2results about How to "Avoid sudden power outages" patented technology

The invention relates to the technical field of architectural design teaching auxiliary equipment, and discloses an architectural design teaching auxiliary device and method based on virtual reality, and the device comprises a bottom plate, the upper surface of the bottom plate is provided with a groove, the interior of the groove is provided with a driving motor, and the output end of the driving motor is fixedly connected with a supporting block. A fixing plate is fixedly connected to the upper surface of the supporting block, a first bearing is fixedly embedded in the upper surface of the fixing plate, a supporting column is fixedly connected to the inner ring of the first bearing, a projection table is fixedly connected to the top end of the supporting column, a sliding groove is formed in the upper surface of the fixing plate, and a sliding block is installed in the sliding groove. According to the building design teaching auxiliary device and method based on virtual reality, the height of the stereo projector can be adjusted through the hydraulic rod, the fixing plate can be driven to rotate through the driving motor, and a worker can conveniently adjust the projection direction of the stereo projector.

This invention provides a method for predicting the lifespan of lithium batteries based on physical neural networks, comprising: constructing a coupled ordinary differential equation of lithium battery charge state and thermodynamic evolution, and establishing a continuous-time dynamic model of lithium battery charge change; constructing a PI-LSTM hybrid analysis framework based on physical information neural networks, and incorporating the coupled ordinary differential equation as a physical constraint term into the loss function of the PI-LSTM hybrid analysis framework; collecting time-series sensing data of lithium battery operation, training the PI-LSTM hybrid analysis framework, and completing the inversion identification of lithium battery physical parameters; based on the trained PI-LSTM hybrid analysis framework, outputting the state of charge and time to depletion of the lithium battery under the target operating condition, and completing the prediction of lithium battery lifespan; this invention aims to achieve accurate and interpretable prediction of lithium battery SOC and TTE in multiple devices, providing support for battery management of electrical equipment such as drones.