AdvancedEngineering trackDE-CP-25

Battery Cell Ageing Model from Cycling Data

Internship role: Werkstudent:in Batterieentwicklung. Fit a capacity-fade model to public cycling datasets, validate on held-out cells and produce a state-of-health estimator with error bounds.

10 Guided Steps480h Internship TierSubmit: GitHub repo or evidence pack + live demo / report + README + milestone logbookVerified CertificateAI Rubric Graded

Program Overview

Internship role: Werkstudent:in Batterieentwicklung. Fit a capacity-fade model to public cycling datasets, validate on held-out cells and produce a state-of-health estimator with error bounds.

What you submit

GitHub repo or evidence pack + live demo / report + README + milestone logbook

Stack: Python, pybamm, pandas, MATLAB optional

How it is graded

Signals: Milestone gates met; measurable result reported; documentation; deployment or evidence reachable; reflective log

Functionality & requirements30
Technical quality & architecture25
Documentation15
Deployment & evidence15
Innovation10
Presentation5

Pass 60% · Merit 75% · Distinction 90%

Learning Outcomes

480-hour Germany programme. Battery gigafactories in Salzgitter, Kaiserslautern and Heide are hiring for cell-ageing analytics.

Target Audience

Engineering Students

Diploma, B.Tech, B.E., BCA, MCA, or M.Tech students seeking practical experience.

Aspiring Developers

Developers who want to build proof-of-work capstone projects for tech resumes.

Job Seekers

Graduates looking for AI-evaluated code review & verified industry credentials.