2 citations · 5 across the 3 of their papers we have counts for
4 papers
Improved active output selection strategy for noisy environments
Adrian Prochaska, Julien Pillas, Bernard Bäker
The test bench time needed for model-based calibration can be reduced with active learning methods for test design. This paper presents an improved strategy for active output selec…
Robust Data-Driven Error Compensation for a Battery Model
Philipp Gesner, Frank Kirschbaum, Richard Jakobi +1
- This work has been submitted to IFAC for possible publication - Models of traction batteries are an essential tool throughout the development of automotive drivetrains. Surprisin…
Space-Filling Subset Selection for an Electric Battery Model
Philipp Gesner, Christian Gletter, Florian Landenberger +3
Dynamic models of the battery performance are an essential tool throughout the development process of automotive drive trains. The present study introduces a method making a large…
Active Output Selection Strategies for Multiple Learning Regression Models
Adrian Prochaska, Julien Pillas, Bernard Bäker
Active learning shows promise to decrease test bench time for model-based drivability calibration. This paper presents a new strategy for active output selection, which suits the n…