基于拆解难度和模糊聚类的泛化报废汽车拆解成本预测

针对报废汽车拆解前的成本评估问题，建立了一种基于拆解难度和模糊聚类的一般性综合成本评价模型。提出了影响报废汽车拆解难度的因素，通过模糊聚类分析确定不同车型在拆解过程中具有相同拆解难度的零组件；给出了聚类模型的拆解成本误差评价方法。以4台3类报废实验车型（轿车、运动型多用途汽车（SUV）、多用途汽车（MPV））的物理拆解实验数据为例，量化评价了基于模糊聚类的泛化拆解成本模型,结果表明，该模型具备各类车型的共性聚类特征，拆解成本最大误差低于28%。建立的拆解成本预测模型为报废汽车拆解企业关于拆解内容的决策问题提供了方法依据。

Prediction of Disassembly Costs of ELVs by Fuzzy Clustering Based on Disassembly Difficulties

Aiming at the problems of cost evaluation before dismantling ELVs, a general comprehensive cost evaluation model was established based on disassembly difficulties and fuzzy clustering. The factors affecting disassembly difficulties of ELVs were put forward. The fuzzy clustering analyses were used to determine the components that had the same disassembly difficulty among the disassembly of different models. An error evaluation method of the disassembly costs was given about the cluster model. Taking the experimental data of physical dismantling of four scrapped experimental vehicles(two cars, one sport utility vehicle, and one multi-purpose vehicle) as examples, a general disassembly cost model was quantified and evaluated based on fuzzy clustering. The results show that the model has the commonality of various models and the maximum error of disassembly cost is less than 28%. The disassembly cost forecasting model helps the technological decision before ELV dismantling in methodology.