A5073765405- Advanced Battery Technologies Research
- Advancements in Battery Materials
- Advanced Battery Materials and Technologies
- Reliability and Maintenance Optimization
- Radiation Effects in Electronics
- Polymer Surface Interaction Studies
- Dendrimers and Hyperbranched Polymers
- Advanced Polymer Synthesis and Characterization
- Tunneling and Rock Mechanics
- Infrastructure Maintenance and Monitoring
Universität Ulm
2022-2024
Mercedes-Benz (Germany)
2020-2024
Daimler (Germany)
2019
Max Planck Institute for Polymer Research
2017
Abstract Precise lifetime predictions for lithium‐ion cells are crucial efficient battery development and thus enable profitable electric vehicles a sustainable transformation towards zero‐emission mobility. However, limitations remain due to the complex degradation of cells, strongly influenced by cell design as well operating storage conditions. To overcome them, machine learning framework is developed based on symbolic regression via genetic programming. This evolutionary algorithm...
Abstract This work compares a state of the art data‐driven model to predict health (SoH) in lithium ion batteries with new prediction based on mechanistic framework. The approach attributes degradation individual components such as loss available capacity each electrode well cyclable lithium. By combining framework models for component losses design experiment, we achieve cycle aging that can degradation‐induced changes discharge potential curve. Using this alongside semi‐empirical calendar...