Public summary
An internship opportunity is available in a research center located in Nuremberg focused on advanced technology research and development in digital power solutions. The role involves supporting the development and validation of battery state estimation algorithms, analyzing large-scale battery management system data to identify degradation and anomalies, and performing quantitative analysis impacting battery performance and lifetime. The position is suitable for MSc or PhD students with knowledge in lithium-ion battery technology and programming skills. English fluency is required; knowledge of German or Chinese is beneficial but not mandatory. The environment promotes innovation, learning, and cross-cultural collaboration with various training opportunities offered.
Responsibilities
Support the development of state estimation algorithms (SOC, SOH) for lithium iron phosphate-based battery energy storage systems. Assist in testing and validation of algorithms from model-in-the-loop to hardware-in-the-loop stages. Analyze large-scale battery management system field data to identify degradation patterns, sensor anomalies, and operational outliers. Perform quantitative analyses investigating cell-level and system-level parameters affecting estimation accuracy and battery lifetime.
Qualifications
Currently enrolled in MSc or PhD program in disciplines related to battery technology, electrical engineering, chemical engineering, physics, computer science, or similar fields. Strong knowledge of lithium-ion battery electrochemistry and degradation mechanisms, ideally with hands-on experience with LFP cells. Experience with battery state estimation algorithms such as Coulomb counting, OCV methods, Kalman filters, and equivalent circuit models. Programming proficiency (Python, Matlab, C++, C) is a plus. Experience testing BMS algorithms is advantageous. Fluent in English; working knowledge of German or Chinese is a plus.