To study the effect of temperature and humidity on the drying indexes and quality indexes of corn and to optimize the corn drying process, an orthogonal experiment of hot air drying with variable temperature and humidity was designed. The drying process of the actual dryer was simulated by taking the gradient of hot air temperature (x) and the gradient of absolute humidity (y) as the experimental factors. The results showed that the drying indexes (drying time, average drying rate, accumulated temperature) reached optimal values under the drying conditions of cooling and dehumidifying; among them, the optimal value of x was 10 °C (50 °C, 40 °C, and 30 °C), and the optimal value of y was 8 g/m³ (25 g/m³, 17 g/m³, and 9 g/m³). The quality indexes (percentage of damage, fatty acid value, germination rate) reached the optimal values under the drying conditions of heating and humidifying; among them, the optimal value of y for the three quality indicators was 8 g/m³ (9 g/m³, 17 g/m³, and 25 g/m³), but the optimal value of x were different, the optimal value of x were 2.65 °C (39.35 °C, 42 °C, and 44.65 °C), 2.24 °C (39.76 °C, 42 °C, and 44.24 °C) and 6.33 °C (35.67 °C, 42 °C, and 48.33 °C). A genetic algorithm was used to transform the multi-objective function into one index, and the results show that: when x was 2.26°C (39.74°C, 42.00°C, and 44.26°C), y was 4.84 g/m³ (12.16 g/m³, 17.00 g/m³, and 21.84 g/m³), the comprehensive characteristics of the drying process can be optimized.

Exhaust air recycling is a simple and commonly used technique to save energy when using a dryer. The fixed-bed drying test device with increased efficiency by condensation is a clean and energy-saving drying test device developed by combining exhaust air recycling and condensation dehumidification technology. In this paper, through comparisons with or without exhaust air circulation using the single factor test of drying process parameters and the response surface test of corn drying on this test device to investigate the energy-saving effect and drying characteristics resulting from the novel drying method of increased efficiency by condensation. We drew the following main conclusions: (1) increased efficiency drying by condensation resulted in an energy savings of 32–56% compared with the conventional open hot air drying; and (2) during the increased efficiency corn drying by condensation, the mean energy and exergy efficiencies were within 31.65–51.26% and 41.69–63.52%, respectively, when the air temperature was in the 30–55 °C range, and they were 24.96–65.28% and 30.40–84.90%, respectively, when the air passed through the grain layer at 0.2–0.6 m/s; both of these increased with increasing air temperature, and decreased with increasing air velocity. These conclusions may constitute an important reference for investigating the energy-saving drying process of increased efficiency by condensation and developing relevant energy-saving drying equipment.

In agricultural production, numerous nonlinear, time-lagged, and continuously disturbed deterministic processes require effective regulation. This study proposed a window AI control method driven by mechanism and data, which was studied and applied in continuous grain drying process based on the concepts of micro-environment absolute water potential and water potential accumulation. A control system for continuous grain drying was established based on absolute water potential accumulation, and three sets of experiments were conducted: constant temperature drying (water potential accumulation control window, hot air temperatures of three drying sections: 40 °C, 40 °C, 40 °C; relative humidity: 35–40%), increasing temperature drying (water potential accumulation control window, hot air temperatures of three drying sections: 35 °C, 40 °C, 45 °C; relative humidity: 35–40%), and a control experiment (equivalent accumulated temperature control window, hot air temperatures of three drying sections: 40 °C, 40 °C, 40 °C; relative humidity: 35–40%). The results showed that the outlet moisture content ranged from 15.08% to 15.86%, 15.30% to 15.91%, and 15.10% to 15.95%, respectively. The outlet moisture control accuracy ranged from −0.42% to 0.36%, −0.2% to 0.41%, and −0.4% to 0.45%, respectively. Analysis of grain quality indicators (damage percentage, germination percentage, fatty acid value) and microscopic structure revealed the following order: increasing temperature drying > constant temperature drying > control experiment. Compared with the control experiment adopting the equivalent accumulated temperature window control method, the proposed method exhibited higher control accuracy and stability. By integrating coupled temperature and humidity parameters into the variables, the quality of dried grains was effectively guaranteed.

Grain drying is a pivotal post-harvest process that safeguards the storage safety and quality of grain. Conventional drying control strategies, however, predominantly rely on empirical operations and single-parameter monitoring. Although the concept of accumulated temperature has been applied in grain drying, few studies have systematically investigated the dynamic characteristics of drying accumulated temperature windows, resulting in a lack of quantitative and stable control criteria for the drying process. This study first defines the drying accumulated temperature window and further classifies it into three types: the equivalent window, actual window, and good window. On this basis, the window characteristics during continuous grain drying are systematically analyzed, accurate calculation methods for equivalent and actual accumulated temperature are established, and a feasible judgment criterion for the good window is proposed. A MATLAB 2022-based simulation model for continuous corn drying is constructed to verify the proposed methods. Experimental results show that three types of windows exhibit distinct dynamic response characteristics: the equivalent accumulated temperature responds instantaneously to changes in drying conditions, while the actual accumulated temperature has a time lag of one complete drying cycle. After the drying process stabilizes, the absolute difference between equivalent and actual accumulated temperature is controlled within 1500 °C·min. A drying process is identified to enter the good window state when the outlet moisture content stably maintains at 14.5 ± 0.5% for more than 3 h. The established simulation model demonstrates high prediction accuracy, with the mean relative errors of key indicators maintained at approximately 5%. This study clarifies the dynamic mechanism of accumulated temperature windows in continuous grain drying and provides a practical quantitative basis for the intelligent control and efficiency improvement of the grain-drying process.