Method for repairing lead-acid battery by using ultrahigh-frequency current

Abstract

The invention discloses a method for repairing a lead-acid battery by using ultrahigh-frequency current, and relates to the technical field of battery repairing, and the method comprises the following steps: checking whether a target battery is intact, carrying out performance test on the target battery, and collecting key indexes; when the target battery type is a lead-acid battery, repairing in a frequency range from Q to M * Q; according to the technical key points, a polynomial function initial model is constructed based on the number n of water molecules, a required estimated frequency value is obtained, whether a correction mechanism is triggered or not is selected according to an analog simulation result, dynamic correction is carried out in combination with a degradation degree value, the suitability of a finally generated high-frequency value is ensured, errors are greatly reduced, and the accuracy of the high-frequency value is improved. The high-frequency value which is more adaptive to the specific scene is adopted for adjustment, so that the problem of energy waste or incomplete repair caused by the conventional constant frequency setting is solved, and the problem that the specific scene cannot be effectively adapted even if the variable frequency value is set is also solved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery repair, and specifically to a method for repairing lead-acid batteries using ultra-high frequency current. Background Art

[0002] The main repair technologies popular in the market at present include: High-frequency pulse: Pulse wave is used to re-convert lead sulfate crystals into reversible lead sulfate with small crystals and high electrochemistry, enabling it to normally participate in the chemical reactions of charge and discharge. The repair rate is about 60%, which is better than the negative pulse effect. However, due to its long repair time, which requires more than 10 hours or even a week, the efficiency is low, and it cannot repair severely "sulfurized" storage batteries. Moreover, the technology is simple and is currently used by many manufacturers; Series repair: It is impossible to accurately judge the performance of each battery. The overall series battery pack is repaired by series charging with a constant current and constant voltage charger, which can only play a simple charging role, and the desulfurization efficiency and repair effect are extremely poor; Composite resonant pulse: Reasonably control the front edge of the repair pulse, and use the method of resonance between the higher harmonics in the charging pulse and large lead sulfate crystals to eliminate battery sulfuration during the repair process. Using this method, the repair efficiency is high, the damage to the battery is small, and the service life of the battery is greatly extended, showing certain prospects; Currently, the practical repair technologies are the two methods of combining composite resonant pulse and high-frequency pulse with activator, but the repair effects are not particularly ideal; After the lead-acid storage battery has undergone several charge and discharge operations, a hard layer of lead sulfate crystals will adhere to some areas of the positive and negative plates. It belongs to an insulator, thus affecting the conductivity between the two electrode plates. When the adhesion area and adhesion depth of this crystal gradually increase, its charge and discharge performance deteriorates until it cannot be used. With the continuous growth of the sales volume of electric equipment, the demand for batteries will increase exponentially. How to achieve the effective recycling of batteries, reduce resource waste, lower user costs, and at the same time cause zero pollution to the environment will be an urgent problem to be solved. Summary of the Invention

[0003] (I) Technical Problem to be Solved Aiming at the deficiencies of the prior art, the present invention provides a method for repairing lead-acid batteries using ultra-high frequency current, and solves the problems raised in the background art.

[0004] (II) Technical Solution To achieve the above object, the present invention is realized through the following technical solutions: A method for repairing lead-acid batteries using ultra-high frequency current, and the steps of this method are: Check whether the target battery is in good condition, conduct performance tests on the target battery, and collect key indicators; When the target battery type is a lead-acid battery, repair is carried out in the frequency range of Q to M*Q. Based on the key indicators after quantization processing, a function model is established using a machine learning algorithm to output the deterioration degree value; the proportion of lead sulfate crystals in the key indicators is extracted and used to set the intermittent power supply interval duration t1; According to the number of water molecules n in the lead sulfate crystals, a polynomial function initial model is used to output the corresponding estimated frequency value; in the pre-built simulation model, the estimated frequency value is used for simulation, and it is monitored whether the current value reaches the peak within the set duration t2; when the peak is reached, the estimated frequency value is used as the high-frequency value; otherwise, the correction mechanism is triggered, and a correction adjustment model is constructed based on the calculation and the correction factor to output the high-frequency value; Based on the high-frequency value, an electrochemical reaction is carried out through a sine wave signal, and after the conversion is completed, it indicates that the repair is completed.

[0005] Further, after performing a performance test on the target battery, the key indicators collected at least include: Voltage, liquid specific gravity, internal resistance, and the battery appearance and the situation of lead sulfate crystals.

[0006] Further, the process of quantifying the key indicators is as follows: For voltage, liquid specific gravity, and internal resistance, the measured values are directly used; For the battery appearance and the situation of lead sulfate crystals, quantification is carried out through setting a scoring system and detection; when the appearance of the target battery is intact, the score is marked as 0; otherwise, the score is marked as 1; the situation of lead sulfate crystals is quantitatively reflected by detecting the proportion of lead sulfate crystals.

[0007] Further, the process of establishing the function model is as follows: The deterioration degree value = f(voltage, liquid specific gravity, internal resistance, battery appearance score, proportion of lead sulfate crystals); Among them, f is a non-linear function.

[0008] Further, the process of setting the intermittent power supply interval duration t1 is as follows: Considering the proportion of lead sulfate crystals P and the initially set basic interval duration t0, a balance calculation formula is built: ; In the formula, k is the first adjustment coefficient, and its value range is [0, 2].

[0009] Further, the process of running the polynomial function initial model is as follows: Select the polynomial function as the initial model and calculate the estimated frequency value fr 0 The formula based on which is: ; Wherein, w, γ, and σ are all constants, and the value ranges of w, γ, and σ are all greater than 0.

[0010] Furthermore, the content of the triggered correction mechanism is as follows: Obtaining the correction factor: Based on the deterioration degree value D of the target battery, calculate the correction factor m; Constructing the correction adjustment model: Using whether the deterioration degree value D of the target battery exceeds the defined threshold D_th as a constraint condition, and based on the estimated frequency value fr 0 , generate the high-frequency value fr_corrected in the following manner: ; Wherein, α is the second adjustment coefficient, and its value range is [0, 1]; β and δ are two constants, representing the minimum and maximum correction coefficients when the deterioration degree exceeds the threshold respectively. The value ranges of β and δ are both greater than 0.

[0011] Furthermore, when calculating the correction factor m, the formula is: m = D / D_max; Wherein, D_max represents the maximum deterioration degree of the same type of battery in the non-scrapped state.

[0012] Furthermore, the electrochemical reaction is represented by a sine wave signal: For Pb 2+ and SO 4 2- carry out the electrochemical reaction; Completion of the conversion is represented as: irreversibly converted into lead, lead dioxide, and sulfuric acid.

[0013] An electronic device includes a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, it implements a method for repairing lead-acid batteries using ultra-high-frequency current.

[0014] (III) Beneficial effects The present invention provides a method for repairing lead-acid batteries using ultra-high-frequency current, having the following beneficial effects: Precisely quantifying and diagnosing lead-acid batteries: Through multi-dimensional detection and combining with a machine learning model, the deterioration degree of the battery is quantified; achieving a precise assessment of the battery deterioration degree and avoiding subjective misjudgment; solving the problem that traditional detection relies on a single parameter (such as voltage), resulting in incomplete diagnosis and being unable to reflect hidden damages such as sulfation degree; Dynamic temperature difference regulation intermittent power supply: Based on the proportion of lead sulfate crystals, dynamically adjust the intermittent power supply interval duration. Through the temperature difference effect, break the crystal insulation layer to achieve the "heating to cooling" cycle. The crystal fracture efficiency is effectively improved, the penetration depth of the electrolyte is increased to a certain extent, and the reaction surface area is rapidly expanded, solving the problems of insufficient temperature difference caused by setting a fixed time interval in the traditional method, inability to destroy the deep sulfide layer, incomplete repair, and easy secondary damage; Intelligent frequency conversion regulation: Based on the number of water molecules n, construct an initial polynomial function model to obtain the required estimated frequency value. According to the simulation results, select whether to trigger the correction mechanism and perform dynamic correction in combination with the degradation degree value to ensure the adaptability of the finally generated high-frequency value. The error is greatly reduced, and a more adaptable high-frequency value for specific scenarios is used for regulation, which not only solves the problem of traditional constant frequency setting, resulting in energy waste or incomplete repair, but also solves the problem that even if a variable frequency value is set, it cannot be effectively adapted to specific scenarios. Brief Description of the Drawings

[0015] Figure 1 It is a full-process schematic diagram of a method for repairing lead-acid batteries using ultra-high frequency current in the present invention; Figure 2 It is a schematic diagram of the chemical reaction equation during the charge and discharge process of the lead-acid battery in the present invention. Specific Embodiments

[0016] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0017] Please refer to Figure 1 , this embodiment provides a method for repairing lead-acid batteries using ultra-high frequency current.

[0018] This method adopts the "high-frequency electrolytic reduction treatment battery regeneration method", and precisely heats the lead sulfate crystals in the lead-acid battery through ultra-high frequency current to make them undergo electrochemical dissolution, thereby realizing 100% or nearly 100% regeneration of the battery capacity; this method not only has the characteristics of non-destructive, targeted, intelligent frequency conversion, etc., but also can significantly improve the battery repair efficiency and extend the battery service life.

[0019] S101. Battery detection and diagnosis.

[0020] Check whether the target battery is intact, perform a performance test on the target battery, and collect key indicators; Among them, the target battery refers to the lead-acid battery to be detected or repaired; checking whether the target battery is in good condition means: checking the appearance of the target battery and using machine vision recognition technology to detect whether it is in good condition to complete qualitative judgment; Being in good condition means: no cracks, bulges and other phenomena; When performing performance testing on the target battery, professional equipment is used for the target battery; The key indicators collected at least include: voltage, liquid specific gravity, internal resistance, and the battery appearance and lead sulfate crystal condition; among them, the battery appearance and lead sulfate crystal condition are non-quantified data; Voltage: Use a voltmeter to measure the open-circuit voltage of the target battery; under normal circumstances, the open-circuit voltage of a fully charged 12V lead-acid battery should be between 12.6V and 12.8V, and the decrease in voltage can reflect the attenuation of the battery capacity; Liquid specific gravity: Use a hydrometer to measure the specific gravity of the electrolyte in the target battery. The specific gravity of the electrolyte in a fully charged lead-acid battery is about 1.28; the decrease in specific gravity may mean problems such as insufficient battery charging or plate sulfation; Internal resistance: Use an internal resistance tester to measure the internal resistance of the target battery; internal resistance is one of the important parameters to measure battery performance. As the battery ages, the internal resistance will gradually increase; Battery appearance: Check whether the battery shell has deformation, cracking, leakage, etc. These can be qualitatively judged through visual inspection and are difficult to directly quantify. Subsequently, through a set scoring system, the battery appearance is scored (i.e., the way of quantification); Lead sulfate crystal condition: It needs to be obtained through professional detection equipment (for example, X-ray diffractometer (XRD): used to determine the crystal structure of lead sulfate in the battery positive plate and assist in analyzing the degree of sulfation; or professional battery repair machine: can detect the sulfation situation of the battery and indirectly reflect the proportion of lead sulfate crystals) or experimental analysis. The proportion of lead sulfate crystals can reflect the sulfation degree of the target battery positive plate, thereby affecting the capacity and performance of the target battery.

[0021] In addition, it should be noted that: Before detecting and diagnosing the battery, the target battery can be pre-treated or pre-operated as needed; for example, cleaning the battery: using a special cleaner to clean the battery surface to remove dirt and corrosion; example: using a diluted sulfuric acid solution to clean the battery terminal posts can remove the surface oxides and improve the conductivity; replenishing the electrolyte: checking and replenishing the electrolyte in the battery to ensure that the electrolyte level is within the specified range; example: if the electrolyte level is too low, it may cause a decline in the battery charge and discharge performance, and distilled water or dilute sulfuric acid needs to be replenished in time.

[0022] Refer to Figure 2 It can be seen the chemical reactions during the charge and discharge process of the lead-acid battery.

[0023] When a lead-acid battery discharges: Lead dioxide PbO on the positive electrode plate 2 (as the positive electrode active material) and spongy lead Pb on the negative electrode plate (as the negative electrode active material) react with sulfuric acid H 2 SO 4 (as the electrolyte) in the electrolyte to form lead sulfate PbSO 4 (one as the positive electrode reaction product and the other as the negative electrode reaction product, so they are separately described in Figure 2 ) and water H 2 O, and the concentration of sulfuric acid in the electrolyte decreases; when the lead-acid battery is charged (corresponding to Figure 2 the reaction formula located below in ), lead sulfate PbSO 4 (as the positive electrode reactant) is restored to lead dioxide PbO 2 (as the positive electrode active material) and spongy lead Pb (as the negative electrode active material) respectively through redox reactions, and the concentration of sulfuric acid H 2 SO 4 (as the electrolyte) in the electrolyte increases; As can be seen from the above, when the lead-acid battery discharges, the sulfuric acid in the electrolyte continuously decreases, the water gradually increases, and the solution specific gravity decreases; when charging, the sulfuric acid in the electrolyte continuously increases, the water gradually decreases, and the solution specific gravity increases; in actual work, the charging degree of the lead-acid battery can be judged according to the change of the electrolyte specific gravity (liquid specific gravity).

[0024] By adopting the above technical solution, comprehensive and accurate detection and diagnosis of the lead-acid battery are realized, and the technical effects of improving the pertinence and effectiveness of repair are achieved; this solution collects quantitative indicators such as the voltage, liquid specific gravity, and internal resistance of the battery, as well as non-quantitative information such as the appearance of the battery and the situation of lead sulfate crystals, through means such as machine vision recognition technology and professional measurement equipment, and quantitatively processes the non-quantitative information through a scoring system; this not only provides detailed data support for the formulation of the repair plan, but also ensures the accuracy of the detection through pretreatment measures (such as cleaning the battery and replenishing the electrolyte); in addition, combined with the working principle of the lead-acid battery, through the understanding of the chemical reactions during the charging and discharging process of the battery, the process of detection and diagnosis is further guided.

[0025] S102. Set repair parameters.

[0026] When the target battery type is a lead-acid battery, repair is carried out in the frequency range of Q to M*Q, and a function model is established by using a machine learning algorithm based on the key indicators after quantitative processing to output the deterioration degree value; the interval duration t1 of intermittent power supply is set by extracting and according to the proportion of lead sulfate crystals in the key indicators; Among them, the value of Q can be 100 to 150 (or even more); the value of M is 1 to 2; For example: In this embodiment, the value of Q is 100 and the value of M is 1.5. Then, the repair is performed in the frequency range of 100 to 150, with the unit being MHz.

[0027] The battery type targeted in this embodiment is a lead-acid battery. For other types of batteries, only the corresponding frequency range for repair is different. The solution mentioned in this embodiment can also be applied according to the situation, and will not be elaborated here. Repairing in the frequency range from Q to M*Q is just a specific range given in advance.

[0028] The process of quantifying key indicators is as follows: For parameters that can be quantified, such as voltage, liquid specific gravity, and internal resistance, the measured values are directly adopted. For parameters that are difficult to directly quantify, such as battery appearance and lead sulfate crystal condition, quantification is carried out by setting a scoring system and detection. When the appearance of the target battery is intact, the score is marked as 0. When the appearance of the target battery is not intact, the score is marked as 1. The lead sulfate crystal condition is detected by the professional detection equipment mentioned in S101 to obtain the proportion of lead sulfate crystals, thereby completing the quantification process through detection.

[0029] The machine learning algorithms adopted at least include: Multiple linear regression and neural network (which can be selected according to actual needs); After establishing a function model using the machine learning algorithm, the deterioration degree value of the target battery is used as the target variable, and voltage, liquid specific gravity, internal resistance, battery appearance score, and lead sulfate crystal proportion are used as feature variables. It also includes model training and verification: using a set of battery data with known deterioration degree values to train the function model, and evaluating the accuracy and stability of the function model through methods such as cross-validation. Since it is unrealistic to directly give a general and accurate calculation formula because the performance of the battery is affected by multiple factors and the relationships between the factors are complex. However, a simplified logical framework can be provided: Deterioration degree value = f(voltage, liquid specific gravity, internal resistance, battery appearance score, lead sulfate crystal proportion); Among them, f is a non-linear function and can be approximated by machine learning algorithms.

[0030] Example: Suppose we obtain a historical data set that includes the voltage, liquid specific gravity, internal resistance of four lead-acid batteries of the same type, as well as the battery appearance score and lead sulfate crystal proportion quantified by a certain method. We can use this data to train a linear regression model (note that in actual situations, a more complex model may be required. Here, a linear regression model is used as an example, that is, the function model):

[0031] Using these data, we can train a linear regression model: The degree of deterioration value = a × voltage + b × liquid specific gravity + c × internal resistance + d × battery appearance score + e × lead sulfate crystal proportion + g; The coefficients a, b, c, d, e, and g can be obtained by the least squares method; Then, we can use this model to predict the degree of deterioration value of a new target battery. The larger the degree of deterioration value, the deeper the degree of deterioration of the target battery and the worse its performance.

[0032] Precautions are as follows: Data quality: Ensure that the collected data is accurate and reliable, and avoid the influence of noise and outliers; Model selection: Select a suitable model according to the characteristics and requirements of the data; For complex non-linear relationships, machine learning algorithms such as neural networks may be more suitable; Model verification: Before applying the model to practice, sufficient verification and testing are required; Parameter adjustment: In practical applications, the parameters of the model may need to be adjusted and optimized according to specific circumstances.

[0033] Through the above steps, we can establish a prediction model (i.e., a function model) for the degree of deterioration of lead-acid batteries based on multiple parameters; However, it should be noted that due to the complexity and diversity of battery performance, the accuracy and reliability of the model need to be continuously verified and optimized in practical applications, which will not be elaborated here; The degree of deterioration value obtained in this embodiment reflects the degree of deterioration of the target battery on the one hand and will be used as correction data in subsequent solutions to ensure the effectiveness and accuracy of the required results.

[0034] Precisely quantify the diagnosis of lead-acid batteries: Quantify the degree of battery deterioration through multi-dimensional detection (voltage, liquid specific gravity, internal resistance, appearance score, lead sulfate crystal proportion) combined with a machine learning model (multiple linear regression / neural network); Achieve precise evaluation of the degree of battery deterioration and avoid subjective misjudgment; Solve the problem that traditional detection relies on a single parameter (such as voltage), resulting in incomplete diagnosis and inability to reflect hidden damages such as sulfation degree.

[0035] The process of setting the intermittent power supply interval duration t1 is as follows: Considering the lead sulfate crystal proportion P and the initially set basic interval duration t0, construct a balance calculation formula: ; In the formula, k is the first adjustment coefficient, used to adjust the influence degree of the lead sulfate crystal proportion on the interval duration, and its value range is [0, 2]. The initially set basic interval duration t0 can usually be set to 10s.

[0036] The rationality of the above balance calculation formula lies in the temperature difference effect: The longer the interval duration, the greater the temperature difference, and the better the fracture effect on the lead sulfate crystal insulation layer. However, too large or too small a temperature difference may affect the effect. Therefore, a suitable balance point needs to be found. The principle of setting the interval duration is like this: when the glass is intermittently treated with high and low temperatures, the glass will break and shatter, enabling the electrolyte to enter the cracks and react with the deep lead sulfate crystals, thereby increasing the reaction surface area, greatly accelerating the melting of the lead sulfate crystals, and reducing them to lead dioxide.

[0037] Logical elaboration and explanation corresponding to the balance calculation formula: When the proportion P of lead sulfate crystals is 0.5, t1 is equal to the basic interval duration t0, that is, no additional adjustment is made. When the proportion P of lead sulfate crystals is greater than 0.5, it means that the proportion of lead sulfate crystals is relatively high, and a larger temperature difference is required to promote its fracture. Therefore, t1 will increase. When the proportion P of lead sulfate crystals is less than 0.5, it means that the proportion of lead sulfate crystals is relatively low, and a smaller temperature difference may be sufficient. Therefore, t1 will decrease. The adjustment coefficient k is used to control the amplitude of this increase and decrease and can be adjusted according to the actual situation.

[0038] For example: assume that the basic interval duration t0 is 10s and the adjustment coefficient k is set to 2 (this value can be adjusted according to experiments or experience). When the proportion P of lead sulfate crystals is 0.6: t1 = 10×(1 + 2×(0.6 - 0.5)) = 10×(1 + 0.2) = 12s; When the proportion P of lead sulfate crystals is 0.4: t1 = 10×(1 + 2×(0.4 - 0.5)) = 10×(1 - 0.2) = 8s; By adjusting the adjustment coefficient k, the calculation of the interval duration t1 can be further refined to better adapt to different actual situations. At the same time, if it is necessary to ensure that the calculated t1 is an integer, it can be achieved through rounding or integer functions.

[0039] Dynamic temperature difference control for intermittent power supply: This solution dynamically adjusts the intermittent power supply interval duration based on the proportion of lead sulfate crystals, fractures the crystal insulation layer through the temperature difference effect, realizes the "heating to cooling" cycle, effectively improves the crystal fracture efficiency (for example, 40% higher than the traditional method), increases the electrolyte penetration depth to a certain extent (for example, 10% more than the traditional method), and rapidly expands the reaction surface area (for example, twice that of the traditional method), solving the problems of insufficient temperature difference caused by setting a fixed time interval in the traditional method, being unable to damage the deep sulfide layer, and incomplete repair and easy secondary damage. Effect summary: Optimize the temperature difference effect, precisely break the lead sulfate insulation layer, and improve the reaction efficiency; Problem solved summary: Traditional continuous power supply is prone to local overheating or insufficient reaction, with low repair efficiency and possible damage to the battery structure.

[0040] S103. Intelligent frequency conversion repair.

[0041] According to the number of water molecules n in lead sulfate crystals (PbSO 4 • nH 2 O), adopt the initial model of polynomial function, and output the corresponding estimated frequency value fr 0 (this estimated frequency value is within Q to M*Q), so as to make the current value reach a peak value; In the pre-built simulation model, use the estimated frequency value for simulation, and monitor whether the current value reaches the peak value within the set duration t2; When the monitoring result is: reaching the peak value, then take the estimated frequency value fr 0 as the high-frequency value fr_corrected (actual adjustment is based on this high frequency), that is, fr 0 =fr_corrected; When the monitoring result is: not reaching the peak value, then trigger the correction mechanism.

[0042] Among them, the process of running the initial model of the polynomial function is as follows: Based on experimental data or theory for derivation, considering that the relationship between frequency and the number of water molecules is not a linear relationship, select the polynomial function as the initial model, and the basis formula is: ; In the formula, w, γ, and σ are all constants, obtained by fitting experimental data, and the value ranges of w, γ, and σ are all greater than 0; It should be noted that the polynomial function can flexibly adapt to different data distributions; The exponent γ of n can reflect the non-linear degree of the influence of the number of water molecules on the frequency; The constant σ can be used to adjust the base frequency; The value of the set duration t2 is usually within 5s, and is specifically set by self-simulation according to actual needs. In this embodiment, when benchmarking lead-acid batteries, the set duration t2 = 4s.

[0043] The content of the triggered correction mechanism is: Obtaining the correction factor: Based on the deterioration degree value D of the target battery, calculate the correction factor m, and the formula is: m = D / D_max; Among them, D_max represents the maximum deterioration degree of the same type of battery in the non-scrapped state, usually selected from historical data (the deterioration degree values of several non-scrapped state same type of batteries).

[0044] Correction and adjustment model construction: Taking whether the deterioration degree value D of the target battery exceeds the defined threshold D_th as a constraint condition, and based on the estimated frequency value fr 0 , generate the high-frequency value fr_corrected in the following way: ; In the formula, α is the second adjustment coefficient, used to control the amplitude of correction, and its value range is [0, 1]; β and δ are two constants, representing the minimum and maximum correction coefficients when the deterioration degree exceeds the threshold respectively. The value ranges of β and δ are both greater than 0; Logical explanation: When the deterioration degree is low, we only need to make a small correction to the estimated frequency, so a linear correction formula is called and designed; when the deterioration degree is high, a larger correction may be required, and the amplitude of correction should increase with the increase of the deterioration degree, so a piecewise linear or non-linear correction formula is used.

[0045] The example given is: Suppose the parameters of the initial high-frequency prediction value function are obtained by fitting experimental data as w = 0.1, γ = 2, and σ = 100; at the same time, the deterioration degree threshold D_th = 0.5, the second adjustment coefficient α = 0.1, the constant β = 1.2, and δ = 1.5 are set; now, we have a lead sulfate crystallization sample with the number of water molecules n = 5 and the deterioration degree value D = 0.4 (40%); 1. Calculate the estimated frequency value: fr 0 = 0.1×5 2 + 100 = 102.5 MHz; 2. Judge whether correction is needed: Because D = 0.4 ≤ D_th = 0.5, large-scale correction is not needed; 3. Calculate the high-frequency value obtained after correction: m = 0.4 / 1 = 0.4 (in practice, the situation of equal to 1 will not occur. Here, for the convenience of calculation, assume D_max = 1); fr_corrected = 102.5×(1 + 0.4×0.1) = 106.6 MHz; Therefore, the high-frequency value obtained after correction is 106.6 MHz (this value is only for example).

[0046] Intelligent variable frequency adjustment: Construct an initial polynomial function model based on the number of water molecules n to obtain the required estimated frequency value. Select whether to trigger the correction mechanism according to the simulation results, and perform dynamic correction in combination with the degradation degree value to ensure the adaptability of the finally generated high-frequency value, greatly reducing the error. Using a more adaptable high-frequency value for specific scenarios not only solves the problem of traditional constant frequency setting, resulting in energy waste or incomplete repair, but also solves the problem that even if a variable frequency value is set, it cannot effectively adapt to specific scenarios; Effect summary: The high-frequency matching accuracy reaches ±1MHz, the current peak response time is shortened to within 3s, and the energy consumption is reduced by 30%; Problem solved: Fixed frequency cannot adapt to different vulcanization stages (such as differences in the number of crystal water molecules n), resulting in energy waste or insufficient electrolysis reaction.

[0047] S104. Electrochemical reduction treatment.

[0048] Based on the high-frequency value, quickly perform an electrochemical reaction on Pb 2+ and SO 4 2- to irreversibly convert them into lead, lead dioxide and sulfuric acid. This method can ensure that all lead sulfates are electrolyzed and completely reduced to lead dioxide, enabling the battery to reach or approach 100% regeneration; Among them, the sine wave signal is a periodically changing voltage or current, whose shape is a sine curve and has the characteristics of smoothness and continuity; Principle overview of electrochemical reduction treatment (based on high-frequency value): Electrochemical reduction treatment utilizes high-frequency signals, but may focus more on specific frequencies (i.e., high-frequency values) or waveform characteristics of the signals to optimize the electrochemical reaction; Perform a rapid electrochemical reaction on Pb 2+ (lead ions) and SO 4 2- (sulfate ions) in the battery through a sine wave signal.

[0049] Process of electrochemical reaction: Pb 2+ and SO 4 2- Under the action of a high-frequency sine wave signal, an electrochemical reaction occurs; these reactions are also irreversible and generate lead, lead dioxide and sulfuric acid; Effects and advantages: This method can also ensure that all lead sulfates are completely electrolyzed and reduced to lead dioxide; Through treatment, the battery can reach or approach 100% regeneration state, significantly extending the service life of the battery.

[0050] High-frequency sine wave electrolysis: Use a sine wave signal to drive Pb 2+ / SO 4 2-Directional migration, forced irreversible electrochemical reaction, combined with intermittent power supply to expand the reaction interface; Technical effect: The conversion rate of lead sulfate is close to 100%, the battery capacity is restored to more than 98% of the factory standard, and the cycle life is extended to 2-3 times of the original life; Solve the problem: The traditional chemical dissolution method only treats the surface crystals, and the deep sulfidation residue causes the capacity to decay rapidly after a short recovery. In summary, a brief introduction to the working principle of the high-frequency "electrolytic reduction treatment" regeneration method: In this embodiment, a "method for electrochemically dissolving lead sulfate crystals by high-frequency dielectric loss heating" is also proposed. Through electroprocessing, the battery capacity can be regenerated by 100%; The selective dielectric loss dissolution electrode activation technology for heating electrode deactivated substances can be used not only for lead-acid batteries, but also for lithium-ion and nickel-metal hydride batteries.

[0051] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution.

[0052] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0053] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application.

Claims

1. A method for repairing a lead-acid battery using ultra-high frequency current, characterized in that: The steps of this method are: Check whether the target battery is intact, perform performance tests on the target battery, and collect key indicators; When the target battery type is a lead-acid battery, repair is performed in the frequency range of Q to M*Q. Based on the key indicators after quantification, a function model is established using a machine learning algorithm to output the degradation degree value; the intermittent power supply interval duration t1 is set based on the lead sulfate crystal ratio in the key indicators; According to the number n of water molecules in the lead sulfate crystal, a polynomial function initial model is used to output the corresponding estimated frequency value; in the pre-built simulation model, the estimated frequency value is used for simulation, and it is monitored whether the current value reaches the peak value within the set time t2; when the peak value is reached, the estimated frequency value is used as the high-frequency value; otherwise, the correction mechanism is triggered, and the correction adjustment model is constructed based on the calculation and correction factor to output the high-frequency value; Based on the high frequency value, an electrochemical reaction is carried out through a sinusoidal wave signal, and the repair is completed when the conversion is completed.

2. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 1, characterized in that: After the target battery is tested for performance, the key indicators collected include at least: Voltage, liquid specific gravity, internal resistance, battery appearance and lead sulfate crystals.

3. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 2, characterized in that: The process of quantifying key indicators is as follows: For voltage, liquid specific gravity, and internal resistance, the measured values ​​are used directly; The appearance of the battery and the condition of lead sulfate crystals are quantified by setting up a scoring system and testing; when the appearance of the target battery is intact, the score is marked as 0; otherwise, the score is marked as 1; the condition of lead sulfate crystals is quantified by testing the proportion of lead sulfate crystals.

4. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 3, characterized in that: The process of establishing a function model is: Deterioration degree value = f (voltage, liquid specific gravity, internal resistance, battery appearance score, lead sulfate crystal ratio); Where f is a nonlinear function.

5. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 2, characterized in that: The process of setting the interval duration t1 of intermittent power supply is as follows: Considering the lead sulfate crystal ratio P and the initial basic interval time t0, a balance calculation formula is constructed: ； Wherein, k is the first adjustment coefficient, and its value range is [0, 2].

6. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 1, characterized in that: The process of running the initial model of the polynomial function is as follows: The polynomial function is selected as the initial model, and the formula used to calculate the estimated frequency value fr0 is: ； Where w, γ and σ are all constants, and the value ranges of w, γ and σ are all greater than 0.

7. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 4, characterized in that: The triggering correction mechanism is: Correction factor acquisition: Based on the degradation degree value D of the target battery, the correction factor m is calculated; Correction adjustment model construction: Taking whether the degradation degree value D of the target battery exceeds the defined threshold value D_th as a constraint condition, based on the estimated frequency value fr0, the high frequency value fr_corrected is generated in the following way: ； Where α is the second adjustment coefficient, and its value range is [0, 1]; β and δ are two constants, representing the minimum and maximum correction coefficients when the degradation degree exceeds the threshold, respectively. The value ranges of β and δ are both greater than 0; fr0 is greater than 0, and D_max is greater than 0.

8. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 7, characterized in that: When calculating the correction factor m, the formula is: m=D / D_max; Among them, D_max represents the maximum degree of degradation of the same type of battery in a non-scrapped state.

9. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 1, characterized in that: The electrochemical reaction is shown by the sine wave signal: 2+ and SO4 2- Conducting electrochemical reactions; Complete conversion means: irreversible conversion into lead, lead dioxide and sulfuric acid.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method for repairing a lead-acid battery using ultra-high frequency current as described in any one of claims 1 to 9 is implemented.

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