A Multi-objective Uncertainty Optimization Method for Vehicle Occupant Restraint System

Abstract

The invention discloses a multi-objective uncertainty optimization method for a vehicle occupant restraint system. The method uses an ellipsoidal convex set model to describe the correlation of uncertain variables of the vehicle occupant restraint system, and uses the interval sequence relationship and interval possibility Transform the multi-objective uncertainty optimization problem into a deterministic optimization problem; in order to improve the calculation efficiency, the local encryption approximate model method is introduced into the iterative solution process, and the approximate model is reconstructed multiple times to ensure the accuracy of the approximate model and calculation results. And through the multi-objective uncertainty optimization method to solve the non-dominated solution set that meets the protection performance of the vehicle occupant restraint system, thereby ensuring the safety of the vehicle occupant; the invention can not only effectively improve the protection performance of the vehicle occupant restraint system, but also can essentially Improving the calculation efficiency and solution quality of optimization has extensive engineering application value in the field of automobile safety.

Description

technical field [0001] The invention relates to the field of vehicle safety, in particular to a multi-objective uncertainty optimization method for an automobile occupant restraint system. Background technique [0002] When a car collides, the car occupant restraint system composed of seat belts, safety seats, airbags and other devices can not only effectively buffer the impact load on the occupants, but also avoid secondary collisions between the occupants and the interior of the vehicle body. Thereby play the role of car occupant protection. Studies have shown that the protective performance of the occupant restraint system will directly determine the degree of occupant injury and death rate. Therefore, the vehicle occupant restraint system is the top priority of vehicle safety technology research. [0003] For the design of vehicle occupant restraint system, the existing optimal design methods have the following problems: [0004] 1. Most of the existing optimization m...

AI Technical Summary

Problems solved by technology

However, many problems in the automotive crash process usually consist of multiple conflicting goals, and the improvement of these design goals may conflict with each other

Therefore, the single-objective optimization method of the vehicle occupant restraint system cannot fully meet the needs of the design

[0006] 3. For complex engineering multi-objective optimization problems such as automotive occupant restraint systems, time-consuming numerical analysis models are often involved

Therefore, in order to overcome the shortcomings of low optimization efficiency, a small number of existing technologies use approximate model technology, such as the patent "A Multi-objective Reliability Optimization Technology for Vehicle Frontal Collision Safety" with the publication number CN102945327A and the publication number as CN102495923A's patent "a hybrid reliability evaluation method for automobile collision safety", but the above-mentioned patent only constructs an approximate model once, and for complex engineering multi-objective optimization problems such as automobile occupant restraint systems, an approximate model The establishment of the method cannot guarantee the accuracy of the optimal design solution

[0007] To sum up, among the current multi-objective optimization design methods for vehicle occupant restraint systems, there is no patent that considers both the correlation between uncertain design variables and multiple reconstructions of approximate models.

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