Research On Parameter Adjustment Based On ATO Automatic Speed Control Operating Curve Feature Extraction

With the advantages of large capacity,punctuality,speed and low cost,urban rail transit has become the primary choice for people traveling in large and medium-sized cities in China.The increasing demand for travel has led to an increase in the intensity of driving,and the increase in line density cannot be supported by manual driving alone,so the research of automatic train driving system(ATO)has become a boom.Speed automatic control is the core function of ATO.This module calculates the target train speed based on the train speed,train position and operation line information,and realizes the train speed control according to the target speed.The speed automatic control process has problems such as nonlinearity and hysteresis,and the existing automatic speed control algorithm will solve these problems by configuring the vehicle control parameters.As the train runs for a long time,the normal loss of the train’s own performance will cause the problem of mismatch between the configuration parameters and the actual performance of the train,thus affecting the accuracy of the system control.Due to the large amount of train operation data,if we only rely on manual extraction of operation data features,it is not only labor-intensive,but also has the problems of small sample data volume and large randomness of sample selection,which reduces the accuracy of train control parameter adjustment.Therefore,automatic extraction of parameters from a large amount of train operation data and automatic adjustment of algorithm control parameters according to actual train performance is of great significance to improve the accuracy of automatic speed control algorithm.In this thesis,we design a feature extraction algorithm for the above problem,firstly,we analyze the train operation state transition process,and extract the traction control delay and braking control delay during the train state transition process;then we propose a braking deceleration calculation method,analyze and calibrate the error of the running resistance that affects the calculation of train braking force in the train performance parameters,and remove the acceleration generated by the train running resistance from the train combined acceleration to get the accurate train braking deceleration.Then,an accurate train braking deceleration is obtained.Finally,the traction control parameters,braking control parameters,target acceleration calculation parameters and precise stopping process parameters are adjusted according to the different operating conditions and operation stages of the train,combined with the meaning of the control parameters in the automatic speed control algorithm,so that the adjusted control parameters are more suitable for the actual train performance and improve the train control accuracy.In order to verify the accuracy of the feature extraction results and the effectiveness of the parameter adjustment results,the vehicle performance parameters are extracted using manual and parameter extraction software to obtain the manually adjusted and softwareadjusted configuration parameters,and the operation process of the same train under different configuration parameters is simulated through the laboratory simulation environment,and the comparison of the simulation operation data reveals that the vehicle control parameters adjusted by using the software-extracted feature results are close to those adjusted by manually extracted feature results.Therefore,the software can realize the automation of parameter extraction and adjustment,and effectively improve the precision of the automatic train control system.