Rapid Thermal Energy Modeling and Analysis of Complex Industrial Hydraulic Systems

Modeling and analyzing the thermal energy behavior of industrial hydraulic systems with useful hydraulic power of 20 kW or higher is a challenging task due to the system’s inherent complexity and the multitude of interacting components. Conventional thermal modeling approaches rely heavily on numerous interdependent parameters and sensor measurements, including temperature, pressure, and flow rate for each port in hydraulic component. This reliance often leads to prolonged modeling times, which can exceed the actual operational time of the hydraulic system by a factor of 2 to 6.5, resulting in costly and time-intensive analysis. To address these limitations and meet industrial demands, this study introduces an enhanced thermal model based on a new temperature parameter, termed the average transient temperature (Tavg), aimed at significantly reducing the modeling time to be shorter than the experimental operation time. Furthermore, Physics informed neural network model is used to determine hydraulic oil specifications during the modeling implementation as one correlation model.

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Publication Details

Journal
International Journal of Fluid Power
Published
2025-04-06
DOI
https://doi.org/10.13052/ijfp1439-9776.2614
Primary Topic
Hydraulic and Pneumatic Systems
Type
article
Field-Weighted Citation Impact
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article

Rapid Thermal Energy Modeling and Analysis of Complex Industrial Hydraulic Systems

Ahmad Al-Issa, Jürgen Weber, Tobias Schulze
International Journal of Fluid Power
Hydraulic and Pneumatic Systems
article

Rapid Thermal Energy Modeling and Analysis of Complex Industrial Hydraulic Systems

Ahmad Al-Issa, Jürgen Weber, Tobias Schulze
article en

Abstract

Modeling and analyzing the thermal energy behavior of industrial hydraulic systems with useful hydraulic power of 20 kW or higher is a challenging task due to the system’s inherent complexity and the multitude of interacting components. Conventional thermal modeling approaches rely heavily on numerous interdependent parameters and sensor measurements, including temperature, pressure, and flow rate for each port in hydraulic component. This reliance often leads to prolonged modeling times, which can exceed the actual operational time of the hydraulic system by a factor of 2 to 6.5, resulting in costly and time-intensive analysis. To address these limitations and meet industrial demands, this study introduces an enhanced thermal model based on a new temperature parameter, termed the average transient temperature (Tavg), aimed at significantly reducing the modeling time to be shorter than the experimental operation time. Furthermore, Physics informed neural network model is used to determine hydraulic oil specifications during the modeling implementation as one correlation model.

International Journal of Fluid Power
Center for Systems Biology Dresden (DE)
Openalex Percentile: Top 92%
Hydraulic and Pneumatic Systems
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