Research On Optimal Adhesion Control Strategy Of Extremum Seeking Without Steady-state Oscillation

The traction performance of trains depends on the adhesion between wheel and rail.Under the influence of complex rail conditions such as rain and snow,wheel idling occurs frequently,and the adhesion between wheel and rail decreases sharply,thus affecting the traction force.In order to give full play to the maximum adhesion between wheel and rail and ensure the efficient and stable output of train traction,it is of great significance to study the suitable trains adhesion control method for the safe and stable operation of trains.This thesis designs an optimal adhesion strategy model based on extremum seeking algorithm without steady-state oscillation to keep the train running stably near the adhesion peak point and improve the overall traction performance of the train.The wheel-rail adhesion process is complex,with strong nonlinearity and randomness.The test of adhesion control system on real vehicles is very difficult.Each real vehicle debugging requires a lot of manpower and material resources causing the high cost.This thesis builds a Hardware-in-the-loop simulation platform which shortens the debugging cycle of the adhesion control system and verifies the real-time and effectiveness of the proposed optimal adhesion control strategy.Firstly,in order to make the train make full use of the wheel-rail adhesion ability and run stably at the adhesion peak point,the sliding mode extremum-seeking algorithm is used to search the optimal creep speed corresponding to the adhesion peak point.By analyzing the parameters of the algorithm,it is clear that there exits contradiction between the steady-state oscillation and the convergence rate of the algorithm.An extremum-seeking algorithm without steady-state oscillation is used to search the optimal creep speed of the current rail surface.The algorithm avoids the steady-state oscillation fundamentally and has a good convergence rate.Optimal adhesion control based on sliding mode extremum-seeking algorithm and extremum-seeking algorithm without steady-state oscillation is established respectively to simulate steady-state oscillation and convergence rate.Secondly,in order to improve the anti-interference capability of optimal adhesion control,an equivalent sliding mode torque controller is designed based on sliding mode control theory.Aiming at the disadvantage of steady-state oscillation in the equivalent sliding mode torque controller,a hyperbolic tangent function is used to replace the symbol function.an equivalent sliding mode torque controller based on hyperbolic tangent function is designed which can stably search the optimal torque of the current rail in real time with strong anti-interference capability.The optimal adhesion control based on hyperbolic tangent function equivalent sliding mode torque controller is established to analyze the anti-interference capability of traction torque for different interference signals.Finally,building a HIL simulation platform for adhesion control.Combined with extremum-seeking algorithm without steady-state oscillation and the equivalent sliding mode torque controller based on hyperbolic tangent function,the optimal adhesion control model is established.The re-adhesion control model based on the combined correction control algorithm is established.Considering different loads and interference signals,the two adhesion control strategies are simulated and analyzed.The simulation results show that compared with the re-adhesion control strategy,the extremum-seeking algorithm without steady-state oscillation proposed in this thesis make full use of the adhesion between wheel and rail,keeps the train running near the maximum adhesion peak point of the current rail surface,and improve the average traction torque,average adhesion utilization rate and traction force of the train.