Multi-objective explosion-proof performance optimization of a novel vehicle door with negative Poisson’s ratio structure

In order to enhance the explosion-proof performance of the door and reduce the injury to passengers caused by the explosion impact load, this paper introduces the negative Poisson’s ratio (NPR) structure to the traditional door, and proposes a NPR explosion-proof door. It adopts the NPR functionally graded material to form the inner core part between the outer panel and inner panel, and sets different thicknesses to different gradient layers to meet the performance requirements of energy absorption and impact resistance. Because the relationships between the parameters and the performance indexes are unknown for this novel door, this work obtains the quantitative relationship between them by means of the response surface model (RSM). Based on this, the optimization mathematical models are established taking the inner panel acceleration, inner panel intrusion, energy absorption of NPR inner core structure and the mass of explosion-proof door as the optimization objectives. Then, a multi-objective optimization design is conducted for the novel explosion-proof door based on adaptive hybrid multi-objective particle swarm optimization (AHMOPSO) algorithm. Simulation results show that compared with the traditional door, the explosion-proof door optimized by AHMOPSO algorithm has better comprehensive explosion-proof performance. The results of this paper can provide some basis for the design and optimization of the explosion-proof door.