129 citations · 224 across the 5 of their papers we have counts for
5 papers
Thermal Neural Networks: Lumped-Parameter Thermal Modeling With State-Space Machine Learning
Wilhelm Kirchgässner, Oliver Wallscheid, Joachim Böcker
With electric power systems becoming more compact and increasingly powerful, the relevance of thermal stress especially during overload operation is expected to increase ceaselessl…
Data Set Description: Identifying the Physics Behind an Electric Motor -- Data-Driven Learning of the Electrical Behavior (Part I)
Sören Hanke, Oliver Wallscheid, Joachim Böcker
Two of the most important aspects of electric vehicles are their efficiency or achievable range. In order to achieve high efficiency and thus a long range, it is essential to avoid…
Data Set Description: Identifying the Physics Behind an Electric Motor -- Data-Driven Learning of the Electrical Behavior (Part II)
Sören Hanke, Oliver Wallscheid, Joachim Böcker
A data set was recorded to evaluate different methods for extracting mathematical models for a three-phase permanent magnet synchronous motor (PMSM) and a two-level IGBT inverter f…
Data-Driven Permanent Magnet Temperature Estimation in Synchronous Motors with Supervised Machine Learning
Wilhelm Kirchgässner, Oliver Wallscheid, Joachim Böcker
Monitoring the magnet temperature in permanent magnet synchronous motors (PMSMs) for automotive applications is a challenging task for several decades now, as signal injection or s…
Data-Driven Recursive Least Squares Estimation for Model Predictive Current Control of Permanent Magnet Synchronous Motors
Anian Brosch, Sören Hanke, Oliver Wallscheid +1
The performance of model predictive controllers (MPC) strongly depends on the model quality. In the field of electric drive control, white-box (WB) modeling approaches derived from…