Thomas Kröger

发表

Impedance detection of the electrical resistivity of the wound tissue around deep brain stimulation electrodes permits registration of the encapsulation process in a rat model

Jan Gimsa, Kathrin Badstübner, Eilhard Mix, 2017 .

A New Class of Highly-Miniaturized Reconfigurable UWB Filters for Multi-Band Multi-Standard Transceiver Architectures

Michael Höft, Thomas Kröger, Mohamed Kheir, 2017, IEEE Access.

Quantifying the state of the art of electric powertrains in battery electric vehicles: Range, efficiency, and lifetime from component to system level of the Volkswagen ID.3

Alexander W. Koch, M. Lienkamp, Olaf Teichert, 2022, eTransportation.

Experimental analysis of lithium-ion cell procurement: Quality differences, correlations, and importance of cell characterization

M. Lienkamp, Manuel Ank, Thomas Kröger, 2023, Journal of Energy Storage.

Increasing the efficiency of li-ion battery cycle life testing with a partial-machine learning based end of life prediction

Thomas Kröger, Markus Schreiber, Thomas Kröger, 2023, Journal of Energy Storage.

Collaborative training of deep neural networks for the lithium-ion battery aging prediction with federated learning

Thomas Kröger, Markus Lienkamp, Annalena Belnarsch, 2023, eTransportation.

Electrical Impedance Properties of Deep Brain Stimulation Electrodes during Long-Term In-Vivo Stimulation in the Parkinson Model of the Rat

Jan Gimsa, Ulrike Gimsa, Reiner Benecke, 2012, BIOSTEC.

Characterization of the Encapsulation Process of Deep Brain Stimulation Electrodes using Impedance Spectroscopy in a Rodent Model

Jan Gimsa, Reiner Benecke, Eilhard Mix, 2012, BIOSIGNALS.

Incoming Inspection of Lithium‐Ion Batteries Based on Multi‐cell Testing

Manuel Ank, Thomas Kröger, Alessandro Sommer, 2024, Energy Technology.

Comparing experimental designs for parameterizing semi-empirical and deep learning-based lithium-ion battery aging models

Kareem Abo Gamra, Thomas Kröger, Sven Maisel, 2025, Journal of Energy Storage.