Temperature-Based Fan Speed Optimization Strategy

Abstract

As energy efficiency and indoor comfort increasingly become key standards in modern residential and office environments, research on intelligent fan speed control systems has become particularly important. This study aims to develop a temperature-feedback-based fan speed optimization strategy to achieve higher energy efficiency and user comfort. Firstly, by analyzing existing fan speed control technologies, their main limitations are identified, such as the inability to achieve smooth speed transitions. To address this issue, a BP-PID speed control algorithm is designed, which dynamically adjusts fan speed based on indoor temperature changes. Experimental validation demonstrates that the designed system can achieve smooth speed transitions compared to traditional fan systems while maintaining stable indoor temperatures. Furthermore, the real-time responsiveness of the system is crucial for enhancing user comfort. Our research not only demonstrates the feasibility of temperature-based fan speed optimization strategies in both theory and practice but also provides valuable insights for energy management in future smart home environments. Ultimately, this research outcome will facilitate the development of smart home systems and have a positive impact on environmental sustainability.