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A lithium battery health status prediction and system suitable for variable operating conditions

PendingCN122085158Asimple featuresAvoid complex feature engineeringElectrical testingElectrical batteryEnergy recovery
This invention discloses a method and system for predicting the health status of lithium batteries under varying operating conditions. First, key operating condition features such as energy recovery power, energy recovery current, equivalent power, average discharge current, and equivalent current are extracted based on historical battery data, and parameters of a decay relationship model between health status and equivalent cycle count are fitted. Second, a Gaussian process regression model is trained using early data to learn the mapping relationship between operating condition features and decay parameters. Then, by combining real-time monitoring and external information, future energy recovery power, average discharge power, and equivalent power are predicted, and corresponding current feature sequences are derived. Finally, the predicted future operating condition features are input into the trained model to obtain predicted decay parameter values, achieving accurate prediction of future health status. This invention significantly improves the accuracy, adaptability, and foresight of health status prediction under varying operating conditions by integrating battery physical models and data-driven methods and introducing future operating condition prediction.
Owner:JIANGSU UNIV OF SCI & TECH

LOD construction method and device for GIS large-range live-action model

According to the LOD construction method and device for the GIS large-range live-action model, the nodes are generated through adaptive iterative segmentation in the HLOD tree construction process, the triangular patch data amount of each node is kept within the threshold value range, and the nodes with the too large triangular patch number cannot be generated; meanwhile, the textures of all the nodes are limited to be kept in a similar range, too large textures cannot be generated, and the optimal configuration effect can be achieved in the rendering scheduling process of the result; meanwhile, after the triangular patches in all the nodes are simplified, the texture features in the texture pyramid are merged, and the method can effectively simplify the grids, maintain the features of the grids, reduce the deformation of the textures to the maximum extent, and ensure the visual effect of the grids. In addition, main memory occupation data is stored in a temporary file by using a memory mapping technology, so that the scheme can process large data volume data exceeding computer memory limitation.
Owner:BEIJING GREEN VALLEY TECH CO LTD +4