Testbed 4.0: The cooling system design

Testbed 4.0: The cooling system design

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The Testbed 4.0 project serves as a physical demonstrator of industrial production designed for testing advanced control strategies and algorithms. This paper focuses on the architecture of a cooling cell, one of the production units within the demonstrator. The cooling cell generates and distributes cold via a closed-loop liquid circuit to other units requiring thermal regulation. A mathematical model of the thermal system was developed in MATLAB/Simulink using measured and estimated parameters, including thermal capacities, flow rate, and heat transfer resistances. Several configurations were simulated to assess the impact of pipe insulation and geometry on temperature profiles. Results confirm that proper thermal design significantly improves cooling efficiency and the cooling aggregate is capable to meet thermal requirements of selected cells. The model will be further refined using measured data once the physical system is completed. In future work, the validated model will be integrated into a predictive control framework (MPC) and used to coordinate multiple cooling requests in a decentralized manner via Asset Administration Shell (AAS) interfaces, aligning with Industry 4.0 principles.

The Testbed 4.0 project serves as a physical demonstrator of industrial production designed for testing advanced control strategies and algorithms. This paper focuses on the architecture of a cooling cell, one of the production units within the demonstrator. The cooling cell generates and distributes cold via a closed-loop liquid circuit to other units requiring thermal regulation. A mathematical model of the thermal system was developed in MATLAB/Simulink using measured and estimated parameters, including thermal capacities, flow rate, and heat transfer resistances. Several configurations were simulated to assess the impact of pipe insulation and geometry on temperature profiles. Results confirm that proper thermal design significantly improves cooling efficiency and the cooling aggregate is capable to meet thermal requirements of selected cells. The model will be further refined using measured data once the physical system is completed. In future work, the validated model will be integrated into a predictive control framework (MPC) and used to coordinate multiple cooling requests in a decentralized manner via Asset Administration Shell (AAS) interfaces, aligning with Industry 4.0 principles.

Cooling system | industrial control | modeling | simulation | testbed

Cooling system | industrial control | modeling | simulation | testbed

BLAŽÍK, M.; KANTOR, M.; MICHALKOVÁ, S.; WOJNAROWSKÝ, K.; JANOUŠEK, T.; ARM, J.

2026

01.01.2025

Brno University of Technology

9788021463202

Proceedings II of the Conference Student Eeict

52

55

3