Electromobility has been growing rapidly in recent years, as a result of green and sustainability policies that promote it, but its growth has been hampered by having less autonomy than combustion vehicles, not being able to directly replace them especially in heavy-duty electric vehicles powertrains. The main objective of this work is to propose an improvement to an already implemented Bidirectional Dual-Active-Bridge (DAB) Partial Power Converter (PPC) topology, seeking to boost efficiency by testing different modulations. The modulation study applied to PPC is interesting in order to identify the cases where the RMS current in the transformer is minimized. Results of the study shows that efficiency of the DAB-based PPC can be optimized by using the correct modulation, with a possible maximum efficiency of 99.41% at 6.526 kW.

Multilevel converters emerge as a promising technology for high-power medium-voltage applications due to their different advantages. On the other hand, model predictive control (MPC) is one of the control techniques that has been widely used in different applications because of its features, such as fast transient response and flexibility to include nonlinearities. The finite control set MPC (FCS-MPC) approach for a seven-level topology converter reduces the number of calculations significantly, nevertheless depends on the circuital model making it sensitive under uncertainties. On the other hand, model-free predictive control (MF-PC) has gained attention due to its accurate prediction without previous knowledge of the power system. This paper proposes MF-PC to predict the current for each phase for the seven-level topology converter. Moreover, simulation results demonstrate superior performance and feasibility of the developed control method compared to the FCS-MPC approach applied to a seven-level topology converter.

One of current challenges in high-density electric vehicles (EVs) is the efficient thermal control of power converters and the reliable management of power flows in motoring/breaking mode for the battery bank. In this line, this paper presents an Active Thermal Control (ATC) scheme to regulate thermal stress in Gallium Nitride High Electron Mobility Transistors (GaN HEMTs) devices of a three-level bidirectional buck-boost DC-DC converter (TLBBC) as a power interface between battery and motor inverter. The TLBBC is designed to operate at a rated power of 20 kW as part of a modular system, by using parallel GaN devices. Proposed control schemes are implemented using systematic linear control design. Finally, the system is simulated and tested for a Mission Profile-Oriented (MPO) based on Highway Fuel Economy Test (HWFET) in order to validate the proposed control schemes.

The behavior of Model Predictive Control (MPC) is by principle affected by the quality of the model used for the controlled system. A parameter mismatch between the plant and the controller can affect drastically the performance of MPC. This paper presents a new strategy called model-free predictive control (MF-PC) to overcome these problems. In this approach, a recursive least squares algorithm is implemented to identify the parameters of an auto-regressive with exogenous input (ARX) model, using input and output measurements of the controlled system. The proposed method enables an accurate prediction of the controlled variables without requiring detailed knowledge about the physical system. Simulation results obtained for the current control of a two-level, three-phase voltage source inverter, demonstrate that the MF-PC is exceptionally robust against the parameter variations and the model uncertainties, compared to conventional finite-control-set MPC.

This paper addresses to some of the latest contributions on the application of Finite Control Set Model Predictive Control (FCS-MPC) in Power Electronics. In FCS-MPC , the switching states are directly applied to the power converter, without the need of an additional modulation stage. The paper shows how the use of FCS-MPC provides a simple and efficient computational realization for different control objectives in Power Electronics. Some applications of this technology in drives, active filters, power conditioning, distributed generation and renewable energy are covered. Finally, attention is paid to the discussion of new trends in this technology and to the identification of open questions and future research topics.