Internship | Physics-Based Battery Management Algorithm Development

Internship | Physics-Based Battery Management Algorithm Development

About this position

Battery packs are currently driving the energy transition in the mobility sector. A battery pack consists of many individual battery cells connected in series or parallel. To ensure proper functioning and safety of all the individual cells, packs are monitored by a Battery Management System (BMS). A BMS is an embedded system which measures voltage, current and temperature to estimate battery metrics such as the state-of-charge. Such estimations are based on ‘empirical’ models (such as equivalent circuit models) that represent the battery. These models face limitations while predicting internal battery states, critical for predicting battery degradation (i.e., ageing) and extending its useful lifetime. In this assignment, you will be developing BMS algorithms based on a modelling approach that uses physics to capture the internal battery states to increase the useful lifetime of a battery.

What will be your role?

Currently, Battery Management Systems typically use empirical models, which focus on predicting output (voltage) based on input (current). While these models can effectively be used for voltage prediction, they are not suitable for monitoring or enforcing physical limits inside the cell that can cause, for example, cell ageing. For this reason, Physics-Based Models (PBMs) are receiving significant attention in research and industry because they can simulate internal states, including ageing reactions. For example, these models are being used for developing fast charging algorithms that prevent ageing in the battery. While scientific literature provides several examples of using these models, their applicability to real-life scenarios still remains uncertain due to lacking of parameters, computational complexity, etc.

The goal of this thesis project is to explore the opportunities of using PBM for practical applications on Battery Management Systems. Possible applications can range from, for example, developing state observers for concentration monitoring in PBM, PBM parametrization, ageing prediction or dynamic charging using model predictive control. The most important goal is that the explored algorithm provides better performance or novel capability compared to existing empirical methods, and that it is useful in real-life scenarios. This assignment is initially intended as a master thesis, but can also be treated as a master thesis + internship.

Assignment tasks:

• Literature survey on the status of PBM in BMS and the possible uses
• Select a use and design controller or observer structure
• Implement in Matlab, Simulink or Python.
• (optional) C-code generation and test on embedded platform

What we expect from you

• Bachelor’s degree in relevant field like Mechanical, Chemical or Electrical Engineering
• Coursing a master in a relevant field like Chemical, Electrical or Control Engineering
• Knowledge in Matlab/Simulink and Python
• A motivation letter tailored for this vacancy. Here you should state why is this topic/vacancy interesting for you. Please, also state what kind of PBM application you would find most interesting.
• Knowledge on embedded systems is a plus

What you'll get in return

You want an internship opportunity on the precursor of your career; an internship gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Furthermore, we provide:

• A highly professional, innovative internship environment, within a team of top experts.
• A suitable internship allowance (615 euro for wo-, hbo- and mbo-students, for a full-time internship).
• Possibility of eight hours of free leave per internship month (for a full-time internship).
• A free membership of Jong TNO, where you can meet other TNO professionals and join several activities, such as sports activities, (work-related) courses or the yearly ski-trip.
• Use of a laptop.
• An allowance for travel expenses in case you don’t receive an OV-card.

TNO as an employer

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world.

At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society.

E-mailadres: subhajeet.rath@tno.nl