4results about How to "Save computing time" patented technology

The application discloses a kind of battery core temperature online estimation and prediction method, system, equipment and storage medium based on mixed TSDM-AMBO-GRU, applied to lithium ion battery core temperature estimation and prediction field, comprising: obtaining battery operating data, and utilizing TSDM to create synthesis of battery operating data, as training set with battery operating data together;Training set is input to BO-GRU-AM framework, and the battery core temperature prediction model based on BO-GRU-AM is obtained by training;Input test set to battery core temperature prediction model, and obtain battery core temperature prediction result.The application not only can effectively overcome the problem caused by uneven distribution of temperature sensors and limited data in lithium ion battery system, and can realize real-time, efficient and accurate battery core temperature prediction under various temperatures and complex conditions, provide reliable fault warning and real-time monitoring support for BMS in practical application.

The present application belongs to the technical field of electrocatalytic materials, and particularly relates to a method for screening high-selectivity iron-nitrogen-carbon electrocatalysts for NO3RR based on a curved structure. The method aims to solve the technical problem of low selectivity of ammonia, the target product, in the nitrate reduction process of existing iron-nitrogen-carbon electrocatalysts due to competing side reactions. The method comprises the following steps: firstly, constructing a planar iron-nitrogen-carbon structure model and a series of tubular iron-nitrogen-carbon structure models with different curvatures; secondly, calculating the adsorption energies of nitrogen atoms and oxygen atoms for the planar and tubular structure models, respectively, and selecting a target tubular iron-nitrogen-carbon structure model based on the adsorption energy data; thirdly, calculating the reaction Gibbs free energies of the planar model and the target tubular model for reducing nitrate to various nitrogen-containing products; and finally, drawing a reaction path free energy diagram at zero potential based on the reaction Gibbs free energies, and analyzing the specific influence of the curved structure on the selectivity of the iron-nitrogen-carbon electrocatalytic nitrate reduction reaction, thereby guiding subsequent experimental research.

The application provides a real-time target detection method in an ultrahigh-resolution image scene, comprising: processing an original image to generate a high-resolution image and a low-resolution image; processing the low-resolution image to obtain a reserved area; cutting the high-resolution image according to the reserved area to generate a plurality of regional subgraphs; and detecting the regional subgraphs to obtain a detection result. The application can quickly detect the area requiring further fine-grained detection from an ultrahigh-resolution image through resolution processing, multi-scale density regression, area determination and area generation processing. In addition, due to the scale normalization, target detection and result merging processing, the final ultrahigh-resolution detection result can be generated. In the target detection stage, the plurality of regional subgraphs can be processed in parallel, which can greatly improve the inference time. Since part of the object-free area can be discarded in the density estimation stage, the required storage resources and calculation time can be saved.