We offer the following research topic

Thesis - Remaining Capacity Prediction for Automotive HV Batteries 

Master Thesis

We are looking for a motivated student to conduct their master thesis in li-ion batterie modelling using statistical-/ physical modelling techniques. The automobile industry's transition to electric vehicles is accelerating, with this paradigm shift, the efficiency and reliability challenges for these complex physical systems are increasing. Since the battery is the most important component in an electric vehicle, the battery state of health determination is of high importance. Therefore, the aim of this master's thesis is to evaluate advanced physical-based modeling approaches, employing state-of-the-art analytical methods, for predicting the remaining capacity of li-ion batteries using sparsely resolved fleet data.

WHAT WE OFFER YOU:

• Literature review on existing analysis techniques for battery aging modeling, sparse model identification for physical systems, and up sampling
• Implementation of data processing routines and feature engineering algorithms on a large data set
• Determination of physical principles and models for capacity estimation
• Definition of baseline for data up sampling
• Concept and implementation of data up sampling with sparse model identification, validation and evaluation of methods
• Battery aging modeling: concept and models (2-3 approaches), validation and evaluation of models
• Comparison with results without up sampling

WHAT WE LOOK FOR:

• Attended lectures on  Introduction to Electrical Engineering, Fundamentals of Electrochemistry, Electrochemistry of Batteries
• Proven experience in applying data science methods
• Strong proficiency in Python
• Highly developed quality awareness with strong attention to details

WHICH STUDY TRACKS WE PREFER:

• Electrical Engineering
• Mechanical Engineering
• Applied Statistics 
• Computer Science
• Technical Mathematics

The successful completion of the thesis is remunerated with a one-time fee of EUR €3.500,00 before tax.

You don't want to write your final thesis just for the books, then explore the mobility of the future together with us! Maybe you will be a part of it soon!

At AVL, we foster and celebrate diversity: We recognize that diverse ways of thinking are required to achieve our vision of a greener, safer, and better world of mobility. Different backgrounds, attitudes, interests, and experiences make us successful. As Equal Opportunity Employer we consider all qualified applicants without regard to ethnicity, religion, gender, sexual orientation or disability status.