Flow force analysis and optimization of lock valve for heavy-duty automatic transmission

Abstract

One of the main factors determining the stability of lock valve during opening is the flow force on spool. The size of the flow force profoundly affects the dynamic characteristics of the spool. In this paper, the flow force on a heavy-duty automatic transmission lock valve during the opening process is analyzed and optimized, and aiming to improve the opening smoothness of the lock valve. First, numerical simulation of the opening process of the main oil chamber flow path in the lock valve is carried out using dynamic mesh technology. The influence of internal flow field on the flow force under different parameters is studied. Second, the structural parameters and peaks of flow force obtained from the random sampling method are used as samples for training and prediction using the BP neural network. The prediction results pass the accuracy test. Last, the prediction results of the BP neural network are optimized using the genetic algorithm. Subsequent results show that this optimization method significantly reduces the flow force of spool and improves stability of the lock valve during opening by only changing the structural parameters. It also provides a new systematic direction for the optimization of other nonlinear mapping relationships.