Adaptive Control of Thermoelectric Cooling System with IOT-based Mobile Application

Precise temperature regulation is critical in applications ranging from electronics cooling to medical storage and laboratory systems. Thermoelectric coolers (TECs), operating via the Peltier effect, offer a compact and energy-efficient solution; however, their nonlinear dynamics and susceptibility to external disturbances make stable control challenges. This research presents a novel compact thermoelectric cooling system that not only regulates the cold-side chamber temperature but also actively constrains the hot-side temperature to prevent thermal overload dual-objective control strategy rarely addressed in literature. Uniquely, both temperature setpoints can be configured in real time via a custom mobile application, enabling remote, user-defined thermal management. The system integrates dual DC fans, with a small cold-side fan introducing controlled disturbances to test robustness and a larger hot-side fan for heat dissipation. Continuous feedback from dual temperature sensors is processed using four implemented control strategies—PID, Adaptive PID, Fuzzy Logic, and Fuzzy-Tuned PID, the latter being designed to optimize nonlinear response under varying load conditions. System development follows a V-model methodology, incorporating mathematical modeling, system identification, and both open- and closed loop control design. Experimental results demonstrate that the Fuzzy-Tuned PID consistently maintained cold-side temperature within ±1–2 °C of the setpoint while safeguarding hot-side limits, even under induced disturbances, outperforming conventional controllers in stability and adaptability. This work contributes a flexible, portable, and intelligent TEC-based solution that bridges advanced control theory with embedded hardware and IoT-enabled real-time interaction, offering significant potential for next-generation compact thermal management systems.