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Multi-objective design optimization of an engine accessory drive system with a robustness analysis

机译：具有稳健性分析的发动机配件驱动系统的多目标设计优化

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Designing a good engine accessory drive system becomes a hard work with its increasingly complicated configuration and high demands on its dynamic characteristics. In this work, a hybrid mutation particle swarm optimization (HMPSO) algorithm is presented to optimize the key structure parameters of an engine accessory drive system for its vibration control. The superiority of the HMPSO algorithm against several other concerned metaheuristic algorithms in terms of solution quality and stability are verified by non-parametric statistical tests on ten benchmark functions. The design problem of the engine accessory drive system is a multi-objective optimization problem; the weighted sum method and main target method are applied to convert it to a single-objective one. Optimization on an example engine accessory drive system using the HMPSO algorithm demonstrates obvious improvement in system vibration after optimization. A robustness analysis is conducted to identify the robustness of dynamic responses of the engine accessory drive system with respect to small variations of the design variables relative to the optimal design in the design space, and suggestions on design of an engine accessory drive system are given according to it.
机译：设计良好的发动机配件驱动系统与其越来越复杂的配置和对其动态特性的高要求进行了艰苦的工作。在这项工作中，提出了一种混合突变粒子群优化优化（HMPSO）算法以优化发动机附件驱动系统的振动控制的关键结构参数。在解决方案质量和稳定性方面，通过非参数统计测试来验证HMPSO算法对几个其他有关的成群质算法的优越性。发动机配件驱动系统的设计问题是多目标优化问题;应用加权和方法和主要目标方法以将其转换为单个目标。使用HMPSO算法的示例发动机附件驱动系统上的优化表明，优化后系统振动的显而易见。进行稳健性分析以识别发动机附件驱动系统相对于设计空间中的最佳设计的小变化的动态响应的鲁棒性，以及根据发动机附件驱动系统的设计建议到它。

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