Abstract: Aiming at the problem that it is difficult to quantify and reduce the carbon emission in the service process of product parts,a low-carbon demand-driven optimization design method for product parts parameters was proposed.A recursive quantization model of component design parameters and carbon emission was established based on the dynamic interactive evolution characteristics of energy during component service.Morris global screening method was used to characterize the parameter sensitivity and coupling strength of components to screen key low-carbon design parameters.A low-carbon optimization model based on the improved balance optimizer algorithm was established with the goal of minimum carbon emissions during component service.The Metropolis criterion was introduced to construct the probabilistic fitness selection strategy,and the candidate solution selection method was improved to reduce the optimization deviation,so as to obtain the optimal parameter design scheme.Finally,the low carbon design parameters of electric tractor were optimized to verify the feasibility and effectiveness of the proposed method.

Key words: low carbon demand, product parts, parameter optimization, improved equilibrium optimizer

摘要： 针对产品零部件服役过程碳排放难以量化和降低的问题,提出一种低碳需求驱动的产品零部件参数优化设计方法。基于零部件服役过程中的能量动态交互演变特性,建立零部件设计参数碳排放递归量化模型;应用Morris全局筛选分析法表征零部件参数敏感度与耦合强度,以筛选关键低碳设计参数;以零部件服役过程碳排放量最低为目标,建立基于改进平衡优化器算法的低碳优化模型,引入Metropolis准则构造概率适应度选择策略,改善候选解选择方法以降低优化偏差,从而获得最佳参数设计方案。最后以电动拖拉机为例进行零部件低碳设计参数优化,验证了所提方法的可行性与有效性。

关键词: 低碳需求, 产品零部件, 参数优化, 改进平衡优化器