Research On Optimization Of ATO Curve Based On Improved Firefly Algorithm

Automatic Train Operation(ATO)is an important part of the intelligent development of Chinese high-speed railways.It can greatly reduce the drivers’ workload decreasing their fatigue;improve the punctuality rate of railway transportation and save the consumption of power resources.ATO on-board equipment is the key equipment for generating ATO operating curves which mainly rely on the on-board equipment to solve the multi-objective optimization equations.In Chinese high-speed railway ATO system,the on-board ATO module is set based on the Automatic Train Protection(ATP).This study obtains multi-objective optimization equations by establishing train kinematics models and analyzes different operating scenarios under the condition of the Chinese Train Control System 3(CTCS-3).Firefly Algorithm(FA)is used to solve the multi-objective equations so as to solve the general problems of ATO operating curves.The main research contents are as follows:Firstly,the structures of CTCS-3 and CTCS-2 as well as ATO system to understand the working principle of the main equipment are analyzed;uses the homogeneous rod model to establish the train dynamics model to analyze the movement state of the train;establishes the working condition conversion relationship and gets the multi-objective optimization equation through the corresponding relationship.Derived according to the established model,the traction calculation formula is used to calculate the energy consumption,running time and others related parameters.Secondly,the operating scenarios of CTCS-3+ATO and CTCS-2+ATO are analyzed and summarized.Introduces the corresponding technical indicators and driving strategies in each scenario,summarizes each scenario,performs nesting processing and considers the general problems of subsequent ATO multi-objective optimization curves.Thirdly,the basic principles of FA are introduced,its advantages and disadvantages are analyzed.Then it improves FA according to actual problems and verifies the optimized performance of the improved FA.The improved FA is compared and analyzed with other excellent algorithms to get an algorithm that is more suitable for this topic.A layered ATO operating curve optimization algorithm is design and the bottom-level algorithm is used to optimize the running time and running energy consumption of the train.On this basis,the top-level algorithm is used to optimize the operating comfort of the train to obtain a train target speed curve that meets actual operating requirements.At the same time,because the target speed curve needs to be adjusted in real time,the concept of time window is introduced so that the current operating conditions can be adjusted in real time during train operation to achieve the optimal target speed curve.Finally,it verifies the multi-objective optimization curves under different simulate operating scenarios.Conclusions can be drawn by comparing the parameters such as running time and running energy consumption in different scenarios.Then,it verifies the effectiveness of the improved FA and solves the general problems of ATO in high-speed railway,laying a theoretical and simulation basis for follow-up ATO research.