Experimental Study and Flow Prediction of Solenoid Valve Performance Under the Coupled Temperature Field

Solenoid valves are crucial in fluid control systems, and temperature variations have a significant impact on their performance under extreme operating conditions. This study explores the role of coupled thermal effect on the performance of solenoid valves with the help of systematic experiments and machine learning modeling, and develops a neural network framework to predict its actual output flow rate under coupled thermal conditions, which provides support for the evaluation and optimization of solenoid valves' performance under complex thermal operating conditions.