Method for determining battery charging safety boundary, battery charging method and electronic device

Abstract

The embodiment of the application provides a kind of battery charging safety boundary determination method, battery charging method and electronic equipment, belong to battery charging technical field.The method comprises: obtaining reference charging safety boundary and the boundary disturbance parameter of reference charging safety boundary;The disturbance degree of boundary disturbance parameter to reference charging safety boundary is calculated, and target safety parameter is obtained;According to target safety parameter, reference charging safety boundary is updated, and target charging safety boundary is obtained.The embodiment of the application can improve the accuracy of battery charging safety boundary determination.

Description

Technical Field

[0001] This application relates to the field of battery charging technology, and in particular to a method for determining the safety boundary of battery charging, a battery charging method, and an electronic device. Background Technology

[0002] In related technologies, battery charging safety boundaries are typically determined based on ideal electrochemical models of the battery. However, in practical applications, factors such as manufacturing processes and aging levels can lead to inconsistencies between individual batteries, causing a mismatch between the ideal battery charging safety boundaries and the actual operating state of the battery. This makes it difficult to achieve the expected safety and charging performance during battery charging. Therefore, improving the accuracy of determining battery charging safety boundaries has become an urgent problem to be solved. Summary of the Invention

[0003] The main objective of this application is to propose a method for determining the safety boundary of battery charging, a battery charging method, and an electronic device, aiming to improve the accuracy of determining the safety boundary of battery charging.

[0004] To achieve the above objectives, a first aspect of this application proposes a method for determining a battery charging safety boundary, the method comprising: Obtain a reference charging safety boundary and boundary perturbation parameters of the reference charging safety boundary; wherein, the reference charging safety boundary is used to indicate the mapping relationship between reference battery state parameters and the maximum allowable charging rate, and the reference battery state parameters include at least reference battery temperature and reference battery state of charge; Calculate the degree of disturbance of the boundary disturbance parameters to the reference charging safety boundary to obtain the target safety parameters; The reference charging safety boundary is updated based on the target safety parameters to obtain the target charging safety boundary; wherein, the target charging safety boundary is used to indicate the mapping relationship between the reference battery state parameters and the target maximum charging rate, and the target maximum charging rate is obtained by updating the maximum allowable charging rate.

[0005] In some embodiments, the boundary disturbance parameters include battery mass production parameters, battery corner region parameters, and sensor measurement error parameters. Calculating the degree of disturbance of the boundary disturbance parameters to the reference charging safety boundary to obtain the target safety parameters includes: The degree of disturbance of the battery mass production parameters to the reference charging safety boundary is calculated to obtain the manufacturing safety parameters; The degree of disturbance of the battery corner region parameters to the reference charging safety boundary is calculated to obtain the corner effect safety parameters; The degree of disturbance of the sensor measurement error parameters to the reference charging safety boundary is calculated to obtain the sensor error safety parameters; The target safety parameter is calculated based on the manufacturing safety parameter, the corner effect safety parameter, and the sensor error safety parameter.

[0006] In some embodiments, calculating the degree of disturbance of the battery mass production parameters to the reference charging safety boundary to obtain the manufacturing safety parameters includes: Electrochemical simulations were performed on the mass production parameters of the battery to obtain the first charging safety boundary; The manufacturing safety parameters are calculated based on the reference charging safety boundary and the first charging safety boundary.

[0007] In some embodiments, calculating the degree of disturbance of the battery corner region parameters to the reference charging safety boundary to obtain corner effect safety parameters includes: Electrochemical simulation was performed on the parameters of the battery corner region to obtain the second charging safety boundary; The corner effect safety parameters are calculated based on the reference charging safety boundary and the second charging safety boundary.

[0008] In some embodiments, the sensor measurement error parameters include temperature error parameters and state of charge error parameters. The calculation of the degree of disturbance of the sensor measurement error parameters to the reference charging safety boundary to obtain sensor error safety parameters includes: The reference charging safety boundary is interpolated based on the temperature error parameter and the state of charge error parameter to obtain the third charging safety boundary. The sensor error safety parameters are calculated based on the reference charging safety boundary and the third charging safety boundary.

[0009] In some embodiments, calculating the target safety parameter based on the manufacturing safety parameter, the corner effect safety parameter, and the sensor error safety parameter includes: Calculate the comprehensive safety parameters based on the manufacturing safety parameters, the corner effect safety parameters, and the sensor error safety parameters; The target security parameter is obtained by calculating the quantile of the comprehensive security parameter based on the preset security reliability; wherein, the target probability is equal to the preset security reliability, and the target probability is the probability that the comprehensive security parameter is greater than or equal to the target security parameter.

[0010] In some embodiments, the step of calculating the quantiles of the comprehensive security parameters based on a preset security reliability to obtain the target security parameters includes: Obtain the standard normal quantile corresponding to the preset security and reliability to get the target reliability; Obtain the mean and standard deviation of the comprehensive safety parameters; The target safety parameter is obtained by calculating the quantiles of the comprehensive safety parameter based on the mean, the standard deviation, and the target reliability.

[0011] To achieve the above objectives, a second aspect of this application provides a battery charging method, the battery charging method comprising: Obtain the current temperature and current state of charge of the target battery; The target charging safety boundary is queried based on the current temperature and the current state of charge to obtain the current maximum charging rate, and the current maximum charging current is determined based on the current maximum charging rate; wherein, the target charging safety boundary is obtained according to the method for determining the battery charging safety boundary described in the first aspect; The target charging current is determined based on the current maximum charging current; wherein the target charging current is less than or equal to the current maximum charging current; The target battery is charged according to the target charging current.

[0012] To achieve the above objectives, a third aspect of the present application provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method described in the first or second aspect.

[0013] To achieve the above objectives, a fourth aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first or second aspect.

[0014] The battery charging safety boundary determination method, battery charging method, electronic device, and computer-readable storage medium proposed in this application embodiment consider the boundary disturbance parameters that cause disturbance to the ideal charging safety boundary, calculate the degree of disturbance of the boundary disturbance parameters to the ideal charging safety boundary to obtain the target safety parameters, and update the ideal charging safety boundary according to the target safety parameters, so that the charging safety boundary can match the actual operating state of the battery, thereby improving the accuracy of the charging safety boundary determination. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for determining the battery charging safety boundary provided in an embodiment of this application; Figure 2 yes Figure 1 The flowchart of step S120 in the middle; Figure 3 yes Figure 2 The flowchart of step S210 in the middle; Figure 4 This is a distribution diagram of manufacturing safety parameters provided in the embodiments of this application; Figure 5 yes Figure 2 The flowchart of step S220 in the text; Figure 6 This is a distribution diagram of the corner effect safety parameters provided in the embodiments of this application; Figure 7 yes Figure 2 The flowchart of step S230 in the middle; Figure 8 This is a distribution diagram of sensor error safety parameters provided in the embodiments of this application; Figure 9 yes Figure 2 The flowchart of step S240 in the text; Figure 10 This is a distribution diagram of the comprehensive security parameters provided in the embodiments of this application; Figure 11 yes Figure 9 The flowchart of step S920 in the middle; Figure 12 This is a flowchart of a battery charging method provided in an embodiment of this application; Figure 13 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0017] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0019] In related technologies, battery charging safety boundaries are typically determined based on ideal electrochemical models of the battery. However, in practical applications, factors such as manufacturing processes and aging levels can lead to inconsistencies between individual batteries, causing a mismatch between the ideal battery charging safety boundaries and the actual operating state of the battery. This makes it difficult to achieve the expected safety and charging performance during battery charging. Therefore, improving the accuracy of determining battery charging safety boundaries has become an urgent problem to be solved.

[0020] Based on this, embodiments of this application provide a method for determining the safety boundary of battery charging, a battery charging method, an electronic device, and a computer-readable storage medium, aiming to improve the accuracy of determining the safety boundary of battery charging.

[0021] The battery charging safety boundary determination method, battery charging method, electronic device, and computer-readable storage medium provided in this application are specifically described through the following embodiments. First, the battery charging safety boundary determination method in this application embodiment is described.

[0022] The method for determining the battery charging safety boundary provided in this application relates to the field of battery charging. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application implementing the method for determining the battery charging safety boundary, but is not limited to the above forms.

[0023] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0024] Figure 1 This is an optional flowchart of a method for determining the battery charging safety boundary provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S110 to S130.

[0025] Step S110: Obtain the reference charging safety boundary and the boundary perturbation parameters of the reference charging safety boundary; wherein, the reference charging safety boundary is used to indicate the mapping relationship between the reference battery state parameters and the maximum allowable charging rate, and the reference battery state parameters include at least the reference battery temperature and the reference battery state of charge. Step S120: Calculate the degree of disturbance of the boundary disturbance parameters to the reference charging safety boundary to obtain the target safety parameters; Step S130: Update the reference charging safety boundary according to the target safety parameters to obtain the target charging safety boundary; wherein, the target charging safety boundary is used to indicate the mapping relationship between the reference battery state parameters and the target maximum charging rate, and the target maximum charging rate is updated from the maximum allowable charging rate.

[0026] In step S110 of some embodiments, a reference charging safety boundary is obtained based on an ideal electrochemical model of the battery combined with experimental calibration. The reference charging safety boundary indicates the mapping relationship between reference battery state parameters and the maximum permissible charging rate. The reference battery state parameters reflect the battery state under ideal conditions and include at least the reference battery temperature and the reference battery state of charge (SOC). The specific values ​​of the reference battery temperature and reference battery state of charge can be set according to actual conditions. For example, the range of the reference battery temperature can be set to -20°C to 50°C with a step size of 5°C, and the range of the reference battery state of charge can be set to 0% to 100% with a step size of 5%. In addition to the reference battery temperature and reference battery state of charge, the reference battery state parameters may also include reference current, reference voltage, and reference state of health (SOH), etc. The reference charging safety boundary is a two-dimensional table of basic charging safety boundaries indexed by temperature and state of charge under ideal conditions. The maximum permissible charging rate refers to the maximum permissible charging rate of the battery under safety constraints such as no lithium plating and no exceeding the cutoff voltage, and its unit is C.

[0027] The reference charging safety boundary is represented as SOC represents the reference battery state of charge, and T represents the reference battery temperature.

[0028] Taking a certain type of wound square lithium-ion battery as an example, its capacity is 50 ampere-hours (Ah), the positive electrode material is lithium nickel cobalt manganese oxide (NCM523), the negative electrode material is artificial graphite, the rated voltage is 3.65 volts (V), and the charging cut-off voltage is 4.2 volts (V). A method combining electrochemical model simulation and experimental calibration is used to obtain the reference charging safety boundary of the battery under different temperatures (T) and different states of charge (SOC). Specific testing methods can refer to existing lithium-ion battery charging boundary testing methods, which will not be elaborated here. The obtained reference charging safety boundary is shown in Table 1, which can be used as the baseline input for subsequent steps. As shown in Table 1, the temperature range is 0℃ to 100℃, with a fixed temperature step size of 10℃, and the SOC range is 0% to 25%, with a random SOC step size.

[0029] Table 1

[0030] In the field of lithium-ion batteries, the stability of internal battery materials (such as positive and negative electrode materials, electrolytes, and separators) is a key factor determining battery cycle life and safety performance. During battery cycle charging and discharging, these internal materials are consumed or degraded due to continuous chemical or electrochemical reactions, such as repeated growth and rupture of the solid electrolyte interface film, electrolyte oxidative decomposition, and transition metal dissolution, leading to battery capacity decay, increased internal resistance, and decreased rate performance. Studies have shown that the high voltage amplitude and duration during battery charging are the core contributing factors to exacerbating these side reactions. To mitigate this problem, existing technologies have proposed various charging strategies, such as multi-step constant current charging, constant current and constant voltage charging, and extreme fast charging. However, these methods are all based on idealized models of single battery cells and fail to fully consider the cell consistency differences that are prevalent in actual battery applications.

[0031] Existing battery charging control logic is typically based on an ideal electrochemical model of a single cell, using pre-set fixed voltage and current thresholds as switching conditions. In real-world applications (such as battery packs, battery stacks, or within individual cells), various inconsistencies and dynamic disturbances make these idealized control strategies difficult to achieve their intended effects. Therefore, this application introduces boundary disturbance parameters to quantify multi-source inconsistencies in battery manufacturing and application. These boundary disturbance parameters include battery mass production parameters, battery corner region parameters, and sensor measurement error parameters. The battery mass production parameters are key manufacturing parameters used in the battery mass production line, including at least one or more of the following: positive and negative electrode coating surface density, compaction density, separator porosity, and electrolyte injection volume. The parameters for the battery corner region are the geometric characteristic parameters of the corner region of the wound battery, including basic geometric parameters (such as the bending radius at the corner centerline, the bending radius of the innermost electrode, and the bending radius at the outermost corner), structural parameters (such as interlayer gap, number of winding turns, and effective stacking height), and deformation parameters (such as maximum tensile strain of the outer layer, maximum compressive strain of the inner layer, bending stiffness, and springback angle). Sensor measurement error parameters include temperature error parameters and state-of-charge (SOC) error parameters. Temperature error parameters reflect the measurement error of the temperature sensor, while SOC error parameters reflect the measurement error of the SOC sensor.

[0032] In battery packs or battery modules connected in series or parallel, each cell exhibits slight differences in capacity, internal resistance, and self-discharge rate at the time of manufacture, and these differences are further amplified during cycle aging. Considering the differences in manufacturing processes, material batches, aging rates, and other factors, parameters such as voltage, internal resistance, and capacity of each cell often show significant inconsistencies. If a uniform charging strategy (such as a uniform voltage threshold) is adopted, some cells may not be fully charged while others are already in an overvoltage state, making it impossible to accurately control the actual residence time of each cell at high voltage. Considering the inconsistencies among multiple cells, this application introduces battery mass production parameters.

[0033] For wound cells, the characteristics of the winding or stacked structure within a single cell lead to heterogeneity in the geometry of the electrodes. For example, the curvature of corner regions is greater, which can easily cause current density concentration and the risk of lithium plating, while the larger surface areas are relatively uniform. There are also inherent differences between the electrode corners and the larger surface areas in terms of current density, electrolyte wetting degree, and lithium-ion diffusion kinetics, resulting in different local overpotentials and side reaction rates. Existing charging strategies only focus on the overall terminal voltage and current of the cell and cannot detect or regulate this non-uniformity of reaction in the internal micro-regions, leading to the risk of lithium plating. Considering the differences in the internal microstructure of the cell, this application introduces parameters for the battery corner regions.

[0034] During charging and discharging, battery cells generate Joule heat and reaction heat, resulting in temperature gradients within and between cells. These temperature differences directly affect the kinetic rate of electrode reactions and the lithium-ion diffusion coefficient, leading to localized deviations in SOC estimation. Uneven temperature distribution and errors in SOC estimation during charging and discharging further exacerbate the risk of localized overcharging or lithium plating. If the charging strategy fails to dynamically adjust to real-time temperature distribution, high-temperature regions may age prematurely due to accelerated reactions, while low-temperature regions may trigger lithium plating due to increased polarization. Simultaneously, detection errors caused by the measurement accuracy and response delay of sensors (such as voltage, current, and temperature sensors) make it difficult for ideal-model-based charging control strategies to accurately match the actual state of the battery cells in practice, thus limiting the actual effectiveness of the charging strategy in improving battery performance. Considering the inconsistencies in temperature and SOC distribution and sensor measurement errors, this application introduces sensor measurement error parameters, setting them as temperature error parameters and SOC error parameters.

[0035] This application provides a more robust and adaptive charging safety boundary, taking into account factors such as differences in consistency among multiple cells, heterogeneity of internal cell structure, uneven heat distribution, and sensor errors. This further shortens the effective time of the battery in the high-voltage region, suppresses side reactions, and improves the overall cycle life of the battery pack.

[0036] Please see Figure 2 In some embodiments, step S120 may include, but is not limited to, steps S210 to S240: Step S210: Calculate the degree of disturbance of the battery mass production parameters to the reference charging safety boundary, and obtain the manufacturing safety parameters; Step S220: Calculate the degree of disturbance of the battery corner region parameters to the reference charging safety boundary to obtain the corner effect safety parameters; Step S230: Calculate the degree of disturbance of the sensor measurement error parameters to the reference charging safety boundary, and obtain the sensor error safety parameters; Step S240: Calculate the target safety parameters based on the manufacturing safety parameters, corner effect safety parameters, and sensor error safety parameters.

[0037] In step S210 of some embodiments, statistical process control (SPC) data for three consecutive months from the battery mass production line are collected to obtain the distribution characteristics of the battery mass production manufacturing parameters. All key manufacturing parameters in the battery mass production parameters follow a normal distribution, with the mean of the normal distribution being the design value and the standard deviation being obtained statistically based on actual data. The distribution characteristics of the battery mass production manufacturing parameters are shown in Table 2.

[0038] Table 2

[0039] Fluctuations in battery manufacturing parameters during mass production can cause changes in the charging boundary. To quantify the impact of inconsistent manufacturing parameters on the charging boundary, this study considers only the differences between battery cells, ignoring the heterogeneity of the internal structure of the cells and sensor measurement errors. The parameters of the battery corner region and the sensor measurement error parameters are fixed at ideal values, and manufacturing safety parameters are calculated. The statistical distribution of battery mass production manufacturing parameters is obtained, and electrochemical model simulations are used to analyze the changes in the charging boundary caused solely by fluctuations in manufacturing parameters, thus deriving the manufacturing safety parameters.

[0040] In step S220 of some embodiments, in addition to the battery mass production parameters, the structural heterogeneity of the corner region of the wound cell also affects the charging boundary. To quantify this effect, only the internal structural heterogeneity of the cell is considered, without considering the differences between cells and the sensor measurement error. The battery mass production parameters and the sensor measurement error parameters are fixed as ideal values, and the corner effect safety parameters are calculated based on the reference charging safety boundary and the battery corner region parameters.

[0041] In step S230 of some embodiments, in addition to the parameters mentioned above, sensor measurement error also affects the charging boundary. To quantify this effect, only sensor measurement error is considered, without considering the differences between cells and the heterogeneity of the internal structure of the cells. The battery mass production parameters and the battery corner area parameters are fixed as ideal values, and the sensor error safety parameters are calculated based on the reference charging safety boundary and the sensor measurement error parameters.

[0042] In step S240 of some embodiments, the final safety parameter that affects the charging boundary is calculated based on three safety parameters: manufacturing safety parameter, corner effect safety parameter, and sensor error safety parameter, to obtain the target safety parameter.

[0043] Steps S210 to S240 above use three boundary disturbance parameters—battery mass production parameters, battery corner region parameters, and sensor measurement error parameters—as quantitative representations of multi-source inconsistencies in the battery manufacturing and application process. They also independently analyze the impact of each of the three disturbances on the charging boundary, thereby quantifying the final impact of various inconsistencies and establishing a robust charging strategy.

[0044] Please see Figure 3 In some embodiments, step S210 may include, but is not limited to, steps S310 to S320: Step S310: Perform electrochemical simulation on the battery mass production parameters to obtain the first charging safety boundary; Step S320: Calculate the safety parameters based on the reference charging safety boundary and the first charging safety boundary.

[0045] In step S310 of some embodiments, an electrochemical model including manufacturing parameters is established. Monte Carlo sampling is performed on the battery mass production manufacturing parameters. The sampled values ​​from each sampling are substituted into the electrochemical model to calculate a first maximum charging rate. A mapping relationship is established between the reference battery state parameters and the first maximum charging rate to obtain a first charging safety boundary. The first charging safety boundary can be expressed as... The first maximum charging rate is the maximum charging rate obtained through Monte Carlo simulation when considering the manufacturing parameter distribution and other factors are idealized. This application does not specifically limit the number of sampling times; for example, the number of sampling times can be 10,000.

[0046] In step S320 of some embodiments, a reference battery temperature and a reference battery state of charge are determined. A maximum permissible charging rate is determined from a reference charging safety boundary based on the reference battery temperature and reference battery state of charge. A first maximum charging rate is determined from a first charging safety boundary based on the reference battery temperature and reference battery state of charge. The ratio between the first maximum charging rate and the maximum permissible charging rate is calculated to obtain the manufacturing safety parameter. The formula for calculating the manufacturing safety parameter is expressed as: , in, Indicates the safety parameters used in manufacturing; This represents the first maximum charging rate at the reference battery temperature T and the reference battery state of charge (SOC). This indicates the maximum permissible charging rate at the reference battery temperature T and the reference battery state of charge (SOC).

[0047] The results of each sampling are statistically analyzed to obtain... The probability distribution at each state point is approximately a normal distribution. , express The mean, express The variance. Taking (25℃, 50%) as an example, we get... The approximate normal distribution N(0.95, 0.022) indicates that fluctuations in manufacturing parameters lead to an average decrease of 5% in charging capacity, with a fluctuation range of ±4% (2). ), It represents the standard deviation.

[0048] Through the above steps S310 to S320, the impact of multi-cell consistency differences on the charging boundary can be quantified.

[0049] Please see Figure 4 Safety factor (manufacturing safety parameters) The probability density follows a normal distribution with a mean of 0.95.

[0050] Please see Figure 5 In some embodiments, step S220 may include, but is not limited to, steps S510 to S520: Step S510: Perform electrochemical simulation on the parameters of the battery corner region to obtain the second charging safety boundary; Step S520: Calculate the corner effect safety parameters based on the reference charging safety boundary and the second charging safety boundary.

[0051] In step S510 of some embodiments, a three-dimensional electrochemical model including corner details is established based on the geometric features of the wound battery cell. Monte Carlo sampling is performed on parameters of the battery corner region, such as geometric parameters and current density concentration coefficient distribution. The sampled values ​​are substituted into the electrochemical model for simulation analysis to calculate the second maximum charging rate. The current density concentration coefficient is the ratio of the peak current at the corner to the average current over the larger area, and it is affected by factors such as the radius of curvature and coating uniformity. A mapping relationship is established between the reference battery state parameters and the second maximum charging rate to obtain the second charging safety boundary. The second charging safety boundary can be expressed as... The second maximum charging rate is the maximum charging rate obtained through Monte Carlo simulation when considering the current density concentration effect in the corner region and other factors are idealized. This application does not specifically limit the number of sampling times; for example, the number of sampling times can be 1000.

[0052] In step S520 of some embodiments, a reference battery temperature and a reference battery state of charge are determined. A maximum permissible charging rate is determined from a reference charging safety boundary based on the reference battery temperature and reference battery state of charge. A second maximum charging rate is determined from a second charging safety boundary based on the reference battery temperature and reference battery state of charge. The ratio between the second maximum charging rate and the maximum permissible charging rate is calculated to obtain a corner effect safety parameter. The formula for calculating the corner effect safety parameter is expressed as: , in, Indicates the safety parameters for the corner effect; This represents the second maximum charging rate at a reference battery temperature T and a reference battery state of charge (SOC). This indicates the maximum permissible charging rate at the reference battery temperature T and the reference battery state of charge (SOC).

[0053] The results of each sampling are statistically analyzed to obtain... The probability distribution at each state point is approximately a normal distribution. , express The mean, express The variance. Taking (25℃, 50%) as an example, we get... The approximate normal distribution N(0.82, 0.032) indicates that the corner region causes an average decrease in charging capacity of 18%, with a fluctuation range of ±6% (2). ), It represents the standard deviation.

[0054] Existing charging strategies are all based on the overall terminal voltage and current of the battery cell for charging control, ignoring the unique structural heterogeneity of wound battery cells. The embodiments of this application take the corner area as the key constraint for determining the charging boundary, and accurately quantify the current density concentration and lithium plating risk caused by the curvature effect at the corner through an electrochemical model. This fundamentally solves the problem of local overcharging and accelerated aging caused by the neglect of internal structural differences in traditional methods.

[0055] Through the above steps S510 to S520, the influence of the structural heterogeneity of the corner region of the wound cell on the charging boundary can be quantified.

[0056] Please see Figure 6 Safety factor (corner effect safety parameter) The probability density follows a normal distribution with a mean of 0.82.

[0057] Please see Figure 7 In some embodiments, step S230 may include, but is not limited to, steps S710 to S720: Step S710: Interpolate the reference charging safety boundary based on the temperature error parameter and the state of charge error parameter to obtain the third charging safety boundary; Step S720: Calculate the sensor error safety parameters based on the reference charging safety boundary and the third charging safety boundary.

[0058] In step S710 of some embodiments, the measurement error distributions of the temperature sensor and the SOC sensor are obtained to obtain temperature error parameters and state-of-charge error parameters. Both the temperature error parameters and the state-of-charge error parameters follow a normal distribution and are independent of each other. The temperature error parameter is the temperature measurement error, which follows a standard normal distribution, i.e. , Indicates temperature measurement error. This represents the variance of the temperature measurement error. The state-of-charge (SOC) error parameter is the SOC estimation error, and it follows a standard normal distribution. , This indicates the SOC estimation error. This represents the variance of the SOC estimation error. In the embodiments of this application, (Unit: °C) (Unit: %), the two are independent of each other.

[0059] A third charging safety boundary is obtained by performing bicubic interpolation on the reference charging safety boundary based on the temperature error parameter and the state-of-charge error parameter. The third charging safety boundary indicates the mapping relationship between the sum of the reference battery temperature and the temperature error parameter, the sum of the reference battery state of charge and the state-of-charge error parameter, and the third maximum charging rate. The third charging safety boundary is represented as follows: .

[0060] In step S720 of some embodiments, a reference battery temperature and a reference battery state of charge (SBC) are determined, and a maximum permissible charging rate is determined from a reference charging safety boundary based on the reference battery temperature and SBC. Temperature error parameters and SBC error parameters are determined, and a first sum is obtained by calculating the sum of the reference battery temperature and the temperature error parameters. A second sum is obtained by calculating the sum of the reference battery SBC and the SBC error parameters. A third maximum charging rate is determined from a third charging safety boundary based on the first and second sums. The ratio between the third maximum charging rate and the maximum permissible charging rate is calculated to obtain a sensor error safety parameter. The formula for calculating the sensor error safety parameter is expressed as: , in, Indicates the sensor error safety parameters; Indicates the third charging safety boundary; This indicates the reference charging safety boundary.

[0061] For any (SOC, T), combined with and The distribution was obtained through Monte Carlo sampling. The probability distribution at each state point is approximately a normal distribution. , express The mean, express The variance. Taking (25℃, 50%) as an example, we get... The approximate normal distribution N(0.97, 0.022) indicates that sensor error causes an average decrease of 3% in charging capacity, with a fluctuation range of ±4% (2). ), express The standard deviation.

[0062] To address the limitations of existing technologies that rely on ideal sensor data and do not consider actual measurement errors, this application incorporates sensor uncertainty into the safety margin design. By obtaining the normal distribution characteristics of sensor errors and converting them into an adaptive reduction coefficient for the charging rate, the charging strategy has anti-interference capabilities in practical engineering applications, avoiding the risk of overcharging caused by detection deviations.

[0063] Through the above steps S710 to S720, the impact of sensor measurement error on the charging boundary can be quantified.

[0064] Please see Figure 8 Safety factor The probability density of (sensor error safety parameters) follows a normal distribution with a mean of 0.97.

[0065] It should be noted that, compared with the Monte Carlo method which simultaneously uses direct sampling of battery manufacturing parameters, battery corner region parameters, and sensor measurement error parameters, the mean and standard deviation of the safety parameters obtained by the direct sampling method have a greater than 99.9% overlap with the mean and standard deviation obtained by the method of calculating the three safety parameters independently. This is mainly because the three safety parameters are independent of each other. Therefore, the Monte Carlo method using direct sampling of original parameters (manufacturing parameters, corner parameters, and sensor errors), or methods considering other safety factors, should be considered within the scope of protection of this application.

[0066] Please see Figure 9 In some embodiments, step S240 may include, but is not limited to, steps S910 to S920: Step S910: Calculate the comprehensive safety parameters based on the manufacturing safety parameters, corner effect safety parameters, and sensor error safety parameters; Step S920: Calculate the quantiles of the comprehensive safety parameters based on the preset safety reliability to obtain the target safety parameters; wherein, the target probability is equal to the preset safety reliability, and the target probability is the probability that the comprehensive safety parameters are greater than or equal to the target safety parameters.

[0067] In step S910 of some embodiments, the probability distribution of the total safety factor is obtained by coupling the fabrication safety parameter, corner effect safety parameter, and sensor error safety parameter into a Monte Carlo simulation. Specifically, the three safety parameters—fabrication safety parameter, corner effect safety parameter, and sensor error safety parameter—are used as inputs for Monte Carlo simulation. This involves performing a large number of random samplings (more than or equal to 10,000 samplings) on the probability distributions of each of the three safety parameters, and calculating the product of the three safety parameters for each sampling to obtain the comprehensive safety parameter. It should be noted that since the three factors affecting the charging boundary are independent or approximately independent, the comprehensive safety parameter can be defined as the product of the three safety parameters. The comprehensive safety parameter is used to quantify the combined impact of various inconsistencies on the charging boundary. The formula for calculating the comprehensive safety parameter is expressed as: , in, Indicates comprehensive safety parameters; Indicates the safety parameters used in manufacturing; Indicates the safety parameters for the corner effect; This indicates the sensor's error safety parameters.

[0068] According to the central limit theorem, the comprehensive safety parameters follow a normal distribution. , This represents the average of the comprehensive safety parameters. This represents the variance of the overall safety parameters. For example, (25℃, 50%). The mean is The standard deviation can be obtained from the statistical analysis of sampling results. Upon inspection, It approximately follows a normal distribution N(0.756, 0.0422).

[0069] like Figure 10 As shown, the safety factor The probability density of (comprehensive safety parameters) follows a normal distribution with a mean of 0.84.

[0070] In step S920 of some embodiments, the preset safety reliability refers to the reliability index set for the safety of battery charging and discharging. For example, a lithium plating probability of less than 0.1% is an acceptable safety probability. Based on the preset safety and reliability level From comprehensive safety parameters Extract quantiles from the distribution and use these quantiles as the target security parameter. The target probability equals the preset safety reliability. The target probability is the probability that the comprehensive safety parameter is greater than or equal to the target safety parameter, expressed as... . .

[0071] Preset security and reliability can be set. The requirement is 99.9%, meaning the charging strategy must cover 99.9% of battery cell scenarios. For each (SOC, T) state point, take... The 0.1% quantile of the distribution is used as .

[0072] like Figure 10 As shown, obtain The 0.1% quantile of the distribution makes ,get It is 0.685.

[0073] Through the above steps S910 to S920, target safety parameters that meet safety constraints can be obtained, and robust charging boundaries can be established based on the target safety parameters.

[0074] Please see Figure 11 In some embodiments, step S920 may include, but is not limited to, steps S1110 to S1130: Step S1110: Obtain the standard normal quantile corresponding to the preset security reliability to obtain the target reliability; Step S1120: Obtain the mean and standard deviation of the comprehensive safety parameters; Step S1130: Calculate the quantiles of the comprehensive safety parameters based on the mean, standard deviation, and target reliability to obtain the target safety parameters.

[0075] In step S1110 of some embodiments, the standard normal quantile corresponding to the preset security reliability is obtained to obtain the target reliability. For example, if the preset security reliability is 99.9%, then the standard normal quantile z is 3.09.

[0076] In step S1120 of some embodiments, the comprehensive safety parameters follow a normal distribution. , The average of comprehensive safety parameters, This represents the standard deviation of the comprehensive safety parameters.

[0077] In step S1130 of some embodiments, the target reliability is multiplied by the standard deviation, and the mean is subtracted from the product to calculate the quantile of the comprehensive safety parameter, thus obtaining the target safety parameter. The formula for calculating the target safety parameter is expressed as follows: , in, This represents the standard normal quantile.

[0078] Through the above steps S1110 to S1130, the target safety parameters that meet the safety constraints can be obtained.

[0079] In step S130 of some embodiments, target safety parameters corresponding to the reference battery temperature and reference battery state of charge are obtained. The maximum allowable charging rate corresponding to the reference battery temperature and reference battery state of charge is obtained from the reference charging safety boundary. The target safety parameters and the maximum allowable charging rate are multiplied to obtain the target maximum charging rate at the reference battery temperature and reference battery state of charge. A mapping relationship between the reference battery temperature and reference battery state of charge and the target maximum charging rate is established based on all temperature and SOC points. By combining these elements, a two-dimensional robust charging boundary map indexed by temperature and SOC is formed, yielding the target charging safety boundary. The target charging safety boundary is a two-dimensional robust charging boundary map based on a probability distribution, and the robust charging boundary is represented as follows: .

[0080] Taking (25℃, 50%) as an example, =0.84 3.09 × 0.05 = 0.84 0.1545 = 0.6855 =2.0×0.6855=1.371C≈1.37C.

[0081] The calculation results for the full temperature range and the SOC range are summarized in Table 3, forming the final two-dimensional map of the robust charging boundary.

[0082] Table 3

[0083] Unlike existing technologies that provide a single fixed threshold, this application uses Monte Carlo simulation to quantify multiple uncertainties such as manufacturing parameter fluctuations, corner effects, and sensor errors into a probability distribution of charging rate, and generates a two-dimensional safety boundary map indexed by temperature and SOC. This map ensures both theoretical rigor and ease of direct deployment in battery management systems, achieving comprehensive optimization of charging speed, corner lithium plating suppression, and cycle life, forming an engineering-deployable probabilistic safety boundary.

[0084] Existing technologies heavily rely on real-time feedback of voltage, current, and temperature measured by sensors for charging control. In practical applications, sensors suffer from measurement errors, sampling delays, and noise interference, leading to discrepancies between the acquired state information, such as estimated SOC and polarization voltage, and the actual state of the battery cells. Executing charging steps based on data containing errors often results in lag or advance of control actions, significantly diminishing the intended purpose of shortening the high-voltage time. This application, taking into full account the differences between individual battery cells, the heterogeneity of the internal structure of the cells, the uneven distribution of the temperature field, and sensor detection errors, designs a charging method that can adaptively adjust charging parameters, effectively suppress local side reactions, and precisely control each cell within the high-voltage time window, thereby significantly improving the cycle stability and lifespan of the battery pack under actual operating conditions.

[0085] Please see Figure 12 This application also provides a battery charging method, which includes, but is not limited to, steps S1210 to S1240: Step S1210: Obtain the current temperature and current state of charge of the target battery; Step S1220: Query the target charging safety boundary based on the current temperature and current state of charge to obtain the current maximum charging rate, and determine the current maximum charging current based on the current maximum charging rate; wherein, the target charging safety boundary is obtained according to the above-mentioned method for determining the battery charging safety boundary; Step S1230: Determine the target charging current based on the current maximum charging current; wherein the target charging current is less than or equal to the current maximum charging current. Step S1240: Charge the target battery according to the target charging current.

[0086] In step S1210 of some embodiments, the current temperature and current state of charge of the target battery are measured in real time by a sensor. The target battery is a battery to be charged.

[0087] In step S1220 of some embodiments, the target charging safety boundary is queried using the current temperature and current state of charge as indexes to obtain the current maximum charging rate. The current maximum charging rate is then multiplied by the rated capacity of the target battery to obtain the current maximum charging current. It should be noted that if the current temperature and current state of charge fall between the grid points of the target charging safety boundary, bilinear interpolation is used to calculate the current maximum charging rate.

[0088] In step S1230 of some embodiments, the target battery is charged with a current not exceeding the current maximum charging current. A target charging current is determined based on the current maximum charging current; the target charging current is the current used to charge the target battery and is less than or equal to the current maximum charging current.

[0089] In step S1240 of some embodiments, the target battery is charged according to the target charging current, and the SOC and temperature are dynamically updated during the charging process to adjust the charging current in real time. Charging ends when the target battery reaches the charging termination condition. The charging termination condition can be set according to the actual situation. For example, the charging termination condition can be that the target battery is fully charged or has reached a set charge level, or that any one of the target battery's voltage, current, and temperature exceeds a limit.

[0090] Through the above steps S1210 to S1240, the charging current can be adaptively adjusted according to the real-time temperature and real-time state of charge of the battery, thereby effectively suppressing local side reactions and accurately controlling each cell to be in the high voltage time window, improving the cycle stability and service life of the target battery under actual working conditions.

[0091] Taking a specific charging instance as an example, when the vehicle is charging in winter, the Battery Management System (BMS) reads T=8℃ and SOC=35%. Referring to Table 3, at T=8℃ and SOC=35%, bilinear interpolation yields... The battery's rated capacity is 50Ah, and the maximum allowable current is 50A. The BMS requests the charger to perform constant current charging at 50A. As charging continues, the SOC rises to 80%, and the temperature rises to 15℃. Referring to Table 3, the maximum allowable charging rate at this state point is 0.6C, and the maximum allowable current is 30A. The BMS requests the charger to reduce the current from 50A to 30A until the battery is fully charged and charging stops.

[0092] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned method for determining the battery charging safety boundary or the battery charging method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0093] Please see Figure 13 , Figure 13 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 1310 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 1320 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 1320 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1320, and the processor 1310 calls and executes the battery charging safety boundary determination method or battery charging method of the embodiments of this application. The input / output interface 1330 is used to implement information input and output; The communication interface 1340 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 1350 transmits information between various components of the device (e.g., processor 1310, memory 1320, input / output interface 1330, and communication interface 1340); The processor 1310, memory 1320, input / output interface 1330 and communication interface 1340 are connected to each other within the device via bus 1350.

[0094] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for determining battery charging safety boundaries or a battery charging method.

[0095] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0096] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0097] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0098] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0100] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0101] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0102] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0103] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0104] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0105] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for determining the safety boundary of battery charging, characterized in that, The method includes: Obtain a reference charging safety boundary and boundary perturbation parameters of the reference charging safety boundary; wherein, the reference charging safety boundary is used to indicate the mapping relationship between reference battery state parameters and the maximum allowable charging rate, and the reference battery state parameters include at least reference battery temperature and reference battery state of charge; Calculate the degree of disturbance of the boundary disturbance parameters to the reference charging safety boundary to obtain the target safety parameters; The reference charging safety boundary is updated based on the target safety parameters to obtain the target charging safety boundary; wherein, the target charging safety boundary is used to indicate the mapping relationship between the reference battery state parameters and the target maximum charging rate, and the target maximum charging rate is obtained by updating the maximum allowable charging rate.

2. The method according to claim 1, characterized in that, The boundary disturbance parameters include battery mass production parameters, battery corner region parameters, and sensor measurement error parameters. Calculating the degree of disturbance of the boundary disturbance parameters to the reference charging safety boundary to obtain the target safety parameters includes: The degree of disturbance of the battery mass production parameters to the reference charging safety boundary is calculated to obtain the manufacturing safety parameters; The degree of disturbance of the battery corner region parameters to the reference charging safety boundary is calculated to obtain the corner effect safety parameters; The degree of disturbance of the sensor measurement error parameters to the reference charging safety boundary is calculated to obtain the sensor error safety parameters; The target safety parameter is calculated based on the manufacturing safety parameter, the corner effect safety parameter, and the sensor error safety parameter.

3. The method according to claim 2, characterized in that, The calculation of the degree of disturbance of the battery mass production parameters to the reference charging safety boundary, to obtain the manufacturing safety parameters, includes: Electrochemical simulations were performed on the mass production parameters of the battery to obtain the first charging safety boundary; The manufacturing safety parameters are calculated based on the reference charging safety boundary and the first charging safety boundary.

4. The method according to claim 2, characterized in that, The calculation of the degree of disturbance of the battery corner region parameters to the reference charging safety boundary, to obtain corner effect safety parameters, includes: Electrochemical simulation was performed on the parameters of the battery corner region to obtain the second charging safety boundary; The corner effect safety parameters are calculated based on the reference charging safety boundary and the second charging safety boundary.

5. The method according to claim 2, characterized in that, The sensor measurement error parameters include temperature error parameters and state of charge error parameters. The calculation of the degree of disturbance of the sensor measurement error parameters to the reference charging safety boundary, to obtain sensor error safety parameters, includes: The reference charging safety boundary is interpolated based on the temperature error parameter and the state of charge error parameter to obtain the third charging safety boundary. The sensor error safety parameters are calculated based on the reference charging safety boundary and the third charging safety boundary.

6. The method according to claim 2, characterized in that, The step of calculating the target safety parameter based on the manufacturing safety parameter, the corner effect safety parameter, and the sensor error safety parameter includes: Calculate the comprehensive safety parameters based on the manufacturing safety parameters, the corner effect safety parameters, and the sensor error safety parameters; The target security parameter is obtained by calculating the quantile of the comprehensive security parameter based on the preset security reliability; wherein, the target probability is equal to the preset security reliability, and the target probability is the probability that the comprehensive security parameter is greater than or equal to the target security parameter.

7. The method according to claim 6, characterized in that, The step of calculating the quantiles of the comprehensive security parameters based on a preset security reliability to obtain the target security parameters includes: Obtain the standard normal quantile corresponding to the preset security and reliability to get the target reliability; Obtain the mean and standard deviation of the comprehensive safety parameters; The quantiles of the comprehensive safety parameter are calculated based on the mean, the standard deviation, and the target reliability to obtain the target safety parameter.

8. A battery charging method, characterized in that, The method includes: Obtain the current temperature and current state of charge of the target battery; The target charging safety boundary is queried based on the current temperature and the current state of charge to obtain the current maximum charging rate, and the current maximum charging current is determined based on the current maximum charging rate; wherein, the target charging safety boundary is obtained by the method for determining the battery charging safety boundary according to any one of claims 1 to 7; The target charging current is determined based on the current maximum charging current; wherein the target charging current is less than or equal to the current maximum charging current; The target battery is charged according to the target charging current.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method of any one of claims 1 to 7 or the method of claim 8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7 or the method of claim 8.

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