Research on Optimal Adhesion Control of High-Speed Train Based on Extremum Seeking Algorithm

The safe and smooth operation of High-Speed trains depends on the adhesion between the wheels and the tracks. In complex track conditions such as rain and snow, wheel slip frequently occurs, leading to a significant reduction in the adhesion between the wheels and tracks. This reduction in adhesion negatively impacts the train's traction and braking performance, resulting in safety concerns. To fully utilize the maximum adhesion capacity between the wheels and tracks, this paper proposes an optimal adhesion control strategy for High-Speed trains based on extremum seeking algorithm. Firstly, a dynamic model for High-Speed trains is established, and a Full-Dimensional state observer is designed to estimate the adhesion coefficient. Next, an extremum seeking algorithm is employed to find the optimal slip velocity for the current track condition. An equivalent sliding mode torque controller is then designed to achieve closed-loop control of the optimal torque. Finally, a semi-physical real-time simulation platform is built to verify the real-time performance and effectiveness of the proposed method. Experimental results demonstrate that the proposed method can maintain the adhesion coefficient near its maximum value, achieving optimal adhesion control.