Study On Comfort Design Optimization And Variant Design Failure Resolution For Seat Skeletons

As an important part of automobile,seat interacts with drivers directly,its shape and layout parameters affect the comfort and fatigue level of drivers greatly.Due to the big differences between the measurement parameters of different groups,the traditional comfort design method of automobile seat skeleton（ASK）can not meet the needs of personalized and customized design of customers.In the process of variant design of ASK,the failure probability of variant design is higher for some parts with complex feature tree.Based on measurement parameters of customers’ body,the static comfort of ASK was analyzed and optimized to meet the personalized and customized design requirements of ASK.In this thesis,by analyzing the modeling mechanism of CATIA,the reasons for the failure of variant design of complex parts were analyzed,and the resolution strategy for the failure of variant design of complex parts in the ASK was studied deeply and systematically.The main reasons of human fatigue in sitting position were analyzed,and three main factors leading to human fatigue were obtained: Muscle fatigue,spinal internal stress and environmental constraints,pressure and shear stress,by establishing the model of skeletal muscle in Anybody simulation software to simulate the driving environment,the simulation analysis of seat height,inclination of the seat backrest,cushion angle and the herizontal distance between H-point and heel point from the four parameters on the above three factors,and the optimization suggestions were given in this thesis.In order to minimize muscle activity,the optimization objective function was established,and the response surface of the objective function and seat parameters was obtained by Response Surface Analysis Method.The comprehensive influence of seat parameters on muscle activity was analyzed,and the seat parameters were optimized.By building the rule reasoning model and combining CATIA secondary development technology,ASK variant design system based on rule reasoning was designed and implemented.Driven by seat parameters optimised after static comfort design,Rapid variant design system of ASK was implemented,not only the static comfort of ASK was improved,but also design quality and design efficiency of ASK were promoted.Based on the breadth-first search algorithm of directed graph,a feature tree empowerment algorithm was designed.The feature tree was treated as a weighted directed acyclic graph.The coupling degree of features was evaluated by the weight value of the graph,the local edge-connectivity and the longest path.The feature tree was divided into several subgraphs,and the optimization process for different subgraphs was proposed,which reduced the coupling degree of features effectively and the failure probability of the variant design of ASK.