Dynamics model for the thermal performance from a lyophilization process, based on a complete transfer functions matrix
DOI:
https://doi.org/10.37636/recit.v32120135Keywords:
Transfer functions matrix, Thermal performance, Lyophilization process.Abstract
During the beginning of the XX century lyophilization was developed as an alternative technology to extend the storage time for fruit and vegetables or other kind of food; however, the energetic consumption of this technology makes it not an option for common food producers, less over for those one that work by the open field cultivation technique. The main energy consumption in a lyophilization systems are the motors from the vacuum pump and from the refrigerant compressors; due to the temperature range needs the lyophilization systems use to have more than one cooling thermodynamic system based on vapor compression. This paper describes an experimental methodology to get a complete state transfer functions matrix, based on the graphical analysis of the concerned transfer functions magnitude spectra. This experimental data came from a set of test performed at the National Laboratory for Cooling Technology Research (LaNITeF) at the Engineering Center for Industrial Development (CIDESI). The intention of this transfer functions matrix is to be applied in a control strategy to then optimize the energetic performance of the concerned lyophilization system. This function transfer matrix is considered complete because there is not a dynamic order reduction considering its degrees of freedom. The transfer functions matrix describes the dynamic relationship between both the inputs variables that describe the energetic consumption of the lyophilization system, and the ambient conditions, as well as the output variables that represent the dynamical states vector with the variables of interest from the concerned process. The simulation from an experimental scenario worked as the graphical validation of the transfer functions matrix characterized experimentally, so the main conclusion of this scientific work is that this transfer functions matrix can be used as dynamic model to implement control and optimization algorithms.
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Copyright (c) 2020 María Elizabeth Rodríguez Ibarra, Eloy Edmundo Rodríguez Vázquez, Ana Marell Arteaga Martínez, Samantha Lilia Narváez Granados, Helen Janeth Zúñiga Osorio, Víctor Miguel Villasana-Velázquez
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