Battery power state calculation method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of batteries, in particular to a battery power state calculation method and device, electronic equipment and a storage medium. Acquiring historical maximum charging current and historical maximum discharging current corresponding to a plurality of historical moments before the current moment corresponding to the target battery; predicting a current predicted maximum charging current corresponding to the current moment based on each historical maximum charging current; determining a target maximum charging current corresponding to the current moment based on the current predicted maximum charging current and a preset battery model; predicting the current predicted maximum discharge current corresponding to the current moment based on each historical maximum discharge current; based on the current predicted maximum discharge current and a preset battery model, determining a target maximum discharge current corresponding to the current moment; and determining the power state of the target battery based on the target maximum charging current and the target maximum discharging current. And the accuracy of the determined power state of the target battery is ensured.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a battery power state calculation method, device, electronic equipment and storage medium. Background Art

[0002] Accurate prediction of the battery's state of power (SOP) plays an important role in the vehicle's starting, acceleration, climbing, and emergency braking, and is the basis for safe and reliable vehicle operation. Currently, in BMS, the common SOP estimation method is the SOC-temperature lookup table, which is usually provided by the battery manufacturer. This open-loop calculation method is simple and easy to implement, but as the current polarization of the battery accumulates, the SOC-temperature table will become less and less accurate. Therefore, the estimated SOP is not accurate.

[0003] Therefore, how to accurately calculate the power state of the battery has become an urgent problem to be solved. Summary of the invention

[0004] In view of this, the present invention provides a battery power state calculation method, device, electronic device and storage medium to solve the problem of how to accurately calculate the power state of the battery.

[0005] In a first aspect, the present invention provides a method for calculating a battery power state, the method comprising:

[0006] Obtain the historical maximum charging current and the historical maximum discharging current corresponding to multiple historical moments before the current moment corresponding to the target battery;

[0007] Based on each historical maximum charging current, predict the current predicted maximum charging current corresponding to the current moment;

[0008] Based on the current predicted maximum charging current and the preset battery model, determine the target maximum charging current corresponding to the current moment;

[0009] Based on each historical maximum discharge current, predict the current predicted maximum discharge current corresponding to the current moment;

[0010] Based on the current predicted maximum discharge current and the preset battery model, determine the target maximum discharge current corresponding to the current moment;

[0011] Based on the target maximum charge current and the target maximum discharge current, a target battery power state is determined.

[0012] The battery power state calculation method provided in the embodiment of the present application obtains the historical maximum charging current and the historical maximum discharging current corresponding to the multiple historical moments before the current moment corresponding to the target battery; based on each historical maximum charging current, the current predicted maximum charging current corresponding to the current moment is predicted, and because the current predicted maximum charging current corresponding to the current moment is predicted based on each historical maximum charging current, the amount of calculation can be reduced, and the accuracy of the predicted current predicted maximum charging current is guaranteed. Then, based on the current predicted maximum charging current and the preset battery model, the target maximum charging current corresponding to the current moment is determined, and the preset battery model is taken into account, thereby ensuring the accuracy of the calculated target maximum charging current. Based on each historical maximum discharge current, the current predicted maximum discharge current corresponding to the current moment is predicted, which reduces the amount of calculation and ensures the accuracy of the predicted current predicted maximum discharge current. Then, based on the current predicted maximum discharge current and the preset battery model, the target maximum discharge current corresponding to the current moment is determined, ensuring the accuracy of the determined target maximum discharge current. Based on the target maximum charging current and the target maximum discharge current, the power state of the target battery is determined, ensuring the accuracy of the determined power state of the target battery.

[0013] In an optional implementation, based on each historical maximum charging current, predicting the current predicted maximum charging current corresponding to the current moment includes:

[0014] The historical maximum charging currents are input into a preset prediction model, which extracts features of the historical maximum charging currents and outputs the current predicted maximum charging current.

[0015] The battery power state calculation method provided in the embodiment of the present application inputs each historical maximum charging current into a preset prediction model, the preset prediction model extracts features of each historical maximum charging current, and outputs the current predicted maximum charging current, thereby ensuring the accuracy of the output current predicted maximum charging current.

[0016] In an optional implementation, determining a target maximum charging current corresponding to the current moment based on the current predicted maximum charging current and a preset battery model includes:

[0017] Based on the current predicted maximum charging current, calculating a first maximum value of the predicted maximum charging current and a first minimum value of the predicted maximum charging current corresponding to the current predicted maximum charging current in a preset confidence interval;

[0018] Based on the predicted first maximum value of the maximum charging current, the predicted first minimum value of the charging current and a preset battery model, a target maximum charging current corresponding to the current moment is determined.

[0019] The battery power state calculation method provided in the embodiment of the present application calculates the first maximum value of the predicted maximum charging current and the first minimum value of the predicted maximum charging current corresponding to the current predicted maximum charging current in a preset confidence interval based on the current predicted maximum charging current, thereby ensuring the accuracy of the determined first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current. Based on the predicted first maximum value of the maximum charging current and the predicted first minimum value of the charging current and the preset battery model, the target maximum charging current corresponding to the current moment is determined, taking into account the preset battery model, thereby ensuring the accuracy of the determined target maximum charging current corresponding to the current moment. This avoids determining the predicted current predicted maximum charging current as the target maximum charging current, resulting in inaccuracy in the power state of the calculated target battery.

[0020] In an optional implementation, determining a target maximum charging current corresponding to the current moment based on the predicted first maximum value of the maximum charging current and the predicted first minimum value of the charging current and a preset battery model includes:

[0021] Determine a first maximum value of the predicted maximum charging current as a first candidate maximum charging current;

[0022] Based on the preset battery model, calculate the surface concentration of the positive electrode solid phase particles at the target battery separator corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the separator, and / or the negative electrode side reaction overpotential at the separator, and / or the terminal voltage;

[0023] Detecting whether the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet corresponding preset constraints;

[0024] If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet the corresponding preset constraints, the first candidate maximum charging current is determined as the target maximum charging current.

[0025] The battery power state calculation method provided in the embodiment of the present application determines the first maximum value of the predicted maximum charging current as the first candidate maximum charging current. Then, based on the preset battery model, the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage are calculated to ensure the accuracy of the calculated surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage. Detect whether the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints. If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet the corresponding preset constraints, then the first candidate maximum charging current is determined as the target maximum charging current. This ensures that the first candidate maximum charging current meets the battery characteristics of the target battery, thereby ensuring the accuracy of the determined target maximum charging current.

[0026] In an optional embodiment, the method further includes:

[0027] If at least one of the battery parameters of the positive electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current does not meet the corresponding preset constraint condition, then half of the sum of the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the second candidate maximum charging current;

[0028] Based on the preset battery model, calculate the surface concentration of the positive electrode solid phase particles at the target battery separator corresponding to the second candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the separator, and / or the negative electrode side reaction overpotential at the separator, and / or the terminal voltage;

[0029] Detecting whether the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current all meet corresponding preset constraints;

[0030] If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current all meet the corresponding preset constraints, then detect whether the first charging current difference between the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference;

[0031] If a first charging current difference between the second candidate maximum charging current and the predicted first minimum charging current is smaller than a preset charging current difference, the second candidate maximum charging current is determined as the target maximum charging current.

[0032] The battery power state calculation method provided in the embodiment of the present application, if there is at least one battery parameter of the positive electrode solid phase particle surface concentration at the diaphragm corresponding to the first candidate maximum charging current, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage that does not meet the corresponding preset constraint conditions, then half of the sum of the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the second candidate maximum charging current, thereby ensuring the accuracy of the determined second candidate maximum charging current. Based on the preset battery model, the positive electrode solid phase particle surface concentration at the diaphragm of the target battery corresponding to the second candidate maximum charging current, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage are calculated; the positive electrode solid phase particle surface concentration at the diaphragm corresponding to the second candidate maximum charging current, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage are detected to see whether they all meet the corresponding preset constraint conditions, thereby detecting whether the second candidate maximum charging current meets the characteristics of the target battery. If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current all meet the corresponding preset constraints, then it is detected whether the first charging current difference between the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference. If the first charging current difference between the second candidate maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference, then the second candidate maximum charging current is determined as the target maximum charging current, thereby ensuring the accuracy of the determined target maximum charging current and satisfying the characteristics of the target battery.

[0033] In an optional embodiment, the method further includes:

[0034] If at least one of the battery parameters including the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current does not meet the corresponding preset constraint conditions, the second candidate maximum charging current is determined as the second maximum value of the predicted maximum charging current; and one-half of the sum of the second maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the third candidate maximum charging current;

[0035] Detecting whether the third candidate maximum charging current meets a preset condition;

[0036] If the third candidate maximum charging current meets the preset condition, the third candidate maximum charging current is determined as the target maximum charging current.

[0037] The battery power state calculation method provided in the embodiment of the present application is that if there is at least one battery parameter in the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the second candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage that does not meet the corresponding preset constraint conditions, then the second candidate maximum charging current is determined as the second maximum value of the predicted maximum charging current; and one-half of the sum of the second maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the third candidate maximum charging current, thereby ensuring the accuracy of the determined third candidate maximum charging current. Detect whether the third candidate maximum charging current meets the preset conditions; if the third candidate maximum charging current meets the preset conditions, then determine the third candidate maximum charging current as the target maximum charging current, thereby ensuring the accuracy of the determined target maximum charging current and meeting the preset requirements.

[0038] In an optional embodiment, the method further includes:

[0039] If the first charging current difference is greater than or equal to the preset charging current difference, the second candidate maximum charging current is determined as the second minimum value of the predicted maximum charging current; and one-half of the sum of the first maximum value of the predicted maximum charging current and the second minimum value of the predicted charging current is determined as the fourth candidate maximum charging current;

[0040] Detecting whether a fourth candidate maximum charging current meets a preset condition;

[0041] If the fourth candidate maximum charging current meets the preset condition, determining the fourth candidate maximum charging current as the target maximum charging current;

[0042] If neither the third candidate maximum charging current nor the fourth candidate maximum charging current meets the preset conditions, the last candidate maximum charging current is determined as the target maximum charging current until the second difference between the predicted current maximum value and the predicted current minimum value is calculated to be less than the preset charging current difference.

[0043] The battery power state calculation method provided in the embodiment of the present application is that if the first charging current difference is greater than or equal to the preset charging current difference, the second candidate maximum charging current is determined as the second minimum value of the predicted maximum charging current; and one-half of the sum of the first maximum value of the predicted maximum charging current and the second minimum value of the predicted charging current is determined as the fourth candidate maximum charging current, thereby ensuring the accuracy of the determined fourth candidate maximum charging current. Detect whether the fourth candidate maximum charging current meets the preset conditions; if the fourth candidate maximum charging current meets the preset conditions, the fourth candidate maximum charging current is determined as the target maximum charging current, thereby ensuring the accuracy of determining the fourth candidate maximum charging current as the target maximum charging current. If both the third candidate maximum charging current and the fourth candidate maximum charging current do not meet the preset conditions, then until the second difference between the current maximum value of the predicted charging current and the current minimum value of the predicted charging current is calculated to be less than the preset charging current difference, the last candidate maximum charging current is determined as the target maximum charging current, thereby ensuring the accuracy of the determined target maximum charging current.

[0044] In a second aspect, the present invention provides a battery power state calculation device, the device comprising:

[0045] An acquisition module, used to acquire the historical maximum charging current and the historical maximum discharging current corresponding to multiple historical moments before the current moment corresponding to the target battery;

[0046] A first prediction module, used for predicting a current predicted maximum charging current corresponding to a current moment based on each historical maximum charging current;

[0047] A first determination module, configured to determine a target maximum charging current corresponding to a current moment based on a current predicted maximum charging current and a preset battery model;

[0048] A second prediction module is used to predict a current predicted maximum discharge current corresponding to a current moment based on each historical maximum discharge current;

[0049] A second determination module, used to determine a target maximum discharge current corresponding to a current moment based on a current predicted maximum discharge current and a preset battery model;

[0050] The third determination module is used to determine the power state of the target battery based on the target maximum charging current and the target maximum discharging current.

[0051] The battery power state calculation device provided in the embodiment of the present application obtains the historical maximum charging current and the historical maximum discharging current corresponding to the multiple historical moments before the current moment corresponding to the target battery; based on each historical maximum charging current, the current predicted maximum charging current corresponding to the current moment is predicted, and because the current predicted maximum charging current corresponding to the current moment is predicted based on each historical maximum charging current, the amount of calculation can be reduced, and the accuracy of the predicted current predicted maximum charging current is guaranteed. Then, based on the current predicted maximum charging current and the preset battery model, the target maximum charging current corresponding to the current moment is determined, and the preset battery model is taken into account, thereby ensuring the accuracy of the calculated target maximum charging current. Based on each historical maximum discharge current, the current predicted maximum discharge current corresponding to the current moment is predicted, which reduces the amount of calculation and ensures the accuracy of the predicted current predicted maximum discharge current. Then, based on the current predicted maximum discharge current and the preset battery model, the target maximum discharge current corresponding to the current moment is determined, ensuring the accuracy of the determined target maximum discharge current. Based on the target maximum charging current and the target maximum discharge current, the power state of the target battery is determined, ensuring the accuracy of the determined power state of the target battery.

[0052] In a third aspect, the present invention provides an electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the battery power status calculation method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0053] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the battery power state calculation method of the first aspect or any corresponding embodiment thereof.

[0054] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the battery power state calculation method of the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1 is a schematic flow chart of a method for calculating a battery power state according to an embodiment of the present invention;

[0057] Figure 2 is a flow chart of another battery power state calculation method according to an embodiment of the present invention;

[0058] Figure 3 is a schematic diagram of a flow chart for calculating a target maximum discharge current according to an embodiment of the present invention;

[0059] Figure 4 is a structural block diagram of a battery power state calculation device according to an embodiment of the present invention;

[0060] Figure 5 It is a schematic diagram of the hardware structure of the electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0062] Accurate prediction of the battery's state of power (SOP) plays an important role in the vehicle's starting, acceleration, climbing, and emergency braking, and is the basis for safe and reliable vehicle operation. Currently, in BMS, the common SOP estimation method is the SOC-temperature lookup table, which is usually provided by the battery manufacturer. This open-loop calculation method is simple and easy to implement, but as the current polarization of the battery accumulates, the SOC-temperature table will become less and less accurate. Therefore, the estimated SOP is not accurate.

[0063] Therefore, how to accurately calculate the power state of the battery has become an urgent problem to be solved.

[0064] It should be noted that the execution subject of the method for calculating the battery power state provided in the embodiment of the present application may be a device for calculating the battery power state, and the device for calculating the battery power state may be implemented as part or all of an electronic device through software, hardware, or a combination of software and hardware, wherein the electronic device may be a server or a terminal, wherein the server in the embodiment of the present application may be a single server or a server cluster composed of multiple servers, and the terminal in the embodiment of the present application may be a smart phone, a personal computer, a tablet computer, a wearable device, an intelligent robot, and other intelligent hardware devices. In the following method embodiments, the execution subject is an electronic device as an example for explanation.

[0065] According to an embodiment of the present invention, an embodiment of a battery power status calculation method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0066] In this embodiment, a battery power state calculation method is provided, which can be used in the above electronic device. Figure 1 is a flow chart of a method for calculating a battery power state according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0067] Step S101, obtaining the historical maximum charging current and the historical maximum discharging current corresponding to a plurality of historical moments before the current moment corresponding to the target battery.

[0068] Optionally, the electronic device may receive the historical maximum charging current and the historical maximum discharging current corresponding to multiple historical moments before the current moment corresponding to the target battery sent by the battery management system.

[0069] Optionally, the electronic device may also detect the target battery to obtain the historical maximum charging current and the historical maximum discharging current corresponding to multiple historical moments before the current moment of the target battery.

[0070] The number of historical moments may be 50 or 80, and the embodiment of the present application does not specifically limit the number of historical moments.

[0071] Step S102: predicting the current predicted maximum charging current corresponding to the current moment based on each historical maximum charging current.

[0072] Specifically, the electronic device may predict the current predicted maximum charging current corresponding to the current moment based on the corresponding relationship between each historical maximum charging current and each historical moment.

[0073] This step will be described in detail below.

[0074] Step S103, determining a target maximum charging current corresponding to the current moment based on the current predicted maximum charging current and a preset battery model.

[0075] Specifically, the electronic device can substitute the current predicted maximum charging current into the preset battery model, and calculate the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the current predicted maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage.

[0076] Then, detect whether the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the current predicted maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints.

[0077] If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the current predicted maximum charging current all meet the corresponding preset constraints, the current predicted maximum charging current is determined as the target maximum charging current.

[0078] It should be noted that the preset battery model may be a P2D model or other models.

[0079] Step S104: predicting a current predicted maximum discharge current corresponding to the current moment based on each historical maximum discharge current.

[0080] Specifically, the electronic device may input each historical maximum discharge current into a preset prediction model, and the preset prediction model extracts features of each historical maximum discharge current and outputs the current predicted maximum discharge current.

[0081] Among them, the preset prediction model can be a Gaussian regression model or a deep learning model. The embodiment of the present application does not specifically limit the preset prediction model.

[0082] For example, taking the Gaussian regression model as an example, Gaussian Process Regression (GPR) is a non-parametric regression method based on the Gaussian Process theory. It is a powerful tool in machine learning. It can fit functions of any form without specifying the form of the model. It is particularly suitable for small samples. When making predictions, Gaussian process regression calculates the posterior distribution of the target function under a given input. This posterior distribution is also a Gaussian distribution. Its mean gives the predicted value, and the variance represents the uncertainty of the prediction. The Gaussian process is completely and uniquely determined by the mean function μ(x) and the covariance function (kernel function) k(x,x'). There are many kernel functions to choose from, such as the exponential square kernel function, the Matérn kernel function, etc. It is expressed as follows:

[0083]

[0084] The mean function reflects the mean value of the function at the input point x:

[0085]

[0086] The kernel function k(x,x') describes the relationship between the function value at x and x'

[0087]

[0088] Predict the function value y*=f(x*) at the new point. The joint distribution of the training point and the prediction point is still Gaussian distribution.

[0089]

[0090] The specific process is as follows: The core of Gaussian process regression is to select a suitable kernel function (also called covariance function), which determines the correlation between data points. Common kernel functions include: linear kernel, Gaussian kernel (RBF), cubic kernel, neural network kernel, and select a suitable kernel function according to the characteristics of the data.

[0091] Gaussian process regression requires optimization of several hyperparameters, such as the length scale parameter of the kernel function, the noise level, etc. Cross-validation (such as leave-one-out or k-fold cross-validation) can be used to select the optimal hyperparameter combination. Then, the training set data is used to fit the Gaussian process model. Finally, the trained Gaussian process model is used to predict the current predicted maximum discharge current at the current moment.

[0092] Step S105 , determining a target maximum discharge current corresponding to the current moment based on the current predicted maximum discharge current and a preset battery model.

[0093] Specifically, the electronic device can calculate the first maximum value of the predicted maximum discharge current and the first minimum value of the predicted maximum discharge current corresponding to the current predicted maximum discharge current in the preset confidence interval based on the current predicted maximum discharge current. The preset confidence interval can be 95% or 90%, and the embodiment of the present application does not specifically limit the preset confidence interval.

[0094] Then, the electronic device determines the first maximum value of the predicted maximum discharge current as the first candidate maximum discharge current; based on the preset battery model, calculates the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum discharge current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the terminal voltage, and detects whether the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum discharge current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints.

[0095] Among them, it should be noted that based on the preset battery model, the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum discharge current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the terminal voltage are calculated, and the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum discharge current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the terminal voltage are detected. Whether they all meet the corresponding preset constraints can be seen below.

[0096] If the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the first candidate maximum discharge current, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints, the first candidate maximum discharge current is determined as the target maximum discharge current.

[0097] If at least one battery parameter among the surface concentration of positive electrode solid phase particles at the diaphragm, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum discharge current does not meet the corresponding preset constraints, then half of the sum of the first maximum value of the predicted maximum discharge current and the first minimum value of the predicted discharge current is determined as the second candidate maximum discharge current.

[0098] Based on the preset battery model, the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the second candidate maximum discharge current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the terminal voltage are calculated. The surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the second candidate maximum discharge current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage are detected to see whether they all meet the corresponding preset constraints.

[0099] If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum discharge current all meet the corresponding preset constraints, then it is detected whether the first discharge current difference between the first maximum value of the predicted maximum discharge current and the first minimum value of the predicted discharge current is less than the preset discharge current difference.

[0100] If the first discharge current difference is less than the preset discharge current difference, the second candidate maximum discharge current is determined as the target maximum discharge current.

[0101] If at least one of the battery parameters including the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum discharge current does not meet the corresponding preset constraints, the second candidate maximum discharge current is determined as the second maximum value of the predicted maximum discharge current; and half of the sum of the second maximum value of the predicted maximum discharge current and the first minimum value of the predicted discharge current is determined as the third candidate maximum discharge current.

[0102] It is detected whether the third candidate maximum discharge current meets a preset condition. If the third candidate maximum discharge current meets the preset condition, the third candidate maximum discharge current is determined as the target maximum discharge current.

[0103] If the first discharge current difference is greater than or equal to the preset discharge current difference, the second candidate maximum discharge current is determined as the second minimum value of the predicted maximum discharge current; and half of the sum of the first maximum value of the predicted maximum discharge current and the second minimum value of the predicted discharge current is determined as the fourth candidate maximum discharge current.

[0104] Detecting whether the fourth candidate maximum discharge current satisfies a preset condition. If the fourth candidate maximum discharge current satisfies the preset condition, determining the fourth candidate maximum discharge current as the target maximum discharge current.

[0105] If neither the third candidate maximum discharge current nor the fourth candidate maximum discharge current satisfies the preset condition, until the second difference between the predicted current maximum value and the predicted current minimum value of the discharge current is calculated to be less than the preset charging current difference, the last candidate maximum discharge current is determined as the target maximum discharge current.

[0106] The specific calculation process of this step can refer to the introduction of step S203 below.

[0107] Step S106 , determining the power state of the target battery based on the target maximum charging current and the target maximum discharging current.

[0108] Specifically, the electronic device calculates the charging power corresponding to the target battery based on the target maximum charging current.

[0109] Exemplarily, the available Ns charging power at time t is calculated as:

[0110] Psop(t)=Isop(t)*V(t)

[0111] The electronic device calculates the discharge power corresponding to the target battery based on the target maximum discharge current.

[0112] Exemplarily, the available Ns discharge power at time t is:

[0113] Psop(t)=Isop(t)*V(t+Ns)

[0114] In the above formula, V(t+Ns) is the terminal voltage after N seconds calculated by substituting Isop into the preset battery model.

[0115] The battery power state calculation method provided in the embodiment of the present application obtains the historical maximum charging current and the historical maximum discharging current corresponding to the multiple historical moments before the current moment corresponding to the target battery; based on each historical maximum charging current, the current predicted maximum charging current corresponding to the current moment is predicted, and because the current predicted maximum charging current corresponding to the current moment is predicted based on each historical maximum charging current, the amount of calculation can be reduced, and the accuracy of the predicted current predicted maximum charging current is guaranteed. Then, based on the current predicted maximum charging current and the preset battery model, the target maximum charging current corresponding to the current moment is determined, and the preset battery model is taken into account, thereby ensuring the accuracy of the calculated target maximum charging current. Based on each historical maximum discharge current, the current predicted maximum discharge current corresponding to the current moment is predicted, which reduces the amount of calculation and ensures the accuracy of the predicted current predicted maximum discharge current. Then, based on the current predicted maximum discharge current and the preset battery model, the target maximum discharge current corresponding to the current moment is determined, ensuring the accuracy of the determined target maximum discharge current. Based on the target maximum charging current and the target maximum discharge current, the power state of the target battery is determined, ensuring the accuracy of the determined power state of the target battery.

[0116] In this embodiment, a battery power state calculation method is provided, which can be used in the above electronic device. Figure 2 is a flow chart of a method for calculating a battery power state according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0117] Step S201, obtaining the historical maximum charging current and the historical maximum discharging current corresponding to multiple historical moments before the current moment corresponding to the target battery.

[0118] For details about this step, please refer to the above description of step S101, which will not be elaborated here.

[0119] Step S202: predicting the current predicted maximum charging current corresponding to the current moment based on each historical maximum charging current.

[0120] Specifically, the above step S202 may include the following steps:

[0121] Step S2021, input each historical maximum charging current into a preset prediction model, the preset prediction model extracts features of each historical maximum charging current, and outputs the current predicted maximum charging current.

[0122] Specifically, the electronic device may input each historical maximum charging current into a preset prediction model, and the preset prediction model extracts features of each historical maximum charging current and outputs the current predicted maximum charging current.

[0123] Among them, the preset prediction model can be a Gaussian regression model or a deep learning model. The embodiment of the present application does not specifically limit the preset prediction model.

[0124] Among them, the Gaussian regression model can be described as above and will not be elaborated here.

[0125] Step S203, determining a target maximum charging current corresponding to the current moment based on the current predicted maximum charging current and a preset battery model.

[0126] Specifically, the above step S203 may include the following steps:

[0127] Step S2031: based on the current predicted maximum charging current, calculate a first maximum value of the predicted maximum charging current and a first minimum value of the predicted maximum charging current corresponding to the current predicted maximum charging current in a preset confidence interval.

[0128] Specifically, the electronic device calculates the first maximum value of the predicted maximum charging current and the first minimum value of the predicted maximum charging current corresponding to the current predicted maximum charging current in the preset confidence interval based on the current predicted maximum charging current. The preset confidence interval can be 95% or 90%, and the embodiment of the present application does not specifically limit the preset confidence interval.

[0129] For example, assuming that the preset confidence interval is 95%, the electronic device uses the formula of the 95% confidence interval to calculate the confidence interval of the current prediction value. The prediction value of Gaussian process regression is accompanied by a mean and variance.

[0130] Step S2032: determining a target maximum charging current corresponding to the current moment based on the predicted first maximum value of the maximum charging current, the predicted first minimum value of the charging current, and a preset battery model.

[0131] Specifically, the above step S2032 may include the following steps:

[0132] Step a1: determine the predicted maximum charging current first maximum value as the first candidate maximum charging current.

[0133] Specifically, the electronic device may determine the predicted first maximum value of the maximum charging current as the first candidate maximum charging current.

[0134] Step a2, based on the preset battery model, calculate the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage.

[0135] Specifically, the electronic device can calculate the surface concentration of positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum charging current based on a preset battery model, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage.

[0136] Step a3, detecting whether the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints.

[0137] Specifically, the electronic device detects whether the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints.

[0138] It should be noted that the preset battery model may be a P2D model or other models.

[0139] For lithium batteries, the safe operating range needs to be evaluated from multiple dimensions, the most important of which are the surface concentration of the positive and negative electrodes and the side reaction overpotential of the negative electrode. If the surface concentration of the positive and negative electrodes is too high or too low, it corresponds to overcharge or overdischarge, and the side reaction overpotential of the negative electrode is an important indicator of lithium deposition. The terminal voltage is still used as a macro-limiting indicator in this method.

[0140] For example, this solution uses a simplified P2D model, and selects the positive electrode solid surface concentration, negative electrode surface concentration, side reaction overpotential and terminal voltage at the diaphragm output by the model as four constraints. Because this patent uses the P2D model, it can be seen from the simulation that the current fluid density at the diaphragm is the largest (the chemical reaction is intense).

[0141] Among them, for the particle surface concentration at the diaphragm, the following formula is used as a constraint:

[0142]

[0143] in, is the surface concentration of positive and negative electrode material particles; The maximum concentration of positive and negative electrode material particles, usually provided by the supplier; They are the minimum and maximum lithiation levels, between 0 and 1, given by the battery cell manufacturer.

[0144] The specific calculation method is as follows: In the P2D model, the solid-phase diffusion process of lithium ions follows Fick's second law and is described by a partial differential equation. The common solution method is Laplace transform. After considering the boundary conditions, the transfer function between the surface ion concentration and the current flow density can be obtained:

[0145]

[0146] Among them, J f is the current fluid density, which will be different along the thickness direction for the P2D model used in this patent; D s is the lithium ion diffusion coefficient of the material; F is the Faraday constant; R s is the particle radius of the positive and negative electrode materials; ε s is the solid volume fraction; s is the complex variable of Laplace transform; this formula can be simplified by various methods and then converted into the time domain for real-time calculation of surface concentration.

[0147] For the negative electrode side reaction overpotential at the diaphragm, it is constrained by the following formula (this condition is only considered when calculating the charging current):

[0148] η sr (L n )=Φ s (L n )-Φ e (L n )-U sr >=0

[0149] It is calculated by the following formula:

[0150] At any position in the negative electrode region:

[0151] In the above formula: is the equilibrium potential of the active material, is the half-cell open circuit voltage, and is the ratio of the surface concentration to the maximum concentration It is obtained in the form of a table lookup, usually provided by the battery cell manufacturer;

[0152] Electrochemical reaction overpotential:

[0153] The overpotential generated by SEI film is:

[0154] Among them, Φ s (L n ), Φ e (L n): solid phase potential and liquid phase potential of the negative electrode near the diaphragm; U sr Side reaction equilibrium potential (usually 0 or a value greater than 0 as a safety margin); f is the current fluid density; a s is the particle specific surface area; i0 is the exchange current density, and the electrochemical reaction constant is related to the distribution of lithium ion concentration in the solid and liquid phases. R is the gas constant; T is the temperature; R sei is the SEI film resistance; α is the electrochemical reaction transfer coefficient, which is usually taken as a fixed value of 0.5.

[0155] In addition, to further ensure safety, the terminal voltage also needs to be limited to the upper and lower cut-off voltages.

[0156] V min ≤V(t)≤V max

[0157] The terminal voltage is calculated by the following formula:

[0158]

[0159] The simplified calculation of the electrochemical model does not belong to the present invention, and the more detailed calculation process can be found in the prior art.

[0160] Step a4, if the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet the corresponding preset constraints, then the first candidate maximum charging current is determined as the target maximum charging current.

[0161] Specifically, if the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet the corresponding preset constraints, the electronic device determines the first candidate maximum charging current as the target maximum charging current.

[0162] Step a5, if there is at least one battery parameter among the surface concentration of positive electrode solid phase particles at the diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage that does not meet the corresponding preset constraints, then half of the sum of the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the second candidate maximum charging current.

[0163] Specifically, if at least one battery parameter among the surface concentration of positive electrode solid phase particles at the diaphragm, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current does not meet the corresponding preset constraints, the electronic device will determine half of the sum of the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current as the second candidate maximum charging current.

[0164] Step a6, based on the preset battery model, calculate the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the second candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage.

[0165] Step a7, detecting whether the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the second candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints.

[0166] Specifically, the electronic device calculates the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the second candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage, and detects the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the second candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage. The process of whether they all meet the corresponding preset constraints can be referred to above.

[0167] Step a8, if the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the second candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage, all meet the corresponding preset constraints, then detect whether the first charging current difference between the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference.

[0168] Specifically, if the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current all meet the corresponding preset constraints, then it is detected whether the first charging current difference between the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference.

[0169] Step a9: if the first charging current difference is less than the preset charging current difference, the second candidate maximum charging current is determined as the target maximum charging current.

[0170] Specifically, if the first charging current difference is less than the preset charging current difference, the electronic device determines the second candidate maximum charging current as the target maximum charging current.

[0171] Step a10, if there is at least one battery parameter among the surface concentration of positive electrode solid phase particles at the diaphragm, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current that does not meet the corresponding preset constraints, then the second candidate maximum charging current is determined as the second maximum value of the predicted maximum charging current; and half of the sum of the second maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the third candidate maximum charging current.

[0172] Specifically, if there is at least one battery parameter among the surface concentration of positive electrode solid phase particles at the diaphragm, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current that does not meet the corresponding preset constraints, then the second candidate maximum charging current is determined as the second maximum value of the predicted maximum charging current; and half of the sum of the second maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the third candidate maximum charging current.

[0173] Step a11, detecting whether the third candidate maximum charging current meets a preset condition.

[0174] Specifically, the process of detecting whether the third candidate maximum charging current satisfies the preset condition can refer to the above process of detecting whether the third candidate maximum charging current satisfies the preset condition, which will not be described in detail here.

[0175] Step a12: if the third candidate maximum charging current meets a preset condition, the third candidate maximum charging current is determined as the target maximum charging current.

[0176] Specifically, if the third candidate maximum charging current meets a preset condition, the electronic device determines the third candidate maximum charging current as the target maximum charging current.

[0177] Step a13, if the first charging current difference is greater than or equal to the preset charging current difference, the second candidate maximum charging current is determined as the second minimum value of the predicted maximum charging current; and half of the sum of the first maximum value of the predicted maximum charging current and the second minimum value of the predicted charging current is determined as the fourth candidate maximum charging current.

[0178] Step a14, detecting whether the fourth candidate maximum charging current meets a preset condition.

[0179] Specifically, the process of detecting whether the fourth candidate maximum charging current satisfies the preset condition can refer to the above process of detecting whether the third candidate maximum charging current satisfies the preset condition, which will not be described in detail here.

[0180] Step a15: if the fourth candidate maximum charging current meets a preset condition, the fourth candidate maximum charging current is determined as the target maximum charging current.

[0181] Step a16, if the third candidate maximum charging current and the fourth candidate maximum charging current do not meet the preset conditions, until the second difference between the predicted current maximum value and the predicted current minimum value is calculated to be less than the preset charging current difference, the last candidate maximum charging current is determined as the target maximum charging current.

[0182] Specifically, if neither the third candidate maximum charging current nor the fourth candidate maximum charging current meets the preset conditions, the calculation is continued based on the third candidate maximum charging current and the fourth candidate maximum charging current until the second difference between the predicted current maximum value and the predicted current minimum value of the charging current is less than the preset charging current difference, and the last candidate maximum charging current is determined as the target maximum charging current.

[0183] Step S204: predicting a current predicted maximum discharge current corresponding to the current moment based on each historical maximum discharge current.

[0184] For details about this step, please refer to the above description of step S104, which will not be elaborated here.

[0185] Step S205 , determining a target maximum discharge current corresponding to the current moment based on the current predicted maximum discharge current and a preset battery model.

[0186] For details about this step, please refer to the above description of step S105, which will not be elaborated here.

[0187] Step S206 , determining the power state of the target battery based on the target maximum charging current and the target maximum discharging current.

[0188] For details about this step, please refer to the above description of step S106, which will not be elaborated here.

[0189] The battery power state calculation method provided in the embodiment of the present application inputs each historical maximum charging current into a preset prediction model, and the preset prediction model extracts features of each historical maximum charging current, outputs the current predicted maximum charging current, and ensures the accuracy of the output current predicted maximum charging current. Based on the current predicted maximum charging current, the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current corresponding to the current predicted maximum charging current in the preset confidence interval are calculated, and the accuracy of the determined first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is ensured.

[0190] Then, the first maximum value of the predicted maximum charging current is determined as the first candidate maximum charging current. Then, based on the preset battery model, the surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage are calculated to ensure the accuracy of the calculated surface concentration of the positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage. Detect whether the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints. If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet the corresponding preset constraints, then the first candidate maximum charging current is determined as the target maximum charging current. This ensures that the first candidate maximum charging current meets the battery characteristics of the target battery, thereby ensuring the accuracy of the determined target maximum charging current.

[0191] If at least one of the battery parameters of the positive electrode solid phase particle surface concentration at the diaphragm corresponding to the first candidate maximum charging current, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage does not meet the corresponding preset constraint conditions, then half of the sum of the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the second candidate maximum charging current, thereby ensuring the accuracy of the determined second candidate maximum charging current. Based on the preset battery model, the positive electrode solid phase particle surface concentration at the diaphragm of the target battery corresponding to the second candidate maximum charging current, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage are calculated; the positive electrode solid phase particle surface concentration at the diaphragm corresponding to the second candidate maximum charging current, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage are detected to see whether they all meet the corresponding preset constraint conditions, thereby detecting whether the second candidate maximum charging current meets the characteristics of the target battery. If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current all meet the corresponding preset constraints, then it is detected whether the first charging current difference between the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference. If the first charging current difference between the second candidate maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference, then the second candidate maximum charging current is determined as the target maximum charging current, thereby ensuring the accuracy of the determined target maximum charging current and satisfying the characteristics of the target battery.

[0192] If at least one of the battery parameters of the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current does not meet the corresponding preset constraint conditions, the second candidate maximum charging current is determined as the second maximum value of the predicted maximum charging current; half of the sum of the second maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the third candidate maximum charging current, ensuring the accuracy of the determined third candidate maximum charging current. Check whether the third candidate maximum charging current meets the preset conditions; if the third candidate maximum charging current meets the preset conditions, the third candidate maximum charging current is determined as the target maximum charging current, ensuring the accuracy of the determined target maximum charging current and meeting the preset requirements.

[0193] If the first charging current difference is greater than or equal to the preset charging current difference, the second candidate maximum charging current is determined as the second minimum value of the predicted maximum charging current; half of the sum of the first maximum value of the predicted maximum charging current and the second minimum value of the predicted charging current is determined as the fourth candidate maximum charging current, thereby ensuring the accuracy of the fourth candidate maximum charging current. Detect whether the fourth candidate maximum charging current meets the preset conditions; if the fourth candidate maximum charging current meets the preset conditions, the fourth candidate maximum charging current is determined as the target maximum charging current, thereby ensuring the accuracy of determining the fourth candidate maximum charging current as the target maximum charging current. If both the third candidate maximum charging current and the fourth candidate maximum charging current do not meet the preset conditions, then until the second difference between the current maximum value of the predicted charging current and the current minimum value of the predicted charging current is calculated to be less than the preset charging current difference, the last candidate maximum charging current is determined as the target maximum charging current, thereby ensuring the accuracy of the determined target maximum charging current.

[0194] For better introduction, the battery power state calculation method provided in the embodiment of the present application is as follows: Figure 3 As shown, an embodiment of the present application provides a flowchart for calculating a target maximum discharge current.

[0195] The electronic device inputs each historical maximum charging current into the Gaussian process regression model, which extracts features from each historical maximum charging current and outputs the current predicted maximum charging current. The electronic device then calculates the first maximum value Imax and the first minimum value Imin of the predicted maximum charging current corresponding to the current predicted maximum charging current in the preset confidence interval.

[0196] The electronic device determines the first maximum value Imax of the predicted maximum charging current as the first candidate maximum charging current Isop. The electronic device inputs Isop into the battery model, and outputs the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage. And detect whether the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints. If so, the first candidate maximum charging current Isop is determined as the target maximum discharge current.

[0197] If not, determine Isop=05*(Imax+Imin). Input Isop into the battery model again, and output the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage. And detect whether the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints. If so, detect whether the end condition of Imax-Imin<ΔI is met. If so, determine Isop as the target maximum discharge current.

[0198] If at least one of the battery parameters of the positive electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage does not satisfy the corresponding constraint condition, then Imax=Isop is determined. Then, Isop=05*(Imax+Imin) is determined again.

[0199] If the end condition of Imax-Imin<ΔI is not satisfied, Imin=Isop is determined, and Isop=05*(Imax+Imin) is determined again.

[0200] This cycle is repeated until Imax-Imin<ΔI is satisfied, then the calculation stops and the last Isop is the final target maximum discharge current.

[0201] In this embodiment, a battery power state calculation device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0202] This embodiment provides a battery power state calculation device, such as Figure 4 As shown, including:

[0203] An acquisition module 301 is used to acquire the historical maximum charging current and the historical maximum discharging current corresponding to multiple historical moments before the current moment corresponding to the target battery;

[0204] A first prediction module 302, configured to predict a current predicted maximum charging current corresponding to a current moment based on each historical maximum charging current;

[0205] A first determination module 303, configured to determine a target maximum charging current corresponding to a current moment based on a current predicted maximum charging current and a preset battery model;

[0206] A second prediction module 304, configured to predict a current predicted maximum discharge current corresponding to a current moment based on each historical maximum discharge current;

[0207] A second determination module 305 is used to determine a target maximum discharge current corresponding to the current moment based on the current predicted maximum discharge current and a preset battery model;

[0208] The third determination module 306 is configured to determine a power state of a target battery based on a target maximum charging current and a target maximum discharging current.

[0209] In some optional implementations, the first prediction module 302 is specifically configured to input each historical maximum charging current into a preset prediction model, and the preset prediction model extracts features of each historical maximum charging current and outputs a currently predicted maximum charging current.

[0210] In some optional embodiments, the first determination module 303 is specifically used to calculate, based on the current predicted maximum charging current, a first maximum value of the predicted maximum charging current and a first minimum value of the predicted charging current corresponding to the current predicted maximum charging current in a preset confidence interval; based on the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current and a preset battery model, determine the target maximum charging current corresponding to the current moment.

[0211] In some optional embodiments, the first determination module 303 is specifically used to determine the first maximum value of the predicted maximum charging current as the first candidate maximum charging current; based on the preset battery model, calculate the surface concentration of positive electrode solid phase particles at the target battery diaphragm corresponding to the first candidate maximum charging current, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage; detect whether the surface concentration of positive electrode solid phase particles at the diaphragm, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet the corresponding preset constraints; if the surface concentration of positive electrode solid phase particles at the diaphragm, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet the corresponding preset constraints, then the first candidate maximum charging current is determined as the target maximum charging current.

[0212] In some optional embodiments, the first determination module 303 is specifically used to determine half of the sum of the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current as the second candidate maximum charging current if at least one of the battery parameters of the positive electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current does not meet the corresponding preset constraint conditions; based on the preset battery model, calculate the positive electrode solid phase particle surface concentration at the target battery diaphragm corresponding to the second candidate maximum charging current, and / or the negative electrode solid phase particle surface concentration at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage; detect the second candidate Whether the surface concentration of the positive electrode solid phase particles at the diaphragm corresponding to the maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints; if the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage all meet the corresponding preset constraints, then detect whether the first charging current difference between the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference; if the first charging current difference is less than the preset charging current difference, the second candidate maximum charging current is determined as the target maximum charging current.

[0213] In some optional embodiments, the first determination module 303 is specifically used to determine the second candidate maximum charging current as the second maximum value of the predicted maximum charging current if at least one battery parameter among the surface concentration of positive electrode solid phase particles at the diaphragm, and / or the surface concentration of negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current does not meet the corresponding preset constraints; determine one-half of the sum of the second maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current as the third candidate maximum charging current; detect whether the third candidate maximum charging current meets the preset conditions; if the third candidate maximum charging current meets the preset conditions, determine the third candidate maximum charging current as the target maximum charging current.

[0214] In some optional embodiments, the first determination module 303 is specifically used to determine the second candidate maximum charging current as the second minimum value of the predicted maximum charging current if the first charging current difference is greater than or equal to the preset charging current difference; determine one-half of the sum of the first maximum value of the predicted maximum charging current and the second minimum value of the predicted charging current as the fourth candidate maximum charging current; detect whether the fourth candidate maximum charging current meets the preset conditions; if the fourth candidate maximum charging current meets the preset conditions, determine the fourth candidate maximum charging current as the target maximum charging current; if both the third candidate maximum charging current and the fourth candidate maximum charging current do not meet the preset conditions, until the second difference between the current maximum value of the predicted charging current and the current minimum value of the predicted charging current is calculated to be less than the preset charging current difference, then determine the last candidate maximum charging current as the target maximum charging current.

[0215] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0216] The battery power state calculation device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0217] The embodiment of the present invention also provides an electronic device having the above Figure 4 The battery power state calculation device shown.

[0218] See also Figure 5 , Figure 5 is a schematic diagram of the structure of an electronic device provided by an optional embodiment of the present invention, such as Figure 5 As shown, the electronic device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.

[0219] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0220] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0221] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0222] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0223] The electronic device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 5 The example of connecting through bus is taken in the following.

[0224] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the electronic device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator rod, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0225] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0226] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0227] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for calculating battery power status, characterized in that: The method comprises: Obtain the historical maximum charging current and the historical maximum discharging current corresponding to multiple historical moments before the current moment corresponding to the target battery; Based on each of the historical maximum charging currents, predicting a current predicted maximum charging current corresponding to the current moment; Based on the current predicted maximum charging current and a preset battery model, determining a target maximum charging current corresponding to the current moment; Based on each of the historical maximum discharge currents, predicting a current predicted maximum discharge current corresponding to the current moment; Determining a target maximum discharge current corresponding to the current moment based on the current predicted maximum discharge current and the preset battery model; The target battery power state is determined based on the target maximum charging current and the target maximum discharging current.

2. The method according to claim 1, characterized in that The predicting the current predicted maximum charging current corresponding to the current moment based on each of the historical maximum charging currents includes: Each of the historical maximum charging currents is input into a preset prediction model, and the preset prediction model extracts features of each of the historical maximum charging currents and outputs the currently predicted maximum charging current.

3. The method according to claim 1, characterized in that The determining, based on the current predicted maximum charging current and a preset battery model, a target maximum charging current corresponding to the current moment includes: Based on the current predicted maximum charging current, calculating a first maximum value of the predicted maximum charging current and a first minimum value of the predicted maximum charging current corresponding to the current predicted maximum charging current in a preset confidence interval; Based on the predicted first maximum value of the maximum charging current, the predicted first minimum value of the charging current and the preset battery model, the target maximum charging current corresponding to the current moment is determined.

4. The method according to claim 3, characterized in that The determining the target maximum charging current corresponding to the current moment based on the predicted first maximum value of the maximum charging current, the predicted first minimum value of the charging current and the preset battery model includes: Determining the predicted maximum charging current first maximum value as a first candidate maximum charging current; Based on the preset battery model, calculating the surface concentration of the positive electrode solid phase particles at the target battery separator corresponding to the first candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the separator, and / or the negative electrode side reaction overpotential at the separator, and / or the terminal voltage; Detecting whether the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet corresponding preset constraints; If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current all meet the corresponding preset constraints, then the first candidate maximum charging current is determined as the target maximum charging current.

5. The method according to claim 4, characterized in that The method further comprises: If at least one of the battery parameters of the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the first candidate maximum charging current does not satisfy the corresponding preset constraint condition, then half of the sum of the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the second candidate maximum charging current; Based on the preset battery model, calculating the surface concentration of the positive electrode solid phase particles at the target battery separator corresponding to the second candidate maximum charging current, and / or the surface concentration of the negative electrode solid phase particles at the separator, and / or the negative electrode side reaction overpotential at the separator, and / or the terminal voltage; Detecting whether the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current all meet corresponding preset constraints; If the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current all meet the corresponding preset constraint conditions, then detect whether the first charging current difference between the first maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is less than the preset charging current difference; If the first charging current difference is less than the preset charging current difference, the second candidate maximum charging current is determined as the target maximum charging current.

6. The method according to claim 5, characterized in that The method further comprises: If at least one of the battery parameters including the surface concentration of the positive electrode solid phase particles at the diaphragm, and / or the surface concentration of the negative electrode solid phase particles at the diaphragm, and / or the negative electrode side reaction overpotential at the diaphragm, and / or the terminal voltage corresponding to the second candidate maximum charging current does not satisfy the corresponding preset constraint condition, then the second candidate maximum charging current is determined as the second maximum value of the predicted maximum charging current; and half of the sum of the second maximum value of the predicted maximum charging current and the first minimum value of the predicted charging current is determined as the third candidate maximum charging current; Detecting whether the third candidate maximum charging current meets a preset condition; If the third candidate maximum charging current meets the preset condition, the third candidate maximum charging current is determined as the target maximum charging current.

7. The method according to claim 6, characterized in that The method further comprises: If the first charging current difference is greater than or equal to the preset charging current difference, the second candidate maximum charging current is determined as the second minimum value of the predicted maximum charging current; and one-half of the sum of the first maximum value of the predicted maximum charging current and the second minimum value of the predicted charging current is determined as the fourth candidate maximum charging current; Detecting whether the fourth candidate maximum charging current meets a preset condition; If the fourth candidate maximum charging current meets the preset condition, determining the fourth candidate maximum charging current as the target maximum charging current; If neither the third candidate maximum charging current nor the fourth candidate maximum charging current satisfies the preset condition, the last candidate maximum charging current is determined as the target maximum charging current until the second difference between the predicted current maximum value and the predicted current minimum value is calculated to be less than the preset charging current difference.

8. A battery power status calculation device, characterized in that: The device comprises: An acquisition module, used to acquire the historical maximum charging current and the historical maximum discharging current corresponding to multiple historical moments before the current moment corresponding to the target battery; A first prediction module, configured to predict a current predicted maximum charging current corresponding to the current moment based on each of the historical maximum charging currents; A first determination module, configured to determine a target maximum charging current corresponding to the current moment based on the currently predicted maximum charging current and a preset battery model; A second prediction module, configured to predict a current predicted maximum discharge current corresponding to the current moment based on each of the historical maximum discharge currents; A second determination module, configured to determine a target maximum discharge current corresponding to the current moment based on the current predicted maximum discharge current and the preset battery model; The third determination module is used to determine the power state of the target battery based on the target maximum charging current and the target maximum discharging current.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the battery power state calculation method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the battery power state calculation method according to any one of claims 1 to 7.

11. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the battery power state calculation method according to any one of claims 1 to 7.

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