Backyard agricultural systems are frequently used for food production in rural tropical regions all over the world. The implementation of these systems has been used as a strategy to increase food security, to preserve the phyto and zoo diversity and to provide an alternative income for poorer rural families. Nevertheless, the absence of appropriate preservation mechanisms and nonrenewable energies can lead to significant production losses that could be prevented by the implementation of solar drying devices. The objective of this project was to design, build and validate a double collector solar device for improved drying performance. To evaluate the double collector solar device, four backyard products frequently used in the Mexico Southwest regional diet were used: carrots, chayote squash, tomatoes, and oyster mushrooms. The results showed that the solar device achieved drying efficiencies between 22.8 and 37.9% by reaching moisture values below the 12.30% threshold, which according to the international standards is considered as “Low Moisture Food”. The evaluation of the double collector solar drier is demonstrated to be an easy-to-apply and environmentally friendly method for food preservation in tropical rural regions by taking advantage of domestic renewable energy resources.

The analysis of the behavior of lithium-ion batteries has gained considerable interest in recent years. There are different alternatives for the analysis of this behavior; however, depending on the type of modeling, there are application and optimization restrictions. In this work, a hybrid model has been made that is capable of predicting the characteristics of a lithium-ion battery. As a novelty, the simplification, at the same time, facilitates the sampling of parameters for their prompt selection for optimization. A new model open to the user is proposed, which has proven to be efficient in simulation time. For example, one hour simulates it in 5 min, providing information detailing how these parameters, State of Health (SOH), Open Circuit Voltage (VOC), State of charge (SOC), and Number of charge and discharge cycles, in the face of temperature variations and charge and discharge cycles. Opening the possibility of optimizing the parameters with different techniques to estimate the performance and dynamics in the face of temperature change and charge and discharge cycles. A model based on linear regressions, manufacturer characteristics, and integrating equations in the electrical model of electrochemical phenomena is proposed.