Internship | Battery Ageing Prediction through Physics-Informed Data-Driven Methods

Internship | Battery Ageing Prediction through Physics-Informed Data-Driven Methods

About this position

The value of an electric vehicle is currently largely determined by the cost of its battery. Hence it is important, especially for fleet operators, to determine the current state of health of the batteries in their vehicles and to understand how long these batteries will last and if any action can be taken to prolong the useful life of the batteries. However, battery ageing is a challenging topic which is as of yet not fully understood by the battery community. Currently, there are several different approaches to modelling and predicting ageing, where the most popular methods are either purely data-driven (machine learning and AI) or physics based.

What will be your role?

You will be predicting battery ageing through a combination of data-driven and physics based methods. Both of these methods have potential, but also come with challenges. To reach their full potential data-driven methods need high quality data in high quantity. However this data is challenging to obtain. Lab data is often of high quality, but low in quantity and expensive to produce. On the other hand, field data is rich in its diversity and quantity, but lacks in quality, as gaps in the data, rogue datapoints and flawed measurements create challenges. Physics-based methods on the other hand face the challenge of requiring very specific data which can only be obtained through cell teardown. The challenge is to combine the best of these two methods.

The goal of this thesis project is to explore how the data-driven methods can be improved through transfer learning based on physics informed features or how the strengths of data-driven and physics-based methods can be leveraged and be combined to overcome their individual shortcoming and together produce more accurate predictions. The most important goal is that the explored approach provides better performance or novel capability compared to existing methods.

Assignment tasks:

• Literature survey on the status of data-driven and physics-based ageing prediction
• Select an approach and design a predictor
• Implement in Python and run on TNO data pipeline

What we expect from you

• Bachelor’s degree in relevant field like Mechanical, Electrical Engineering, Physics, Chemistry or Data Science
• Coursing a master in a relevant field like Data Science/AI or Electrochemistry
• Knowledge of Machine Learning and Python

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.