GaN enabled OLED Driver for Automotive Lighting Application

The impressive features, both in a design and technical aspect, of the Organic LED (OLED) lighting technology have attracted the interest of the research and commercial world and have recently be in the spotlight of the automotive industries, like the Lighting Department of Audi. Some of the most exciting features of these lights are the exibility, transparency and the very small thickness. It is reasonable, therefore, that in order to take full advantage of this new technology the electronics that drive these lights, that is the dc/dc converter, should also be characterised of low prole, exibility and small size. A boost towards the direction of the converter minimization and high power density operation could be the recently commercialised power switching technology of Gallium Nitride (GaN) devices. This technology, which exploits the advantages of the wide band gap semiconductors, offers high frequency, high power density, low switching losses operation and low profle design, as well. As every newly commercialised technology, the areas of application that at most exploit the advantages of these switches are still to be found, but it is expected that applications that require high power density or low profle features, like the OLED applications, could benefit the most from the GaN technology. This area is the exact topic of the current master thesis. At this project a dc/dc converter based on GaN switching devices is designed and built. The converter is purposed for the driving of Organic LED lights that belong to the tail light system of a vehicle. As such, the electrical, mechanical and thermal specifications of the converter are based on the guidelines of the Lighting Department of the Audi automotive industry and the nature of the Organic LED lighting. At this thesis, the required dc/dc converter is designed, built, measured and assessed for its adequacy to the defined requirements. During the design part of this project the necessary simulations are conducted. For the purpose of estimating the losses of the GaN device a detailed analytical model for the switching transients is used. Also, both the possibilities of using a planar and a discrete coil are investigated during the simulations and the two components, which were built in the lab, are compared experimentally. A final prototype of the converter is also built in the lab and the experimental and simulated results are then compared and assessed. The assessment of the results showed that the features of the GaN device can be fully exploited at this application and can offer the low profile and high power density requirements. In order, however, to achieve the minimization of the magnetic component more advanced and wider range of core materials are required, especially if a planar coil is desired. Finally, full exploitation of the detailed analytical GaN loss model requires specialised software tools or accurate analytical models in order to determine the values of the various parasitics and the thermal resistance of the component, both strongly related to the PCB layout. This, also, means that during the design procedure in order to achieve better accuracy -which is required at applications which push the frequency to the limits - the PCB design layout parameters should be included in the iterative process of the parameter specificationElectrical Sustainable EnergyElectrical Engineering, Mathematics and Computer Scienc

A Distributed Predictive Control of Energy Resources in Radiant Floor Buildings

This paper studies the impact of using different types of energy storages integrated with a heat pump for energy efficiency in radiant-floor buildings. In particular, the performance of the building energy resources management system is improved through the application of distributed model predictive control (DMPC) to better anticipate the effects of disturbances and real-time pricing together with following the modular structure of the system under control. To this end, the load side and heating system are decoupled through a three-element mixing valve, which enforces a fixed water flow rate in the building pipelines. Hence, the building temperature control is executed by a linear model predictive control, which in turn is able to exchange the building information with the heating system controller. On the contrary, there is a variable action of the mixing valve, which enforces a variable circulated water flow rate within the tank. In this case, the optimization problem is more complex than in literature due to the variable circulation water flow rate within the tank layers, which gives rise to a nonlinear model. Therefore, an adaptive linear model predictive control is designed for the heating system to deal with the system nonlinearity trough a successive linearization method around the current operating point. A battery is also installed as a further storage, in addition to the thermal energy storage, in order to have the option between the charging and discharging of both storages based on the electricity price tariff and the building and thermal energy storage inertia. A qualitative comparative analysis has been also carried out with a rule-based heuristic logic and a centralized model predictive control (CMPC) algorithm. Finally, the proposed control algorithm has been experimentally validated in a well-equipped smart grid research laboratory belonging to the ERIGrid Research Infrastructure, funded by European Union's Horizon 2020 Research and Innovation Programme