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Thesis Worker: Model based predictions of battery state of health

Thesis Worker at Volvo Cars 

Welcome to explore the world of Volvo Cars by writing your thesis with us! As a thesis worker in our organization, you are supported by a supervisor who follows you during your project. All thesis projects are arranged in business-critical areas and therefore you will be able to contribute to our company purpose – providing freedom to move in a safe, sustainable, and personal way – from day one!  

 

Background

With the rapid development of electrification, the ageing of Li ion batteries has received increased attention in recent years.  With the battery being the largest and most expensive component in a Battery Electrified Vehicle (BEV) the understanding of battery ageing is critical to both the sustainability and the profitability of any BEV. Battery lifetime is also a key attribute for the car customers, affecting the second-hand value and expected lifetime of the vehicle. These aspects make it highly important to be able to monitor, follow up and make forecasts of the battery state-of-health (SOH) in the customer fleet.

The goal of this thesis project is to evaluate models best suitable for predicting battery SOH until end of life on both individual cars as well as for the entire customer fleet.

 

Scope

As Master thesis student you will be working on development of prediction methods for usage of batteries. You will have the opportunity to cooperate with colleagues within the Battery Hardware Department, other supporting departments as well as various stake holders for battery SOH. You will be part of a highly motivated team working with field data where there is strong interest in creating new insights.

In the master thesis project ‘Model based predictions of battery state of health’ you will be working on analysing field data with focus on battery SOH. The project will build on previous studies on car fleet SOH and knowledge/data from cell testing with the aim to identify models suitable for battery SOH estimations. To reach further there is a need to get a deeper understanding of how the vehicle data can be used to predict battery SOH and how the SOH data itself should be interpreted and used in the best way. There is also a need to take on a more holistic approach on the model identification, where both data driven approaches as well as data from cell testing are taken into consideration and compared.

 

Duration

  • The duration of the Thesis is 20 weeks

  • The Thesis starts in Jan 2025.

  • 30 ECTS (academic credits) if in agreement with your Thesis Advisor in University

  • This thesis is suitable for 1- 2 students

 

How to Learn More and Apply
Selection will be ongoing during the application period, so do not hesitate to send in your application. Attach your resume and cover letter stating your interests within the given area and your thoughts and credentials. Please note that due to GDPR applications by email will not be accepted.

 

If you have any additional questions regarding the position, you are welcome to contact:

Supervisor Robert Johansson, robert.johansson.4@volvocars.com

Recruiting Manager, Anette Garnemark at anette.garnemark@volvocars.com

 

Who are we?

Everything we do starts with people. Our purpose is to provide freedom to move, in a personal, sustainable and safe way. We are committed to simplifying our customers’ lives by offering better technology solutions that improve their impact on the world and bringing the most advanced mobility innovations to protect them, their loved ones and the people around them. 


Volvo Cars’ continued success is the result of a collaborative, diverse, and inclusive working environment. The people of Volvo Cars are committed to making a difference in our world. Today, we are one of the most well-known and respected car brands, with over 40,000 employees across the globe. We believe in bringing out the best in each other and harnessing the true power of people. At Volvo Cars your career is designed around your talents and aspirations so you can reach your full potential. Join us on a journey of a lifetime as we create safety, autonomous driving and electrification technologies of tomorrow.

 

Gothenburg, SE, 40531

Job requisition ID:  73178

Apply now »