Automated Parameter Identification for Lithium Ion Battery Cells

Electric Vehicles (EVs) are increasingly becoming an alternative for road transportation due to their potential environmental benefits and the depletion of carbon-based fuels resources. However, a wider application of such EVs still needs to overcome several technological barriers, many of them given by limitations in battery technology. Batteries are the main source of energy of an EV and it is also the most expensive component. Therefore, strategies that lead to extended the battery life (i.e., less ageing) can have a positive effect in a wider implementation of EVs.

One of the strategies that can be used to extend the battery life, consist of improving modelling techniques such that the internal degradation processes of the batteries are better understood. One strategy consist of using battery models based on physics-based phenomena’s. These models can describe internal battery states (such as potentials, and concentrations) and ageing related parameters such as capacity and internal resistance, which are not measurable with sensors.

However, identifying the model parameters is not a trivial task because of the equations complexity and limited input/output sensor information. Likewise, such models are highly complex and often not suitable for control applications with (near) real time constraints.

The purpose of this assignment is develop a methodology for first, estimating the parameters of a battery physic-based ageing model, and second providing simplified version of such a model. The assignment covers the following tasks:

• Familiarize with physics-based models of batteries.
• Critical state-of-the-art revision of non-intrusive identification techniques.
• Familiarize with modelling software for such models (e.g., Comsol, Pybamm, etc).
• Model strategy selection for predicting battery age, based on literature review.
• Design and implementation of an algorithm to identify the ageing part of the model parameters, based on ageing data and voltage and current experiments.
• Algorithm testing with simulation data and (if time allows) with measured data from battery cells.
• Design and implement a technique to simplify the chosen ageing model, such that it can be used for control purposes.
• Reporting writing.
• Final presentation to colleagues.

This assignment can be divided in two parts, where the first part is carried out as an internship and the second part as a master thesis.

• You have a bachelor’s degree in a relevant field, for example, electrical or chemical engineering.
• You are coursing a master in a relevant field such as control systems.
• You have broad experience in Matlab/Simulink.
• You have previous experiences/courses with control systems, especially related to optimization and modelling techniques.
• Modelling of chemical processes is desired but not a must.
• Modelling of batteries is desired but not a must.

You want to work on the precursor of your career; a work placement 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. Naturally, we provide suitable work placement compensation.

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. Want to know more? Read what steps we are taking in the area of diversity and inclusion.

After the first CV selection, the application process will be conducted by the concerning department. TNO will provide a suitable internship agreement. If you have any questions about this vacancy, you can contact the contact person mentioned below.