Chassis technical specifications such as durability and ride comfort are the focuses during vehicle development projects. Additionally, robustness is also important as it is related to manufacturing costs as well as chassis performance in the total life cycle. This article proposes a robust multi-objective optimization approach to improve chassis specifications while taking the physical random factors into consideration. The adaptive–sparse polynomial chaos expansion (PCE) method with Chebyshev polynomials of the second kind has been applied to predict responses' uncertainty moments according to the uncertain-but-bounded parameters. Industrial cases related to chassis development have been tested, including an analytical formula, a quarter-car model and a finite element twist beam. For each problem a Pareto front that represents the best compromises between objectives and their robustness is obtained and the comparison tests prove a good robustness prediction by the Chebyshev PCE method. These examples demonstrate the effectiveness and reliability of the approach, in particular its ability to save computational costs for a complex system.

耐用性和乘坐舒适性等底盘技术规格是车辆开发项目的重点。此外，稳健性也很重要，因为它与制造成本以及整个生命周期中的底盘性能有关。本文提出了一种鲁棒的多目标优化方法，以在考虑物理随机因素的同时改进底盘规格。具有第二类切比雪夫多项式的自适应稀疏多项式混沌展开 (PCE) 方法已被应用于根据不确定但有界参数预测响应的不确定矩。与底盘开发相关的工业案例已经过测试，包括分析公式、四分之一汽车模型和有限元扭梁。对于每个问题，获得代表目标及其稳健性之间最佳折衷的帕累托前沿，并且比较测试证明了 Chebyshev PCE 方法的良好稳健性预测。这些例子证明了该方法的有效性和可靠性，特别是它为复杂系统节省计算成本的能力。