Research On Optimization Of Electric Pneumatic Braking On ATO Trains

In recent years,under the improvement of urbanization level and the growth of urban population,urban rail transit system has developed rapidly.It becomes one of the mainstream modes of transportation for the short-distance travel.At the same time,the increasing transportation demand also puts forward higher requirements for urban rail transit.At present,the automatic operation control system of urban rail trains is still mainly based on PID controller.Problems that the control object model is not accurate enough and the parameters cannot be adjusted in real time have not been overcome.It is time-consuming and labor-consuming to manually adjust parameters before the line operation,and it is impossible to adjust parameters in real time according to different external conditions such as weather and environment during the trains’ running.As a result,the control performance of ATO system may not satisfy the requirements.Therefore,it is significant to research the adaptive adjustment methods of PID parameters.According to the above problems,our paper summarizes the existing PID parameters tuning method,then proposes a new real-time self-tuning scheme of PID controller parameters.Firstly,in order to optimize the parking accuracy of the train,a more accurate train dynamics model considering electric-pneumatic hybrid braking is proposed according to the actual operation of the train.The model is divided into six train running stages: the coasting stage,the traction establishment stage,the re-traction stage,the traction removal stage,the electric braking stage,and the parking brake stage.The parameters of each stage can be fitted out according to the actual data.Then,according to the requirements of PID parameters and the established refined model,this paper proposes an improved Fruit Fly Optimization Algorithm.The algorithm is improved from search step,population partition and penalty mechanism.Compared with other algorithms,this algorithm has obvious advantages in running time,optimization accuracy and stability.Therefore,based on the data of Yizhuang line in Beijing subway,our paper selects this algorithm to identify the parameters of train dynamics model and PID controller.Finally,a parameters calculation software is designed in the paper according to the above model and algorithm.The software has the function of calculating parameters of train dynamics model and PID controller,and provides users with a good software interface.Simulations are carried with the real data of different weather and line environments of Yizhuang Line in Beijing subway.Through the simulation results we obtain the influence of changes in external conditions on the parameters of the PID controller,verify that the model is consistent with the actual train running process,and prove the algorithm have a good real-time performance,stability,adaptability and parking accuracy.The results further show that the method proposed in our paper is valuable for the research of the train dynamics model and the adjustment of PID parameters.There are 54 figures,12 tables and 45 references in the paper.