Structural lightweight optimization is one of the key themes to continuously improve vehicle performance. However, most of the studies so far have not considered reliability and manufacturing issues brought about by the uncertainty of tolerances in structural lightweight optimization. In this study, a reliability-based design for lightweight vehicle structures with uncertain manufacturing accuracy is proposed. This method can provide not only the optimal design variables but also the maximum allowable deviation range. The main design variables lacking sample information are regarded as interval variables and other design parameters as probabilistic values. A progressive reliability-based design with uncertain manufacturing accuracy is established for lightweight vehicle structures by employing the transformation method of the interval model and the decoupling strategy of the probabilistic model. Firstly, the general test function is used to analyze the accuracy and efficiency of the reliability decoupling method. Then, lightweight optimization models of a classic cantilever beam and two vehicle structures (parking robot frame, energy absorption box) are established respectively, and the effectiveness of the present optimization method is verified. The optimized design results show that the optimal variables and the corresponding maximum allowable deviation range under acceptable manufacturing requirements can be obtained. The requirements for manufacturing accuracy can be reduced by appropriately increasing the deviation range of the design variables, which may lead to a reduction in manufacturing cost. This study aims to provide feasible design options by optimizing lightweight structures considering uncertain manufacturing accuracy.

结构轻量化的优化是不断提高车辆性能的关键主题之一。但是，到目前为止，大多数研究都没有考虑结构轻量化优化中公差不确定性带来的可靠性和制造问题。在这项研究中，提出了一种基于可靠性的轻量化车辆结构的设计，其制造精度不确定。该方法不仅可以提供最佳设计变量，而且可以提供最大允许偏差范围。缺少样本信息的主要设计变量被视为区间变量，其他设计参数被视为概率值。通过采用区间模型的转换方法和概率模型的解耦策略，为轻型车辆结构建立了具有不确定制造精度的基于可靠性的渐进式设计。首先，使用通用测试函数来分析可靠性去耦方法的准确性和效率。然后，分别建立了经典悬臂梁和两个车辆结构（停车机器人框架，能量吸收箱）的轻量化优化模型，并验证了该优化方法的有效性。优化的设计结果表明，可以获得可接受的制造要求下的最佳变量和相应的最大允许偏差范围。通过适当地增大设计变量的偏差范围，可以降低对制造精度的要求，从而可以降低制造成本。这项研究旨在通过考虑不确定的制造精度来优化轻型结构，从而提供可行的设计方案。