A Study on Dynamic Adjustment of Radiator Fan in Automotive Cooling System Based on Fuzzy Algorithm

This work explores the application of fuzzy theory to shorten the development timeline and enhance the flexibility of fan speed control logic for automotive radiators, using vehicle speed and engine temperature as input variables. With the variability of vehicle operating conditions, traditional fan speed control methods often require consideration of multiple parameters such as air conditioning pressure, the amount and temperature of coolant, engine rotational temperature, and various driving conditions, leading to extended development times for fan controllers. To address this, we adopted a fuzzy logic controller (FLC) to design a novel fan speed regulation mechanism that dynamically adjusts fan speed based on real-time changes in vehicle speed and engine temperature. Our research method includes establishing a fuzzy control system model, defining the fuzzy sets for input and output variables, and their corresponding fuzzy rules. Through simulation testing, we evaluated the performance of the fuzzy control strategy under different operating conditions. The results indicate that compared to traditional control methods, the fuzzy control approach provides greater flexibility in fan speed development, thereby ensuring that the engine temperature remains within an ideal range. This study demonstrates the potential of fuzzy theory in controlling complex systems and provides a new approach to enhancing the flexibility of fan development and optimizing vehicle cooling systems. Future work will explore input variables and control strategies to improve system performance and adaptability.