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Thesis Worker-Estimate Charging Time Using Machine Learning

 

Thesis Work – Estimate Charging Time Using Machine Learning

 

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 

 

When charging a battery there is a need to estimate the time it takes to charge to certain states of charge (SoC). This to allow customer to make informed decisions and better plan their trip. Charging time is however dependant on multiple factors, both internal such as the temperature and the properties of the specific battery, as well as external factors such as ambient temperature and the specific attributes of the charging station.

 

Due to the breadth and complexity of possible factors affecting charging, conventional modelling algorithms can often struggle with inaccuracy, especially in unusual situations. This complexity along with the large amount of data for charging time readily available instead invites a machine learning approach.

 

 

Scope 

 

In this master thesis we want to investigate the use of machine learning to estimate charging time for the batteries. We will analyze and process available data and use it to train and evaluate a neural network. Furthermore, we will explore the possibility to add an adaptive component to the charging time calculation, further optimizing it down to the individual car level.  

 

Do you fit the profile 

You are currently enrolled as a student in the final year of a master’s degree in electrical engineering, engineering physics, applied mathematics, computer sciences or similar. You need strong skills in suitable programming languages (Matlab, Simulink, Python, or similar) and have knowledge in methods of machine learning. The work will be conducted on-site at Volvo Cars.

 

Duration 

  • January to June 2025
  • 30 points ECTS (academic credits) if in agreement with your Thesis Advisor in University 
  • This thesis is to be conducted by 2 Students working in pair. 

 

 

Be part of the change – apply today!

Applications should include your CV and a brief personal letter stating your interests within the given area and your thoughts and credentials. We are continuously screening applications and will fill the position as soon as we find a good match. So do not hesitate to send in your application.

 

Apply as soon as possible but no later than  2024-10-31.

 

Please note that due to GDPR applications via email will not be accepted.

 

For questions about the thesis work please contact

Fredrik Bengtsson at fredrik.bengtsson.3@volvocars.com   

 

Volvo Cars - Driving change together 

Volvo Cars’ success is the result of a collaborative, diverse, and inclusive working environment. Today, we are one of the most well-known and respected car brands, with around 43,000 employees across the globe. At Volvo Cars, your career is designed around your skills and aspirations, allowing you to reach your fullest potential. 

 

 

 

 

Gothenburg, SE, 40531

Job requisition ID:  73663

Apply now »