Abstract: Method for analyzing and predicting state of health of a lithium battery includes: collecting battery data within a predetermined time interval, where the battery data comprises at least battery operating time, current, and voltage; determining a target area based on the battery data; establishing a relationship between a cumulative capacity of the target area and the state of health of the battery; correlating the number of cycles in the current state of the battery with the state of health of the battery using the cumulative capacity of the target area and determining a relationship between the number of cycles and the state of health of the battery; and predicting the state of health of the battery in the future according to the relationship between the number of cycles and the state of health of the battery. The method is simple and easy to operate, and practical as well.

Abstract: A heterogeneous computing terminal for task scheduling is provided, including a processing unit and multiple computing units. The heterogeneous computing terminal generates a task scheduling strategy. The target computing unit acquires a target upgrade program, is upgrade based on the target upgrade program, processes a target task and sends a processing result to the processing unit. The processing unit combines processing results sent by multiple target computing units to obtain a processing result of an initial task set. The heterogeneous computing terminal can upgrade the computing unit online, that is, dynamically update the computing unit, thereby greatly expanding the versatility of the computing unit of hardware. Scheduling strategy adapted to the task can be generated, and the computing unit can dynamically provide better task processing capabilities. The computing efficiency of the heterogeneous computing terminal is improved.

Abstract: A method for calculating a state of charge of a battery is provided. The method includes: estimating a first state of charge of the battery by using a first state of charge estimation algorithm; estimating a second state of charge of the battery by using a second state of charge estimation algorithm; determining a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge based on state data of the battery; and calculating the state of charge of the battery based on the first state of charge and the first weight, and the second state of charge and the second weight. With method for calculating a state of charge of a battery in the present disclosure, the accuracy of calculating the state of charge of the battery can be improve d with a lower computation cost.

Abstract: A method and a device for forecasting an electric load, an electronic device, and a computer-readable storage medium are provided. The method includes: acquiring historical load data prior to a forecast date; generating a load sequence based on the historical load data; performing variational mode decomposition on the load sequence, to obtain multiple intrinsic mode components and a residual that are corresponding to the load sequence; and inputting the multiple intrinsic mode components and the residual into respective forecasting models, and determining a load value on the forecast date based on forecasting results of all the forecasting models. With the method and the device, the electronic device, and the computer-readable storage medium, the load sequence is decomposed based on the variational mode decomposition, so that more dimensional feature information in the load sequence can be mined. Moreover, the residual is also used as valid data.

Abstract: The invention provides a method and system for identifying electrochemical model parameters based on capacity change rate. The method includes: acquiring operating data from an actual operation process of a lithium battery and cleaning an actual operating data set from the operating data; generating a simulated operating data set through simulation of a preset electrochemical model; performing parameter identification based on a preset first loss function, the actual operating data set, and the simulated operating data set; calculating capacity convergence coefficient; comparing capacity convergence coefficient with a preset convergence threshold value; when greater than the preset convergence threshold value, regenerating the simulated operating data set; and when not greater than the preset convergence threshold value, outputting an electrochemical model parameter set as a parameter identification result.

Abstract: A thermal-runaway warning method, system, and terminal for a power station are provided. The method comprises: obtaining collected data of a battery module comprised in the power station, wherein the collected data comprises collected temperature values of the battery module collected by temperature measuring devices; normalizing the collected data to obtain a standard dataset; training a CNNLSTM-based temperature predicting model based on the standard dataset to obtain a trained CNNLSTM-based temperature predicting model; and obtaining a predicted temperature value of the battery module within an output time window based on the trained CNNLSTM-based temperature predicting model, and determining whether there is a risk of thermal runaway in the power station based on the predicted temperature value.

Abstract: A hot-plugging edge computing system includes at least an elastic database, a data processing module, and hot-plugging computing modules. The elastic database is configured to store data through an SSD array with a configurable number of SSDs. The data processing module is connected to the elastic database and each of the hot-plugging computing modules, and controls data storage in the elastic database, monitors and assigns a task to each of the hot-plugging computing modules. Each of the hot-plugging computing modules performs data computing based on the corresponding task assigned by the data processing module, and returns a computing result to the corresponding data processing module.

Abstract: The invention discloses a method, a system, a device, and a medium for detecting a battery state of health. The method includes extracting a target curve segment from a first charging characteristic curve of a battery under test; and determining, according to a corresponding relation between characteristic parameters of the target curve segment and the battery state of health, the battery state of health matching the characteristic parameters of the target curve segment, and determining the battery state of health as the battery state of health of the battery under test. By utilizing said corresponding relation as the calculation basis, the invention improves the reliability and accuracy of the detection of battery state of health detection. The invention also tracks instances of abusive conditions that accelerate battery aging, assessing whether such conditions accelerate battery degradation and issuing warnings accordingly.

Abstract: A method for analyzing battery life degradation, a storage medium, and an electronic device are provided. The method includes: obtaining battery data of a device, where the battery data includes a voltage and a current of a battery of the device; estimating an open circuit voltage of the battery based on the battery data; establishing a function curve between a state of charge and the open circuit voltage of the battery; extracting a life degradation curve based on the function curve; and performing life degradation analysis on the battery based on the life degradation curve. In the present disclosure, a dQ/dV curve of the battery can be accurately extracted under complex working conditions, thereby ensuring accuracy of the battery life degradation analysis, and achieving desirable practical applicability under complex working conditions.

Abstract: A method for estimating an internal resistance of a lithium battery, a storage medium, and an electronic device are provided. The method includes: sampling a current and a voltage of the lithium battery at a preset sampling interval; inputting the current and the voltage of the lithium battery to an internal resistance estimation equivalent circuit model, determining to-be-estimated parameters of the model, and determining expressions of an open circuit voltage and an internal resistance of the battery; obtaining a range of each of the to-be-estimated parameters of the model based on a memory factor of the model; and inputting the range of each of the to-be-estimated parameters to an internal resistance distribution model to obtain a total internal resistance of the battery, and determining a distribution of the total internal resistance by repeatedly running the internal resistance distribution model, to obtain different estimated values of the total internal resistance.

Abstract: The invention provides a Kalman filter-based SOC estimation method, system and medium, and an electronic device therewith. The method includes extracting a cell voltage of a battery pack to calculate a terminal voltage, and matching the terminal voltage in a preset lookup table to obtain an initial value of the SOC; calculating an initial capacity of the battery pack based on the initial value of the SOC, and calculating a state value of the SOC and an observed value of the SOC in an interval period based on the initial capacity; calculating a Kalman gain based on the state value of the SOC and the observed value of the SOC, and updating an estimated value of the SOC based on the Kalman gain.

Abstract: The invention provides method, apparatus and storage medium for adjusting the charging-discharging efficiency ratio of an energy storage power station.

Abstract: The invention provides an apparatus and a method for managing an energy storage power station. The apparatus includes: a first main control module communicatively connected with a battery cluster management unit (BCMU) for collecting battery information of the first priority in an energy storage power station system, and performing protection and control on the energy storage power station system according to the battery information of the first priority; and a second main control module communicatively connected with the first main control module and the BCMU, respectively, for collecting battery information of the second priority in the energy storage power station system. The second main control module operably transmits the collected battery information of the second priority to the first main control module. The first main control module operably manages the battery information of the first priority and the battery information of the second priority in a unified manner.

Abstract: The invention provides methods, systems and terminal devices for analyzing a state of a battery pack based on cell parameters thereof. The method comprises acquiring cell voltages of each cell and total voltages of the battery pack within a preset time; performing data cleaning on the cell voltages and the total voltages of the battery pack; calculating a voltage standard score of the cells based on the cell voltages after data cleaning, and calculating a voltage standard score of the battery pack based on the total voltages after data cleaning; and performing a time-domain analysis on the voltage standard score of each cell and/or the voltage standard score of the battery pack.

Abstract: The invention provides methods, devices and non-transitory tangible computer-readable storage media for estimating a state of charge of a battery and extracting a charging curve of the battery. The method for estimating the state of charge of the battery includes estimating a first state of charge of the battery; determining a charging curve that conforms to the present charging scenario, wherein the present charging scenario is characterized by at least one of parameters including an ambient temperature, a charging rate, an internal resistance, a state of health, a lifespan, and an open circuit voltage of the battery; and correcting the first state of charge according to the charging curve to obtain a final state of charge of the battery.

Abstract: The invention provides a method, a system and a terminal device for analyzing states of battery packs in a battery cluster. The method includes acquiring cell voltages of each battery pack in the battery cluster within a preset time; performing data cleaning on the acquired cell voltages; calculating a voltage standard score of each cell based on the cell voltages after data cleaning; calculating a mean value and a standard deviation of said voltage standard score; for each battery pack, plotting scattered points based on the mean value and the standard deviation, and performing closed curve fitting to the scattered points to obtain a closed curve; and analyzing the state of the battery pack based on the closed curve.