Research On Dynamic Requirement-driven Multi-objective Optimal Configuration Design Technology Of Bogie

In 2017,China’s third-generation Fuxing series EMUs was put into operation.It is one of the important representatives of the world’s most advanced high-speed train technology,which means that China’s high-speed train technology has entered a new stage.High-speed train is a customized complex product,which has accumulated a lot of design knowledge.Configuration design can reuse design knowledge,which is one of the mainstream design methods of high-speed train.Bogie is one of the core technologies of high-speed train and the focus of design.At present,the uncertainty of requirement is less considered in the research of configuration design,which can’t better adapt to the dynamic requirement.Meanwhile,most of the optimization objectives of the current configuration design are cost or matching,which is relatively one-sided.Based on this,this thesis studies the configuration method of highspeed train bogies.The main contents are as follows:(1)This thesis analyzes the significance of considering uncertain requirement in the current high-speed train bogie configuration design,and on this basis,analyzes the shortcomings of the traditional bogie configuration design.Then it analyzes the requirement characteristics and structural characteristics of the bogie,and puts forward the research framework and technical route of the full text configuration design.(2)The analysis method of uncertainty requirement of high-speed train bogie is studied.Firstly,the source of uncertainty in the requirement for high-speed train bogies is analyzed.Then the requirement data is obtained from the bidding documents and literature,and the weight of requirement is analyzed by combining subjective and objective methods.The fault Bayesian network analysis operation and maintenance data is obtained.Finally,the subjective and objective weights are combined to obtain the comprehensive weights of the requirement to support the configuration solution process.(3)The modeling method of bogie configuration adapting to dynamic requirement is studied.Firstly,the framework of the configuration model is determined,divided into the base configuration model and the instance multidimensional evaluation model.Then the relationship between configuration components is established through the base configuration model to accommodate the dynamic problems caused by requirement uncertainty.Finally,the multi-dimensional evaluation model of the instance is used to quantify the satisfaction,environmental protection,and economic performance of the instance,so as to support the quick comparison of the configuration scheme when the configuration is solved.(4)The configuration solution method of multi-objective combinatorial optimization is studied.In this thesis,the configuration process is regarded as a multi-objective combinatorial optimization process,and a multi-objective combinatorial optimization solution model of high-speed train bogie configuration scheme is established.Finally,based on the constraints formed by case statistics,supplemented by the constraints formed by expert experience and functional relationships,the NSGA-II algorithm is used to obtain the Pareto optimal configuration scheme set.