A method for repairing lead-acid batteries using ultra-high frequency current

Abstract

The present invention discloses a method for repairing lead-acid batteries using ultra-high frequency current, which relates to the technical field of battery repair. The steps of this method are as follows: check whether the target battery is in good condition, conduct performance tests on the target battery, and collect key indicators; under the condition that the target battery type is a lead-acid battery, repair it in the frequency range of Q to M*Q; the technical key points are: based on the number of water molecules n, construct an initial polynomial function model 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 deterioration degree value to ensure the adaptability of the finally generated high-frequency value, greatly reducing the error. By using a more adaptable high-frequency value for specific scenarios for adjustment, it 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.

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:

[0003] High-frequency pulse: Pulse waves are 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 many manufacturers are currently using it; 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 resonance 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 combination of composite resonance pulse and high-frequency pulse plus activator in two ways, 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

[0004] (I) Technical Problems to be Solved

[0005] In view of the deficiencies of the prior art, the present invention provides a method for repairing lead-acid batteries using ultra-high frequency current, which solves the problems raised in the background art.

[0006] (II) Technical Solutions

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions:

[0008] A method for repairing lead-acid batteries using ultra-high frequency current, and the steps of this method are as follows:

[0009] Check whether the target battery is in good condition, conduct a performance test on the target battery, and collect key indicators;

[0010] When the target battery type is a lead-acid battery, perform repair in the frequency range of Q to M*Q. Based on the key indicators after quantization processing, use a machine learning algorithm to establish a function model and output the deterioration degree value; extract and set the intermittent power supply interval duration t1 according to the lead sulfate crystal proportion in the key indicators;

[0011] According to the number of water molecules n in the lead sulfate crystal, use the initial polynomial function model to output the corresponding estimated frequency value; in the pre-built simulation model, use the estimated frequency value for simulation and monitor whether the current value reaches the peak within the set duration t2; when it reaches the peak, take the estimated frequency value as the high frequency value; otherwise, trigger the correction mechanism, calculate and construct a correction adjustment model based on the correction factor, and output the high frequency value;

[0012] Based on the high frequency value, perform an electrochemical reaction through a sine wave signal, and after completion of the conversion, it indicates that the repair is completed.

[0013] Furthermore, after performing a performance test on the target battery, the key indicators collected at least include:

[0014] Voltage, liquid specific gravity, internal resistance, battery appearance, and lead sulfate crystal condition.

[0015] Furthermore, the process of quantifying the key indicators is as follows:

[0016] For voltage, liquid specific gravity, and internal resistance, directly adopt the measured values;

[0017] For the battery appearance and lead sulfate crystal condition, quantify through setting a scoring system and detection; when the appearance of the target battery is intact, mark the score as 0; otherwise, mark the score as 1; the lead sulfate crystal condition is quantitatively reflected by detecting the proportion of lead sulfate crystals.

[0018] Furthermore, the process of establishing the function model is as follows:

[0019] Deterioration degree value = f(voltage, liquid specific gravity, internal resistance, battery appearance score, lead sulfate crystal proportion);

[0020] Among them, f is a non-linear function.

[0021] Furthermore, the process of setting the intermittent power supply interval duration t1 is as follows:

[0022] Considering the lead sulfate crystal proportion P and the initially set basic interval duration t0, construct an equilibrium calculation formula:

[0023] ;

[0024] Wherein, k is the first adjustment coefficient, and its value range is [0, 2].

[0025] Furthermore, the process of running the initial model of the polynomial function is as follows:

[0026] Select the polynomial function as the initial model, and the formula for calculating the estimated frequency value fr0 is:

[0027] ;

[0028] Wherein, w, γ, and σ are all constants, and the value ranges of w, γ, and σ are all greater than 0.

[0029] Furthermore, the content of the triggered correction mechanism is:

[0030] Obtaining the correction factor: Based on the deterioration degree value D of the target battery, calculate the correction factor m;

[0031] Constructing the correction adjustment model: Taking whether the deterioration degree value D of the target battery exceeds the defined threshold D_th as a constraint condition, and generating the high-frequency value fr_corrected according to the following method based on the estimated frequency value fr0:

[0032] ;

[0033] Wherein, α is the second adjustment coefficient, and its value range is [0, 1];

[0034] β and δ are two constants, representing the minimum and maximum correction coefficients when the deterioration degree exceeds the threshold respectively, and the value ranges of β and δ are both greater than 0.

[0035] Furthermore, when calculating the correction factor m, the formula is: m = D / D_max;

[0036] Wherein, D_max represents the maximum deterioration degree of the same type of battery in the non-scrapped state.

[0037] Furthermore, the electrochemical reaction is represented by a sine wave signal: For Pb 2+ and SO4 2- to carry out the electrochemical reaction;

[0038] Completion of the conversion is represented as: irreversibly converted into lead, lead dioxide, and sulfuric acid.

[0039] 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, a method for repairing a lead-acid battery using ultra-high frequency current is implemented.

[0040] (III) Beneficial effects

[0041] The present invention provides a method for repairing lead-acid batteries using ultra-high frequency current, which has the following beneficial effects:

[0042] Precisely quantify the diagnosis of lead-acid batteries: Through multi-dimensional detection and combined with machine learning models, the degree of battery deterioration is quantified; the accurate assessment of the degree of battery deterioration is realized, avoiding subjective misjudgment; 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, is solved.

[0043] Dynamically regulate the intermittent power supply by temperature difference: Based on the proportion of lead sulfate crystals, the intermittent power supply interval time is dynamically adjusted. Through the temperature difference effect, the crystal insulation layer is broken, and the "heating to cooling" cycle is realized. 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. The problems that traditional methods have insufficient temperature difference due to setting a fixed time interval, unable to break the deep sulfation layer, and incomplete repair and easy to cause secondary damage are solved.

[0044] Intelligent frequency conversion regulation: Based on the number of water molecules n, an initial polynomial function model is constructed to obtain the required estimated frequency value. Whether to trigger the correction mechanism is selected according to the simulation results, and dynamic correction is carried out in combination with the degree of deterioration value to ensure the adaptability of the finally generated high-frequency value. The error is greatly reduced. Using a more adaptable high-frequency value for specific scenarios for regulation 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

[0045] 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;

[0046] Figure 2 It is a schematic diagram of the chemical reaction equation during the charge and discharge process of lead-acid batteries in the present invention. Detailed Embodiments

[0047] 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 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 shall fall within the protection scope of the present invention.

[0048] Please refer to Figure 1 , this embodiment provides a method for repairing lead-acid batteries using ultra-high frequency current.

[0049] This method adopts the "high-frequency electrolytic reduction treatment for battery regeneration method", which precisely heats the lead sulfate crystals in the lead-acid battery through ultra-high-frequency current to cause their electrochemical dissolution, thereby achieving 100% or nearly 100% regeneration of the battery capacity. This method not only has the characteristics of being non-destructive, targeted, and intelligent frequency conversion, but also can significantly improve the battery repair efficiency and extend the battery service life.

[0050] S101. Battery detection and diagnosis.

[0051] Check whether the target battery is in good condition, conduct a performance test on the target battery, and collect key indicators.

[0052] 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 a qualitative judgment.

[0053] In good condition means: there are no phenomena such as cracks and bulges.

[0054] When conducting a performance test on the target battery, use professional equipment for the target battery.

[0055] The key indicators collected at least include: voltage, liquid specific gravity, internal resistance, and the battery appearance and lead sulfate crystal conditions. Among them, the battery appearance and lead sulfate crystal conditions are non-quantified data.

[0056] Voltage: Measure the open-circuit voltage of the target battery using a voltmeter. Under normal circumstances, the open-circuit voltage of a fully charged 12V lead-acid battery should be between 12.6V and 12.8V. The decrease in voltage can reflect the attenuation of the battery capacity.

[0057] Liquid specific gravity: Measure the specific gravity of the electrolyte in the target battery using a hydrometer. The specific gravity of the electrolyte in a fully charged lead-acid battery is about 1.28. The decrease in specific gravity may mean that the battery is undercharged or there are problems such as plate sulfation.

[0058] Internal resistance: Measure the internal resistance of the target battery using an internal resistance tester. Internal resistance is one of the important parameters to measure the battery performance. As the battery ages, the internal resistance will gradually increase.

[0059] Battery Appearance: Check whether the battery case is deformed, cracked, leaking, 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., a way of quantification); Lead Sulfate Crystal Condition: It needs to be obtained through professional testing 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 a professional battery repair machine: can detect the sulfation condition 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 positive plate of the target battery, thereby affecting the capacity and performance of the target battery.

[0060] In addition, it should be noted that:

[0061] Before detecting and diagnosing the battery, the target battery can be pretreated or pre-operated as needed; for example, Clean the battery: Use a special cleaner to clean the battery surface to remove dirt and corrosion; Example: Use a diluted sulfuric acid solution to clean the battery terminal posts, which can remove the surface oxides and improve the conductivity; Supplement the electrolyte: Check and supplement 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 the battery charge and discharge performance to decline, and distilled water or dilute sulfuric acid needs to be supplemented in a timely manner.

[0062] Refer to Figure 2 It can be seen the chemical reactions during the charge and discharge process of lead-acid batteries.

[0063] When a lead-acid battery discharges: Lead dioxide PbO2 on the positive plate (as the positive active material) and spongy lead Pb on the negative plate (as the negative active material) react with sulfuric acid H2SO4 in the electrolyte (as the electrolyte) to generate lead sulfate PbSO4 (one as the product of the positive reaction and the other as the product of the negative reaction, so they are separately expressed in Figure 2 and water H2O, and the concentration of sulfuric acid in the electrolyte decreases; When the lead-acid battery is charging (corresponding to the reaction formula at the lower part in Figure 2 ): Lead sulfate PbSO4 (as the positive reactant) is restored to lead dioxide PbO2 (as the positive active material) and spongy lead Pb (as the negative active material) respectively through redox reactions, and the concentration of sulfuric acid H2SO4 in the electrolyte (as the electrolyte) increases;

[0064] As can be seen from the above, when a 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 lead-acid batteries can be judged based on the change in the electrolyte specific gravity (liquid specific gravity).

[0065] By adopting the above technical solution, a comprehensive and accurate detection and diagnosis of lead-acid batteries is achieved, and the technical effect of improving the pertinence and effectiveness of repair is achieved; through means such as machine vision recognition technology and professional measuring equipment, 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, 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 pre-treatment measures (such as cleaning the battery and replenishing the electrolyte); in addition, combined with the working principle of lead-acid batteries, 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.

[0066] S102. Set repair parameters.

[0067] 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 using a machine learning algorithm based on the key indicators after quantitative processing to output the deterioration degree value; extract and set the interval duration t1 of intermittent power supply according to the proportion of lead sulfate crystals in the key indicators.

[0068] Among them, the value of Q can be 100 to 150 (or even more); the value of M is 1 to 2.

[0069] For example: in this embodiment, the value of Q is 100 and the value of M is 1.5, then repair is carried out in the frequency range of 100 to 150, and the unit is: MHz.

[0070] This embodiment is aimed at lead-acid batteries. For other types of batteries, only the corresponding repair frequency ranges are different, and the solution mentioned in this embodiment can also be applied according to the situation, which will not be elaborated here; carrying out repair in the frequency range of Q to M*Q only gives a specific range in advance.

[0071] The process of quantitatively processing the key indicators is as follows:

[0072] For parameters that can be quantified, such as voltage, liquid specific gravity, and internal resistance, the measured values are directly adopted.

[0073] For parameters that are difficult to directly quantify, such as the appearance of the battery and the situation of lead sulfate crystals, quantification is carried out by setting a scoring system and detection; when the appearance of the target battery is intact, the marked score is 0; when the appearance of the target battery is non-intact, the marked score is 1; the situation of lead sulfate crystals 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.

[0074] The machine learning algorithms adopted at least include:

[0075] Multiple linear regression and neural networks (to be selected according to actual needs);

[0076] After establishing a function model using machine learning algorithms, the degradation degree value of the target battery is used as the target variable, and voltage, liquid specific gravity, internal resistance, battery appearance score, and the proportion of lead sulfate crystals are used as feature variables; it also includes model training and verification: using a set of battery data with known degradation degree values to train the function model, and evaluating the accuracy and stability of the function model through methods such as cross-validation;

[0077] Since it is unrealistic to directly give a general and precise 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:

[0078] Degradation degree value = f(voltage, liquid specific gravity, internal resistance, battery appearance score, proportion of lead sulfate crystals);

[0079] Among them, f is a non-linear function and can be approximated by machine learning algorithms.

[0080] Example: Suppose we obtain a historical dataset 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 the proportion of lead sulfate crystals quantified in a certain way. 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):

[0081]

[0082] Using this data, we can train a linear regression model:

[0083] Degradation degree value = a × voltage + b × liquid specific gravity + c × internal resistance + d × battery appearance score + e × proportion of lead sulfate crystals + g;

[0084] The coefficients a, b, c, d, e, and g can be obtained through the least squares method;

[0085] Then, we can use this model to predict the degradation degree value of the new target battery. The larger the degradation degree value, the deeper the degradation degree of the target battery and the worse its performance.

[0086] Precautions are as follows:

[0087] 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, it may be necessary to adjust and optimize the parameters of the model according to specific circumstances.

[0088] Through the above steps, we can establish a lead-acid battery degradation degree prediction model (i.e., a function model) 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 degradation degree value obtained in this embodiment preliminarily reflects the degradation degree of the target battery on the one hand, and on the other hand, it will be used as correction data in subsequent solutions to ensure the effectiveness and accuracy of the required results.

[0089] Precisely quantify the diagnosis of lead-acid batteries:

[0090] Quantify the battery degradation degree through multi-dimensional detection (voltage, liquid specific gravity, internal resistance, appearance score, proportion of lead sulfate crystals) combined with a machine learning model (multiple linear regression / neural network); Achieve accurate assessment of the battery degradation degree 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.

[0091] The process of setting the intermittent power supply interval duration t1 is as follows:

[0092] Considering the proportion of lead sulfate crystals P and the initially set basic interval duration t0, construct a balance calculation formula:

[0093] ;

[0094] In the formula, k is the first adjustment coefficient, which is used to adjust the influence degree of the proportion of lead sulfate crystals on the interval duration, and its value range is [0, 2]. The initially set basic interval duration t0 can usually be set to 10s.

[0095] The rationality of the above balance calculation formula lies in the temperature difference effect:

[0096] 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 temperature difference may affect the effect. Therefore, it is necessary to find a suitable balance point; The principle of setting the interval duration is like: performing intermittent high-temperature and low-temperature treatment on glass, and the glass will break and shatter; This allows the electrolyte to enter the cracks and react with the deep lead sulfate crystals, thereby increasing the reaction surface area and greatly accelerating the melting of the lead sulfate crystals to reduce them to lead dioxide.

[0097] Logical elaboration and explanation corresponding to the balance calculation formula:

[0098] 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;

[0099] When the proportion P of lead sulfate crystals is greater than 0.5, it indicates that the proportion of lead sulfate crystals is relatively high, and a larger temperature difference is required to promote its fracture, so t1 will increase; when the proportion P of lead sulfate crystals is less than 0.5, it indicates that the proportion of lead sulfate crystals is relatively low, and a smaller temperature difference may be sufficient, so 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.

[0100] 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);

[0101] When the proportion P of lead sulfate crystals is 0.6:

[0102] t1 = 10×(1 + 2×(0.6 - 0.5)) = 10×(1 + 0.2) = 12s;

[0103] When the proportion P of lead sulfate crystals is 0.4:

[0104] t1 = 10×(1 + 2×(0.4 - 0.5)) = 10×(1 - 0.2) = 8s;

[0105] 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.

[0106] Dynamic temperature difference control intermittent power supply:

[0107] This solution dynamically adjusts the intermittent power supply interval duration based on the proportion of lead sulfate crystals, breaks 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, expanded to 2 times the traditional method), solving the problems of insufficient temperature difference caused by setting a fixed time interval in the traditional method, inability to break the deep sulfide layer, incomplete repair, and easy to cause secondary damage;

[0108] Effect summary: Optimize the temperature difference effect, accurately break the lead sulfate insulation layer, and improve the reaction efficiency; Problem summary: Traditional continuous power supply is prone to local overheating or insufficient reaction, with low repair efficiency and possible damage to the battery structure.

[0109] S103, Intelligent frequency conversion repair.

[0110] According to the number of water molecules n in lead sulfate crystals (PbSO4•nH2O), use the initial polynomial function model to output the corresponding estimated frequency value fr0 (this estimated frequency value is within Q to M*Q), which is used 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;

[0111] When the monitoring result is: reaching the peak value, then take the estimated frequency value fr0 as the high frequency value fr_corrected (actual adjustment is based on this high frequency), that is, fr0 = fr_corrected;

[0112] When the monitoring result is: not reaching the peak value, then trigger the correction mechanism.

[0113] Among them, the process of running the initial polynomial function model is as follows:

[0114] Based on experimental data or theory 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:

[0115] ;

[0116] 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;

[0117] The value of the set duration t2 is usually within 5s, and is specifically set by self-simulation according to actual requirements. In this embodiment, when benchmarking lead-acid batteries, the set duration t2 = 4s.

[0118] The content of the triggered correction mechanism is:

[0119] 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; where 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).

[0120] 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, based on the estimated frequency value fr0, generate the high frequency value fr_corrected in the following way:

[0121] ;

[0122] In the formula, α is the second adjustment coefficient used to control the magnitude of correction, and its value range is [0, 1];

[0123] β and δ are two constants, representing the minimum and maximum correction coefficients respectively when the deterioration degree exceeds the threshold, and the value ranges of both β and δ are greater than 0;

[0124] The logical explanation is as follows: 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 magnitude of the correction should increase with the increase of the deterioration degree, so a piecewise linear or non-linear correction formula is used.

[0125] The example given is as follows:

[0126] Suppose the parameters of the initial high-frequency estimated value function obtained by fitting experimental data are w = 0.1, γ = 2, and σ = 100; meanwhile, 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 crystal sample with the number of water molecules n = 5 and the deterioration degree value D = 0.4 (40%);

[0127] 1. Calculate the estimated frequency value:

[0128] fr0 = 0.1 × 5 2 + 100 = 102.5 MHz;

[0129] 2. Determine whether correction is needed:

[0130] Since D = 0.4 ≤ D_th = 0.5, no large correction is needed;

[0131] 3. Calculate the high-frequency value obtained after correction:

[0132] m = 0.4 / 1 = 0.4 (in practice, the situation of being equal to 1 will not occur. Here, for the convenience of calculation, assume D_max = 1);

[0133] fr_corrected = 102.5 × (1 + 0.4 × 0.1) = 106.6 MHz;

[0134] Therefore, the high-frequency value obtained after correction is 106.6 MHz (this value is only for example).

[0135] Intelligent frequency conversion adjustment:

[0136] Construct an initial polynomial function model based on the number of water molecules n to obtain the required estimated frequency value. Determine whether to trigger the correction mechanism based on the simulation results, and perform dynamic correction in combination with the deterioration degree value to ensure the adaptability of the finally generated high-frequency value, greatly reducing the error. Adjust using a more adaptable high-frequency value for specific scenarios, which not only solves the problem of traditional fixed-frequency settings that lead to energy waste or incomplete repair, but also solves the problem that even setting variable frequency values cannot effectively adapt to specific scenarios;

[0137] 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 frequencies cannot adapt to different vulcanization stages (such as differences in the number of crystal water molecules n), resulting in energy waste or insufficient electrolysis reactions.

[0138] S104. Electrochemical reduction treatment.

[0139] Based on the high-frequency value, quickly perform an electrochemical reaction on Pb 2+ and SO4 2- to irreversibly convert them into lead, lead dioxide, and sulfuric acid. This method can ensure that all lead sulfate is electrolyzed and completely reduced to lead dioxide, enabling the battery to reach or approach 100% regeneration;

[0140] Among them, the sine wave signal is a periodically changing voltage or current, with a shape like a sine curve, featuring smoothness and continuity; Principle overview of electrochemical reduction treatment (based on high-frequency value):

[0141] 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 SO4 2- (sulfate ions) in the battery through the sine wave signal.

[0142] Process of the electrochemical reaction:

[0143] Pb 2+ and SO4 2- undergo an electrochemical reaction under the action of a high-frequency sine wave signal; these reactions are also irreversible, generating lead, lead dioxide, and sulfuric acid; Effects and advantages: This method can also ensure that all lead sulfate is completely electrolyzed and reduced to lead dioxide; Through treatment, the battery can reach or approach 100% regeneration, significantly extending the battery's service life.

[0144] High-frequency sine wave electrolysis:

[0145] Drive Pb 2+ / SO4 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 the original life; Problem solved: The traditional chemical dissolution method only treats the surface crystals, and the deep sulfidation residue causes the capacity to rapidly decay after a short recovery.

[0146] In summary, a brief introduction to the working principle of the high-frequency "electrolytic reduction treatment" regeneration method:

[0147] In this embodiment, the "electrochemical dissolution method for heating lead sulfate crystals by high-frequency dielectric loss" 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.

[0148] 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 will realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or in 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.

[0149] 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.

[0150] 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 can easily think of changes or substitutions within the technical scope disclosed in this application, and all of them should be covered by 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; The key indicators include at least: voltage, liquid specific gravity, internal resistance, battery appearance and lead sulfate crystals; 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; The value range of Q is: 100 to 150, unit: MHz; the value of M is 1 to 2; 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: 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.

3. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 2, 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.

4. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 3, 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].

5. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 4, 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.

6. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 5, characterized in that: The triggered 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.

7. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 6, 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.

8. The method for repairing a lead-acid battery using ultra-high frequency current according to claim 7, characterized in that: The electrochemical reaction is represented by a sine wave signal: an electrochemical reaction of Pb2+ and SO42-; Complete conversion means: irreversible conversion into lead, lead dioxide and sulfuric acid.

9. 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 8 is implemented.

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