Experimental Validation and Advanced Intelligent Control of a Solar-Driven Thermoelectric Cooling System MATLAB/Simulink Modeling, and Simulation

The accelerating global shift toward sustainable, energy-efficient technologies has underscored the need for innovative solutions that integrate renewable energy sources with advanced intelligent control. Solar photovoltaic (PV) technology, as a mature and decentralized power generation option, offers significant potential when coupled with thermoelectric cooling systems based on Peltier modules compact, solid-state, and environmentally benign alternatives to conventional vapor-compression refrigeration.This study addresses critical gaps in literature by developing and experimentally validating a solar-driven thermoelectric cooling system, rigorously modeled and simulated in MATLAB/Simulink.A novel feature of the proposed framework is the integration of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to accurately model and regulate the thermal behavior of TEC1-12706 Peltier modules under dynamic solar irradiance conditions, leveraging both experimental data and manufacturer specifications. To further enhance transient performance and stability, two advanced control strategies classical Proportional Integral Derivative (PID) and hybrid Fuzzy–PID (FPID) are systematically designed, tuned, and benchmarked against each other.Distinguished by its foundation in comprehensive experimental characterization, this work delivers a validated, high-fidelity simulation platform that reduces reliance on iterative physical prototyping. Quantitative results demonstrate the superior efficacy of the FPID controller, achieving a 25% reduction in overshot, an 18% improvement in rise time, and a 22% decrease in steady-state error, alongside a more than 20% increase in coefficient of performance (COP), relative to the PID baseline under identical test conditions.By demonstrating both technical rigor and industrial relevance, this framework offers a scalable and cost-effective pathway toward sustainable, off-grid refrigeration solutions, directly supporting UN Sustainable Development Goals related to energy efficiency and climate action. The validated model provides a robust reference for researchers and practitioners in renewable energy integration, intelligent thermal management, and embedded control, paving the way for further advancements in smart, green cooling technologies.