基于多工况关联的无人车辆车身结构轻量化优化设计

The higher requirements are put forward for the environmental adaptability of special unmanned vehicles in the future battlefield. In order to meet the requirements of multi-working conditions, high maneuverability and low-cost development of special unmanned vehicles, the truss body structure of unmanned vehicles is optimized by the idea of multi-working conditions correlation design and lightweight optimization. However, considering that there are many design variables, large design space and too many simulation times in multi-working conditions, a lightweight optimization method of body structure based on multi-working conditions correlation is proposed; In the proposed method, the strategy of reducing design variables interval is used to reduce the design space. Gaussian process surrogate model is introduced to replace the simulation analysis for realizing the rapid performance evaluation of structural design scheme, and the optimization of the scheme is realized using genetic algorithm. The experimental results show that the mass of the final optimization scheme is 14. 12% lower than that of the initial scheme and 8. 87% lower than that of the scheme optimized only by Gaussian process under the condition of multi-disciplinary performance simulation verification, such as stiffness, strength and mode.