888 results about "Current cycle" patented technology

The invention discloses a DBA management method and device in an FTTR scene and an optical line terminal. The method is applied to a PON MAC chip, wherein the PON MAC chip comprises a CPU unit and a logic unit. The method comprises the following steps that: a CPU (Central Processing Unit) determines the uplink service bandwidth of each AllocID in each sub-period in the current DBA period; the CPU unit takes at least part of the sub-periods as sub-distribution periods, and determines BWMap data of the first sub-distribution period and the second sub-distribution period; the CPU unit sends the length of the silent window, the BWMap data of the first sub-allocation period, the BWMap data of the second sub-allocation period and the total length of the current DBA period to the logic unit; the logic unit determines the number of the remaining sub-allocation periods in the current DBA, and takes the BWMap data of the second sub-allocation period as the BWMap data of each remaining sub-allocation period to obtain complete BWMap data in the current DBA period; and the logic unit sends the BWMap data of the current DBA period, so that the problem that the DBA cannot adapt to the use requirement of the FTTR scene is solved, and the low-delay requirement of the DBA is met.

The invention relates to the technical field of computers, and provides a game acceleration method, a game accelerator and a storage medium. The method comprises the following steps: in response to a game acceleration request initiated by a game client for an external service game, sending a network state detection packet set to an acceleration node group according to a preset detection period, and receiving a network state data packet set fed back by the acceleration node group; determining a current cycle packet loss rate and a next cycle packet loss rate corresponding to each acceleration node based on the network state detection packet set and the network state data packet set; determining a target transmission path and a target transmission mode based on the packet loss rate of the current period and the packet loss rate of the next period; and transmitting the original game data packet to a target game server through the target transmission path and the target transmission mode to complete game acceleration. According to the method, the network delay and the packet loss rate when the game user plays the outer clothing game can be effectively reduced, so that the game experience of the user is improved.

The invention relates to the technical field of servers, and discloses a method and device for executing heat dissipation operation, computer equipment and a storage medium, and the method comprises the steps: in a current period, obtaining actual temperature values corresponding to each heating component in multiple periods; inputting the actual temperature values corresponding to each heating part in the plurality of periods into a pre-constructed temperature prediction model to obtain a predicted temperature value of each heating part in the next period; according to the actual temperature value of the target heating component in the current period and the predicted temperature value of the target heating component in the next period, whether heat dissipation operation is executed on the target heating component or not is determined; when it is determined that the heat dissipation operation is executed on the target heating component, the actual temperature value of the target heating component in the current period is input into a pre-constructed heat dissipation control model, and a target control quantity is obtained; and according to the target control quantity, the heat dissipation operation quantity of the target heat dissipation component within the preset distance range of the target heating component is increased. According to the invention, resource waste can be reduced.

The invention relates to the technical field of industrial park intelligent monitoring, and particularly discloses a data acquisition and monitoring control method based on an intelligent industrial park, which comprises the following steps: acquiring key state data of equipment in real time, including operation time, operation temperature and operation power; an advanced signal processing algorithm is used for calculating an operation temperature abnormal index and an operation power abnormal index, the system can comprehensively evaluate the state of equipment and accurately judge whether slight or serious abnormal conditions exist or not based on detailed data analysis results, and the system can not only give out instant early warning notifications but also give out alarm information according to the serious abnormal conditions. According to the method, a machine learning model is adopted to predict the future operation state of the equipment, the equipment state abnormal coefficient in each future monitoring period is predicted based on the equipment state data in the current period, and classification and dynamic regulation and control of the equipment state are carried out according to a preset threshold value.

The invention discloses a response control method for a charging station participating in a low-voltage treatment scene, and the method comprises the following steps: S1, collecting the voltage data of a charging pile, calculating a deviation, and judging a low-voltage grade; s2, when the deviation is in a light interval, outputting reactive power support voltage in proportion; s3, when the deviation exceeds a heavy threshold value, reducing active power and starting V2G feedback; s4, constructing a graph structure model, and extracting inter-node power coupling and user behavior factors; s5, inputting the model into an improved prediction controller, predicting a future voltage state, and optimizing and outputting a current period power control value; s6, power adjustment is executed, and feedback power is slowly output in the V2G stage; and S7, comparing the control deviation with the behavior factor change, updating the node control priority, and feeding back for rolling optimization of the next period. According to the invention, while the charging regulation and control precision is improved, the user experience and the voltage stability are effectively considered, and the method is suitable for various low-voltage treatment scenes.

The invention provides a photovoltaic energy storage inverter power coordination control method based on an adaptive algorithm, and relates to the technical field of data processing, and the method comprises the steps: collecting the output power data of a photovoltaic module, the state data of an energy storage device, and the load demand data of a grid connection point, and carrying out the normalization processing of the data; calculating to obtain an initial power distribution parameter of the current period; respectively calculating a load change trend factor and a power fluctuation trend factor based on the load demand data and the output power data of the historical period, and coupling the load change trend factor and the power fluctuation trend factor to form a trend coupling factor; carrying out self-adaptive repair through a trend coupling factor; combining real-time grid-connected point load demand data with energy storage device state data to generate a target power distribution instruction and an energy storage charging and discharging adjustment instruction, and respectively issuing the instructions to an inverter control unit and an energy storage device control unit; according to the invention, the accuracy of the photovoltaic energy storage inverter power coordination control method is improved.

The invention discloses a motor control method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a three-phase current, converting the three-phase current into a total current of a current period in a static coordinate system, and extracting a high-frequency current of the current period from the total current; extracting a rotor position and a rotor rotating speed from the high-frequency current; compensating the rotor rotating speed by using the expected rotating speed to obtain a quadrature-axis expected current; converting the total current into a quadrature-direct axis coordinate system, extracting a fundamental frequency current from the quadrature-direct axis coordinate system, compensating the fundamental frequency current by using a quadrature axis expected current and a direct axis bias current to obtain a first expected voltage, superposing the first expected voltage and a direct axis high-frequency voltage, and performing coordinate system conversion on a superposition result by using a rotor position to obtain a second expected voltage; obtaining a second expected voltage under the static coordinate system; and the three-phase current of the current period is controlled according to the second expected voltage to drive the motor, so that the motor has more obvious salient polarity through the direct-axis bias current, and vector control over the electrode is achieved.

The invention discloses an inverter circuit, a maximum power tracking method thereof and energy storage inverter equipment, the inverter circuit comprises a full-bridge circuit, a transformer and a half-bridge circuit, the full-bridge circuit is connected to the half-bridge circuit through the transformer, the full-bridge circuit is connected with a photovoltaic module, and the half-bridge circuit is connected with an alternating current side; the maximum power tracking method comprises the following steps: acquiring the input power of the photovoltaic module in the current period and the input power of the photovoltaic module in the previous period, and the reference output voltage of the inverter in the first period; determining a voltage adjustment step length according to the power deviation and the voltage deviation, the power deviation being based on the input power of the current period and the previous period, and the voltage deviation being based on the input voltage of the photovoltaic module of the current period and the previous period; obtaining the reference output voltage of the current period according to the voltage adjustment step length and the reference output voltage of the previous period; and generating a driving signal according to the reference output voltage of the current period so as to control the inverter circuit. According to the invention, the maximum power point of the photovoltaic module can be tracked by the inverter circuit.

The invention relates to the field of air conditioner system control, in particular to an air conditioner energy saving method and device, electronic equipment and a storage medium. The method comprises the steps that the actual temperature of each partition of the current space is obtained in real time, the accuracy and instantaneity of temperature data are ensured, the set temperature of each partition in the current period is determined, namely the ideal temperature state that the space needs to reach is determined, and the target and direction of temperature regulation and control can be determined. According to the method, the difference between the actual temperature and the set temperature is utilized, the refrigerant flow and the refrigerant temperature needed by each partition are calculated, and a scientific basis is provided for time arrangement of temperature regulation and control by predicting the target period needed by each partition from the actual temperature to the set temperature. And according to the refrigerant flow and the refrigerant temperature corresponding to each partition, the refrigerant opening degree valve is adjusted in the corresponding target period, so that the energy of the air conditioner is further saved on the premise of ensuring the user experience in the current space.

The invention relates to the technical field of temperature control, in particular to a temperature adjusting method for a liquid cooling over-charging power source module. The method comprises the steps that temperature values and parameter values are collected, and temperature stability is obtained according to the temperature value difference in a period and the difference with the standard temperature; classifying the periods according to the temperature stability, clustering the screened periods, obtaining the influence degree of parameters on the temperature stability according to the differences between the periods and the temperature stability and parameter values in the clustering clusters, and clustering all the periods to screen a target clustering cluster based on the obtained importance of each parameter; obtaining a reference weight according to the similarity and the temperature stability of the periods in the target cluster, and obtaining a proportionality coefficient adjustment parameter through the proportionality coefficient difference and the reference weight; and acquiring the proportionality coefficient of the current period based on the proportionality coefficient adjusting parameter, and controlling the temperature value according to the proportionality coefficient. According to the invention, the precision of temperature control is improved.

The invention relates to a biLSTM-based SOC-SOH joint estimation method and system. The method comprises the following steps of obtaining voltage, temperature, current, SOC and SOH time sequence data of an energy storage device in a current cycle period; inputting the voltage and temperature time sequence data into a temperature and voltage prediction sub-network, and outputting a voltage prediction curve and a temperature prediction curve of a next cycle period; inputting the voltage prediction curve, the temperature prediction curve and the current time sequence data into an SOC prediction sub-network, and outputting an SOH prediction curve; and inputting the voltage prediction curve, the temperature prediction curve, the current time sequence data and the SOH prediction curve into an SOH prediction sub-network, and outputting an SOC prediction curve. Compared with the prior art, the method has the advantages of high estimation precision and the like.

The invention discloses a multi-pump operation liquid cooling system and a pump switching method, and the pump switching method comprises the steps: obtaining the real-time working information of each circulating pump, including the real-time gear information, the real-time operation duration, the real-time step frequency and the current cycle period count; determining a gear coefficient based on the real-time gear information, and obtaining a step correction coefficient; on the basis of the gear coefficient, the real-time operation duration, the step correction coefficient and the real-time step frequency, the accumulated loss value of each circulating pump is determined; an accumulated threshold value is obtained, the accumulated loss value of each circulating pump is compared with a preset accumulated threshold value, and a circulating pump switching instruction is generated according to a comparison result; according to the pump switching method, the operation parameters of the circulating pump are monitored in real time to calculate the accumulated loss value, the service life loss can be accurately evaluated, the service life balance of the pump set is achieved, the service life asymmetry caused by timing switching is avoided, the overall service life is prolonged, the switching of the circulating pump better fits the actual operation condition, and the adaptability and efficiency of the liquid cooling system are improved.

Disclosed techniques relate to next fetch predictor circuitry configured to operate in conjunction with a trace cache. The trace cache circuitry may identify and store traces of instructions based on predicted directions of one or more control transfer instructions. Trace next fetch predictor circuitry may predict a next fetch address based on a current fetch address for a current cycle, which may include predicting a next fetch address following execution of a first trace stored in the trace cache circuitry. The first trace may include multiple fetch groups and multiple control transfer instructions. Arbitration circuitry may select from among multiple predictors and the trace next fetch predictor may have priority in response to a trace cache hit. Disclosed techniques may advantageously improve overall fetch bandwidth in the context of trace cache hits.

The invention relates to the technical field of energy storage analysis of new energy electric vehicles, and provides an energy storage data analysis method and system for a new energy electric vehicle. The method comprises the steps of obtaining and collecting electric energy storage data of a new energy electric vehicle in a current period, analyzing the electric energy storage data, determining the energy storage change condition of an energy storage system of a new energy battery in the period, and determining the working state of the energy storage system of the new energy electric vehicle according to the energy storage change condition, the cycle includes a charging process and at least one discharging process. The energy storage change condition of the user in the period is analyzed by taking the charging and discharging behaviors of the user as the period, so that the individuation degree of energy storage data analysis is improved, and the accuracy of energy storage analysis is further improved.

A production schedule estimation method and a production schedule estimation system are provided. The production schedule estimation method includes the following steps. Current-day work-in-process data, machine group cycle time data of a machine group, and productivity data of the machine group are obtained. The current-day work-in-process data, the cycle time data of the machine group, and the productivity data of the machine group are inputted into a prediction model. Current-day cycle time data and a current-day move volume for each of multiple stations in the machine group are calculated through the prediction model. And, current-day move data is calculated according to the current-day cycle time data and the current-day move volume for each of the multiple stations in the machine group.

The invention discloses an electric bicycle health state evaluation method, system and device and a storage medium, and belongs to the field of lithium battery electric bicycles, and the method comprises the following steps: obtaining historical SOC data and current SOC data of an electric bicycle battery; calculating the current cycle index of the battery, and calculating the habitual charging depth of the user; obtaining the charging nominal capacity of the battery, and calculating to obtain a capacity attenuation empirical model; calculating a mean health state under the current cycle index; the current charging depth and the current charging capacity are calculated, whether the current charging depth meets the calibration condition or not is judged, and if yes, the average health state is calibrated through the charging nominal capacity and the current charging capacity, and the current cycle number is corrected; and if the calibration condition is not met or the calibration is completed, outputting the average health state of the electric bicycle. According to the invention, the battery health state can be monitored in an electric bicycle scene, a user is helped to know the health degree of the battery, and the use safety of the battery is improved.

The invention relates to a method for predicting the residual life of a power battery, and belongs to the technical field of batteries, and the method comprises the steps: carrying out the fusion of historical data and real-time data of a target power battery, and obtaining fusion data; obtaining an initial humidity coefficient and an initial charge-discharge rate coefficient based on humidity fluctuation in the fusion data and the real-time data; introducing the temperature difference of the target power battery at the current cycle index into a first relation to determine an initial temperature coefficient; obtaining the predicted loss capacity and the actual capacity of the target power battery in the current cycle index; and predicting the residual life of the target power battery in the next cycle index based on the initial humidity coefficient, the initial charge-discharge rate coefficient, the initial temperature coefficient, the predicted loss capacity, the actual capacity, the humidity fluctuation and the charge-discharge rate. According to the method, the temperature, humidity and charge-discharge rate of the target power battery are used as influence factors of the battery life for calculation, so that the accuracy of predicting the residual life of the battery is improved.

The invention relates to the technical field of computers, and discloses a fault alarm method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining identification information and a starting dependency sequence of each service operated by a main node in a current period; obtaining the service state of each service according to the identification information of each service and the starting dependency sequence; when it is determined that the service state of the target service is abnormal or the service state of the target service is not obtained, a configuration file of the target service in the current period and a file content index value of the target service in a previous period corresponding to the current period are obtained according to the identification information of the target service, and the target service is any service; determining the fault type of the target service according to the configuration file of the target service in the current period and the file content index value of the target service in the previous period; and generating an alarm notification according to the identification information of the target service and the fault type, and sending the alarm notification to the client. According to the invention, the troubleshooting efficiency can be improved.

Disclosed herein are systems and methods for self-isolation of power-management integrated circuits (PMICs) of memory modules under and in response to fault conditions. In an embodiment, a PMIC is operably engaged with a memory module that is operably engaged with a platform. The memory module includes a non-volatile-memory block having a power supply controlled by the PMIC. The PMIC has a critical-fault signal pin that can be asserted to shut down the platform. The PMIC determines whether at least one critical fault occurred during a prior cycle, and also determines whether a critical fault occurs during a bootup sequence during a current cycle. Based on determining that a prior-cycle critical fault occurred and that a critical fault occurs during the bootup sequence, the PMIC sets a critical-fault indicator corresponding to the current critical fault; powers down the power supply; and does not assert the critical-fault signal pin.

The invention discloses a fuse test method and device and a readable medium. The method comprises the following steps: outputting a current required by a test through a direct-current power supply module; the electronic load module is matched with the direct-current power supply module to simulate various working condition tests, wherein the working condition tests comprise a fusing time test, a durability test, a pulse test, a current gradient test and a current circulation impact test; man-machine interaction including function setting and data display is carried out through the touch screen module; the operation of each module is controlled through the middle computer module, and an external communication interface connected with an upper computer is provided. By simulating various working conditions, the performance of the fuse under different conditions can be comprehensively evaluated, and the test accuracy and efficiency are improved.

The invention discloses a self-adaptive adjustment method and system for the die-casting temperature of a die-casting die, and relates to the field of die-casting temperature adjustment, and the method comprises the steps: synchronously obtaining a real-time temperature data flow and a real-time control output flow of the die-casting die, and constructing a time sequence data model capable of representing the internal thermal dynamic characteristics of the die-casting die; on the basis, a depth time sequence prediction model is introduced, and the future temperature response track of the system is accurately deduced. Furthermore, process targets such as a temperature set value are fused, and a model predictive control framework is utilized to carry out prospective rolling optimization on future multi-step control output so as to solve an optimal control instruction sequence. And finally, taking the first instruction of the sequence as the actual control output of the current period. Therefore, the advanced and accurate output of the controlled quantity can be realized, and the thermal hysteresis effect is effectively overcome, so that the high-precision and high-stability self-adaptive adjustment of the die-casting temperature is realized.

The invention relates to the technical field of battery management, in particular to a lithium battery remaining life prediction method and device, terminal equipment and a storage medium, and the method comprises the steps: determining the working parameters and environmental parameters of a target battery and the cell type of the target battery; determining a corresponding pre-constructed life prediction model according to the type of the battery cell; the life prediction model is constructed according to the working parameters and the environmental parameters; and determining the current cycle charging and discharging times of the target battery, and obtaining the residual life of the target battery according to the life prediction model, the cycle charging and discharging times, the environmental parameters and the working parameters. Therefore, more relevant factors are considered in the life prediction of the lithium battery, the prediction result is more accurate, and the prediction process is more convenient.

The invention relates to the technical field of computers, and provides a power supply method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the current load data of electric equipment in real time in a current period; on the basis of the current load data, predicting target power of the electric equipment in the next period by adopting a mode of combining a load prediction model and statistical analysis; adjusting power output of a power supply system to the electric equipment based on the target power of the electric equipment; wherein the load prediction model is obtained through training by taking historical load data of a first period in historical data of the electric equipment as a sample and taking historical detection power of a second period in the historical data as a label based on a machine learning model, and the second period is the next period of the first period. According to the invention, the target power of the electric equipment can be accurately and dynamically predicted according to the current load data, so that the power supply output of the power supply system is dynamically adjusted.

The invention discloses a phase current reconstruction method for high-modulation-ratio three-resistance sampling of a permanent magnet synchronous motor. The phase current reconstruction method comprises the following steps: S1, obtaining a preliminary sampling frame; s2, generating boundary input data; s3, initializing a rule weight parameter set; s4, obtaining a weighted candidate current interval set; s5, performing cross check on the weighted candidate current interval set and the output of the comparator array, eliminating inference branches which do not conform to the polarity and amplitude limit of hardware, obtaining a candidate current interval set subjected to boundary reduction, and fusing the candidate current interval set with a reconstructed three-phase current vector of a previous pulse width modulation period to generate a reconstructed three-phase current vector of a current period; and S6, periodically and circularly executing the steps S1 to S5, and completing real-time closed-loop control of the phase current reconstruction method for high-modulation-ratio three-resistance sampling of the permanent magnet synchronous motor after the error of the reconstructed three-phase current vector is continuously kept to be smaller than a preset value under the high-modulation-ratio driving condition. According to the invention, steady-state fitting in the current estimation process is realized, and abrupt change points are prevented from generating abnormal output.

The invention relates to the technical field of power grid regulation and control, in particular to a power grid elastic balance planning regulation and control method based on supply and demand balance. Obtaining an electric energy fitting curve according to the electric energy characteristic sequence of the historical period; obtaining a change coefficient according to the electric energy difference characteristics of the electric energy fitting curve in adjacent time periods before and after the current adjustment moment; obtaining an electric energy estimated value according to the electric energy characteristic sequence and the change coefficient of the current period; obtaining a fitting change factor according to the electric energy change characteristics of the electric energy fitting curve before the current adjustment moment; obtaining an actual change factor according to the electric energy change characteristics of the electric energy characteristic sequence of the current period before the current adjustment moment; and obtaining a correction coefficient according to the fitting change factor and the actual change factor. The electric energy predicted value is obtained according to the correction coefficient and the electric energy estimated value; power supply matching is carried out according to the electric energy predicted values of the power generation area and the power utilization area, and the power grid supply-demand balance regulation accuracy is improved.

The invention discloses a position-free sensing method for a joint module based on rotating speed estimation and virtual Z correction. The method comprises the following steps: firstly, acquiring three-phase current of a permanent magnet motor for a joint module, and acquiring d-axis estimated current of a current period based on a d-axis current model in combination with a state quantity of the permanent magnet motor in a previous control period; based on the d-axis estimated current, constructing a rotating speed estimator taking the d-axis estimated current error as a sliding mode surface to obtain the estimated rotating speed of the motor rotor; integrating the estimated rotating speed, and combining with the initial position of the rotor to obtain the estimated position of the motor rotor in the current period; at the same time, at the zero crossing point of the stator phase current, the estimation position is forcibly corrected to a predetermined electrical angle corresponding to the zero crossing point so as to eliminate the integral error. The invention aims to directly estimate the rotating speed without depending on any intermediate signal, and simulate the correction mechanism of a mechanical sensor to eliminate the estimation error, thereby realizing high-performance noise-free full-speed-domain position-free sensing control.

The invention provides an I / O resource management method for a distributed system and related equipment. The distributed system comprises a plurality of nodes, and the plurality of nodes share one storage system. The method comprises the following steps: according to a preset period duration, periodically obtaining respective I / O resource usage amounts of a plurality of nodes for the storage system based on a previous period, and pre-estimating an I / O resource application amount for the storage system in a current period; obtaining the total amount of pre-configured I / O resources for the storage system in the current period; and based on the respective I / O resource application amounts of the plurality of nodes, respectively allocating corresponding I / O resource allocation amounts to the plurality of nodes from the total I / O resource amounts, so that the nodes access the storage system in the current period based on the allocated I / O resource allocation amounts.

The invention relates to a method for calculating matrix multiplication, an artificial intelligence chip, a calculation device, a medium and a program product. The method comprises the following steps of: accumulating a calculation result of a current cycle calculation and a calculation result of a previous cycle calculation of matrix multiplication executed in a thread bundle group granularity by utilizing a buffer which is configured in a calculation core and is used for accumulation operation; determining whether the last cycle calculation of the matrix multiplication performed at the thread bundle group granularity is completed; and in response to determining that the last cycle computation of the matrix multiplication performed at the thread bundle group granularity is completed, writing the computation results accumulated via the buffer to the register file. According to the invention, the write bandwidth of the register and the occupation of the register space can be obviously reduced.

The invention relates to a slitting deviation rectifying method, a slitting deviation rectifying device and a slitting deviation rectifying system for a battery pole piece. The slitting deviation rectifying method for the battery pole piece comprises the steps that slitting positioning is conducted on a plurality of corresponding frames of coated pole piece images after slitting according to deviation rectifying reference edges of the coated pole piece images before slitting, and the transverse distance of a slitting device in the current period is obtained; whether the transverse distance of the slitting device in the current period is abnormal or not is detected; if no abnormity exists, comprehensive deviation correction calculation is conducted on the front face expected position and the back face expected position of the slitting device and the transverse distance of the slitting device in the current period, the current comprehensive deviation correction amount is obtained, a deviation correction signal is sent to the slitting device according to the comprehensive deviation correction amount, and deviation correction is conducted on the slitting device; and finally, according to a feedback signal after the deviation correction of the slitting device is completed, slitting positioning is carried out again. The slitting deviation rectifying method for the battery pole piece has the advantages that material waste is remarkably reduced, and deviation rectifying accuracy is effectively improved.

The invention provides a zero-voltage starting control module, a driving circuit and an active clamping converter, and the module comprises a timing unit which carries out the timing of a first time length; the time length acquisition unit is used for acquiring the time length from the turn-off of the clamping tube to the complete release of the secondary inductive current of the transformer to obtain a second time length; the comparison unit is used for comparing the first duration with the second duration; and the dead time adjusting unit is used for adjusting the conduction time and the first duration of the clamping tube in the next period based on the comparison result of the current period so as to realize self-adaptive zero-voltage starting control. The circuit is realized by adopting a digital circuit, accurate control can be realized, the control range is relatively wide, zero-voltage conduction control is dynamically realized, the system efficiency is improved, the use of a capacitor in an analog circuit is reduced, and the area cost of a chip is reduced.