Technology, energy, agriculture transport AIC

Vladimir DIDUR – Doctor of Technical Sciences, Professor, Head of the Department of Agricultural Engineering, Uman National University (Instytutska St., 1, Uman, 20301, Ukraine). e-mail: didur.vv@gmail.com. https://orcid.org/0000-0001-7584-5073).
Irina LEONTIUK – Candidate of Agricultural Sciences, Associate Professor of the Department of Biology, Uman National University (Instytutska St., 1, Uman, 20301, Ukraine). е-mail: irinaleontyuk0@gmail.com. https://orcid.org/0000-0001-5458-1048).
Yaroslav BILOKIN – Postgraduate Student, Poltava State Agrarian University (1/3 Skovorydy St., Poltava, 36003, Ukraine), е-mail: yaroslav.v.bilokin@pdaa.ua. https://orcid.org/0009-0003-4510-2780).
Ievgenii PETRYCHENKO – Uman National University of Horticulture, Department of Agroengineering, (Institutska St., 1, 20300 Uman, Ukraine), е-mail: 22102210g@ukr.net  https://orcid.org/0000-0003-1037-077X).

The results of studies of the effect of preliminary extrusion preparation of castor seeds on the parameters of the pressing process and the quality of the obtained oil are presented. Based on the analysis of thermophysical processes, a five-zone model of extruder temperature regimes is proposed, taking into account heat exchange, mass exchange and individual characteristics of raw materials, an observer model is derived for estimating the output of the target product 
Based on the regression model, the change in pressure in the pre-matrix zone of a single-screw extruder is described, depending on the moisture content of the raw material, the rotation frequency of the screw, and the diameter of the forming channel of the matrix. The experimental dependences of the product temperature on the drive power and productivity for different humidity are summarized, and the interpretation of the response surfaces obtained is presented. 
The proposed combined model apparatus allows overcoming the limitations of existing control systems, in addition, the observer model provides the possibility of implementing adaptive control algorithms, as well as the optimization of extrusion parameters allows to increase oil output by 12-15% and improve its quality characteristics.
The obtained results provide a scientific basis for the development of intelligent control systems for extrusion–pressing processes of castor oil production, oriented toward variable raw material properties and energy constraints of equipment. The proposed approach integrates physically grounded thermophysical models with empirical regression dependencies, enabling real-time prediction of technological parameters and formation of control actions based on the criterion of maximizing oil yield while preserving its quality characteristics. The practical value of the study lies in the possibility of using the developed modeling framework in the design and modernization of press–extruders for oilseed processing, as well as in the implementation of adaptive control algorithms that ensure improved energy efficiency of the process and stability of product parameters under conditions of varying moisture content and fractional composition of seeds.

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