This project focuses on advanced control of medium voltage fast chargers for electrical vehicles in order to minimize charging times and reduce the strain on the electricity grid. This involves research in model predictive control, self-learning control, optimization, and on the application side, power systems stability and battery modeling for control. The research is part of the NEON (New energy outlook for the Netherlands) NWO (Dutch Research Council) project and it will be conducted within the Control Systems (CS) group of the Department of Electrical Engineering, TU/e, in cooperation with the Electromechanics and Power Electronics (EPE) and Electrical Energy Systems (EES) groups, Damen, Prodrive and the other NEON partners.
NEON is a multidisciplinary project that address three related societal challenges: clean energy, intelligent green transport, and climate action. It aims at developing solutions for quickly transforming our energy and mobility systems from running on fossil fuels to running on renewables. NEON will make use of a cross-disciplinary and integral approach to address complex aspects of the energy transition: the interaction between energy and mobility, the relation between technology innovation and personal preferences, the regulation and standardization of future energy and mobility systems, etc. This will involve the collaboration of several academic and industrial partners from the Netherlands across multiple science domains.
Within NEON, this PhD project focuses on the challenge of charging mobility. Large scale integration of electrical vehicles (EVs) within power grids is a pressing challenge that requires fast charging solutions and optimal scheduling of charging to sustain grid stability. Grid operators favor building a limited number of medium voltage fast charging stations with high capacity instead of rebuilding low voltage electricity infrastructure at a large scale. Also, EVs manufacturers favor fast charging stations to increase range of electric vehicles (Illustration: McKibillo - IEEE Spectrum). Therefore, the aim of this project is to develop efficient medium voltage fast chargers for electrical vehicles by new power electronics design and advanced, model based predictive control. To this end, research in model predictive control, self-learning control, optimization tailored for medium-voltage fast chargers and EVs will be conducted. The research also involves laboratory work in terms of implementation and experimental verification of the research results on a prototype charger developed by TU/e in collaboration with industrial partners.
Main research directions:
Control Systems group
The CS group research activities span all facets of systems and control theory, such as linear, nonlinear and hybrid systems theory, model predictive control, distributed control, machine learning for control, modeling and identification, formal methods in control. The CS group has a strong interconnection with industry via national and European funded projects in a variety of application areas like high-precision mechatronics, power electronics, and sustainable energy (mobility, transport, smart grids). CS owns an Autonomous Motion laboratory and hosts several high-tech setups. The PhD student will join the group and interact with the other members of the CS group (around 40 researchers), where he/she will participate in a mix of academic and industrial research activities. Research within the CS Group is characterized by personal supervision. The PhD student will have access to the advanced courses offered by the Dutch Institute for Systems and Control, and will attend the yearly Benelux Meeting on Systems and Control.
For the PhD position in this project, a candidate with a MSc degree in Systems and Control, Electrical Engineering, or Mechanical Engineering will be selected and hired as a doctoral student in the Control Systems Group for a 4-year period. The candidate should have the following competences:
Do you recognize yourself in this profile and would you like to know more? Please contact dr. Mircea Lazar, m.lazar[a]tue.nl, or go to https://www.tue.nl/en/research/researchers/mircea-lazar/
For information about terms of employment, please contact HR department, hrservices.flux[a]tue.nl
Please visit www.tue.nl/jobs to find out more about working at TU/e!
We invite you to submit a complete application by using the 'apply now'-button on this page. The application should include a:
We look forward to your application and will screen it as soon as we have received it. Screening will continue until the position has been filled.