observer

A. Specht, O. Wallscheid, J. Böcker, in: 2014 International Power Electronics Conference (IPEC-Hiroshima 2014-ECCE ASIA), 2014, pp. 1501–1507


2013

Wirkungsgradoptimale Arbeitspunktsteuerung für einen permanenterregten Synchronmotor mit vergrabenen Magneten unter Berücksichtigung von Temperatureinflüssen

O. Wallscheid, J. Böcker, in: ETG-Fachbericht-Internationaler ETG-Kongress 2013–Energieversorgung auf dem Weg nach 2050, 2013


Discrete-time model of an IPMSM based on variational integrators

A. Specht, S. Ober-Blöbaum, O. Wallscheid, C. Romaus, J. Böcker, in: Electric Machines & Drives Conference (IEMDC), 2013 IEEE International, 2013, pp. 1411–1417


2012

A precise open-loop torque control for an interior permanent magnet synchronous motor (IPMSM) considering iron losses

W. Peters, O. Wallscheid, J. Böcker, in: IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society, 2012, pp. 2877–2882


2011

Optimierte Regelung für mobile Elektromotoren

O. Wallscheid, W. Peters, J. Böcker, Aktuelle Technik (2011), 5(1), pp. 30–33


Current controller with defined dynamic behavior for an interior permanent magnet synchronous motor

W. Peters, O. Wallscheid, J. Böcker, in: IECON 2011-37th Annual Conference of the IEEE Industrial Electronics Society, 2011, pp. 534–538


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