Abstract
The comprehensive evaluation of the performance parameters of the mobile welding robot driven by the fuel cell hybrid power system is beneficial to optimizing the energy efficiency and control performance of the system. However, few studies have paid attention to this aspect. Rough analytic hierarchy process and entropy weight method are used to calculate the weight of the evaluation index. Cloud model is used to synthesize all evaluation indicators to determine the status level. First, the golden section method is used to determine the evaluation criteria, and through cloud model, the evaluation criteria and measured parameters of the single evaluation index are transformed into corresponding evaluation reference clouds and evaluation clouds. Second, the weight of the evaluation index is determined by the method of the rough analytic hierarchy process, and the method of the entropy weight is used to revise the method of the rough analytic hierarchy process. The single evaluation reference cloud and evaluation cloud are aggregated to get the comprehensive evaluation reference cloud, and the comprehensive evaluation of the reference cloud is carried out. The evaluation cloud for each evaluation cycle. Finally, according to the correlation between the comprehensive evaluation cloud and the comprehensive evaluation standard cloud, the performance level of each evaluation cycle is determined. In this paper, the randomness and fuzziness of the qualitative concepts are solved by using the characteristics of the cloud model. Combined with rough analytic hierarchy process, the objectivity of the data is maintained and the advantages of the expert evaluation are enhanced. The validity of the model is verified by comparing the existing methods. These studies evaluate and classify the real-time status of the fuel cell robot, and provide a basis for the performance optimization and energy optimization of the hybrid power system controllers.
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