Research On BIW Parameterization Modeling And Multi-objective Lightweight Optimization Design Method

With the rapid development of the automotive industry, the car ownership increasedsignificantly in worldwide. The vehicle had played a huge role in human life and economicsphere. The growing influence changed people’s life and work. But with the high-speedincreasing in car ownership of the world, it was influenced the energy, the environment andthe traffic safety enormous. Although electric cars was the best solution, at actual technologylevel, any other method could not be more economic than fossil fuel. As for conventionalfuels for cars. Current vehicle research was developing in high efficiency, low energyconsumption and low emissions, which were all close to vehicle quality. So, the vehiclelightweight was most effective ways to reduce the fuel consumption and emissions atpresent.The body was an important part of the whole vehicle.Most of the vehicle body weremake up of stamping parts, which had a complex structure and was composed of many parts.is an important part of whole. Its expense occupy almost60%of the investment cost. Thebody mass occupy about30-40%of the whole vehicle. In no-live load condition, about70%of the vehicle’s gas consumption was expended on the vehicle body. Therefore, the bodylightweight was important to the vehicle lightweight, also it was one of the main researchsubjects in vehicle industry.The research was developed based on the project “research on the body parameterizedlightweight design technology and its integrated application on the target models”which wasa part of the National Twelfth five-year Science and Technology Support Program “R&D ofthe key lightweight technology and integrated application on the car”. As a Chinese car wasthe research object, using implicit parameterization software SFE-concept, respectivelyestablished the car body geometry structures such as engine class, floor and side wall. Assembly relationship among the structures were established by using mapping rmethod.Composing three-dimensional solid BIW parameterization model, then, export. the FEMmodel in SFE-concept.Getting the initial parameterization FEM model, then, the mode and stiffness analysiswere carried out. Based on the BIW model, the whole car was built and the car crashanalysis was carried out. According to the ratio of each parts’ energy absorption to the wholecar’s energy absorption in100%frontal crash of the car, the safety related parts and thenon-safety related parts were distinguished. All of the analysis results were compared withthe experiment. Through the comparison results, the accuracy of the BIW parameterizationmodel was proved.The sensitivity analysis of the mode and stiffness were carried out. Because the shapevariables and the safety performance were hard to calculate the sensitivity, the relativityanalysis was used instead of the sensitivity analysis. Finally, the variables which were usedfor reducing the body mass and supplementing the performance were determined. Thosevariables were groundwork for the Multi-objective lightweight optimization design.According to the actual situation, The BIW multi-objective lightweight optimizationdesign was divided into two parts. One was non-safety parts lightweight optimization design,the other was safety parts lightweight optimization design.As the mass and stiffness of the BIW were the targets, the lower-order naturalfrequency was the constraint, the non-safety parts lightweight optimization design wascarried out. The NSGA-II method was utilized in the optimization. Finally, according to thepreference, the ultimate solution was selected in the Pareto frontier.Based on the result of non-safety parts lightweight optimization design, the non-safetyparts lightweight optimization design was carried out, in which the mass and the cabinacceleration peak as the targets and the mode, stiffness and the other safety performences asthe constraints. The optimization was indirect. An approximate model was established byusing the EBFNN method, which was utilized in the multi-objective lightweightoptimization design. After the two optimization process, the mass of the BIW was reduced from326.22kg to292.95kg. The lightweight effect was very obviously, while the performences of the BIWwere changed less Simultaneously. Although some of the performance were less reduced,those reduction were within7%. The lightweight coefficient was reduced from4.49to4.33.The results indicated that the optimization obtained a very well effect.