TU Darmstadt / ULB / TUbiblio

Assessing Energy Efficiency Measures for Hydraulic Systems using a Digital Twin

Ioshchikhes, Borys ; Borst, Fabian ; Weigold, Matthias (2022)
Assessing Energy Efficiency Measures for Hydraulic Systems using a Digital Twin.
In: Procedia CIRP, 107
doi: 10.1016/j.procir.2022.05.137
Article, Bibliographie

Abstract

As manufacturing companies around the world face the challenge of reducing CO2 emissions and achieving their climate goals, increasing energy efficiency provides a promising solution while potentially reducing costs. Hydraulic systems are used in a wide range of applications such as heating, ventilation, air conditioning or machine tools and account for approximately 11 % of the electric energy demand in the German industry in 2017. Furthermore, up to 25 million tons of CO2 are emitted annually in Germany as a result of their operation. Against this background, the following paper aims to increase the energy efficiency of hydraulic systems through automated assessment of energy efficiency measures during system operation. Therefore, we present a modular approach for real-time assessing of energy efficiency measures using a digital twin, which contains an expert system combined with real-time simulation models. To detect inefficiencies without time consuming analysis and substantial user expertise, the expert system automatically identifies system leakage and increased flow resistance using a multi-output regression model. Finally, the expert system aims at engaging operators to implement energy efficiency measures by quantifying their respective energy saving potentials. The proposed measures are applied to the virtual representation of a hydraulic system in real-time. Therefore, a Modelica simulation model is developed, which is exported as a functional mock-up unit (FMU) and integrated into a Python framework. If measures lead to an improvement in energy efficiency, these are recommended to the operator. The overall concept is validated using a physical hydraulic system within the ETA Research Factory. The validation of the prototype shows that the developed approach can be applied to industrial applications and help in reducing their energy consumption.

Item Type: Article
Erschienen: 2022
Creators: Ioshchikhes, Borys ; Borst, Fabian ; Weigold, Matthias
Type of entry: Bibliographie
Title: Assessing Energy Efficiency Measures for Hydraulic Systems using a Digital Twin
Language: English
Date: 2022
Publisher: Elsevier B.V.
Journal or Publication Title: Procedia CIRP
Volume of the journal: 107
DOI: 10.1016/j.procir.2022.05.137
Abstract:

As manufacturing companies around the world face the challenge of reducing CO2 emissions and achieving their climate goals, increasing energy efficiency provides a promising solution while potentially reducing costs. Hydraulic systems are used in a wide range of applications such as heating, ventilation, air conditioning or machine tools and account for approximately 11 % of the electric energy demand in the German industry in 2017. Furthermore, up to 25 million tons of CO2 are emitted annually in Germany as a result of their operation. Against this background, the following paper aims to increase the energy efficiency of hydraulic systems through automated assessment of energy efficiency measures during system operation. Therefore, we present a modular approach for real-time assessing of energy efficiency measures using a digital twin, which contains an expert system combined with real-time simulation models. To detect inefficiencies without time consuming analysis and substantial user expertise, the expert system automatically identifies system leakage and increased flow resistance using a multi-output regression model. Finally, the expert system aims at engaging operators to implement energy efficiency measures by quantifying their respective energy saving potentials. The proposed measures are applied to the virtual representation of a hydraulic system in real-time. Therefore, a Modelica simulation model is developed, which is exported as a functional mock-up unit (FMU) and integrated into a Python framework. If measures lead to an improvement in energy efficiency, these are recommended to the operator. The overall concept is validated using a physical hydraulic system within the ETA Research Factory. The validation of the prototype shows that the developed approach can be applied to industrial applications and help in reducing their energy consumption.

Uncontrolled Keywords: expert system, machine learning, predicitve efficiency, real-time simulation, ETA im Bestand
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW)
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > ETA Energy Technologies and Applications in Production
Date Deposited: 09 Jun 2022 05:08
Last Modified: 03 May 2023 07:03
PPN: 495452912
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details