关注
Phillip Stoffel
Phillip Stoffel
RWTH Aachen University, E.ON Energy Research Center
在 eonerc.rwth-aachen.de 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Evaluation of advanced control strategies for building energy systems
P Stoffel, L Maier, A Kümpel, T Schreiber, D Müller
Energy and Buildings 280, 112709, 2023
382023
Real-time modeling of a 48V P0 mild hybrid vehicle with electric compressor for model predictive control
P Griefnow, J Andert, F Xia, S Klein, P Stoffel, M Engels, D Jolovic
SAE Technical Paper, 2019
192019
Safe operation of online learning data driven model predictive control of building energy systems
P Stoffel, P Henkel, M Rätz, A Kümpel, D Müller
Energy and AI 14, 100296, 2023
132023
Development of a long-term operational optimization model for a building energy system supplied by a geothermal field
A Kümpel, P Stoffel, D Müller
Journal of Thermal Science 31 (5), 1293-1301, 2022
92022
Cloud-based optimal control of individual borehole heat exchangers in a geothermal field
P Stoffel, A Kümpel, D Müller
Journal of thermal science 31 (5), 1253-1265, 2022
72022
Real-life data-driven model predictive control for building energy systems comparing different machine learning models
P Stoffel, M Berktold, D Müller
Energy and Buildings 305, 113895, 2024
62024
Combining data-driven and physics-based process models for hybrid model predictive control of building energy systems
P Stoffel, C Löffler, S Eser, A Kümpel, D Müller
2022 30th Mediterranean Conference on Control and Automation (MED), 121-126, 2022
42022
Self-adjusting model predictive control for modular subsystems in HVAC systems
A Kümpel, P Stoffel, D Müller
Journal of Physics: Conference Series 2042 (1), 012037, 2021
42021
From plans to programs: A holistic toolchain for building data applications
G Bode, F Stinner, M Baranski, E Brümmendorf, X Cai, A Kümpel, ...
Journal of Physics: Conference Series 1343 (1), 012117, 2019
32019
Identifying the validity domain of machine learning models in building energy systems
M Rätz, P Henkel, P Stoffel, R Streblow, D Müller
Energy and AI, 100324, 2023
22023
Evaluation of linear and nonlinear system models in hierarchical model predictive control of HVAC systems
S Eser, P Stoffel, A Kumpel, D Muller
Journal of Physics: Conference Series 2042 (1), 012032, 2021
22021
Distributed model predictive control of a nonlinear building energy system using consensus ADMM
S Eser, P Stoffel, A Kümpel, D Müller
2022 30th Mediterranean Conference on Control and Automation (MED), 902-907, 2022
12022
Comparative study of neural network based and white box model predictive control for a room temperature control application
P Stoffel, M Berktold, A Gall, A Kiimpel, D Muller
Journal of Physics: Conference Series 2042 (1), 012043, 2021
12021
Comparison of simulation tools for optimizing borehole heat exchanger field operation
E Heim, P Stoffel, S Düber, D Knapp, A Kümpel, D Müller, N Klitzsch
Geothermal Energy 12 (1), 24, 2024
2024
Interpretable data-driven model predictive control of building energy systems using SHAP
P Henkel, T Kasperski, P Stoffel, D Müller
6th Annual Learning for Dynamics & Control Conference, 222-234, 2024
2024
A Modular Python Framework for Rapid Development of Advanced Control Algorithms for Energy Systems
S Eser, T Storek, F Wüllhorst, S Dähling, J Gall, P Stoffel, D Müller
Available at SSRN 4884846, 2024
2024
Toward Trustworthy Machine Learning Models for Fault Detection in Energy Systems
M Rätz, P Henkel, P Stoffel, R Streblow, D Müller
Proceedings of the 10th ACM International Conference on Systems for Energy …, 2023
2023
Distributed model predictive control of building energy systems coupled to geothermal fields
M Baranski, P Stoffel, A Kümpel, M Stiller, T Storek, M Schumacher, ...
Journal of Physics: Conference Series 1343 (1), 012074, 2019
2019
Practical Design and Implementation of Iot-Based Occupancy Monitoring Systems for Office Buildings: A Case Study
P Fatehi Karjou, S Khodadad Saryazdi, P Stoffel, D Müller
Sina and Stoffel, Phillip and Müller, Dirk, Practical Design and …, 0
系统目前无法执行此操作,请稍后再试。
文章 1–19