PhD on Intelligent data-driven charge management system for future electrified mobility

Introduction

• Are you passionate about advancing sustainable mobility solutions?
• Are you eager to work on the intersection of AI, optimization, and energy management?
• Are you interested to apply and valorize scientific results in this field in electrified mobility, together with a highly innovative company?

Then, we are looking for you!

Job Description

We invite highly motivated students with a strong background in mathematical system theory, data science and control to apply for a PhD position within the Control Systems Technology (CST) section at the Department of Mechanical Engineering, Eindhoven University of Technology. The mission of the CST section is to develop new methods and tools in the area of Systems Theory, Control Engineering and Mechatronics. The research focuses on understanding the fundamental system properties that determine the performance of mechanical engineering systems, and exploiting this knowledge for the design of the high-tech systems of the future. In the Automotive research line, our research is committed to accelerate the introduction of smart and green mobility by self-learning control for future powertrains.

Driven by societal concerns about global warming and local air quality, the focus on electric vehicles continues to grow. To further accelerate their adoption, key challenges such as charging infrastructure, range anxiety, and affordability must be effectively addressed. For their control systems, this means energy efficiency, operational costs, vehicle range and battery life have to optimized while maintaining passenger comfort. In practice, the performance of charging strategies is limited due to model uncertainties and unknown disturbances. As a result, there is an urgent need for early anomaly detection (e.g. failure in thermal and battery system) and risk averse charging strategies. This project tackles the integration of early anomaly detection, prediction of long term vehicle usage, and charge management in electric vehicles using AI techniques. This is applied to an innovative, revolutionary use case: wireless charging method (so called Dynamic Wireless Power Transfer (DWPT)), enabling real-time, coordinated charging for multiple EVs during driving.

Within the project, your research will focus on:

• Smart and early anomaly detection with limited labeled data and health states monitoring, using high-fidelity simulations, (generative) probabilistic AI models, transfer learning, physics-informed AI, and semi-supervised learning;
• Accurate and robust energy consumption and demand prediction, using advanced neural architectures, transfer learning, and physics-informed hybrid models to efficiently process long time-series data and reduce training data requirements across diverse operational domains;
• Intelligent multi-vehicle DWPT charging optimization, using energy-aware recommendations and coordinated control via reinforcement learning and model predictive techniques to reduce driver anxiety and enhance traffic flow;
• Performance evaluation and system validationvia high-fidelity simulations, Hardware-in-the-Loop setups, and demonstration vehicles in collaboration with the industry partner.

The developed AI-driven classification, prediction and control strategies will support the sustainable, scalable deployment of electric mobility solutions.

This position will help you to build both a strong academic and industrial research profile. You will have access to the graduate courses at the Dutch Institute of Systems and Control (DISC) and will have the opportunity to collaborate with industry and academic researchers worldwide. By joining us, you will be part of a vibrant community of more than 60 researchers including faculty members, postdocs and PhDs working on diverse topics in the field of dynamical systems and control and its applications. 

This PhD position is jointly supervised by professor Frank Willems and professor Emilia Silvas.

Job Requirements

• A master’s degree (or an equivalent university degree) in systems and control, mechanical engineering, electrical engineering, data science or applied mathematics.
• Strong background in data-based and learning techniques or systems and control theory.
• Affinity with the application domain: electric vehicles
• Knowledge on programming language Matlab/Simulink and Python is expected.
• Experience and/or a keen interest in the field of systems and control.
• Eager to work within an interdisciplinary team of industry and academic researchers.
• Willing to travel to industry partner (approximately twice per week, travel time 1 hour each way).
• Fluent in spoken and written English.

Conditions of Employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you: 

• Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. 
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 max. € 3,881).  
• A year-end bonus of 8.3% and annual vacation pay of 8%. 
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process. 
• An excellent technical infrastructure, on-campus children's day care and sports facilities.  
• An allowance for commuting, working from home and internet costs. 
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates. 

Information and application

About us

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. 

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager prof.dr.ir. Frank Willems, F.P.T.Willems@tue.nl, TU/e webpage Frank Willems.

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services Gemini (HRServices.Gemini@tue.nl) or HR Advice (HRAdviceME@tue.nl).

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.