A lithium battery charging control method, system and device

Abstract

The application relates to a lithium battery charging control method, system and equipment, and relates to the field of charging control, which comprises the following steps: acquiring an initial power residual value, a charging environment temperature and charging rate time sequence information, inputting the information into an associated polarization voltage prediction model for processing, generating a power residual value increment rate and polarization voltage time sequence information; inputting the polarization voltage time sequence information into an associated instantaneous discharge current calibration model of the lithium battery model for processing, generating a reverse instantaneous discharge calibration current; performing charging control quality evaluation on the charging rate time sequence information to obtain a charging control quality coefficient; and performing lithium battery charging control when the charging control quality coefficient is greater than or equal to a charging control quality coefficient threshold. Through the introduction of the charging control quality evaluation based on the polarization voltage prediction and the instantaneous discharge current calibration during the fast charging of the lithium battery of the electric tool, the influence on the battery life is minimized, and the technical effect of giving consideration to the charging speed and the battery life is achieved.

Description

Technical Field

[0001] This invention relates to the field of charging control, and more particularly to a lithium battery charging control method, system, and device. Background Technology

[0002] Power tools are widely used in various fields, and their convenience and efficiency are highly valued. However, with the increasing popularity of power tools, users have placed higher demands on the charging speed and lifespan of lithium batteries used in these tools. Current technologies typically employ high-rate charging to achieve fast charging of lithium batteries. However, high-rate charging leads to severe polarization within the battery, reducing its usable capacity and charging efficiency. To reduce polarization, existing technologies often use instantaneous discharge, intermittently discharging the battery for short periods during charging to decrease internal polarization. However, while frequent instantaneous discharge can reduce polarization to some extent, it also negatively impacts battery lifespan. Instantaneous discharge generates additional heat within the battery, accelerating the aging of battery materials and reducing cycle life. Therefore, achieving fast charging of lithium batteries for power tools while minimizing polarization and the impact of instantaneous discharge on battery life has become a pressing technical challenge. Summary of the Invention

[0003] This invention addresses the technical problem in existing power tool lithium battery fast charging scenarios where high-rate charging leads to severe battery polarization, requiring instantaneous discharge to reduce polarization, but instantaneous discharge can affect battery life. The invention provides a lithium battery charging control method, system, and device to solve this problem.

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

[0005] In a first aspect, the present invention provides a lithium battery charging control method, comprising: acquiring initial residual capacity, charging ambient temperature, and charging rate timing information; inputting the initial residual capacity, charging ambient temperature, and charging rate timing information into a lithium battery model-related polarization voltage prediction model for processing to generate residual capacity increment rate and polarization voltage timing information; inputting the timing endpoint polarization voltage of the polarization voltage timing information into a lithium battery model-related instantaneous discharge current calibration model for processing to generate a reverse instantaneous discharge calibration current; evaluating the charging rate timing information based on the reverse instantaneous discharge calibration current, residual capacity increment rate, and polarization voltage timing information to obtain a charging control quality coefficient; and performing lithium battery charging control 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.

[0006] Secondly, the present invention provides a lithium battery charging control system, comprising: a data acquisition module for acquiring initial residual capacity, charging ambient temperature, and charging rate timing information; a prediction processing module for inputting the initial residual capacity, charging ambient temperature, and charging rate timing information into a lithium battery model-related polarization voltage prediction model for processing, generating residual capacity increment rate and polarization voltage timing information; a calibration generation module for inputting the timing endpoint polarization voltage of the polarization voltage timing information into a lithium battery model-related instantaneous discharge current calibration model for processing, generating a reverse instantaneous discharge calibration current; a quality evaluation module for evaluating the charging rate timing information based on the reverse instantaneous discharge calibration current, residual capacity increment rate, and polarization voltage timing information, obtaining a charging control quality coefficient; and a charging control module for controlling lithium battery charging 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.

[0007] Thirdly, this application provides a power tool charging device for implementing a lithium battery charging control method.

[0008] The beneficial effects of this invention are:

[0009] This process acquires initial battery capacity, ambient temperature, and charging rate timing information to comprehensively understand the current charging status and conditions of the battery, providing essential information for subsequent charging control. The initial battery capacity, ambient temperature, and charging rate timing information are then input into a lithium battery model associated with its polarization voltage prediction for processing. This generates the battery capacity increment rate and polarization voltage timing information, enabling the prediction of polarization voltage changes and the rate of increase in battery capacity during charging, providing crucial data for subsequent charging control quality assessment. Finally, the timing endpoint polarization voltage of the polarization voltage timing information is input into a lithium battery model associated with its instantaneous discharge current calibration for processing, generating a reverse instantaneous discharge calibration current. Based on the predicted polarization voltage, the appropriate instantaneous discharge current magnitude is determined. This approach effectively reduces polarization while minimizing its impact on battery life. Based on the reverse instantaneous discharge calibration current, residual capacity increment rate, and polarization voltage timing information, the charging rate timing information is evaluated to obtain a charging control quality coefficient, reflecting 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, lithium battery charging control is performed based on the charging rate timing information. It is determined whether the current charging rate timing information meets the requirements. If it does, charging control is executed based on the current charging rate timing information to achieve a fast, efficient, and low-loss charging process. This minimizes the impact on battery life while ensuring charging speed, effectively solving the problems in existing technologies. Attached Figure Description

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

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

[0012] In the attached diagram, the components represented by each number 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 Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0016] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed herein.

[0017] Example 1:

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

[0019] S100: Acquires initial remaining battery level, charging ambient temperature, and charging rate timing information.

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

[0021] The initial charge level represents the remaining charge level of a lithium battery at the start of charging. This initial charge level can be measured in real-time by the battery's built-in charge metering circuit or read directly from the battery management system. Ambient temperature is a crucial external factor affecting lithium battery charging performance. To obtain this temperature, temperature sensors are placed near the battery pack to collect real-time temperature data of the environment during charging. These sensors include thermocouples, resistance temperature detectors (RTDs), and semiconductor temperature sensors. The charging rate timing information represents the change in charging current relative to the battery's rated capacity throughout the charging process. A higher charging rate results in a higher charging current and faster charging speed, but may also lead to greater polarization and heat generation. To obtain suitable charging rate timing information, it can be randomly generated within a certain range based on the lithium battery's rated charging parameters (such as rated voltage, rated capacity, and maximum charging current) and actual usage requirements. Alternatively, the charger or external energy management system can provide the corresponding charging rate timing information according to a predetermined charging strategy.

[0022] By acquiring the initial and remaining charge value, charging ambient temperature, and charging rate timing information, basic information is provided for lithium battery charging control.

[0023] S200: Input the initial residual value of the battery capacity, the charging ambient temperature, and the charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing, and generate the residual value increment rate and polarization voltage timing information.

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

[0025] Different lithium battery models vary in materials, structure, and capacity, resulting in different charge and discharge characteristics. Therefore, to obtain accurate prediction results, it is necessary to construct and train corresponding polarization voltage prediction models for different lithium battery models. In practical applications, a polarization voltage prediction model library can be pre-established for mainstream lithium battery models, and the corresponding associated polarization voltage prediction model can be called for calculation based on the actual battery model used.

[0026] S300: Input the timing endpoint 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.

[0027] Specifically, the polarization voltage timing information for the entire charging process was obtained through a correlated polarization voltage prediction model. To quantitatively assess the degree of polarization during charging, special attention needs to be paid to the last time point of the polarization voltage timing information, i.e., the polarization voltage value at the end of the timing sequence. This polarization voltage at the end of the timing sequence is input into a correlated instantaneous discharge current calibration model corresponding to the lithium battery model to obtain a reference value for the reverse discharge current used to suppress the polarization effect, i.e., the reverse instantaneous discharge calibration current. The correlated instantaneous discharge current calibration model is obtained by fitting experimental data from a specific lithium battery model using algorithms such as regression analysis. This model reflects the optimal instantaneous discharge current value corresponding to different polarization voltage levels of the lithium battery. The input parameter of the correlated instantaneous discharge current calibration model is the polarization voltage at the end of the timing sequence, 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-duration, high-current discharge to the lithium battery in the opposite direction to the charging current just before the charging process ends. This effectively reduces the polarization effect inside the lithium battery, improves energy conversion efficiency, and extends the battery's cycle life. However, the reverse instantaneous discharge current cannot be too large, otherwise it will cause irreversible damage to the lithium battery. Therefore, a reasonable reference value for the reverse discharge current needs to be provided by the associated instantaneous discharge current calibration model based on the magnitude of the polarization voltage at the end of the time series.

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

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

[0031] Specifically, by processing the initial residual value of the charge, the charging ambient temperature, and the charging rate timing information, the reverse instantaneous discharge calibration current, the residual value increment rate, and the polarization voltage timing information are obtained. These parameters are then used to evaluate the initially given charging rate timing information and 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 residual capacity increment rate, and polarization voltage timing information are substituted into this function to calculate a quantified charging control quality coefficient. The magnitude of this coefficient reflects the quality of the current charging rate timing; a larger value indicates higher charging control quality, and vice versa. The specific form of the charging control quality evaluation function can be designed based on actual needs and experience. For example, a weighted summation method can be used, multiplying each parameter by its corresponding weight coefficient and then summing the results to obtain the final charging control quality coefficient. The magnitude of the weight coefficient reflects the degree of influence of each parameter on the charging control quality and can be set based on theoretical analysis and experimental data.

[0033] By obtaining the charging control quality coefficient, the quality of a given charging rate timing information can be quantitatively reflected. A higher charging control quality coefficient indicates that the charging rate timing information can better suppress polarization effects, improve charging efficiency, and extend battery life while ensuring charging speed. Therefore, the introduction of the charging control quality coefficient provides an important basis for subsequent lithium battery charging control, helping to quickly find the optimal charging rate timing 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, lithium battery charging control is performed according to the charging rate timing information.

[0035] Specifically, to determine whether charging rate timing information can be directly applied to actual lithium battery charging control, a preset charging control quality coefficient threshold is introduced as an evaluation 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, the current charging rate timing information is considered to be directly usable to guide the subsequent actual charging control process.

[0036] In this scenario, the charging current is automatically adjusted based on the charging rate values ​​specified in the charging rate timing information for each time period. Simultaneously, the battery's voltage, temperature, and other status parameters are monitored in real time to ensure a safe, efficient, and controllable charging process. Furthermore, as charging nears its end, a short-term reverse discharge is applied to the battery, referencing the obtained reverse instantaneous discharge calibration current, to suppress polarization and improve charging performance. The charging control quality coefficient threshold is set based on factors such as the lithium battery model and capacity, the power limitations of the charging equipment, and the safety requirements of the usage scenario.

[0037] By directly using the current charging rate timing information for lithium battery charging control when the charging control quality coefficient reaches or exceeds a preset threshold, unnecessary iterative optimization can be avoided, the charging control decision time can be shortened, and charging efficiency can be improved. Simultaneously, since this charging rate timing information has already been evaluated and screened, it can effectively suppress polarization effects and extend battery life while ensuring charging speed, thus achieving ideal charging control results.

[0038] Furthermore, embodiments of this application also include:

[0039] S410: Constructing a multi-constraint function:

[0040]

[0041] Where x1 represents the charging time, x2 represents the rate of increase of the remaining charge value, x3 represents the rate of increase of the polarization voltage, x4 represents the polarization voltage at the end of the time sequence, and x5 represents the reverse instantaneous discharge calibration current. i0 The threshold value of the constraint parameter x representing the i-th attribute i The parameter representing the constraint of the i-th attribute, x i Belongs to (x1, x2, x3, x4, x5), a i Characterizing the adjustment parameter of the i-th attribute, a i ≥1, f(x1, x2, x3, x4, x5) characterizes the charging control quality coefficient;

[0042] S420: When the charging duration is less than or equal to the charging duration threshold, and the residual power increment rate is greater than or equal to the residual power 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 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, the multi-constraint function is invoked to perform control quality evaluation and obtain the charging control quality coefficient.

[0043] In a preferred embodiment, to evaluate the charging control quality and obtain the charging control quality coefficient, firstly, a multi-constraint function for quantifying the evaluation of the charging control quality is constructed, namely:

[0044]

[0045] The function's independent variables include five attribute constraint parameters: charging time x1, residual capacity increment rate x2, polarization voltage increment rate x3, timing end polarization voltage x4, and reverse instantaneous discharge calibration current x5. Each attribute constraint parameter has its corresponding parameter threshold, i.e., x. i0 Specifically, they are represented as x. 10 x 20 x 30 x 40 and x 50 The multi-constraint function takes the form of the sum of the absolute values ​​of the differences between the five attribute constraint parameters and their thresholds, and then takes the remainder by a. i The logarithm to the base . Where a i The parameter for adjusting the i-th attribute is used to control the degree of influence of each attribute constraint parameter on the overall 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 more from its threshold, a iThe larger the logarithm of the base, the greater the negative impact of that attribute on charging control quality. Adding the logarithmic values ​​of the five attributes allows for a comprehensive evaluation of the combined impact of the five attribute constraint parameters, yielding a quantified charging control quality coefficient.

[0046] Simultaneously, the rules specify when to invoke the multi-constraint function to evaluate charging control quality. Specifically, the multi-constraint function will only be invoked to calculate the charging control quality coefficient when all five attribute constraint parameters simultaneously meet the following conditions: charging duration is less than or equal to the charging duration threshold; the residual capacity increment rate is greater than or equal to the residual capacity increment rate threshold; the polarization voltage increment rate is less than or equal to the polarization voltage increment rate threshold; the timing endpoint 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. These five conditions are set to ensure that charging control quality evaluation is performed only when certain performance requirements are met during the charging process, thus avoiding unnecessary computational overhead.

[0047] By employing a charging control quality evaluation method based on multiple constraint functions, various key performance indicators of the charging process can be comprehensively considered, quantifying the quality of charging control and providing important references for subsequent optimization control. Compared with simple single-indicator evaluation, this method can more comprehensively and accurately assess the quality of charging control, helping to find the optimal charging strategy and maximizing battery life while ensuring charging speed and efficiency.

[0048] Furthermore, embodiments of this application also include:

[0049] S430: When the charging duration is greater than the charging duration threshold, or / and the residual power increment rate is less than the residual power increment rate threshold, or / and the polarization voltage increment rate is greater than the polarization voltage increment rate threshold, or / and the timing end 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 one feasible implementation, when any of the following conditions occur, instead of calculating multiple constraint functions, the charging control quality coefficient is directly set to negative infinity: charging duration exceeds a charging duration threshold; the residual capacity increment rate is lower than the residual capacity increment rate threshold; the polarization voltage increment rate exceeds the polarization voltage increment rate threshold; the timing endpoint polarization voltage exceeds the polarization voltage threshold; and the reverse instantaneous discharge calibration current exceeds the reverse instantaneous discharge current threshold. The reason for directly setting the charging control quality coefficient to negative infinity in these cases is that one or more key performance indicators of the charging process have significantly exceeded acceptable limits, and even if other indicators perform normally, the overall charging control quality is unlikely to reach a satisfactory level. To avoid unnecessary calculations of multiple constraint functions in these cases, the quality assessment result using negative infinity as the charging control quality coefficient is directly provided.

[0051] By pre-identifying and handling certain extreme cases, unnecessary computational overhead is reduced, improving the efficiency of charging control quality evaluation. Simultaneously, unacceptable charging control schemes are clearly identified, providing clear boundary conditions for subsequent optimization control, avoiding lingering near inferior solutions, accelerating convergence speed, and laying the foundation for achieving optimal charging control of lithium batteries.

[0052] Furthermore, embodiments of this application also include:

[0053] S110: Receive basic lithium battery information, wherein the basic lithium battery information includes the lithium battery model and the initial remaining capacity;

[0054] S120: The charging ambient temperature is collected via an environmental sensor;

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

[0056] In a preferred embodiment, when acquiring the initial charge level, charging ambient temperature, and charging rate timing information, the system first receives basic information about the lithium battery, including the lithium battery model and the current initial charge level. The lithium battery model information is subsequently used to select the corresponding associated polarization voltage prediction model and associated instantaneous discharge current calibration model, as different lithium battery models may have significantly different performance parameters and optimal charging strategies. The initial charge level reflects the remaining charge level of the lithium battery before the start of this charging phase and serves as a benchmark for assessing charge changes during charging. This basic lithium battery information is provided by the lithium battery management system or obtained through communication with the lithium battery pack.

[0057] Simultaneously, environmental sensors collect temperature information about the environment in which the lithium battery is located to obtain the charging ambient temperature. The charging ambient temperature is a crucial external factor affecting the charging performance of lithium batteries; under different temperature conditions, parameters such as the optimal charging rate and polarization characteristics of the lithium battery may change. Therefore, obtaining accurate charging ambient temperature in real time is essential for charging control. Various temperature sensors with suitable temperature ranges and sufficient accuracy can be selected for the environmental sensors, such as thermocouples, resistance temperature detectors (RTDs), and semiconductor temperature sensors.

[0058] Simultaneously, based on preset charging rate and charging duration constraint ranges, a set of charging rate timing information is randomly generated. The charging rate timing information defines the charging rate (i.e., the ratio of charging current to the battery's rated capacity) at various time points throughout the entire charging process. A reasonable charging rate timing design can effectively suppress polarization effects and extend battery life while ensuring charging speed. To obtain feasible charging rate timing information, it is necessary to pre-set the charging rate and charging duration constraint ranges. The charging rate constraint range limits the range of charging rates for each time period, set according to factors such as the lithium battery's rated charging rate and temperature characteristics; the charging duration constraint range limits the total charging time, taking into account both practical application requirements and battery health. Generating charging rate timing information through random configuration within the given constraint range can, to some extent, increase the diversity of the search space and improve the probability of obtaining the optimal charging rate timing information.

[0059] By acquiring initial charge balance, ambient charging temperature, and charging rate timing information, key parameters affecting lithium battery charging performance can be obtained, providing necessary data support for subsequent charging control and improving the safety, reliability, and economy of lithium battery charging.

[0060] Furthermore, embodiments of this application also include:

[0061] S600: When the charging control quality coefficient is less than the charging control quality coefficient threshold, determine whether the number of historical charging rate time sequence information is greater than or equal to the population size threshold.

[0062] S700: If the number of 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 duration constraint interval, and then the process returns to the start.

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

[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, the charging control quality coefficient and its threshold are compared. If the charging control quality coefficient is less than the preset threshold, it indicates that the current charging rate timing information needs further optimization. To effectively guide subsequent optimization, a population size threshold is introduced to determine whether the amount of historical charging rate timing information already obtained is sufficient. The size of the population size threshold can be set according to factors such as problem complexity and computational resource limitations.

[0066] If the amount of historical charging rate time-series information has not yet 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 duration constraint interval. This involves randomly generating new charging rate time-series data within the constraint interval to replace the original data. This random perturbation can, to some extent, help escape local optima and increase the probability of obtaining the global optimum. If the amount of historical charging rate time-series information has reached or exceeded the population size threshold, the current charging rate time-series information is guided to be updated using existing historical charging rate time-series information, combined with the charging rate constraint interval and charging duration constraint interval. Guided update refers to the targeted correction of the current solution (i.e., the current charging rate time-series information) based on high-quality solutions from historical data (such as charging rate time-series information with high charging control quality coefficients), guiding it towards a better outcome. Specific strategies for guided update can employ various heuristic optimization algorithms, such as crossover and mutation operations in genetic algorithms and speed update rules in particle swarm optimization. Guided update fully utilizes existing high-quality solution information, accelerating convergence speed and improving optimization efficiency.

[0067] Whether performing a random update or a guided update, the new charging rate timing information obtained from the update will be returned to the beginning of the entire method process, and will go through a series of steps such as charging control quality evaluation and threshold judgment again, until 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 iterated and optimized until the charging control quality coefficient threshold is met. This adaptive optimization mechanism can automatically adjust the optimization strategy and iteration count based on real-time historical data, ensuring both optimization efficiency and versatility and robustness, thus providing a strong guarantee for obtaining the optimal charging control.

[0069] Furthermore, embodiments of this application also include:

[0070] S810: The historical charging rate timing information is clustered to obtain the first cluster of historical charging rate timing information up to the Nth cluster of historical charging rate timing information;

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

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

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

[0074] In a preferred embodiment, when guiding the update of charging rate time-series information, the existing historical charging rate time-series information is first clustered. The purpose of clustering is to group similar charging rate time-series information into the same cluster, while charging rate time-series information between different clusters has certain differences. Clustering can be performed using clustering algorithms such as K-means clustering, hierarchical clustering, and density clustering. The result of clustering is that the historical charging rate time-series information is divided into several clusters, denoted as the first cluster up to the Nth cluster. Then, using the clustering results, i.e., the first cluster up to the Nth cluster, the current charging rate time-series information is cross-guided for updating. Specifically, several historical charging rate time-series information are randomly selected from different clusters, and the charging rate data for certain time periods are cross-combined to generate new charging rate time-series information, denoted as the first updated charging rate time-series information. Cross-cluster operations can reorganize and merge high-quality information from different clusters, increasing the diversity and quality of new solutions.

[0075] Subsequently, within each cluster, the current charging rate timing information is guided to be updated. Specifically, the historical charging rate timing information of the first cluster is traversed up to the Nth cluster. One or more high-quality solutions (such as charging rate timing information with high charging control quality coefficients) are selected from each cluster. The charging rate data for a portion of the current solution is replaced with the data for the corresponding time period of the high-quality solution, generating new charging rate timing information, denoted as the second updated charging rate timing information. This intra-cluster guided update operation fully utilizes the local high-quality information within each cluster to finely optimize and improve the current solution. Then, the first and second updated charging rate timing information are combined as the result of this round of guided updates and added to the charging rate timing information update result. These updated charging rate timing information will return to the beginning of the entire method process to undergo a new round of charging control quality evaluation and optimization until the requirements are met.

[0076] By employing two levels of operations—inter-cluster crossover and intra-cluster guidance—the diversity of solutions is increased while maintaining the fineness of optimization. This significantly improves the optimization efficiency and quality of charging rate timing information, accelerates convergence, and provides strong support for obtaining optimal charging rate timing information online in real time.

[0077] Furthermore, embodiments of this application also include:

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

[0079] S812: Extract the first time step count of the first historical charging rate timing information and the second time step count of the second historical charging rate timing information;

[0080] S813: Construct a first high-dimensional coordinate system using the larger of the first time-time number and the second time-time number as the dimension;

[0081] S814: Based on the first high-dimensional coordinate system, process the first historical charging rate time series information and the second historical charging rate time series information respectively to obtain the first distribution coordinates and the 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 the distribution distance threshold, add the first historical charging rate timing information and the second historical charging rate timing information into the same cluster historical charging rate timing information.

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

[0084] S817: Until all the historical charging rate time-series information is clustered, the first cluster of historical charging rate time-series information is obtained up to the Nth cluster of historical charging rate time-series information;

[0085] Wherein, when the number of the first time moments is less than the number of the larger time moments, the first historical charging rate timing information is padded with zeros at the end to obtain the first historical charging rate update timing information.

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

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

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

[0089] Subsequently, a unified metric space is constructed for the first and second historical charging rate time series information to be compared, in order to calculate the similarity between the two historical charging rate time series information. Specifically, the larger of the first and second time series counts is taken as the dimension of the coordinate system, constructing a high-dimensional coordinate system, denoted as the first high-dimensional coordinate system. For example, assuming the first time series count is 10 and the second time series count is 12, the larger time series count is 12. Thus, a 12-dimensional coordinate system is constructed, with 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 ​​at the first 10 time points, and the last two components are padded with zeros as needed (see S818 and S819 for specific processing methods). In this way, 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 calculation 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 to points in the coordinate system, and the corresponding coordinate representations are obtained, denoted 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 time points (the number of first time points) is equal to the dimension of the first high-dimensional coordinate system (i.e., the larger number of time points), the charging rate values ​​of each time point are directly filled into the respective dimensions of the coordinate system to obtain the first distribution coordinates (S819). If the number of first time points is less than the larger number of time points, zeros are padded to the end of the first historical charging rate time series information to make its length 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 number of second time points is equal to the larger number of time points, the second distribution coordinates are directly mapped; if the number of second time points is less than the larger number of time points, zeros are padded first and then mapped. Through the above processing, regardless of whether the original lengths of two historical charging rate time series information are equal, they can be mapped to the same high-dimensional coordinate system to obtain a unified coordinate representation, which facilitates subsequent similarity measurement and clustering operations.

[0090] Next, by comparing the distance between the first and second distribution coordinates, it is determined whether the corresponding two historical charging rate time series information belong to the same cluster. First, the distance between the first and second distribution coordinates in high-dimensional space is calculated, where the distance metric includes Euclidean distance, Manhattan distance, etc. Then, the calculated distance is compared with a preset distribution distance threshold. If the distance is less than or equal to the distribution distance threshold, the two historical charging rate time series information are considered to have a high similarity and should be classified into the same cluster, and the original first and second historical charging rate time series information are added to the same cluster's historical charging rate time series information. Conversely, if the distance is greater than the distribution distance threshold, the two historical charging rate time series information are considered to have a large difference and should be classified into different clusters, and the original first and second historical charging rate time series information are added to the different cluster's historical charging rate time series information. The distribution distance threshold is a preset 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 tolerance for difference, and the fewer 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. A suitable value can be determined through empirical settings or cross-validation.

[0091] The clustering process is repeated until all samples in the historical charging rate time-series information set are assigned to a cluster. In practice, this process is implemented in a loop. Specifically, in each iteration, two samples are randomly selected from the historical charging rate time-series information set, and the clustering process is performed. Based on the distance between the distribution coordinates, each historical charging rate time-series information is assigned to the corresponding cluster. Then, the next pair of samples is selected from the remaining samples, and the above operation is repeated until all samples are assigned to the corresponding cluster. After the clustering process is completed, the original historical charging rate time-series information set is divided into several disjoint subsets, each subset corresponding to a cluster, containing a set of similar historical charging rate time-series information. These clusters are sequentially named according to the order of their generation: first cluster historical charging rate time-series information, second cluster historical charging rate time-series information, ..., up to the Nth cluster historical charging rate time-series information. The historical charging rate time-series information within each cluster has a high degree of similarity, while the historical charging rate time-series information between different clusters has certain differences.

[0092] Clustering based on distribution distance can effectively reflect the distribution characteristics and intrinsic 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 both between and within clusters, the diversity of new solutions can be increased, while the characteristics of high-quality solutions within each cluster can be inherited. This helps to quickly locate the optimal solution in the search space, improving optimization efficiency and quality.

[0093] To address the issue of discrepancies between the number of historical charging rate time-series information to be mapped and the dimension of the high-dimensional coordinate system, the process for obtaining the distributed coordinates is further explained and supplemented. Specifically, for the first historical charging rate time-series information, the relationship between its number of times (the first number of times) and the dimension of the first high-dimensional coordinate system (i.e., the larger number of times) is first determined. If the number of first times is less than the larger number of times, it indicates 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. In this case, zero-padding is performed on the first historical charging rate time-series information, i.e., zero elements are added to the end. The number of zero elements added is equal to the larger number of times minus the number of first times, making its length equal to the dimension of the coordinate system, thus obtaining the zero-padding first historical charging rate update time-series information. Then, the zero-padding first historical charging rate update time-series information is mapped to the first high-dimensional coordinate system to obtain the first distributed coordinates. Conversely, if the number of first time points is exactly equal to the number of larger time points, then there is no need for zero-padding; 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 pertain to 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 second time points is less than the number of larger time points, then zero-padding is performed on the second historical charging rate time series information to obtain the second historical charging rate update time series information, which is then mapped to obtain the second distribution coordinates; if the number of second time points is equal to the number of larger time points, then the second distribution coordinates are directly mapped.

[0094] By padding with zeros at the end, it can be ensured that regardless of the length of the original historical charging rate time series information, it can be mapped to the same high-dimensional coordinate system, obtaining a unified coordinate representation. Although this processing method will change the distribution characteristics of the original data to some extent, it provides a comparable benchmark for samples with different time series lengths, enabling distance-based clustering operations to proceed smoothly. In practical applications, in addition to padding with zeros at the end, other time series alignment methods can be considered, such as linear interpolation and dynamic time warping. The specific method chosen depends on the actual needs.

[0095] Furthermore, embodiments of this application also include:

[0096] S821: Randomly extract the historical charging rate timing information of the kth cluster and the historical charging rate timing information of the yth cluster from the historical charging rate timing information of the first cluster up to the historical charging rate timing information of the Nth cluster;

[0097] S822: Extract the maximum solution of the charging control quality coefficient of the historical charging rate timing information of the kth cluster, and set it as the guiding solution of the yth cluster;

[0098] S823: Extract the maximum solution of the charging control quality coefficient of the historical charging rate timing information of the yth cluster, and set it as the guiding solution of the kth cluster;

[0099] S824: Guide the update of the preset number of tail solutions of the historical charging rate timing information of the y-th cluster according to the guided solution of the y-th cluster, and guide the update of the preset number of tail solutions of the historical charging rate timing information of the k-th cluster according to the guided solution of the k-th cluster, to obtain the first updated charging rate timing information.

[0100] In a preferred embodiment, during inter-cluster crossover guided updates, firstly, two clusters are randomly selected from the historical charging rate time-series information of the first cluster up to the Nth cluster, denoted as the historical charging rate time-series information of the kth cluster and the historical charging rate time-series information of the yth cluster, respectively, for subsequent inter-cluster crossover operations. Here, 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, avoiding premature entrapment in local optima. Then, a high-quality solution is selected from the historical charging rate time-series information of the kth cluster as a reference to guide the update of the historical charging rate time-series information of the yth cluster. Specifically, the solution with the largest charging control quality coefficient is first found from the historical charging rate time-series information of the kth cluster, i.e., the charging rate time-series information with the best evaluation result in the historical charging rate time-series information of the kth cluster, denoted as the guiding solution of the yth cluster, which will be used to guide the update of the historical charging rate time-series information of the yth cluster. By selecting the optimal solution from one cluster as an 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 time series information of cluster y, and it is denoted as the guiding solution of cluster k. This solution will be used to guide the update of the historical charging rate time series information of cluster k. 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 characteristics of its own cluster and absorb the excellent genes of other clusters, thereby improving the quality and diversity of solutions.

[0101] Subsequently, using the obtained guiding solutions for the y-th and k-th clusters, the historical charging rate time-series information for the k-th and y-th clusters is updated to obtain the first updated charging rate time-series information. Specifically, for each cluster, a preset number of tail solutions are selected, and the charging rate data for a portion of these tail solutions within a certain time period is replaced with the data from the corresponding guiding solution within the same time period, thus obtaining the updated charging rate time-series information. The preset number of tail solutions refers to some charging rate time-series information located at the end of each cluster, and their ranking within that cluster (e.g., sorted from largest to smallest according to the charging control quality coefficient) is relatively low. Selecting tail solutions for updating aims to optimize and improve relatively poor solutions while retaining high-quality solutions within each cluster, thereby improving the overall solution quality. During the guiding update process, the entire guiding solution is not directly copied to the tail solutions; instead, a portion of the guiding solution's time period is selected for replacement. This is done to inherit the excellent features of the guiding solution while retaining some useful information from the tail solutions themselves, achieving fusion and synergy between the two. By adjusting the length and position of the replaced time period, the intensity and scope of the guided update can be controlled. After the guided update of the preset number of tail solutions for the historical charging rate time series information of both the k-th cluster and the y-th cluster is completed, a new set of charging rate time series information is obtained, namely the first updated charging rate time series information. This updated time series information integrates the superior features of different clusters, reflecting the effect of inter-cluster crossover.

[0102] By randomly selecting different clusters for cross-referencing and using the optimal solutions between clusters to guide the updating of the tail solutions of another cluster, information exchange and complementary advantages between different clusters are achieved. This inter-cluster cross-referencing and update strategy can effectively balance the quality and diversity of solutions, preserving the excellent characteristics of each cluster while continuously guiding the search to a better region, thereby improving the efficiency and effectiveness of optimizing charging rate timing information.

[0103] The lithium battery charging control method provided in this embodiment of the invention has at least the following technical effects:

[0104] Acquiring initial charge balance, ambient charging temperature, and charging rate timing information reflects the battery's charging state and conditions, providing a foundation for optimized charging control. This information is then input into a lithium battery model's associated polarization voltage prediction model for processing, generating charge balance increment rate and polarization voltage timing information. This provides crucial data for subsequent charging control quality evaluation and helps optimize charging strategies. The timing endpoint polarization voltage of the polarization voltage timing information is input into a lithium battery model's associated instantaneous discharge current calibration model for processing, generating a reverse instantaneous discharge calibration current. This optimizes the instantaneous discharge strategy, improving charging efficiency while protecting the battery. Based on the reverse instantaneous discharge calibration current, charge balance increment rate, and polarization voltage timing information, the charging rate timing information is evaluated to obtain a charging control quality coefficient. This coefficient reflects the quality of the current charging rate timing information and provides a basis for subsequent charging control decisions. When the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, lithium battery charging control is performed based on 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] Example 2:

[0106] like Figure 2 As shown, based on the same inventive concept as the lithium battery charging control method provided in Embodiment 1, this embodiment of the invention also provides a lithium battery charging control system, including:

[0107] Data acquisition module 11 is used to acquire initial remaining power value, charging ambient temperature and charging rate timing information;

[0108] Prediction processing module 12 is used to input the initial residual value of the battery capacity, the charging ambient temperature, and the charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing, and generate the residual value increment rate and polarization voltage timing information.

[0109] The calibration generation module 13 is used to input the timing end 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.

[0110] The quality assessment module 14 is used to assess the charging control quality of the charging rate timing information based on the reverse instantaneous discharge calibration current, the residual charge increment rate and the polarization voltage timing information, and to obtain the charging 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] Constructing multi-constraint functions:

[0114]

[0115] Where x1 represents the charging time, x2 represents the rate of increase of the remaining charge value, x3 represents the rate of increase of the polarization voltage, x4 represents the polarization voltage at the end of the time sequence, and x5 represents the reverse instantaneous discharge calibration current. i0 The threshold value of the constraint parameter x representing the i-th attribute i The parameter representing the constraint of the i-th attribute, x i Belongs to (x1, x2, x3, x4, x5), a i Characterizing the adjustment parameter of the i-th attribute, a i ≥1, f(x1, x2, x3, x4, x5) characterizes the charging control quality coefficient;

[0116] When the charging duration is less than or equal to the charging duration threshold, and the residual charge increment rate is greater than or equal to the residual charge increment rate threshold, and the polarization voltage increment rate is less than or equal to the polarization voltage increment rate threshold, and the timing endpoint 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, the multi-constraint function is invoked to perform control quality evaluation and obtain the charging control quality coefficient.

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

[0118] When the charging duration is greater than the charging duration threshold, or / and the residual charge increment rate is less than the residual charge increment rate threshold, or / and the polarization voltage increment rate is greater than the polarization voltage increment rate threshold, or / and the timing end 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] Receive basic information about the lithium battery, wherein the basic information about the lithium battery includes the lithium battery model and the initial remaining capacity;

[0121] The charging ambient temperature is collected using an environmental sensor;

[0122] The charging rate timing information is obtained by randomly configuring the charging rate constraint interval and the charging duration constraint interval.

[0123] Furthermore, embodiments of this application also include 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, determine whether the number of historical charging rate time sequence information is greater than or equal to the population size threshold.

[0125] If the number of 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 duration constraint interval, and then the process returns to the start.

[0126] If the number of historical charging rate time series information is greater than or equal to the population size threshold, the charging rate time series information is updated in a guided manner based on the historical charging rate time series information, combined with the charging rate constraint interval and the charging duration constraint interval, and then the process returns to the start.

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

[0128] The historical charging rate timing information is clustered to obtain the first cluster of historical charging rate timing information up to the Nth cluster of historical charging rate timing information;

[0129] The historical charging rate timing information of the first cluster up to the historical charging rate timing information of the Nth cluster is updated by inter-cluster cross-guided update to obtain the first updated charging rate timing information;

[0130] Traverse the first cluster of historical charging rate timing information until the Nth cluster of historical charging rate timing information performs intra-cluster guided update of the charging rate timing information to obtain the 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 scaling optimization module also includes the following execution steps:

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

[0134] Extract the first time step count of the first historical charging rate time sequence information and the second time step count of the second historical charging rate time sequence information;

[0135] A first high-dimensional coordinate system is constructed using the larger of the first time-time number and the second time-time number 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 the first distribution coordinates and the second distribution coordinates;

[0137] When the distribution distance between the first distribution coordinates and the second distribution coordinates is less than or equal to the distribution distance threshold, the first historical charging rate time sequence information and the second historical charging rate time sequence information are added to the historical charging rate time sequence information of the same cluster.

[0138] Otherwise, add the first historical charging rate timing information and the second historical charging rate timing information into the heterogeneous cluster historical charging rate timing information;

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

[0140] Wherein, when the number of the first time moments is less than the number of the larger time moments, the first historical charging rate timing information is padded with zeros at the end to obtain the first historical charging rate update timing information.

[0141] The first historical charging rate update time sequence information is distributed to the first high-dimensional coordinate system to obtain the first distribution coordinates;

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

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

[0144] Randomly extract the historical charging rate timing information of the kth cluster and the historical charging rate timing information of the yth cluster from the historical charging rate timing information of the first cluster up to the historical charging rate timing information of the Nth cluster;

[0145] The maximum solution of the charging control quality coefficient extracted from the historical charging rate timing information of the kth cluster is set as the guiding solution of the yth cluster.

[0146] The maximum solution of the charging control quality coefficient extracted from the historical charging rate timing information of the y-th cluster is set as the guiding solution of the k-th cluster.

[0147] Based on the guided solution of the y-th cluster, a preset number of tail solutions of the historical charging rate timing information of the y-th cluster are guided to update, and based on the guided solution of the k-th cluster, a preset number of tail solutions of the historical charging rate timing information of the k-th cluster are guided to update, thereby obtaining the first updated charging rate timing information.

[0148] Example 3:

[0149] This invention provides a power tool charging device for implementing a lithium battery charging control method, comprising:

[0150] Acquire initial remaining battery level, charging ambient temperature, and charging rate timing information;

[0151] The initial residual charge value, the charging ambient temperature, and the charging rate timing information are input into the associated polarization voltage prediction model of the lithium battery model for processing, to generate the residual charge value increment rate and polarization voltage timing information;

[0152] The polarization voltage timing information is input 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 charge increment rate, and the polarization voltage timing information, the charging rate timing information is used to evaluate the charging control quality and obtain the charging control quality coefficient.

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

[0155] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0156] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied 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] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0158] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction set implemented in a process. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0159] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0160] Although preferred embodiments of the invention have been described, those skilled in the art, once they have learned the basic inventive concept, can make other changes and modifications to these embodiments.

[0161] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this invention and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. A lithium battery charging control method, characterized in that, include: Acquire initial remaining battery level, charging ambient temperature, and charging rate timing information; The initial residual charge value, the charging ambient temperature, and the charging rate timing information are input into the associated polarization voltage prediction model of the lithium battery model for processing, to generate the residual charge value increment rate and polarization voltage timing information. The polarization voltage timing information is input 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 charge increment rate, and the polarization voltage timing information, the charging rate timing information is used to evaluate the charging control quality and obtain the charging control quality coefficient. When the charging control quality coefficient is greater than or equal to the charging control quality coefficient threshold, lithium battery charging control is performed according to the charging rate timing information. When the charging control quality coefficient is less than the charging control quality coefficient threshold, determine whether the number of historical charging rate time sequence information is greater than or equal to the population size threshold. If the number of 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 duration constraint interval, and then the process returns to the start. If the number of historical charging rate time series information is greater than or equal to the population size threshold, the charging rate time series information is updated in a guided manner based on the historical charging rate time series information, combined with the charging rate constraint interval and the charging duration constraint interval, and then the process returns to the start.

2. The method as described in claim 1, characterized in that, Based on the reverse instantaneous discharge calibration current, the residual charge increment rate, and the polarization voltage timing information, the charging rate timing information is used to evaluate the charging control quality and obtain a charging control quality coefficient, including: Constructing multi-constraint functions: ， in, Characterizing charging time, Characterizing the rate of increase of residual power, Characterizing the rate of polarization voltage increment, Characterizing the polarization voltage at the end of the time series, Characterizing the reverse instantaneous discharge calibration current, The threshold value representing the constraint parameter of the i-th attribute. Characterizes the constraint parameters of the i-th attribute. belong , Characterizes the adjustment parameter of the i-th attribute. ≥1, Characterizes the charging control quality coefficient; When the charging duration is less than or equal to the charging duration threshold, and the residual charge increment rate is greater than or equal to the residual charge increment rate threshold, and the polarization voltage increment rate is less than or equal to the polarization voltage increment rate threshold, and the timing endpoint 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, the multi-constraint function is invoked to perform control quality evaluation and obtain the charging control quality coefficient.

3. The method as described in claim 2, characterized in that, Also includes: When the charging duration is greater than the charging duration threshold, or / and the residual charge increment rate is less than the residual charge increment rate threshold, or / and the polarization voltage increment rate is greater than the polarization voltage increment rate threshold, or / and the timing end 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 as described in claim 1, characterized in that, Acquire initial remaining battery capacity, ambient charging temperature, and charging rate timing information, including: Receive basic information about the lithium battery, wherein the basic information about the lithium battery includes the lithium battery model and the initial remaining capacity; The charging ambient temperature is collected using an environmental sensor; The charging rate timing information is obtained by randomly configuring the charging rate constraint interval and the charging duration constraint interval.

5. The method as described in claim 1, characterized in that, 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 before returning to the start process, including: The historical charging rate timing information is clustered to obtain the first cluster of historical charging rate timing information up to the Nth cluster of historical charging rate timing information; The historical charging rate timing information of the first cluster up to the historical charging rate timing information of the Nth cluster is updated by inter-cluster cross-guided update to obtain the first updated charging rate timing information; Traverse the first cluster of historical charging rate timing information until the Nth cluster of historical charging rate timing information performs intra-cluster guided update of the charging rate timing information to obtain the 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.

6. The method as described in claim 5, characterized in that, The historical charging rate timing information is clustered to obtain the first cluster of historical charging rate timing information up to the Nth cluster, including: Obtain the first historical charging rate timing information and the second historical charging rate timing information of the historical charging rate timing information; Extract the first time step count of the first historical charging rate time sequence information and the second time step count of the second historical charging rate time sequence information; A first high-dimensional coordinate system is constructed using the larger of the first time-time number and the second time-time number 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 the first distribution coordinates and the second distribution coordinates; When the distribution distance between the first distribution coordinates and the second distribution coordinates is less than or equal to the distribution distance threshold, the first historical charging rate time sequence information and the second historical charging rate time sequence information are added to the historical charging rate time sequence information of the same cluster. Otherwise, add the first historical charging rate timing information and the second historical charging rate timing information into the heterogeneous cluster historical charging rate timing information; Until all the historical charging rate time-series information is clustered, the first cluster of historical charging rate time-series information is obtained up to the Nth cluster of historical charging rate time-series information; Wherein, when the number of the first time moments is less than the number of the larger time moments, the first historical charging rate timing information is padded with zeros at the end to obtain the first historical charging rate update timing information. The first historical charging rate update time sequence information is distributed to the first high-dimensional coordinate system to obtain the first distribution coordinates; When the number of the first time moments is equal to the number of the larger time moments, the first historical charging rate time sequence information is distributed to the first high-dimensional coordinate system to obtain the first distribution coordinates.

7. The method as described in claim 5, characterized in that, The historical charging rate timing information of the first cluster up to the historical charging rate timing information of the Nth cluster is updated by inter-cluster cross-guided updates to obtain the first updated charging rate timing information, including: Randomly extract the historical charging rate timing information of the kth cluster and the historical charging rate timing information of the yth cluster from the historical charging rate timing information of the first cluster up to the historical charging rate timing information of the Nth cluster; The maximum solution of the charging control quality coefficient extracted from the historical charging rate timing information of the kth cluster is set as the guiding solution of the yth cluster. The maximum solution of the charging control quality coefficient extracted from the historical charging rate timing information of the y-th cluster is set as the guiding solution of the k-th cluster. Based on the guided solution of the y-th cluster, a preset number of tail solutions of the historical charging rate timing information of the y-th cluster are guided to update, and based on the guided solution of the k-th cluster, a preset number of tail solutions of the historical charging rate timing information of the k-th cluster are guided to update, thereby obtaining the first updated charging rate timing information.

8. A lithium battery charging control system, characterized in that, A lithium battery charging control method for implementing any one of claims 1-7 includes: The data acquisition module is used to acquire the initial remaining power value, charging ambient temperature, and charging rate timing information. The prediction processing module is used to input the initial residual value of the battery, the charging ambient temperature, and the charging rate timing information into the associated polarization voltage prediction model of the lithium battery model for processing, and generate the residual value increment rate and polarization voltage timing information. The calibration generation module is used to input the timing end 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 is used to assess the charging control quality of the charging rate timing information based on the reverse instantaneous discharge calibration current, the residual charge increment rate, and the polarization voltage timing information, and to obtain a charging control quality coefficient. A 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 the charging control quality coefficient threshold.

9. A power tool charging device, characterized in that, Used to implement a lithium battery charging control method as described in any one of claims 1-7.

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