Lithium battery charging control method, system and equipment

Abstract

The invention relates to a lithium battery charging control method, system and device, and relates to the field of charging control, and the method comprises the steps: obtaining an electric quantity initial residual value, a charging environment temperature and charging rate time sequence information, inputting a correlation polarization voltage prediction model for processing, and generating an electric quantity residual value increment rate and polarization voltage time sequence information; inputting the polarization voltage time sequence information into an associated transient discharge current calibration model of the lithium battery model for processing, and generating a reverse transient discharge calibration current; performing charging control quality evaluation on the charging rate time sequence information to obtain a charging control quality coefficient; and when the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, performing lithium battery charging control. When the lithium battery of the electric tool is quickly charged, charging control quality evaluation based on polarization voltage prediction and instantaneous discharge current calibration is introduced, so that the influence on the service life of the battery is minimized, and the technical effect of considering the charging speed and the service life of the battery is achieved.

Description

Technical Field

[0001] The present invention relates to the field of charging control, and in particular to a lithium battery charging control method, system and device. Background Art

[0002] Power tools are widely used in various fields, and their convenience and efficiency are highly favored. However, with the popularity of power tools, users have put forward higher requirements for the charging speed and service life of power tool lithium batteries. In the prior art, in order to achieve fast charging of lithium batteries, high-rate charging is usually adopted. However, high-rate charging will cause serious polarization inside the battery, which will reduce the available capacity of the battery and reduce the charging efficiency. In order to reduce the degree of polarization, the prior art usually adopts the method of instantaneous discharge, that is, the battery is intermittently discharged for a short time during the charging process to reduce the degree of polarization inside the battery. However, although frequent instantaneous discharge can reduce the degree of polarization to a certain extent, it will also have an adverse effect on the service life of the battery. Instantaneous discharge will cause additional heat to be generated inside the battery, accelerate the aging of the battery material, and reduce the cycle life of the battery. Therefore, how to minimize the degree of polarization while achieving fast charging of power tool lithium batteries, while minimizing the impact of instantaneous discharge on battery life, has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] The present invention aims to solve the technical problem in the prior art that in the scenario of rapid charging of lithium batteries for electric tools, high-rate charging leads to severe battery polarization, and instantaneous discharge is needed to reduce the polarization degree, but instantaneous discharge affects the battery life. A lithium battery charging control method, system and device are provided to solve the problem.

[0004] The technical solution of the present invention to solve the above technical problems is as follows:

[0005] In a first aspect, the present invention provides a lithium battery charging control method, comprising: obtaining an initial residual power value, a charging environment temperature, and a charging rate timing information; inputting the initial residual power value, the charging environment temperature, and the charging rate timing information into an associated polarization voltage prediction model of the lithium battery model for processing, and generating a residual power value increment rate and polarization voltage timing information; inputting the timing end point polarization voltage of the polarization voltage timing information into an associated instantaneous discharge current calibration model of the lithium battery model for processing, and generating a reverse instantaneous discharge calibration current; based on the reverse instantaneous discharge calibration current, the residual power value increment rate, and the polarization voltage timing information, performing a charging control quality evaluation on the charging rate timing information, and obtaining a charging control quality coefficient; when the charging control quality coefficient is greater than or equal to a charging control quality coefficient threshold, performing lithium battery charging control according to the charging rate timing information.

[0006] In a second aspect, the present invention provides a lithium battery charging control system, including: a data acquisition module, used to obtain an initial residual value of power, a charging environment temperature and a charging rate timing information; a prediction processing module, used to input the initial residual value of power, the charging environment temperature and the charging rate timing information into an associated polarization voltage prediction model of the lithium battery model for processing, and generate a residual power value increment rate and polarization voltage timing information; a calibration generation module, used to input the timing end point polarization voltage of the polarization voltage timing information into an associated instantaneous discharge current calibration model of the lithium battery model for processing, and generate a reverse instantaneous discharge calibration current; a quality assessment module, used to perform a charging control quality assessment on the charging rate timing information based on the reverse instantaneous discharge calibration current, the residual power value increment rate and the polarization voltage timing information, and obtain a charging control quality coefficient; a charging control module, used to control the charging of the lithium battery according to the charging rate timing information when the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold.

[0007] In a third aspect, the present application provides an electric tool charging device for implementing a lithium battery charging control method.

[0008] The beneficial effects of the present invention are:

[0009] Obtain the initial remaining value of power, charging environment temperature and charging rate timing information to fully understand the current charging status and charging conditions of the battery, and provide necessary information for subsequent charging control; input the initial remaining value of power, charging environment temperature and charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing, generate the remaining value of power increment rate and polarization voltage timing information, realize the polarization voltage change trend during the charging process, and predict the rate of increase of the remaining value of power, providing key basis for subsequent charging control quality evaluation; input the timing end point polarization voltage of the polarization voltage timing information into the associated instantaneous discharge current calibration model of the lithium battery model for processing, generate the reverse instantaneous discharge calibration current, and determine the appropriate instantaneous discharge current size according to the predicted polarization voltage. , so as to effectively reduce the degree of polarization and minimize the impact on battery life; based on the reverse instantaneous discharge calibration current, the residual power value increment rate and the polarization voltage timing information, the charging control quality evaluation is performed on the charging rate timing information to obtain the charging control quality coefficient, which reflects the quality of the current charging rate timing information; when the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, the lithium battery charging is controlled according to the charging rate timing information to determine whether the current charging rate timing information meets the requirements. If the requirements are met, the charging control is performed according to the current charging rate timing information to achieve a fast, efficient and low-loss charging process, which minimizes the impact on battery life while ensuring the charging speed, and effectively solves the problems in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A schematic diagram of a lithium battery charging control method provided by the present invention;

[0011] Figure 2 This is a structural schematic diagram of a lithium battery charging control system provided by the present invention.

[0012] In the accompanying drawings, the components represented by the reference numerals are as follows:

[0013] Data acquisition module 11, prediction processing module 12, calibration generation module 13, quality assessment module 14, charging control module 15. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0015] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0016] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in the present invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present invention.

[0017] Embodiment 1:

[0018] like Figure 1 As shown, an embodiment of the present invention provides a lithium battery charging control method, comprising:

[0019] S100: Obtaining initial remaining power value, charging environment temperature and charging rate timing information.

[0020] Specifically, before executing charging control, it is necessary to obtain the initial remaining power value of the lithium battery, the charging environment temperature and the charging rate timing information.

[0021] The initial remaining value of the power represents the remaining power level of the lithium battery when charging begins. The initial remaining value of the power can be measured in real time by the power metering circuit of the lithium battery, or it can be directly read from the battery management system of the lithium battery. The charging environment temperature is an important external factor affecting the charging performance of the lithium battery. In order to obtain the charging environment temperature, a temperature sensor is arranged near the lithium battery pack to collect the temperature data of the battery environment in real time during the charging process. Among them, the temperature sensor includes thermocouples, thermal resistors, semiconductor temperature sensors, etc. The charging rate timing information represents the change of the charging current relative to the multiple of the rated capacity of the battery during the entire charging process. Among them, the greater the charging rate, the greater the charging current and the faster the charging speed, but it may also bring greater polarization effect and heating problems. In order to obtain appropriate charging rate timing information, it is randomly generated within a certain range according to the rated charging parameters of the lithium battery (such as rated voltage, rated capacity, maximum charging current, etc.) and actual use requirements, or the charger or external energy management system can provide corresponding charging rate timing information according to the established charging strategy.

[0022] By obtaining the initial remaining power value, charging environment temperature and charging rate timing information, basic information is provided for lithium battery charging control.

[0023] S200: Inputting the initial remaining power value, the charging environment temperature and the charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing to generate a remaining power value increment rate and polarization voltage timing information.

[0024] Specifically, after obtaining the initial residual value of the power, the charging environment temperature and the charging rate sequence information, this information is input into the associated polarization voltage prediction model corresponding to the lithium battery model. The associated polarization voltage prediction model is based on a large number of experimental data of lithium batteries of the same model under different charging conditions, and is trained using machine learning algorithms (such as neural networks, support vector machines, etc.). The input parameters of the associated polarization voltage prediction model include the initial residual value of the power, the charging environment temperature and the charging rate sequence information, and the output parameters include the rate of increment of the residual value of the power and the polarization voltage sequence information. Among them, the rate of increment of the residual value of the power characterizes the rate of increase of the remaining power of the lithium battery under a given charging rate sequence, reflects the energy transfer efficiency during the charging process, and provides a basis for subsequent charging evaluation. The polarization voltage sequence information characterizes the changes in the additional voltage caused by various polarization effects inside the lithium battery during the entire charging process. The main sources of polarization voltage include ohmic polarization, charge transfer polarization, concentration polarization, etc., which will affect the charging efficiency and cycle life of the lithium battery. The polarization voltage timing information generated by the associated polarization voltage prediction model can quantitatively reflect the polarization level during the charging process, providing an important reference for subsequent charging optimization control.

[0025] Since different types of lithium batteries have differences in materials, structures, capacities, etc., their charge and discharge characteristics are also different. Therefore, in order to obtain accurate prediction results, it is necessary to build and train corresponding polarization voltage prediction models for different lithium battery models. In practical applications, a polarization voltage prediction model library can be established in advance for mainstream lithium battery models, and the corresponding associated polarization voltage prediction model can be called for calculation according to the actual battery model used.

[0026] S300: Inputting the timing end point polarization voltage of the polarization voltage timing information into the associated instantaneous discharge current calibration model of the lithium battery model for processing to generate a reverse instantaneous discharge calibration current.

[0027] Specifically, the polarization voltage timing information of the entire charging process is obtained through the associated polarization voltage prediction model. In order to quantitatively evaluate the polarization degree of the charging process, special attention should be paid to the last time point of the polarization voltage timing information, that is, the polarization voltage value at the end of the timing. The timing end polarization voltage is input into the associated instantaneous discharge current calibration model corresponding to the lithium battery model to obtain the reverse discharge current reference value for suppressing the polarization effect, that is, the reverse instantaneous discharge calibration current. The associated instantaneous discharge current calibration model is based on the experimental data of a specific model of lithium battery and is fitted by algorithms such as regression analysis. The model reflects the optimal instantaneous discharge current value corresponding to the lithium battery at different polarization voltage levels. The input parameter of the associated instantaneous discharge current calibration model is the timing end polarization voltage, and the output parameter is the reverse instantaneous discharge calibration current.

[0028] The so-called reverse instantaneous discharge calibration current refers to applying a short-term high current discharge in the opposite direction of the charging current to the lithium battery when charging is about to end. This can effectively reduce the polarization effect inside the lithium battery, improve the energy conversion efficiency, and extend the cycle life of the battery. However, the reverse instantaneous discharge current cannot be too large, otherwise it will cause irreversible damage to the lithium battery. Therefore, it is necessary to give a reasonable reverse discharge current reference value based on the magnitude of the timing end point polarization voltage by the associated instantaneous discharge current calibration model.

[0029] Similar to the associated polarization voltage prediction model, the associated instantaneous discharge current calibration model is also related to the lithium battery model. Different types of lithium batteries may have different optimal reverse discharge current values. Therefore, in practical applications, it is necessary to pre-build and store the corresponding associated instantaneous discharge current calibration model for different lithium battery models so that it can be called as needed.

[0030] S400: Based on the reverse instantaneous discharge calibration current, the residual power value increment rate and the polarization voltage timing information, a charging control quality evaluation is performed on the charging rate timing information to obtain a charging control quality coefficient.

[0031] Specifically, by processing the initial remaining charge value, charging environment temperature and charging rate timing information, the reverse instantaneous discharge calibration current, the remaining charge value increment rate and the polarization voltage timing information are obtained. Then, these parameters are used to evaluate the initially given charging rate timing information to determine its quality.

[0032] First, a charging control quality evaluation function that comprehensively considers multiple parameters is constructed. Then, parameters such as the reverse instantaneous discharge calibration current, the rate of increase in the residual value of the electric charge, and the polarization voltage timing information are substituted into the function to calculate the quantized charging control quality coefficient. The size of this coefficient reflects the quality of the current charging rate timing. The larger the value, the higher the charging control quality, and vice versa. The specific form of the charging control quality evaluation function can be designed according to actual needs and experience. For example, in the form of weighted summation, each parameter is multiplied by its corresponding weight coefficient, and then the final charging control quality coefficient is obtained by summing up. Among them, the size of the weight coefficient reflects the degree of influence of each parameter on the charging control quality, which can be set according to theoretical analysis and experimental data.

[0033] By obtaining the charge control quality coefficient, the quality of the given charge rate sequence information can be quantitatively reflected. The higher the charge control quality coefficient, the better the charge rate sequence information can suppress the polarization effect, improve the charging efficiency, and extend the battery life while ensuring the charging speed. Therefore, the introduction of the charge control quality coefficient provides an important basis for the subsequent implementation of lithium battery charging control, and helps to quickly find the optimal charge rate sequence information that balances various performance indicators.

[0034] S500: When the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, the lithium battery charging is controlled according to the charging rate timing information.

[0035] Specifically, in order to determine whether the charging rate timing information can be directly applied to the actual lithium battery charging control, a preset charging control quality coefficient threshold is introduced as a judgment criterion. The obtained charging control quality coefficient is compared with the charging control quality coefficient threshold. If the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, it is considered that the current charging rate timing information can be directly used to guide the subsequent actual charging control process.

[0036] In this case, the charging current is automatically adjusted according to the charging rate values ​​corresponding to each time period specified in the charging rate timing information, and the battery voltage, temperature and other state parameters are monitored in real time to ensure that the charging process is safe, efficient and controllable. At the same time, when charging is about to end, the battery is subjected to a short reverse discharge with reference to the reverse instantaneous discharge calibration current obtained to suppress the polarization effect and improve the charging performance. Among them, the charging control quality coefficient threshold is set according to factors such as the model and capacity of the lithium battery, the power limit of the charging equipment, and the safety requirements of the usage scenario.

[0037] When the charge control quality coefficient reaches or exceeds the preset threshold, the current charge rate timing information is directly used to control the lithium battery charge, which can avoid unnecessary iterative optimization, shorten the time of charge control decision-making, and improve charging efficiency. At the same time, since the charge rate timing information has passed the evaluation and screening, it can effectively suppress the polarization effect and extend the battery life while ensuring the charging speed, and can obtain an ideal charge control effect.

[0038] Furthermore, the embodiment of the present application also includes:

[0039] S410: Constructing multi-constraint functions:

[0040]

[0041] Among them, x1 represents the charging time, x2 represents the incremental rate of the residual power, x3 represents the incremental rate of the polarization voltage, x4 represents the polarization voltage at the end of the timing sequence, x5 represents the reverse instantaneous discharge calibration current, and x i0 Characterizes the threshold value of the constraint parameter of the i-th attribute, x i Characterizes the i-th attribute constraint parameter, x i belongs to (x1, x2, x3, x4, x5), a i Characterizes the adjustment parameter of the i-th attribute, a i ≥1, f(x1, x2, x3, x4, x5) represents the charging control quality factor;

[0042] S420: When the charging time is less than or equal to the charging time threshold, and the rate of increase in the remaining power is greater than or equal to the rate of increase in the remaining power, and the rate of increase in the polarization voltage is less than or equal to the rate of increase in the polarization voltage, and the polarization voltage at the end of the timing is less than or equal to the polarization voltage threshold, and the reverse instantaneous discharge calibration current is less than or equal to the reverse instantaneous discharge current threshold, the multi-constraint function is called to perform control quality evaluation to obtain the charging control quality coefficient.

[0043] In a preferred embodiment, in order to evaluate the charging control quality and obtain the charging control quality coefficient, firstly, a multi-constraint function for quantitatively evaluating the charging control quality is constructed, namely:

[0044]

[0045] The independent variables of this function include five attribute constraint parameters, namely, charging time x1, remaining power increment rate x2, polarization voltage increment rate x3, timing end point polarization voltage x4 and reverse instantaneous discharge calibration current x5. Each attribute constraint parameter has its corresponding parameter threshold, namely x i0 , specifically represented by x 10 、x 20 、x 30 、x 40 and x 50 The form of the multi-constraint function is the sum of the absolute values ​​of the differences between the five attribute constraint parameters and their thresholds, and then taking a i The logarithm of the base. i is the i-th attribute adjustment parameter, which is used to control the influence of each attribute constraint parameter on the entire function value. i The value of is greater than or equal to 1, and the specific value is set according to actual needs and experience. The output value f(x1, x2, x3, x4, x5) of the multi-constraint function is the quantized charging control quality coefficient. Specifically, when a certain attribute constraint parameter deviates from its threshold, the more a iThe larger the logarithmic value of the base, the greater the negative impact of the attribute on the charging control quality. By adding the logarithmic values ​​of the five attributes, the comprehensive impact of the five attribute constraint parameters can be comprehensively evaluated to obtain a quantified charging control quality coefficient.

[0046] At the same time, it is specified when the multi-constraint function should be called to evaluate the charging control quality. Specifically, the multi-constraint function will be called to calculate the charging control quality coefficient only when the five attribute constraint parameters meet the following conditions at the same time: the charging time is less than or equal to the charging time threshold; the residual power value increment rate is greater than or equal to the residual power value increment rate threshold; the polarization voltage increment rate is less than or equal to the polarization voltage increment rate threshold; the timing end point polarization voltage is less than or equal to the polarization voltage threshold; the reverse instantaneous discharge calibration current is less than or equal to the reverse instantaneous discharge current threshold. These five conditions are set to ensure that the charging control quality evaluation is only performed when the charging process meets certain performance requirements to avoid unnecessary calculation overhead.

[0047] The charging control quality evaluation method based on multi-constraint functions can comprehensively consider the key performance indicators of the charging process, quantify the pros and cons of charging control, and provide an important reference for subsequent optimization control. Compared with simple single indicator evaluation, it can more comprehensively and accurately judge the quality of charging control, which helps to find the optimal charging strategy and maximize the battery life while ensuring charging speed and efficiency.

[0048] Furthermore, the embodiment of the present application also includes:

[0049] S430: When the charging duration is greater than the charging duration threshold, or / and the remaining power value increment rate is less than the remaining power value increment rate threshold, or / and the polarization voltage increment rate is greater than the polarization voltage increment rate threshold, or / and the timing end point polarization voltage is greater than the polarization voltage threshold, or / and the reverse instantaneous discharge calibration current is greater than the reverse instantaneous discharge current threshold, the charging control quality coefficient is set to negative infinity.

[0050] In a feasible implementation, when any of the following situations occurs, there is no need to calculate the multi-constraint function, but the charging control quality coefficient is directly set to negative infinity, including: the charging time exceeds the charging time threshold; the residual power value increment rate is lower than the residual power value increment rate threshold; the polarization voltage increment rate exceeds the polarization voltage increment rate threshold; the timing end point polarization voltage exceeds the polarization voltage threshold; the reverse instantaneous discharge calibration current exceeds the reverse instantaneous discharge current threshold. The reason why the charging control quality coefficient is directly set to negative infinity in these cases is that at this time one or more key performance indicators of the charging process have obviously exceeded the acceptable range. Even if other indicators perform normally, the overall charging control quality is difficult to reach a satisfactory level. In order to avoid unnecessary multi-constraint function calculations in these cases, the quality assessment result of using negative infinity as the charging control quality coefficient is directly given.

[0051] By pre-identifying and handling certain extreme situations, unnecessary computational overhead can be reduced and the efficiency of charging control quality assessment can be improved. At the same time, unacceptable charging control schemes are clearly identified, providing clear boundary conditions for subsequent optimization control, avoiding wandering near inferior solutions, accelerating convergence speed, and laying the foundation for achieving optimal charging control of lithium batteries.

[0052] Furthermore, the embodiment of the present application also includes:

[0053] S110: receiving basic information of a lithium battery, wherein the basic information of the lithium battery includes the model of the lithium battery and the initial remaining power value;

[0054] S120: collecting the charging environment temperature through an environmental sensor;

[0055] S130: Obtaining the charging rate timing information based on the random configuration of the charging rate constraint interval and the charging duration constraint interval.

[0056] In a preferred embodiment, when obtaining the initial remaining power value, charging environment temperature and charging rate timing information, first, the basic information of the lithium battery is received, including the lithium battery model and the current initial remaining power value. Among them, the lithium battery model information is subsequently used to select the corresponding associated polarization voltage prediction model and the associated instantaneous discharge current calibration model, because the performance parameters and optimal charging strategies of lithium batteries of different models may vary greatly. The initial remaining power value reflects the remaining power level of the lithium battery before the start of this charging, and is a benchmark value for evaluating the change in power during the charging process. The basic information of the lithium battery is provided by the lithium battery management system, or obtained by communicating with the lithium battery pack.

[0057] At the same time, the temperature information of the environment in which the lithium battery is located is collected through the environmental sensor to obtain the charging environment temperature. The charging environment temperature is an important external factor that affects the charging performance of the lithium battery. Under different temperature conditions, the optimal charging rate, polarization characteristics and other parameters of the lithium battery may change. Therefore, real-time acquisition of accurate charging environment temperature is crucial for charging control. Among them, the environmental sensor can use various temperature sensors with suitable temperature range and accuracy that meet the requirements, such as thermocouples, thermal resistors, semiconductor temperature sensors, etc.

[0058] At the same time, according to the preset charging rate constraint interval and charging time constraint interval, a set of charging rate timing information is randomly generated. The charging rate timing information defines the charging rate (i.e., the ratio of the charging current to the rated capacity of the battery) in each time period during the entire charging process. Reasonable charging rate timing design can effectively suppress the polarization effect and extend the battery life while ensuring the charging speed. In order to obtain feasible charging rate timing information, it is necessary to pre-set the charging rate constraint interval and the charging time constraint interval. Among them, the charging rate constraint interval limits the value range of the charging rate in each time period, which is set according to the rated charging rate, temperature characteristics and other factors of the lithium battery; the charging time constraint interval limits the time length of the entire charging process, which must take into account the actual application requirements and the health of the battery. Within the given constraint interval, the charging rate timing information is generated by random configuration, which can increase the diversity of the search space to a certain extent and improve the probability of obtaining the optimal charging rate timing information.

[0059] By acquiring the initial remaining power value, charging environment temperature and charging rate timing information, the key parameters affecting the charging performance of the lithium battery are obtained, providing necessary data support for subsequent charging control and improving the safety, reliability and economy of lithium battery charging.

[0060] Furthermore, the embodiment of the present application also includes:

[0061] S600: When the charging control quality coefficient is less than the charging control quality coefficient threshold, determining whether the amount of historical charging rate time series information is greater than or equal to a population size threshold;

[0062] S700: If the amount of the historical charging rate time series information is less than the population size threshold, the charging rate time series information is randomly updated based on the charging rate constraint interval and the charging time constraint interval, and then the process is returned to the start process;

[0063] S800: If the amount of the historical charging rate timing information is greater than or equal to the population size threshold, based on the historical charging rate timing information, combined with the charging rate constraint interval and the charging duration constraint interval, the charging rate timing information is guided to be updated and then the process is returned to the start process.

[0064] In a preferred embodiment, an adaptive optimization mechanism is introduced to iteratively update the charging rate timing information when the charging control quality coefficient does not meet the requirements until satisfactory charging rate timing information is obtained.

[0065] First, compare the charge control quality coefficient and the charge control quality coefficient threshold. When the charge control quality coefficient is less than the preset charge control quality coefficient threshold, it indicates that the current charge rate timing information needs to be further optimized and improved. In order to effectively guide the subsequent optimization direction, the population size threshold is introduced to determine whether the amount of historical charge rate timing information currently obtained is sufficient. The size of the population size threshold can be set according to factors such as the complexity of the problem and the limitation of computing resources.

[0066] If the number of historical charging rate time series information has not reached the population size threshold, the current charging rate time series information is randomly updated according to the preset charging rate constraint interval and charging time constraint interval, that is, new charging rate time series data is randomly generated within the constraint interval to replace the original data. By means of random perturbation, the local optimal solution can be jumped out to a certain extent, and the probability of obtaining the global optimal solution can be increased. If the number of historical charging rate time series information has reached or exceeded the population size threshold, the existing historical charging rate time series information is used, combined with the charging rate constraint interval and the charging time constraint interval, to guide the update of the current charging rate time series information. The so-called guided update refers to the directional correction of the current solution (i.e., the current charging rate time series information) according to the high-quality solution in the historical data (such as the charging rate time series information with a higher charging control quality coefficient), so that it evolves in a better direction. Among them, the specific strategy of guided update can adopt various heuristic optimization algorithms, such as the crossover mutation operation of the genetic algorithm, the speed update rule of the particle swarm optimization algorithm, etc. Through guided update, the existing high-quality solution information is fully utilized to accelerate the convergence speed and improve the optimization efficiency.

[0067] Regardless of whether a random update or a guided update is performed, the new charging rate timing information obtained by the update will return to the starting process of the entire method, and go through a series of steps such as charging control quality evaluation and threshold judgment again until the charging rate timing information with a charging control quality coefficient greater than or equal to the charging control quality coefficient threshold is obtained.

[0068] By introducing two strategies, random update and guided update, the charging rate timing information is continuously optimized iteratively until the charging control quality coefficient threshold is met. This adaptive optimization mechanism can automatically adjust the optimization strategy and number of iterations according to the real-time situation of historical data, while ensuring the optimization efficiency and taking into account the versatility and robustness, providing a strong guarantee for obtaining the optimal charging control.

[0069] Furthermore, the embodiment of the present application also includes:

[0070] S810: Clustering the historical charging rate time series information to obtain a first cluster of historical charging rate time series information to an Nth cluster of historical charging rate time series information;

[0071] S820: performing inter-cluster cross-guidance update on the charging rate timing information of the first cluster of historical charging rate timing information to the Nth cluster of historical charging rate timing information to obtain first updated charging rate timing information;

[0072] S830: Traversing the first cluster of historical charging rate timing information until the Nth cluster of historical charging rate timing information performs cluster-guided update on the charging rate timing information to obtain second updated charging rate timing information;

[0073] S840: Add the first updated charging rate timing information and the second updated charging rate timing information into the charging rate timing information update result.

[0074] In a preferred embodiment, when guiding and updating the charging rate timing information, first, clustering is performed on the existing historical charging rate timing information. The purpose of clustering is to classify similar charging rate timing information into the same cluster, while the charging rate timing information between different clusters has certain differences. Among them, clustering processing can use clustering algorithms such as K-means clustering, hierarchical clustering, and density clustering. The result of clustering is to divide the historical charging rate timing information into several clusters, which are recorded as the first cluster of historical charging rate timing information until the Nth cluster of historical charging rate timing information. Then, using the result of clustering, that is, the first cluster of historical charging rate timing information until the Nth cluster of historical charging rate timing information, the current charging rate timing information is cross-guided and updated between clusters. Specifically, a number of historical charging rate timing information are randomly selected from different clusters, and the charging rate data of certain time periods are cross-combined to generate new charging rate timing information, which is recorded as the first updated charging rate timing information. Through cross-cluster cross-operations, high-quality information from different clusters can be reorganized and integrated, increasing the diversity and quality of new solutions.

[0075] Subsequently, the current charging rate timing information is guided and updated within each cluster. Specifically, the historical charging rate timing information of the first cluster is traversed until the historical charging rate timing information of the Nth cluster, and one or more high-quality solutions (such as charging rate timing information with a higher charging control quality coefficient) are selected from each cluster, and the charging rate data of part of the time period of the current solution is replaced with the data of the corresponding time period of the high-quality solution, and new charging rate timing information is generated, which is recorded as the second updated charging rate timing information. Through the operation of guided update within the cluster, the local high-quality information within each cluster can be fully utilized to finely optimize and improve the current solution. Subsequently, the first updated charging rate timing information and the second updated charging rate timing information are taken together as the result of this round of guided update, and added to the charging rate timing information update result. These updated charging rate timing information will return to the starting process of the entire method to undergo a new round of charging control quality evaluation and optimization improvement until the requirements are met.

[0076] Through two levels of operations, namely, inter-cluster crossing and intra-cluster guidance, the diversity of solutions is increased while taking into account the refinement of optimization. This can significantly improve the optimization efficiency and quality of the charging rate timing information, accelerate the convergence speed, and provide strong support for obtaining the optimal charging rate timing information online and in real time.

[0077] Furthermore, the embodiment of the present application also includes:

[0078] S811: Obtaining first historical charging rate timing information and second historical charging rate timing information of the historical charging rate timing information;

[0079] S812: extracting the first moment quantity of the first historical charging rate time series information and the second moment quantity of the second historical charging rate time series information;

[0080] S813: constructing a first high-dimensional coordinate system by taking the larger number of the first number of moments and the second number of moments as a dimension;

[0081] S814: Processing the first historical charging rate time series information and the second historical charging rate time series information respectively based on the first high-dimensional coordinate system to obtain first distribution coordinates and second distribution coordinates;

[0082] S815: When the distribution distance between the first distribution coordinates and the second distribution coordinates is less than or equal to a distribution distance threshold, adding the first historical charging rate timing information and the second historical charging rate timing information to the same cluster historical charging rate timing information;

[0083] S816: Otherwise, adding the first historical charging rate timing information and the second historical charging rate timing information to the heterogeneous cluster historical charging rate timing information;

[0084] S817: until the historical charging rate timing information is clustered, the first cluster of historical charging rate timing information is obtained until the Nth cluster of historical charging rate timing information is obtained;

[0085] When the first moment number is smaller than the larger moment number, the first historical charging rate timing information is padded with 0 to obtain the first historical charging rate update timing information;

[0086] S818: Distribute the first historical charging rate update time series information to the first high-dimensional coordinate system to obtain first distribution coordinates;

[0087] S819: When the first number of moments is equal to the larger number of moments, the first historical charging rate time series information is distributed to the first high-dimensional coordinate system to obtain first distribution coordinates.

[0088] In a preferred embodiment, when obtaining the first cluster of historical charging rate timing information to the Nth cluster of historical charging rate timing information, first, two samples are randomly selected from the historical charging rate timing information, which are recorded as the first historical charging rate timing information and the second historical charging rate timing information. Historical charging rate timing information refers to the charging rate timing data generated in the previous historical charging process and evaluated for charging control quality. Each historical charging rate timing information records the charging rate value corresponding to each time point in a complete charging process. Since the actual charging time may vary due to different optimization strategies, the number of time points contained in different historical charging rate timing information may be different. Secondly, the number of time points contained in the first historical charging rate timing information and the second historical charging rate timing information are extracted, and recorded as the first moment number and the second moment number respectively. The moment number reflects the timing length of the historical charging rate timing information. For the first historical charging rate time series information, the number of moments is equal to the number of charging rate data points in the time series, that is, the first moment number; similarly, the number of moments of the second historical charging rate time series information is the second moment number. By extracting the number of moments, we can know the length difference in the time dimension of the two historical charging rate time series information to be compared, and prepare for the subsequent coordinate system construction and distribution mapping.

[0089] Subsequently, a unified metric space is constructed for the first historical charging rate time series information and the second historical charging rate time series information to be compared, so as to subsequently calculate the similarity between the two historical charging rate time series information. The specific approach is to take the larger value of the first moment number and the second moment number as the dimension of the coordinate system, and construct a high-dimensional coordinate system, recorded as the first high-dimensional coordinate system. For example, assuming that the number of the first moment is 10 and the number of the second moment is 12, the larger moment number is 12. Thus, a 12-dimensional coordinate system is constructed, each dimension corresponding to a time point in the historical charging rate time series information. In this 12-dimensional coordinate system, each historical charging rate time series information can be represented as a 12-dimensional vector, where the first 10 components correspond to the charging rate values ​​of the first 10 time points, and the last 2 components are filled with zeros as appropriate (see S818 and S819 for specific processing methods). In this way, the two historical charging rate time series information with unequal time series lengths are mapped to the same high-dimensional space, laying the foundation for subsequent similarity calculations and clustering operations. Then, based on the first high-dimensional coordinate system, the first historical charging rate time series information and the second historical charging rate time series information are processed respectively, mapped as points in the coordinate system, and the corresponding coordinate representations are obtained, which are recorded as the first distribution coordinates and the second distribution coordinates respectively. Specifically, for the first historical charging rate time series information, if its number of moments (the first moment number) is equal to the dimension of the first high-dimensional coordinate system (i.e., the larger moment number), the charging rate values ​​of each time point are directly filled into each dimension of the coordinate system in turn to obtain the first distribution coordinates (S819). If the first moment number is less than the larger moment number, the tail of the first historical charging rate time series information is padded with zeros so that its length is equal to the dimension of the coordinate system, and then mapped to obtain the first distribution coordinates (S818). Similarly, the second historical charging rate time series information is processed in the same way. If the second moment number is equal to the larger moment number, the second distribution coordinates are directly mapped; if the second moment number is less than the larger moment number, zeros are padded first and then mapped. Through the above processing, no matter whether the original lengths of two historical charging rate time series information are equal, they can be mapped into the same high-dimensional coordinate system to obtain a unified coordinate representation, which is convenient for subsequent similarity measurement and clustering operations.

[0090] Afterwards, by comparing the distance between the first distribution coordinate and the second distribution coordinate, it is determined whether the corresponding two historical charging rate time series information belong to the same cluster. First, the distance between the first distribution coordinate and the second distribution coordinate in the high-dimensional space is calculated, wherein the distance metric includes Euclidean distance, Manhattan distance, etc.; then, the calculated distance is compared with the preset distribution distance threshold. If the distance is less than or equal to the distribution distance threshold, it is considered that the similarity of the two historical charging rate time series information is high and should be classified into the same cluster, and the original first historical charging rate time series information and the second historical charging rate time series information are added to the same cluster historical charging rate time series information; on the contrary, if the distance is greater than the distribution distance threshold, it is considered that the difference between the two historical charging rate time series information is large and should be classified into different clusters, and the original first historical charging rate time series information and the second historical charging rate time series information are added to the different cluster historical charging rate time series information. Among them, the distribution distance threshold is a pre-set parameter used to control the granularity of clustering. The smaller the distribution distance threshold, the higher the requirement for similarity, and the more clusters may be formed; the larger the distribution distance threshold, the greater the difference that can be tolerated, and the fewer the number of clusters may be formed. The value of the distribution distance threshold needs to be adjusted according to the characteristics of the specific problem and actual needs. The appropriate value can be determined through empirical settings or cross-validation.

[0091] The clustering process is repeated until all samples in the historical charging rate timing information set are assigned to a certain cluster. In actual operation, this process is implemented in a loop. Specifically, in each iteration, two samples are randomly selected from the historical charging rate timing information set, and the clustering process is performed. The historical charging rate timing information is classified into the corresponding cluster according to the distance between the distribution coordinates; then, the next pair of samples is selected from the remaining samples, and the above operation is repeated until all samples are classified into the corresponding cluster. When the clustering process is completed, the original historical charging rate timing information set is divided into several non-overlapping subsets, each subset corresponds to a cluster, containing a set of similar historical charging rate timing information. These clusters are recorded in the order of generation as the first cluster of historical charging rate timing information, the second cluster of historical charging rate timing information, ..., until the Nth cluster of historical charging rate timing information. The historical charging rate timing information within each cluster has a high degree of similarity, while the historical charging rate timing information between different clusters has certain differences.

[0092] The clustering results based on distribution distance can better reflect the distribution characteristics and internal structure of historical charging rate time series information in high-dimensional space, laying the foundation for subsequent inter-cluster crossover and intra-cluster guidance. By performing optimization operations between clusters and within clusters, the diversity of new solutions can be increased, and the characteristics of high-quality solutions within each cluster can be inherited, which helps to quickly locate the optimal solution in the search space and improve optimization efficiency and quality.

[0093] Among them, considering the situation that the number of moments of the historical charging rate time series information to be mapped is inconsistent with the dimension of the high-dimensional coordinate system, the distribution coordinate acquisition process is further explained and supplemented. Specifically, for the first historical charging rate time series information, first determine the size relationship between its number of moments (the first moment number) and the dimension of the first high-dimensional coordinate system (that is, the larger moment number). If the first moment number is smaller than the larger moment number, it means that the length of the first historical charging rate time series information is insufficient and cannot be directly mapped to the high-dimensional coordinate system. At this time, the first historical charging rate time series information is padded with zeros, that is, zero elements are added at the end of it, where the number of added zero elements is the larger moment number minus the first moment number, so that its length is equal to the dimension of the coordinate system, thereby obtaining the first historical charging rate update time series information after zero padding. Then, the first historical charging rate update time series information after zero padding is mapped to the first high-dimensional coordinate system to obtain the first distribution coordinates. On the contrary, if the number of the first moment is exactly equal to the number of the larger moment, there is no need to perform tail zero padding, and the first historical charging rate time series information can be directly mapped to the first high-dimensional coordinate system to obtain the first distribution coordinates. Although S818 and S819 are for the first historical charging rate time series information, the processing method for the second historical charging rate time series information is exactly the same. That is, if the number of the second moment is less than the number of the larger moment, the second historical charging rate time series information is padded with zeros to obtain the second historical charging rate update time series information, and then mapped to obtain the second distribution coordinates; if the number of the second moment is equal to the number of the larger moment, the second distribution coordinates are directly mapped.

[0094] By padding the tail with zeros, it can be ensured that no matter how long the original historical charging rate time series information is, it can be mapped to the same high-dimensional coordinate system to obtain a unified coordinate representation. Although this processing method will change the distribution characteristics of the original data to a certain extent, it provides a comparable measurement benchmark for samples with different time series lengths, allowing distance-based clustering operations to proceed smoothly. In practical applications, in addition to padding the tail with zeros, other time series alignment methods can also be considered, such as linear interpolation, dynamic time warping, etc. The specific method to be selected can be determined according to actual needs.

[0095] Furthermore, the embodiment of the present application also includes:

[0096] S821: randomly extracting the kth cluster of historical charging rate sequence information and the yth cluster of historical charging rate sequence information from the first cluster of historical charging rate sequence information to the Nth cluster of historical charging rate sequence information;

[0097] S822: extracting the maximum solution of the charging control quality coefficient of the k-th cluster of historical charging rate time series information, and setting it as the guiding solution of the y-th cluster;

[0098] S823: extracting the maximum solution of the charging control quality coefficient of the historical charging rate time series information of the yth cluster, and setting it as the guiding solution of the kth cluster;

[0099] S824: guiding and updating a preset number of tail solutions of the historical charging rate timing information of the yth cluster according to the guided solution of the yth cluster, and guiding and updating a preset number of tail solutions of the historical charging rate timing information of the kth cluster according to the guided solution of the kth cluster to obtain the first updated charging rate timing information.

[0100] In a preferred embodiment, when performing inter-cluster cross-guidance update, first, two clusters are randomly selected from the historical charging rate timing information of the first cluster to the historical charging rate timing information of the Nth cluster, and are respectively recorded as the historical charging rate timing information of the kth cluster and the historical charging rate timing information of the yth cluster, for subsequent inter-cluster crossover operations. Among them, k and y are two different cluster numbers, which can be any two natural numbers between 1 and N. By randomly selecting different clusters for crossover, the diversity of new solutions can be increased to avoid falling into local optimality too early. Then, a high-quality solution is selected from the historical charging rate timing information of the kth cluster as a reference for guiding the update of the historical charging rate timing information of the yth cluster. The specific approach is to first find the solution with the largest charging control quality coefficient from the historical charging rate timing information of the kth cluster, that is, the charging rate timing information with the best evaluation result in the historical charging rate timing information of the kth cluster, which is recorded as the guiding solution of the yth cluster, and will be used to guide the update of the historical charging rate timing information of the yth cluster. By selecting the optimal solution from one cluster as the update reference for another cluster, the exchange and sharing of high-quality information between different clusters can be achieved. Similarly, the solution with the largest charging control quality coefficient is found from the historical charging rate timing information of the yth cluster, and it is recorded as the guiding solution of the kth cluster, which will be used to guide the update of the historical charging rate timing information of the kth cluster. Through this cross-guidance method, information exchange and complementary advantages between different clusters can be achieved, so that the updated solution can inherit the high-quality features of the cluster and absorb the excellent genes of other clusters, thereby improving the quality and diversity of the solution.

[0101] Subsequently, the obtained guided solution of the yth cluster and the guided solution of the kth cluster are used to update the historical charging rate timing information of the kth cluster and the historical charging rate timing information of the yth cluster respectively, so as to obtain the first updated charging rate timing information. Specifically, for each cluster, a preset number of tail solutions are selected, and the charging rate data of some time periods of these tail solutions are replaced with the data of the corresponding guided solution in the corresponding time period, so as to obtain the updated charging rate timing information. Among them, the preset number of tail solutions refers to some charging rate timing information located at the rear of each cluster, and the sorting in the cluster (such as sorting from large to small according to the charging control quality coefficient) is in a relatively backward position. The tail solution is selected for updating in order to optimize and improve the relatively poor solutions while retaining the high-quality solutions in each cluster, so as to improve the overall solution quality. In the process of guided update, the entire guided solution is not directly copied to the tail solution, but a part of the time period of the guided solution is selected for replacement. The purpose of this is to inherit the excellent characteristics of the guided solution while retaining some useful information of the tail solution itself, so as to achieve the fusion and synergy of the two. By adjusting the length and position of the replaced time period, the strength and scope of the guided update can be controlled. After the preset number of tail solutions of the historical charging rate timing information of the kth cluster and the historical charging rate timing information of the yth cluster are guided and updated, a new set of charging rate timing information is obtained, namely the first updated charging rate timing information. These updated timing information integrates the high-quality features of different clusters and reflects the effect of inter-cluster crossover.

[0102] By randomly selecting different clusters for crossover and using the optimal solution between clusters to guide and update the tail solution of another cluster, information exchange and complementary advantages between different clusters can be achieved. This inter-cluster crossover guidance update strategy can effectively balance the quality and diversity of solutions, while retaining the excellent characteristics of each cluster, and continuously guide the search to a better area, thereby improving the efficiency and effect of charging rate timing information optimization.

[0103] A lithium battery charging control method provided by an embodiment of the present invention has at least the following technical effects:

[0104] Obtaining the initial residual value of power, charging environment temperature and charging rate sequence information reflects the charging state and charging conditions of the battery, providing a basis for charging optimization control. The initial residual value of power, charging environment temperature and charging rate sequence information are input into the associated polarization voltage prediction model of the lithium battery model for processing to generate the residual value increment rate and polarization voltage sequence information, which provides an important basis for the subsequent charging control quality evaluation and helps to optimize the charging strategy. The polarization voltage at the time end of the polarization voltage sequence information is input into the associated instantaneous discharge current calibration model of the lithium battery model for processing to generate the reverse instantaneous discharge calibration current, optimize the instantaneous discharge strategy, and protect the battery while improving the charging efficiency. Based on the reverse instantaneous discharge calibration current, the residual value increment rate and the polarization voltage sequence information, the charging control quality of the charging rate sequence information is evaluated to obtain the charging control quality coefficient, which reflects the quality of the current charging rate sequence information and provides a decision-making basis for subsequent charging control. When the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, the lithium battery charging control is performed according to the charging rate timing information. If the charging control quality meets the standard, the current charging rate timing is directly executed to achieve a fast, efficient and low-loss charging process.

[0105] Embodiment 2:

[0106] like Figure 2 As shown, based on the same inventive concept as the lithium battery charging control method provided in the first embodiment, the embodiment of the present invention further provides a lithium battery charging control system, including:

[0107] The data acquisition module 11 is used to obtain the initial remaining value of the power, the charging environment temperature and the charging rate timing information;

[0108] The prediction processing module 12 is used to input the initial remaining power value, the charging environment temperature and the charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing, and generate the remaining power value increment rate and polarization voltage timing information;

[0109] The calibration generation module 13 is used to input the timing end point polarization voltage of the polarization voltage timing information into the associated instantaneous discharge current calibration model of the lithium battery model for processing to generate a reverse instantaneous discharge calibration current;

[0110] The quality assessment module 14 is used to perform a charge control quality assessment on the charge rate timing information based on the reverse instantaneous discharge calibration current, the residual power value increment rate and the polarization voltage timing information to obtain a charge control quality coefficient;

[0111] The charging control module 15 is used to control the charging of the lithium battery according to the charging rate timing information when the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold.

[0112] Furthermore, the quality assessment module 14 includes the following execution steps:

[0113] Construct a multi-constraint function:

[0114]

[0115] Among them, x1 represents the charging time, x2 represents the incremental rate of the residual power, x3 represents the incremental rate of the polarization voltage, x4 represents the polarization voltage at the end of the timing sequence, x5 represents the reverse instantaneous discharge calibration current, and x i0 Characterizes the threshold value of the constraint parameter of the i-th attribute, x i Characterizes the i-th attribute constraint parameter, x i belongs to (x1, x2, x3, x4, x5), a i Characterizes the adjustment parameter of the i-th attribute, a i ≥1, f(x1, x2, x3, x4, x5) represents the charging control quality factor;

[0116] When the charging time is less than or equal to the charging time threshold, and the remaining power value increment rate is greater than or equal to the remaining power value increment rate threshold, and the polarization voltage increment rate is less than or equal to the polarization voltage increment rate threshold, and the timing end point polarization voltage is less than or equal to the polarization voltage threshold, and the reverse instantaneous discharge calibration current is less than or equal to the reverse instantaneous discharge current threshold, call the multi-constraint function to perform control quality evaluation and obtain the charging control quality coefficient.

[0117] Furthermore, the quality assessment module 14 further includes the following execution steps:

[0118] When the charging duration is greater than the charging duration threshold, or / and the remaining power value increment rate is less than the remaining power value increment rate threshold, or / and the polarization voltage increment rate is greater than the polarization voltage increment rate threshold, or / and the timing endpoint polarization voltage is greater than the polarization voltage threshold, or / and the reverse instantaneous discharge calibration current is greater than the reverse instantaneous discharge current threshold, the charging control quality coefficient is set to negative infinity.

[0119] Furthermore, the data acquisition module 11 includes the following execution steps:

[0120] Receiving basic information of a lithium battery, wherein the basic information of the lithium battery includes the model of the lithium battery and the initial remaining power value;

[0121] collecting the charging environment temperature through an environmental sensor;

[0122] Based on the random configuration of the charging rate constraint interval and the charging time constraint interval, the charging rate timing information is obtained.

[0123] Furthermore, the embodiment of the present application also includes a rate optimization module, which includes the following execution steps:

[0124] When the charging control quality coefficient is less than the charging control quality coefficient threshold, determining whether the amount of historical charging rate time series information is greater than or equal to a population size threshold;

[0125] If the amount of the historical charging rate time series information is less than the population size threshold, the charging rate time series information is randomly updated based on the charging rate constraint interval and the charging time constraint interval, and then the process is returned to the start process;

[0126] If the amount of the historical charging rate timing information is greater than or equal to the population size threshold, the charging rate timing information is guided and updated according to the historical charging rate timing information, combined with the charging rate constraint interval and the charging duration constraint interval, and then the starting process is returned.

[0127] Furthermore, the rate optimization module also includes the following execution steps:

[0128] Clustering the historical charging rate time series information to obtain a first cluster of historical charging rate time series information to an Nth cluster of historical charging rate time series information;

[0129] Performing inter-cluster cross-guidance update on the charging rate timing information of the first cluster of historical charging rate timing information to the Nth cluster of historical charging rate timing information to obtain first updated charging rate timing information;

[0130] Traversing the first cluster of historical charging rate timing information until the Nth cluster of historical charging rate timing information performs cluster-guided update on the charging rate timing information to obtain second updated charging rate timing information;

[0131] The first updated charging rate timing information and the second updated charging rate timing information are added to the charging rate timing information update result.

[0132] Furthermore, the rate optimization module also includes the following execution steps:

[0133] Obtaining first historical charging rate timing information and second historical charging rate timing information of the historical charging rate timing information;

[0134] Extracting the first moment quantity of the first historical charging rate time series information and the second moment quantity of the second historical charging rate time series information;

[0135] Constructing a first high-dimensional coordinate system with the larger number of the first number of moments and the second number of moments as the dimension;

[0136] Based on the first high-dimensional coordinate system, the first historical charging rate time series information and the second historical charging rate time series information are processed respectively to obtain first distribution coordinates and second distribution coordinates;

[0137] When the distribution distance between the first distribution coordinates and the second distribution coordinates is less than or equal to a distribution distance threshold, adding the first historical charging rate timing information and the second historical charging rate timing information to the same cluster historical charging rate timing information;

[0138] Otherwise, the first historical charging rate timing information and the second historical charging rate timing information are added to the heterogeneous cluster historical charging rate timing information;

[0139] Until the historical charging rate time series information is clustered, the first cluster of historical charging rate time series information is obtained until the Nth cluster of historical charging rate time series information is obtained;

[0140] When the first moment number is smaller than the larger moment number, the first historical charging rate timing information is padded with 0 to obtain the first historical charging rate update timing information;

[0141] Distributing the first historical charging rate update time series information to the first high-dimensional coordinate system to obtain first distribution coordinates;

[0142] When the first number of moments is equal to the larger number of moments, the first historical charging rate time series information is distributed to the first high-dimensional coordinate system to obtain first distribution coordinates.

[0143] Furthermore, the rate optimization module also includes the following execution steps:

[0144] Randomly extracting the kth cluster of historical charging rate sequence information and the yth cluster of historical charging rate sequence information from the first cluster of historical charging rate sequence information to the Nth cluster of historical charging rate sequence information;

[0145] Extract the maximum solution of the charging control quality coefficient of the k-th cluster of historical charging rate time series information, and set it as the guiding solution of the y-th cluster;

[0146] Extract the maximum solution of the charging control quality coefficient of the historical charging rate time series information of the y-th cluster and set it as the guiding solution of the k-th cluster;

[0147] A preset number of tail solutions of the historical charging rate timing information of the yth cluster are guided and updated according to the guided solution of the yth cluster, and a preset number of tail solutions of the historical charging rate timing information of the kth cluster are guided and updated according to the guided solution of the kth cluster to obtain the first updated charging rate timing information.

[0148] Embodiment three:

[0149] An embodiment of the present invention provides an electric tool charging device for implementing a lithium battery charging control method, comprising:

[0150] Obtain the initial remaining power value, charging environment temperature and charging rate timing information;

[0151] Inputting the initial remaining power value, the charging environment temperature and the charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing to generate the remaining power value increment rate and polarization voltage timing information;

[0152] Inputting the timing end point polarization voltage of the polarization voltage timing information into the associated instantaneous discharge current calibration model of the lithium battery model for processing to generate a reverse instantaneous discharge calibration current;

[0153] Based on the reverse instantaneous discharge calibration current, the residual power value increment rate and the polarization voltage timing information, the charging control quality evaluation is performed on the charging rate timing information to obtain a charging control quality coefficient;

[0154] When the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, the lithium battery charging control is performed according to the charging rate timing information.

[0155] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0156] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0157] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or multiple boxes.

[0158] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction system, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0159] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0160] Although preferred embodiments of the present invention have been described, additional changes and modifications may occur to these embodiments once those skilled in the art understand the basic inventive concepts.

[0161] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of the present invention and its equivalent technology, the present invention is also intended to include these changes and variations.

Claims

1. A lithium battery charging control method, characterized in that: include: Obtain the initial remaining power value, charging environment temperature and charging rate timing information; Inputting the initial remaining power value, the charging environment temperature and the charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing to generate the remaining power value increment rate and polarization voltage timing information; Inputting the timing end point polarization voltage of the polarization voltage timing information into the associated instantaneous discharge current calibration model of the lithium battery model for processing to generate a reverse instantaneous discharge calibration current; Based on the reverse instantaneous discharge calibration current, the residual power value increment rate and the polarization voltage timing information, the charging control quality evaluation is performed on the charging rate timing information to obtain a charging control quality coefficient; When the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, the lithium battery charging control is performed according to the charging rate timing information.

2. The method according to claim 1, characterized in that Based on the reverse instantaneous discharge calibration current, the residual power value increment rate and the polarization voltage timing information, the charging rate timing information is evaluated for charging control quality to obtain a charging control quality coefficient, including: Construct a multi-constraint function: Among them, x1 represents the charging time, x2 represents the incremental rate of the residual power, x3 represents the incremental rate of the polarization voltage, x4 represents the polarization voltage at the end of the timing sequence, x5 represents the reverse instantaneous discharge calibration current, and x i0 Characterizes the threshold value of the constraint parameter of the i-th attribute, x i Characterizes the i-th attribute constraint parameter, x i belongs to (x1, x2, x3, x4, x5), a i Characterizes the adjustment parameter of the i-th attribute, a i ≥1, f(x1, x2, x3, x4, x5) represents the charging control quality factor; When the charging time is less than or equal to the charging time threshold, and the remaining power value increment rate is greater than or equal to the remaining power value increment rate threshold, and the polarization voltage increment rate is less than or equal to the polarization voltage increment rate threshold, and the timing end point polarization voltage is less than or equal to the polarization voltage threshold, and the reverse instantaneous discharge calibration current is less than or equal to the reverse instantaneous discharge current threshold, call the multi-constraint function to perform control quality evaluation and obtain the charging control quality coefficient.

3. The method according to claim 2, characterized in that Also includes: When the charging duration is greater than the charging duration threshold, or / and the remaining power value increment rate is less than the remaining power value increment rate threshold, or / and the polarization voltage increment rate is greater than the polarization voltage increment rate threshold, or / and the timing endpoint polarization voltage is greater than the polarization voltage threshold, or / and the reverse instantaneous discharge calibration current is greater than the reverse instantaneous discharge current threshold, the charging control quality coefficient is set to negative infinity.

4. The method according to claim 1, characterized in that Obtain the initial remaining power value, charging environment temperature and charging rate timing information, including: Receiving basic information of a lithium battery, wherein the basic information of the lithium battery includes the model of the lithium battery and the initial remaining power value; collecting the charging environment temperature through an environmental sensor; Based on the random configuration of the charging rate constraint interval and the charging time constraint interval, the charging rate timing information is obtained.

5. The method according to claim 1, characterized in that Also includes: When the charging control quality coefficient is less than the charging control quality coefficient threshold, determining whether the amount of historical charging rate time series information is greater than or equal to a population size threshold; If the amount of the historical charging rate time series information is less than the population size threshold, the charging rate time series information is randomly updated based on the charging rate constraint interval and the charging time constraint interval, and then the process is returned to the start process; If the amount of the historical charging rate timing information is greater than or equal to the population size threshold, the charging rate timing information is guided and updated according to the historical charging rate timing information, combined with the charging rate constraint interval and the charging duration constraint interval, and then the starting process is returned.

6. The method according to claim 5, characterized in that According to the historical charging rate sequence information, combined with the charging rate constraint interval and the charging time constraint interval, the charging rate sequence information is guided and updated and then returned to the start process, including: Clustering the historical charging rate time series information to obtain a first cluster of historical charging rate time series information to an Nth cluster of historical charging rate time series information; Performing inter-cluster cross-guidance update on the charging rate timing information of the first cluster of historical charging rate timing information to the Nth cluster of historical charging rate timing information to obtain first updated charging rate timing information; Traversing the first cluster of historical charging rate timing information until the Nth cluster of historical charging rate timing information performs cluster-guided update on the charging rate timing information to obtain second updated charging rate timing information; The first updated charging rate timing information and the second updated charging rate timing information are added to the charging rate timing information update result.

7. The method according to claim 6, characterized in that Clustering the historical charging rate time sequence information to obtain the first cluster of historical charging rate time sequence information to the Nth cluster of historical charging rate time sequence information includes: Obtaining first historical charging rate timing information and second historical charging rate timing information of the historical charging rate timing information; Extracting the first moment quantity of the first historical charging rate time series information and the second moment quantity of the second historical charging rate time series information; Constructing a first high-dimensional coordinate system with the larger number of the first number of moments and the second number of moments as the dimension; Based on the first high-dimensional coordinate system, the first historical charging rate time series information and the second historical charging rate time series information are processed respectively to obtain first distribution coordinates and second distribution coordinates; When the distribution distance between the first distribution coordinates and the second distribution coordinates is less than or equal to a distribution distance threshold, adding the first historical charging rate timing information and the second historical charging rate timing information to the same cluster historical charging rate timing information; Otherwise, the first historical charging rate timing information and the second historical charging rate timing information are added to the heterogeneous cluster historical charging rate timing information; Until the historical charging rate time series information is clustered, the first cluster of historical charging rate time series information is obtained until the Nth cluster of historical charging rate time series information is obtained; When the first moment number is smaller than the larger moment number, the first historical charging rate timing information is padded with 0 to obtain the first historical charging rate update timing information; Distributing the first historical charging rate update time series information to the first high-dimensional coordinate system to obtain first distribution coordinates; When the first number of moments is equal to the larger number of moments, the first historical charging rate time series information is distributed to the first high-dimensional coordinate system to obtain first distribution coordinates.

8. The method according to claim 6, characterized in that Performing inter-cluster cross-guidance update on the charging rate timing information of the first cluster of historical charging rate timing information to the Nth cluster of historical charging rate timing information to obtain first updated charging rate timing information, including: Randomly extracting the kth cluster of historical charging rate sequence information and the yth cluster of historical charging rate sequence information from the first cluster of historical charging rate sequence information to the Nth cluster of historical charging rate sequence information; Extract the maximum solution of the charging control quality coefficient of the k-th cluster of historical charging rate time series information, and set it as the guiding solution of the y-th cluster; Extract the maximum solution of the charging control quality coefficient of the historical charging rate time series information of the y-th cluster and set it as the guiding solution of the k-th cluster; A preset number of tail solutions of the historical charging rate timing information of the yth cluster are guided and updated according to the guided solution of the yth cluster, and a preset number of tail solutions of the historical charging rate timing information of the kth cluster are guided and updated according to the guided solution of the kth cluster to obtain the first updated charging rate timing information.

9. A lithium battery charging control system, characterized in that: A lithium battery charging control method for implementing any one of claims 1 to 8, comprising: A data acquisition module, which is used to obtain the initial remaining value of the power, the charging environment temperature and the charging rate timing information; A prediction processing module, the prediction processing module is used to input the initial remaining power value, the charging environment temperature and the charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing, and generate a remaining power value increment rate and polarization voltage timing information; A calibration generation module, the calibration generation module is used to input the timing end point polarization voltage of the polarization voltage timing information into the associated instantaneous discharge current calibration model of the lithium battery model for processing, and generate a reverse instantaneous discharge calibration current; A quality assessment module, the quality assessment module is used to perform a charge control quality assessment on the charge rate timing information based on the reverse instantaneous discharge calibration current, the residual power value increment rate and the polarization voltage timing information to obtain a charge control quality coefficient; A charging control module, wherein the charging control module is used to control the charging of the lithium battery according to the charging rate timing information when the charging control quality coefficient is greater than or equal to a charging control quality coefficient threshold.

10. An electric tool charging device, characterized in that: Used to implement a lithium battery charging control method as described in any one of claims 1-8.

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