Experimental Validation of a Dynamic Adsorption Chiller Model Using Optimal Experimental Design
| Autor: | Postweiler, Patrik, Gibelhaus, Andrej, Engelpracht, Mirko, Seiler, Jan Michael, Bardow, André |
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| Přispěvatelé: | Meyer, Thomas, Corrales, José, Graf, Rupert, Hüls, Walther, Kühn, Roland, Ziegler, Felix |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Zdroj: | ISHPC 2021 Proceedings: Online Pre-Conference 2020 Berlin : Technische Universität Berlin 28-32 (2020). doi:10.18154/RWTH-2020-09121 ISHPC 2021 proceedings – online pre-conference 2020 : August 17th, 2020, Technische Universität Berlin, Campus Charlottenburg / editor: Thomas Meyer, co-editors: José Corrales, Rupert Graf, Walther Hüls, Roland Kühn, Felix Ziegler ISHPC 2021 proceedings – online pre-conference 2020 : August 17th, 2020, Technische Universität Berlin, Campus Charlottenburg / editor: Thomas Meyer, co-editors: José Corrales, Rupert Graf, Walther Hüls, Roland Kühn, Felix ZieglerInternational Sorption Heat Pump Conference 2021 : online pre-conference, ISHPC 2021, online, 2020-08-17-2020-08-17 |
| DOI: | 10.18154/rwth-2020-09121 |
| Popis: | A potential way to reduce the global greenhouse gas emissions for cooling and heating are thermally-driven cooling and heating technologies, such as sorption chillers. However, sorption chillers often suffer from high electricity consumption due to sub-optimal system integration. To optimize system integration, model-based approaches are very promising, but require valid models. For efficient model validation, we present a method based on the Optimal Experimental Design (OED) and apply the method to a dynamic adsorption chiller model. For this purpose, we plan an experiment with OED, execute it and estimate the unknown model parameters. To improve parameter accuracy and thus a valid model, we repeat the procedure iteratively. The results show that the presented method leads to a valid adsorption chiller model with only three optimally planned experiments. Furthermore, we show that the experimental effort decreases by up to 83 % compared to randomly planned experiments. ISHPC 2021 Proceedings: Online Pre-Conference 2020 |
| Databáze: | OpenAIRE |
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