Master Thesis within Battery Field Data & Diagnostics

Husqvarna Group collects substantial amounts of operational data from its battery-powered products, but the information is spread across systems and is not yet analyzed systematically. This thesis aims to help establish a structured framework for battery data analysis, improving understanding of customer usage, faults and end-of-life behavior. The findings will support battery diagnostics, product development and collaboration with dealerships.

The assignment

• Review research on battery field-data analysis, fault diagnosis and methods for characterizing usage.
• Map available datasets, evaluate their quality, and clean and prepare them for analysis.
• Investigate fault records, charging and discharging patterns, and operating conditions.
• Apply statistical and machine learning techniques to classify faults and cluster usage patterns, identifying trends and potential root-cause indicators.
• Create dashboards or other visualizations to communicate the results.
• Conduct workshops and interviews with battery R&D teams and product groups to validate findings and understand their needs.
• Recommend a process for sharing battery data and insights with dealerships, considering diagnosis, customer support and warranty handling.
• Document the work and present the conclusions according to university requirements.

Who we are looking for

• Master’s student in data science, AI or machine learning, applied mathematics, statistics, electrical engineering or a related discipline.
• Good Python and SQL skills; familiarity with tools such as pandas and scikit-learn is relevant.
• Experience with Databricks or Power BI is advantageous.
• Interest in lithium-ion batteries and battery management systems; previous battery knowledge is beneficial but not mandatory.
• Strong English communication skills and the ability to explain findings to technical and non-technical audiences.

What we offer

• A thesis project within the Battery Competence Center’s Advanced Development Department.
• The opportunity to work with operational battery datasets and engage with battery R&D teams and product groups.
• Work with potential applications in battery reliability, diagnostics, future designs and dealership services.

Practical details

Planned start: early 2027. Apply with a CV and cover letter as soon as possible, no later than 12 November 2026. Project questions: Matthias Heim, matthias.heim@husqvarnagroup.com.