Thesis - Optimizing Battery Testing for EVs: Machine Learning in Lab Management

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We offer the following research topic

Thesis – Optimizing Battery Testing for EVs: Machine Learning in Lab Management

Master Thesis

Batteries, being the most valuable and defining component of electric vehicles (EVs), are of paramount importance to future mobility. The demand for battery testing facilities is soaring, with capacities being reserved years ahead. Here, prototype battery components (cells, modules) are the unit under test (UUT) to potentially thousands of test instruments (e.g., cyclers).
The planning process involves a multitude of tasks, including the organization of workloads, parameters, and test procedures, mapping of UUTs to test equipment, as well as the setup of equipment. The task of reliably planning and managing the usage, control, and inventory of thousands of test channels surpasses human capabilities due to its complexity. Classic optimization methods on the other hand reach their limits due to plant uncertainties (eg., unavailability due unplanned maintenance) and sometimes unpredictable behavior of the unit under test itself. In this work, new ML-based algorithms shall be implemented, analyzed, and compared to existing methods in managing test labs.

YOUR RESPONSIBILITIES:

• Analyze and adapt data models for battery testing
• Implement simple test environment to simulate battery test lab
• Analyze state of the art in ML applicable to plant management
• Select appropriate approaches and implement prototypes for tasks in the battery testing facility (e.g. allocate test equipment)
• Design an agent prototype that interacts with the environment
• Design dashboard prototypes to properly communicate necessary changes in resource allocation

YOUR PROFILE:

• Ongoing master study in the fields of Computer Science, Telematics or Physics
• Good programming skills in Python
• C# skills appreciated
• Knowledge of machine learning algorithms (e.g. reinforcement learning)
• Knowledge of data structures and translations
• Good knowledge of German and English
• Presence from time to time at our headquarter in Graz required

WE OFFER:

• You can write your thesis independently and receive professional guidance and support from our experienced employees.
• You will have the opportunity to exchange ideas with experts in the company and benefit from their expertise.
• Take the opportunity to immerse yourself in the world of AVL and embed your theoretical knowledge in a practical environment.

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.

You are interested in a job at AVL but you are not sure how to apply or want to know what happens after you send your application?

AVL is not just about cars. It’s about changing the future. Together.

Location:

Graz, AT

Company: AVL List GmbH

Job Function: Battery

Contract Type: Thesis

Posting Date: Oct 13, 2024

Job ID: 37277

About AVL

AVL is one of the world’s leading mobility technology companies for development, simulation and testing in the automotive industry, and beyond. We provide concepts, solutions and methodologies in fields like vehicle development and integration, e-mobility, automated and connected mobility (ADAS/AD), and software for a greener, safer, better world of mobility.

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