Model Predictive Control for Wireless Power Transfer
Power electronics plays a key role in many modern industrial and domestic applications, having a major socio-economic impact. In the future, power electronics will be a key enabling technology, being wireless power transfer and electric vehicles one of the most promising application areas. In this context, the increasing performance and complexity of power converters, as well as the strong requirements in terms of efficiency, power density and cost, has made classical control techniques obsolete.
Considering this framework, this proposal considers the use of the high performance wideband gap-based TAPAS board as a perfect test-bench to develop new control techniques for power electronic converters. The selected application is a multi-coil wireless power transfer system controlled by using model predictive control. By using this technique, it will be possible to include complex control constraints that are not possible using classical linear control: soft-switching operation and monitoring, multi-load management, coupling tracking and operation optimization, among others. The performance obtained by using this approach will outperform current classical linear controllers, enabling the development of future high-performance applications. The results of this study can be applied to many fields including wireless power transfer for home devices, electric vehicles or induction heating, among others.
Technical set-up and implementation:
In this proposal, the TAPAS board will be used as a flexible power electronics set-up to power a multi-coil wireless power transfer system. This system will be based on a resonant converter, whose tuning and control require usually complex control techniques. Moreover, this system will be able to power and manage multi-load systems, being these constraints included in the control optimization process. In this context, model predictive control has been selected as a powerful technique to fulfill these requirements . The implementation of such controller will be made in the uP architecture, being its implementation optimization for real-time operation of the study points .
Sergio Lucia. TU Berlin, Germany. Model predictive control specialist.
Benjamin Karg. TU Berlin, Germany. PhD student.
Oscar Lucia. University of Zaragoza, Spain. Power electronics specialist.
This project will require 1 TAPAS board
 S. Lucía, D. Navarro, H. Sarnago, and O. Lucía, "Model predictive control for resonant power converters applied to induction heating," in IEEE International Symposium on Industrial Electronics, 2018.
 S. Lucia, D. Navarro, O. Lucia, P. Zometa, and R. Findeisen, "Optimized FPGA Implementation of Model Predictive Control for Embedded Systems Using High Level Synthesis Tool," IEEE Transactions on Industrial Informatics, vol. 14, no. 1, pp. 137-145, 2017.
this idea will get oneTAPAS dev kit