10results about How to "Accurate loss" patented technology

The invention relates to the technical field of charging load prediction, in particular to an electric vehicle charging load prediction method and system combining sequence decomposition and feature extraction and a storage medium. Comprising the steps of performing variational mode decomposition on time sequence load data to obtain a plurality of intrinsic mode functions; performing zero padding expansion on each intrinsic mode function, and then converting the intrinsic mode function to a frequency domain; enhancing the frequency domain data through a multi-layer perceptron based on complex domain calculation; constructing a prediction model based on a complex field attention module and a residual module, inputting the enhanced spectrum data into the prediction model, extracting a data characteristic frequency combination through the complex field attention module and the residual module, and carrying out weighted summation on all intrinsic mode functions as the output of the prediction model; and calculating a difference value between real data and prediction data according to a mean square error of a time sequence and an average absolute value error of a frequency spectrum to obtain time domain and frequency domain mixed loss, and updating prediction model parameters. According to the invention, the problem of large prediction error under the influence of random load fluctuation is solved.

The present invention proposes a high-precision core loss measurement device with multiple input waveforms. The device includes a periodic square wave voltage generation module, a multi-waveform input generation module and a core loss measurement module. The periodic square wave voltage generation module generates a periodic square wave voltage, and the multi-waveform input generation module generates a variety of common voltage waveforms, and then generates current waveforms of different shapes on the primary winding of the magnetic core to be measured through different switch combinations and switch tube conduction timings. The core loss measurement module uses the inductance in the air-core transformer to partially compensate for the error amplification effect caused by the voltage and current phase angle difference caused by the inductance of the magnetic core to be measured. By calculating the compensation factor, the error caused under any input waveform is reduced to close to 0, thereby achieving high-precision measurement of the core loss. The present invention solves the problem of sensitivity to measurement phase error when measuring core loss using the dual-winding method, and can accurately measure the core loss at high frequencies.

The embodiment of the present application discloses a method, device and medium for counting goods at a retail end, which belongs to the technical field of goods counting and solves the problem of low accuracy and efficiency of goods counting. The shelf information and goods information entered by the retail end shop are obtained to construct a goods counting template; the information to be counted is received, and the corresponding goods category library is determined based on the information to be counted, and in the goods category library, the goods information to be counted and the goods information in the goods counting template are matched for goods association; based on the goods category corresponding to the information to be counted, the corresponding inventory statistical unit is determined, and based on the information to be counted, the goods association matching result and the inventory statistical unit, the goods inventory data is generated in the goods inventory template; the goods inventory data is audited, and the goods inventory data is adjusted based on the audit result; based on the audit result and the adjusted data, the goods loss of the retail end shop is determined to assess the retail end shop based on the goods loss.

The embodiment of the present application discloses a method, device, computer equipment and storage medium for training a routing decision model. A first node is determined from multiple nodes in a dynamic network, and a first network state and a first network action corresponding to the first node are determined; the first network state and the first network action are input into an evaluation sub-model, and an evaluation value of each first network action is output; the target first network action with the largest evaluation value and the second node of the target first network action are determined; the reward value of the second network action, the second network state and the target first network action of the second node pair is input into the target sub-model, and the target value of the target first network action is output; the model loss of the evaluation sub-model is determined according to the target value and the largest evaluation value, the model parameters of the evaluation sub-model are adjusted according to the model loss, and the execution is returned to determine the first node from multiple nodes in the dynamic network until the model loss meets the preset loss condition, and the trained routing decision model is obtained.

The application relates to a photovoltaic simulation prediction method and system based on a cellular automaton, which comprises the following steps: cleaning, spatial registration, interpolation, supervised classification and rasterization processing of multi-source data, construction of a photovoltaic distribution data and environmental factor database; construction of a photovoltaic expansion and photovoltaic loss optimal classification model to obtain the contribution degree result and marginal effect characteristics of each influence factor; calculation of a photovoltaic expansion and photovoltaic loss comprehensive suitability score, generation of a photovoltaic expansion suitability map and a photovoltaic loss suitability map through spatial mapping; after the operation rules and parameter constraint set of the cellular automaton model are determined, the candidate pixel set is screened, the conversion quantity is controlled, and each cellular state is iteratively updated step by step, so that the prediction simulation of the photovoltaic facility space expansion and loss process is realized. According to the technical scheme, the photovoltaic space bidirectional dynamic accurate simulation can be completed through the cellular automaton, and interactive parameter adjustment is supported to adapt to diversified planning scenes.

This invention relates to the fields of marine meteorology and navigation, and discloses a method for predicting meteorological factors for ship navigation based on marine meteorological information. This method is used to predict meteorological factors for ship navigation, assess navigation risks, and plan alternative routes. The method includes processing meteorological data and ship data for a target sea area to obtain historical meteorological time series and ship motion response sequences; constructing state vector trajectories of meteorological factors using historical meteorological data, establishing a dynamic model library, and obtaining the ship motion response function to meteorology based on meteorological and motion response data; generating deterministic meteorological factor prediction sequences by embedding the current meteorological state into the dynamic model; and constructing stochastic differential equations to generate probabilistic prediction distributions of meteorological factors. This invention integrates data-driven and physical constraints, providing more comprehensive navigation decision support.

The invention relates to the technical field of wireless power transfer (WPT), particularly discloses a WPT system coupling mechanism loss calculation method and system based on partition calculation, and aims at the characteristics of nonuniform magnetic field intensity distribution and nonuniform magnetic flux density distribution of a coil. Discretizing the magnetic field intensity distribution diagram of the continuous coil and the magnetic flux density modulus distribution diagram of the magnetic core to obtain different coil subareas and magnetic core subareas, and calculating the area proportion of each coil subarea and the volume proportion of each magnetic core subarea; each coil partition takes the magnetic field intensity peak value of the coil partition as the magnetic field intensity value participating in calculation, and each magnetic core partition takes the magnetic flux density peak value of the magnetic core partition as the magnetic flux density participating in calculation, so that on the basis of an existing loss calculation model, the loss of each partition is independently calculated, and finally summation is carried out to obtain the loss calculation model. The total loss of the coil and the magnetic core is obtained, and the total loss of the coupling mechanism is further obtained. Experiments verify the accuracy of the method.

The application discloses a method for estimating loss of a hybrid switching converter based on a simulation model, and is implemented according to the following steps: selecting SiC-MOSFET and Si-IGBT device models according to system capacity; performing parameter calibration on SiC-MOSFET double-pulse testing and Si-IGBT pulse testing according to the device models; turning off SiC / SiHyS converter SiC-MOSFET and Si-IGBT, testing the hybrid switching tube voltage drop V F when the load current flows reversely; estimating the loss of the SiC / SiHyS converter based on a Matlab simulation model; calculating the junction temperature of the device according to the loss, and updating the SiC-MOSFET value and the Si-IGBT value in real time to obtain an accurate loss estimation value, and completing the estimation. The method solves the problems that the existing loss estimation method for the hybrid switching power is inaccurate, and the system loss cannot be calculated in real time in the entire power range.

The application belongs to the technical field of transformers, and discloses a linear phase-shifting transformer core loss calculation method, system, device and terminal, which is based on a classical trinomial loss separation model, three loss coefficients are calculated by using a least square method; the influence of local hysteresis loop, magnetic field non-sine, tooth slot effect and skin effect on the loss model and the loss coefficient is analyzed, the static magnetic density characteristics of the linear phase-shifting transformer are obtained based on finite element simulation calculation; the tangential magnetic density and the radial magnetic density of each characteristic point are separated, and Fourier analysis is carried out, the fundamental wave magnetic density and each harmonic magnetic density are substituted into the improved loss separation model. The core loss of the linear phase-shifting transformer in the stable operation state can be accurately calculated, the calculation precision is greatly improved, which can provide a reference for the efficient operation of the transformer, and has important significance for the optimization design of the linear phase-shifting transformer body and the realization of the minimum loss control of the multiple superposition inverter system of the linear phase-shifting transformer.

The present application provides a method for calculating the high-frequency circulating current of a motor simulator branch taking into account nonlinear factors. The inverter of the motor simulator adopts a cascade coupling topology structure of m-phase 2 parallel branches, including the following steps: S1, establishing an equivalent circuit model of the cascade coupling topology of any one-phase 2 parallel branch and obtaining model parameters; S2, determining an expression of the maximum branch high-frequency circulating current of the cascade coupling topology based on the equivalent circuit model of the cascade coupling topology; S3, obtaining the hysteresis loop of the magnetic ring of the cascade coupling topology, wherein the hysteresis loop includes a linear interval and a nonlinear interval; S4, correcting the expression of the maximum branch high-frequency circulating current of the cascade coupling topology based on the hysteresis loop. The method provided in the present application can effectively improve the calculation accuracy of the maximum branch high-frequency circulating current of the cascade coupling topology of the motor simulator.