Abstract This paper proposes a parametric synthesis of two different trunk lid mechanisms for sedan vehicles, incorporating three different population-based optimization techniques: Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and the Differential Evolution (DE). For this purpose, the kinematic equations of the mechanisms are derived and implemented in the quasi-static analysis to determine the necessary driving forces. The lengths and initial angles of four-bar linkage are optimized in order to minimize the sum of the differences between the target and calculated hand force values. The optimization results of the design variables and the performances of the optimization methods are presented. The outcomes indicate that the proposed design procedure is able to provide a trunk lid mechanism in which the target value of driving force in every moving angle is achieved. Furthermore, it is observed that the optimization techniques show different performances due to the fact that they provide better and faster optimal solutions than each other for different cases. The results of this paper are of utmost importance for the manufacturer to obtain an automated design process for the trunk lid mechanisms.

中文翻译：

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使用基于群体的优化算法对轿车的两种不同行李箱盖机制进行参数合成

摘要 本文提出了两种不同的轿车后备箱盖机制的参数综合，结合了三种不同的基于群体的优化技术：粒子群优化 (PSO)、遗传算法 (GA) 和差分进化 (DE)。为此，在准静态分析中推导出并实施机构的运动学方程，以确定必要的驱动力。优化了四杆连杆的长度和初始角度，以最小化目标和计算手力值之间的差异之和。给出了设计变量的优化结果和优化方法的性能。结果表明，所提出的设计程序能够提供一种行李箱盖机构，其中在每个移动角度都达到了驱动力的目标值。此外，观察到优化技术表现出不同的性能，因为它们在不同情况下提供了比彼此更好更快的最佳解决方案。本文的结果对于制造商获得行李箱盖机构的自动化设计流程至关重要。