采用等效电路模型、分数阶阻抗模型和简化电化学模型对航空应急电池组进行SOC(state of charge)估计。分别构建三种不同物理域模型,结合扩展卡尔曼滤波算法,进行SOC估计。估算了多种工况下SOC,并给出估计精度;搭建硬件测试平台对三种模...采用等效电路模型、分数阶阻抗模型和简化电化学模型对航空应急电池组进行SOC(state of charge)估计。分别构建三种不同物理域模型,结合扩展卡尔曼滤波算法,进行SOC估计。估算了多种工况下SOC,并给出估计精度;搭建硬件测试平台对三种模型的实时性进行了评估;最后根据SOC估计误差、实时性、适用性等对三种模型进行综合评价。认为简化电化学模型具有较高估计精度和较好适应性,使用该模型估计常温三个工况SOC的最大估计误差为3.09%。展开更多
In implementing mass customization, how to respond rapidly to customers’ requirements is a key problem. Configuration design is considered effective in early stage of product design. This paper studies a configuratio...In implementing mass customization, how to respond rapidly to customers’ requirements is a key problem. Configuration design is considered effective in early stage of product design. This paper studies a configuration method based on constraints and fuzzy decision for product family. The configuration method is evolved from constraint based product configuration. It employs fuzzy optimum selection in the reasoning process, which can select similar components when customers’ requirements can not be met precisely. In the configurator, product family is represented with GBOM(Generic Bill Of Material) and ACL(Article Characteristic List). Every node of GBOM has an ACL to list all instances of a component family. Constraints are attached to every node, which involves variable definition and constraints definition. In the reasoning process, constraint satisfaction and fuzzy optimum selection interact to search optimum solution. A prototype is developted to demonstrate how to run the configurator. The paper ends with a discussion of advantages, future work of the configuration method.展开更多
A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For ...A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For the balancing problem for the scenario-based robust assembly line with a finitely large number of potential scenarios, the direct solution methodology considering all potential scenarios is quite time-consuming. A scenario relaxation algorithm that embeds genetic al- gorithm is developed. This new algorithm guarantees termination at an optimal robust solution with relatively short running time, and makes it possible to solve robust problems with large quantities of potential scenarios. Extensive computational results are reported to show the efficiency and effectiveness of the proposed algorithm.展开更多
文摘采用等效电路模型、分数阶阻抗模型和简化电化学模型对航空应急电池组进行SOC(state of charge)估计。分别构建三种不同物理域模型,结合扩展卡尔曼滤波算法,进行SOC估计。估算了多种工况下SOC,并给出估计精度;搭建硬件测试平台对三种模型的实时性进行了评估;最后根据SOC估计误差、实时性、适用性等对三种模型进行综合评价。认为简化电化学模型具有较高估计精度和较好适应性,使用该模型估计常温三个工况SOC的最大估计误差为3.09%。
文摘In implementing mass customization, how to respond rapidly to customers’ requirements is a key problem. Configuration design is considered effective in early stage of product design. This paper studies a configuration method based on constraints and fuzzy decision for product family. The configuration method is evolved from constraint based product configuration. It employs fuzzy optimum selection in the reasoning process, which can select similar components when customers’ requirements can not be met precisely. In the configurator, product family is represented with GBOM(Generic Bill Of Material) and ACL(Article Characteristic List). Every node of GBOM has an ACL to list all instances of a component family. Constraints are attached to every node, which involves variable definition and constraints definition. In the reasoning process, constraint satisfaction and fuzzy optimum selection interact to search optimum solution. A prototype is developted to demonstrate how to run the configurator. The paper ends with a discussion of advantages, future work of the configuration method.
基金Supported by the National High Technology Research and Development Programme of China （No. 2006AA04Z160） and the National Natural Science Foundation of China （ No. 60874066）.
文摘A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For the balancing problem for the scenario-based robust assembly line with a finitely large number of potential scenarios, the direct solution methodology considering all potential scenarios is quite time-consuming. A scenario relaxation algorithm that embeds genetic al- gorithm is developed. This new algorithm guarantees termination at an optimal robust solution with relatively short running time, and makes it possible to solve robust problems with large quantities of potential scenarios. Extensive computational results are reported to show the efficiency and effectiveness of the proposed algorithm.
