Pulse current regulation method for rapid charging of military special power supply

Abstract

The present application relates to the technical field of charging regulation, and particularly relates to a pulse current regulation method for rapid charging of a military special power supply. The method comprises the following steps: obtaining a corresponding pulse current beam of a military lithium battery in a rapid charging process and performing pulse regulation parameter calculation to obtain a corresponding pulse current amplitude, pulse current frequency and pulse current duty cycle in the rapid charging process; obtaining a corresponding type, voltage grade and measurement accuracy requirement of the military lithium battery and performing internal resistance polarization alternating current measurement and battery interference probability estimation to generate a military rapid charging battery interference probability; performing health interval mapping evaluation based on the military rapid charging battery interference probability and performing pulse current regulation analysis on the pulse current amplitude, pulse current frequency and pulse current duty cycle to generate a corresponding pulse current regulation strategy of the military lithium battery in different states. The present application can accurately control the corresponding pulse current in the rapid charging process.

Description

Technical Field

[0001] This invention relates to the field of charging regulation technology, and in particular to a pulse current regulation method for fast charging of military special power supplies. Background Technology

[0002] With the ever-increasing power demands of modern military equipment, especially in battlefield environments, higher requirements are being placed on efficient, fast, and stable military-grade special power supplies, specifically lithium batteries capable of generating high-voltage pulses. Existing charging technologies largely rely on constant current charging and constant voltage charging methods, which, while ensuring battery charging safety, have limited charging speed and efficiency. Particularly with high-power military lithium batteries, prolonged charging not only wastes time but also leads to battery damage due to thermal effects, even posing safety hazards. Furthermore, traditional charging methods lack real-time monitoring and precise control of battery status, failing to dynamically adjust the charging current according to the battery's characteristics at different charging stages, resulting in significantly reduced charging efficiency or even failure to charge. Summary of the Invention

[0003] Therefore, it is necessary for the present invention to provide a pulse current regulation method for fast charging of military special power supplies, so as to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a pulse current regulation method for fast charging of military special power supplies includes the following steps: Step S1: Obtain the pulse current beam corresponding to the military lithium battery during fast charging, and calculate the pulse control parameters based on the pulse current beam corresponding to the military lithium battery during fast charging to obtain the pulse current amplitude, pulse current frequency and pulse current duty cycle corresponding to the fast charging process. Step S2: Obtain the type, voltage level, and measurement accuracy requirements of the military lithium battery, and perform internal resistance polarization AC measurement on the corresponding battery pack during fast charging based on the type, voltage level, and measurement accuracy requirements of the military lithium battery to obtain the internal resistance of the military lithium battery. Step S3: Estimate the battery interference probability of the corresponding battery pack during fast charging based on the internal resistance of the military lithium battery to generate the interference probability of the military fast charging battery; perform a health interval mapping evaluation on the corresponding battery pack based on the interference probability of the military fast charging battery to obtain the health status of the battery pack corresponding to the military lithium battery, including the normal charging state and the aging state of the battery. Step S4: Based on the health status of the battery pack corresponding to the military lithium battery, perform pulse current regulation analysis on the pulse current amplitude, pulse current frequency and pulse current duty cycle corresponding to the pulse current beam during the fast charging process, and generate pulse current regulation strategies for the military lithium battery under different states.

[0005] Furthermore, step S1 includes the following steps: Step S11: Obtain the pulse current beam corresponding to the military lithium battery during fast charging; Step S12: Perform high-frequency noise filtering on the pulse current beam corresponding to the military lithium battery during fast charging, and apply adaptive filtering to adjust the corresponding filtering parameters to remove high-frequency noise and random noise in the pulse current beam, and generate a pulse current beam after high-frequency noise reduction. Step S13: Perform low-frequency sliding filtering on the pulse current beam after high-frequency noise reduction. By setting a sliding window with a window size of 5, and using the sliding average filtering of the low-frequency noise corresponding to the pulse current beam after high-frequency noise reduction according to the sliding window, a smoothed pulse current beam is obtained. Step S14: Calculate the pulse control parameters based on the smoothed and filtered pulse current beam to obtain the pulse current amplitude, pulse current frequency, and pulse current duty cycle during the fast charging process.

[0006] Furthermore, step S14 includes the following steps: Step S141: Obtain the zero-crossing point of the corresponding pulse current signal through the smoothed pulse current beam, and determine the start and end times of each waveform in the smoothed pulse current beam based on the zero-crossing point of the pulse current signal. Step S142: Estimate the pulse period based on the start and end times of each waveform in the pulse current beam to obtain the pulse period corresponding to the pulse current beam. Step S143: Obtain the maximum and minimum values ​​of the pulse current signal corresponding to each pulse period of the pulse current beam, and calculate the pulse amplitude based on the maximum and minimum values ​​of the pulse current signal to obtain the pulse current amplitude corresponding to the fast charging process. Step S144: Calculate the number of pulse cycles per unit time using the pulse cycle corresponding to the pulse current beam as the frequency, so as to obtain the pulse current frequency corresponding to the fast charging process. Step S145: Obtain the high-level time of the pulse current beam within one pulse period and the total time of the entire period by using the pulse period corresponding to the pulse current beam. Calculate the corresponding duty cycle based on the ratio between the high-level time and the total time of the entire period to obtain the corresponding pulse current duty cycle during the fast charging process.

[0007] Furthermore, step S2 includes the following steps: Step S21: Obtain the type, voltage level, and measurement accuracy requirements of the military lithium battery; Step S22: Select an internal resistance tester with micro-ohm level measurement accuracy, adaptability to a wide voltage range including 0-1000V, and anti-interference capability according to the type, voltage level, and measurement accuracy requirements of the military lithium battery, and establish a reliable connection between the positive and negative test lines of the internal resistance tester and the positive and negative terminals of the battery pack during the fast charging process. Step S23: Obtain the usage frequency corresponding to the military lithium battery, set the corresponding measurement cycle according to the usage frequency corresponding to the military lithium battery, and inject an AC current between 1kHz and 10kHz into the battery pack by starting the positive and negative terminals of the internal resistance tester when the battery pack is not charging or discharging within the corresponding measurement cycle, and measure the AC voltage response at the corresponding terminals to generate the AC voltage for measuring the internal resistance of the military battery. Step S24: Based on the injected AC current and the AC voltage of the military battery internal resistance measurement, perform AC polarization measurement on the corresponding battery pack during the fast charging process to obtain the internal resistance of the military lithium battery.

[0008] Furthermore, step S24 includes the following steps: Step S241: Obtain the electrochemical characteristics of the military lithium battery pack by the corresponding battery pack during the fast charging process; Step S242: Obtain the AC circuit connection structure between the battery pack and the internal resistance tester of the military lithium battery, and establish a mathematical relationship model between the battery internal resistance, polarization resistance and AC current and AC voltage based on the AC circuit connection structure and the corresponding electrochemical characteristics of the military lithium battery pack. Step S243: Use the AC voltage measured by the internal resistance of the military battery as the input to the mathematical relationship model, and separate the voltage components caused by the internal resistance and polarization resistance of the battery through Fourier transform and impedance calculation. Step S244: Calculate the AC impedance amplitude and phase angle required for the battery internal resistance to generate polarized AC based on the corresponding voltage components caused by the battery internal resistance and polarization resistance. Step S245: Based on the AC impedance amplitude and phase angle required to generate polarized AC based on the battery internal resistance, perform internal resistance polarized AC measurement on the injected AC current and the corresponding voltage component caused by the battery internal resistance to obtain the internal resistance of the military lithium battery.

[0009] Furthermore, step S3 includes the following steps: Step S31: Estimate the battery interference probability of the corresponding battery pack during fast charging based on the internal resistance of the military lithium battery to generate the interference probability of the military fast charging battery. Step S32: Based on the interference probability of military fast-charging batteries, perform battery health interval mapping on the corresponding battery pack during fast charging to obtain the battery pack health interval corresponding to military lithium batteries. Step S33: Calculate the trend of change of the internal resistance of the military lithium battery over a period of time using the moving average method to obtain the trend of change of the internal resistance of the military battery. Step S34: Based on the battery pack health range corresponding to the military lithium battery, assess the health status of the internal resistance change trend of the military battery to obtain the battery pack health status corresponding to the military lithium battery, including normal charging status and battery aging status.

[0010] Furthermore, step S31 includes the following steps: By acquiring the corresponding voltage, temperature, humidity, electromagnetic interference, charge / discharge cycles, internal chemical reaction rate, internal pulse ion migration characteristics, and electrode material stability characteristics of the battery pack during the fast charging process, a set of internal interference factors corresponding to the battery pack can be obtained. Based on the internal resistance of military lithium batteries, battery interference correlation mining is performed on the various interference factors in the battery internal interference factor set corresponding to the battery pack, in order to mine and analyze the potential correlation between battery internal resistance and various interference factors, as well as the interaction relationship between various interference factors. Based on the potential correlation between the battery internal resistance and various interference factors, as well as the interaction between various interference factors, an interference propagation network is constructed between the internal resistance of military lithium batteries and various interference factors within the set of internal interference factors. The internal resistance of military lithium batteries and various interference factors are regarded as nodes in the network, and the potential correlation and interaction are regarded as edges between nodes. At the same time, an initial occurrence probability value is assigned by considering the occurrence probability of each interference factor and its attenuation characteristics during propagation, so as to generate an interference correlation network between the battery internal resistance and various interference factors. Based on the interference correlation network between the battery internal resistance and various interference factors, the interference propagation path corresponding to the battery internal resistance is determined, and the battery interference probability is estimated based on the interference propagation path and the corresponding initial occurrence probability value on the path, so as to generate the interference probability of military fast charging battery.

[0011] Furthermore, the health status assessment in step S34 specifically means that if the internal resistance of the military battery continues to rise over a period of time and exceeds the corresponding battery pack health range, then the health status of the battery pack corresponding to the military lithium battery is determined to be that the battery is in an aging state; otherwise, it is determined to be in a normal charging state.

[0012] Furthermore, step S4 includes the following steps: Step S41: When the health status of the battery pack corresponding to the military lithium battery is determined to be normal charging state, the pulse current amplitude is adjusted to 60%-80% of the maximum charging current according to the rated capacity and charging time requirements of the battery pack corresponding to the military lithium battery, and the pulse frequency is adjusted to 500Hz-1000Hz. At the same time, the pulse current duty cycle is dynamically adjusted according to the charging stage of the battery pack. In the early stage of charging, the pulse current duty cycle can be set to 40%-50%, and when the remaining power is 90%-99% and it is about to be fully charged, the pulse current duty cycle is gradually reduced to 20%-30%, thus generating the pulse current control strategy corresponding to the normal charging state. Step S42: When the health status of the military lithium battery pack is determined to be that the battery is in an aging state, the pulse current amplitude is reduced by 20%-30% compared to the normal charging state to reduce the internal heat generation and polarization reaction of the battery pack. The pulse frequency is increased to 1.2-1.5 times that of the normal charging state to improve the ion transport efficiency inside the battery pack by using high-frequency pulses. The pulse current duty cycle is reduced to 70%-80% of the normal charging state through diffusion regulation between internal pulse ions. This generates the pulse current regulation strategy corresponding to the aging state of the battery.

[0013] Furthermore, the reduction of the pulse current duty cycle to 70%-80% of the normal charging state through diffusion regulation between internal pulse ions in step S42 includes the following steps: Obtain the internal pulse ion concentration, electrode spacing, and electrolyte conductivity of the battery pack in a military lithium battery. Ion diffusion analysis was performed on the internal pulse ions in the battery pack of military lithium batteries based on the internal pulse ion concentration, electrode spacing and electrolyte conductivity, so as to obtain the diffusion path, diffusion rate and diffusion direction of the internal pulse ions in the electrolyte. Based on the diffusion path, diffusion rate, and diffusion direction of the internal pulse ions in the electrolyte, the duty cycle of the corresponding pulse current is reduced to 70%-80% of that under normal charging conditions through diffusion regulation between the internal pulse ions.

[0014] The beneficial effects of this invention are: The pulse current regulation method for fast charging of military special power supplies proposed in this invention has the following advantages compared with the prior art: by accurately acquiring and regulating the pulse current beam during the fast charging process of military lithium batteries, the charging efficiency and battery life can be effectively improved. Compared with traditional continuous current, pulse current can reduce the heat accumulation inside the battery during charging, avoid battery overheating, and thus reduce the rate of battery degradation. Accurate calculation of the amplitude, frequency, and duty cycle of the pulse current can dynamically adjust according to different battery needs and states, ensuring that the battery is not only fast but also stable during charging. The fine control of these parameters can ensure that the battery is always in the optimal working state during fast charging, avoid battery damage caused by excessive current, and reduce the increase in battery internal resistance caused by overcharging. This allows the power supply to work more efficiently under different charging needs and minimizes energy loss. Secondly, precise internal resistance testing of the battery pack through internal resistance polarization AC measurement not only assesses energy loss during fast charging but also accurately predicts battery health and performance degradation. Battery internal resistance is a crucial factor affecting charging efficiency and battery performance, especially during fast charging, where increased internal resistance leads to higher battery temperature and longer charging time. Accurate internal resistance measurement provides key data for battery health management, enabling effective regulation and optimization during charging to prevent abnormal charging states. This ensures battery stability and safety during charging, avoiding safety hazards caused by excessive internal resistance, and enabling real-time monitoring and precise control of battery status. Furthermore, by estimating the interference probability based on battery internal resistance, the battery's operating status during charging can be monitored in real time, potential battery interference problems can be predicted, and abnormal situations can be identified in advance, thereby reducing risks and losses during charging. Meanwhile, the health interval mapping assessment can determine the specific health status of the battery by dynamically evaluating the battery pack status. By accurately identifying whether the battery is in a normal charging state or has already aged, it can help to take timely and targeted measures to ensure the stable operation of the battery pack. This can also avoid failures caused by battery performance degradation and ensure the long-term stable power supply of military lithium batteries in complex environments.Finally, by regulating the pulse current based on the battery pack's health status, optimized charging strategies can be implemented for different battery pack conditions. This regulation not only ensures the battery is in a safe and effective charging state but also flexibly adjusts the amplitude, frequency, and duty cycle of the pulse current according to the battery's different health conditions. For batteries in good health, a higher charging rate can be used to improve charging efficiency; while for aging batteries, the amplitude of the pulse current can be appropriately reduced and the corresponding frequency increased to extend the charging time and avoid putting excessive burden on the battery. This regulation strategy based on battery health status makes the charging process more intelligent and precise, maximizing battery life while maintaining high-efficiency charging performance. This allows for dynamic adjustment of the charging current according to the characteristics of the battery at different charging stages, thereby improving the charging efficiency of military lithium batteries. Attached Figure Description

[0015] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic flowchart of the pulse current regulation method for fast charging of military special power supplies according to the present invention. Figure 2 for Figure 1 A detailed flowchart of step S1; Figure 3 for Figure 2 A detailed flowchart of step S14. Detailed Implementation

[0016] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0017] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0018] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated items listed.

[0019] To achieve the above objectives, please refer to Figures 1 to 3 This invention provides a pulse current regulation method for fast charging of military special power supplies, the method comprising the following steps: Step S1: Obtain the pulse current beam corresponding to the military lithium battery during fast charging, and calculate the pulse control parameters based on the pulse current beam corresponding to the military lithium battery during fast charging to obtain the pulse current amplitude, pulse current frequency and pulse current duty cycle corresponding to the fast charging process. Step S2: Obtain the type, voltage level, and measurement accuracy requirements of the military lithium battery, and perform internal resistance polarization AC measurement on the corresponding battery pack during fast charging based on the type, voltage level, and measurement accuracy requirements of the military lithium battery to obtain the internal resistance of the military lithium battery. Step S3: Estimate the battery interference probability of the corresponding battery pack during fast charging based on the internal resistance of the military lithium battery to generate the interference probability of the military fast charging battery; perform a health interval mapping evaluation on the corresponding battery pack based on the interference probability of the military fast charging battery to obtain the health status of the battery pack corresponding to the military lithium battery, including the normal charging state and the aging state of the battery. Step S4: Based on the health status of the battery pack corresponding to the military lithium battery, perform pulse current regulation analysis on the pulse current amplitude, pulse current frequency and pulse current duty cycle corresponding to the pulse current beam during the fast charging process, and generate pulse current regulation strategies for the military lithium battery under different states.

[0020] In the embodiments of this invention, please refer to Figure 1 The diagram shown is a flowchart illustrating the steps of the pulse current regulation method for fast charging of a military special power supply according to the present invention. In this example, the pulse current regulation method for fast charging of a military special power supply includes the following steps: Step S1: Obtain the pulse current beam corresponding to the military lithium battery during fast charging, and calculate the pulse control parameters based on the pulse current beam corresponding to the military lithium battery during fast charging to obtain the pulse current amplitude, pulse current frequency and pulse current duty cycle corresponding to the fast charging process. In this embodiment of the invention, a current sensor is connected in series in the fast charging circuit of a military lithium battery. When a pulse current passes through, the sensor generates an induced current signal on the secondary side that is proportional to the primary side current, based on the principle of electromagnetic induction. This induced current signal is converted into a voltage signal suitable for measurement by a signal conditioning circuit and then transmitted to a data acquisition card. The data acquisition card samples the voltage signal at a sampling rate of 10kHz and transmits the sampled data to an industrial control computer. In the computer, a pre-written data analysis program processes the acquired pulse current beam data. By detecting the zero-crossing point of the pulse current signal, the start and end times of each pulse waveform are determined, and the pulse period is calculated. For example, if a pulse waveform starts at 0.001s and ends at 0.002s, the pulse period is 0.001s. Based on the pulse period, the maximum and minimum values ​​of the current signal within one pulse period are found, and the pulse current amplitude is calculated. For example, if the maximum value is 8A and the minimum value is 2A, the pulse current amplitude is 6A. At the same time, the pulse current frequency is obtained by calculating the number of pulse periods per unit time (e.g., 1 second). Assuming there are 1000 pulse periods in 1 second, the pulse current frequency is 1000Hz. The pulse current duty cycle is obtained by recording the time the pulse current is at a high level and the total pulse period, and calculating the ratio of the two. For example, if the high level time is 0.0006s, the pulse period is 0.001s, and the duty cycle is 60%, then the pulse current amplitude, frequency, and duty cycle during the fast charging process can be obtained.

[0021] Step S2: Obtain the type, voltage level, and measurement accuracy requirements of the military lithium battery, and perform internal resistance polarization AC measurement on the corresponding battery pack during fast charging based on the type, voltage level, and measurement accuracy requirements of the military lithium battery to obtain the internal resistance of the military lithium battery. In this embodiment of the invention, the corresponding type (e.g., lithium-ion battery pack power supply), voltage level (e.g., 24V), and measurement accuracy requirements (e.g., ±0.1mΩ) of the military lithium battery are obtained from its product manual, technical specifications, or built-in memory chip. An internal resistance tester with micro-ohm-level measurement accuracy and a wide voltage range (0-1000V) is selected. The positive and negative test leads of the internal resistance tester are securely connected to the positive and negative terminals of the battery pack during fast charging using dedicated alligator clips to ensure reliable connection. A control program is written on an industrial control computer to set the measurement parameters of the internal resistance tester according to the power supply type and voltage level. For example, for lithium-ion battery packs, a suitable AC injection current frequency range (1kHz-10kHz) is set. During the measurement cycle, when the battery pack is not in a charging / discharging state, the internal resistance tester is controlled to inject AC current (e.g., AC current with an injection frequency of 5kHz) into the battery pack and the AC voltage response at the corresponding terminals of the battery pack is measured. According to Ohm's law, the internal resistance of the military lithium battery is calculated using the injected AC current and the measured AC voltage. Assuming the injected AC current is 1A and the measured AC voltage is 0.5V, then the battery internal resistance is 0.5Ω.

[0022] Step S3: Estimate the battery interference probability of the corresponding battery pack during fast charging based on the internal resistance of the military lithium battery to generate the interference probability of the military fast charging battery; perform a health interval mapping evaluation on the corresponding battery pack based on the interference probability of the military fast charging battery to obtain the health status of the battery pack corresponding to the military lithium battery, including the normal charging state and the aging state of the battery. In this embodiment of the invention, a pre-built database of the relationship between battery internal resistance and interference probability is used. This database is accumulated from a large amount of experimental data and covers the probability statistics of interference of different types of military batteries under various internal resistance states. A query program is written on an industrial control computer, using the previously obtained internal resistance of military lithium batteries (assumed to be 0.5Ω) as the query condition, and performs precise matching in the database. If there is no completely matching internal resistance value in the database, the interference probability is estimated by linear interpolation. For example, if the database records an interference probability of 10% for an internal resistance of 0.4Ω and an interference probability of 20% for an internal resistance of 0.6Ω, the interference probability corresponding to an internal resistance of 0.5Ω can be calculated to be approximately 15%. This generates the interference probability of military fast-charging batteries. Using professional battery health assessment software, such as BatteryLifePro, the relevant parameters such as battery type and fast charging mode are set in the software, and the generated interference probability of military fast-charging batteries is imported. The software maps the interference probability to the corresponding battery health range according to the built-in health assessment model, thereby determining the health status of the battery pack. For example, when the interference probability is in the range of 10%-20%, the corresponding battery pack health status is "normal, with possible slight aging". If the interference probability is less than 10%, the health status is "normal charging status".

[0023] Step S4: Based on the health status of the battery pack corresponding to the military lithium battery, perform pulse current regulation analysis on the pulse current amplitude, pulse current frequency and pulse current duty cycle corresponding to the pulse current beam during the fast charging process, and generate pulse current regulation strategies for the military lithium battery under different states.

[0024] In this embodiment of the invention, by writing a pulse current regulation and analysis program on an industrial control computer, when the health state of the battery pack corresponding to the military lithium battery is determined to be in a normal charging state, a suitable pulse current amplitude range is calculated based on the rated capacity of the battery pack (e.g., 50Ah) and the charging time requirement (e.g., charging to be completed within 2 hours). Assuming the maximum charging current of the battery pack is 10A, the pulse current amplitude is regulated between 6A (10A×60%) and 8A (10A×80%). The corresponding amplitude parameters are set in the pulse current regulation device (e.g., a programmable power controller). For the pulse frequency, it is set in the range of 500Hz-1000Hz, such as 800Hz. The pulse current duty cycle is determined according to the charging... The charging process is dynamically adjusted during the charging phase. Initially, the current is set at 40%-50%, such as 45%. As the battery approaches full charge, it gradually decreases to 20%-30%, and when the remaining charge reaches 90%, it's adjusted to 25%. When the battery pack is in an aging state, to reduce heat generation and polarization, the pulse current amplitude is reduced. For example, if the normal amplitude is 7A, it's reduced by 20%-30% to 5.2A. The pulse frequency is increased to 1.2-1.5 times the normal frequency; assuming a normal frequency of 800Hz, it's adjusted to 1000Hz. The pulse current duty cycle is determined using professional electrochemical testing equipment to obtain the internal pulse ion concentration, electrode spacing, and electrolyte conductivity of the battery pack. Ion diffusion analysis is performed using computational chemistry software Materials Studio. Based on the diffusion path, speed, and direction, the duty cycle is reduced to 70%-80% of the normal charging state using a pulse current control device. For example, if the initial normal duty cycle is 45%, it's adjusted to 33%. This generates the pulse current control strategy for military lithium batteries under different states.

[0025] Furthermore, step S1 includes the following steps: Step S11: Obtain the pulse current beam corresponding to the military lithium battery during fast charging; Step S12: Perform high-frequency noise filtering on the pulse current beam corresponding to the military lithium battery during fast charging, and apply adaptive filtering to adjust the corresponding filtering parameters to remove high-frequency noise and random noise in the pulse current beam, and generate a pulse current beam after high-frequency noise reduction. Step S13: Perform low-frequency sliding filtering on the pulse current beam after high-frequency noise reduction. By setting a sliding window with a window size of 5, and using the sliding average filtering of the low-frequency noise corresponding to the pulse current beam after high-frequency noise reduction according to the sliding window, a smoothed pulse current beam is obtained. Step S14: Calculate the pulse control parameters based on the smoothed and filtered pulse current beam to obtain the pulse current amplitude, pulse current frequency, and pulse current duty cycle during the fast charging process.

[0026] As an embodiment of the present invention, reference Figure 2 As shown, Figure 1 A detailed flowchart of step S1 is shown below. In this embodiment, step S1 includes the following steps: Step S11: Obtain the pulse current beam corresponding to the military lithium battery during fast charging; In this embodiment of the invention, a current sensor is used in the charging circuit of a military lithium battery to acquire the pulse current beam corresponding to the fast charging process. The current sensor is connected in series in the charging circuit, and the pulse current passes through its primary side wire. According to the principle of electromagnetic induction, an induced current signal proportional to the primary side current is generated on the secondary side. This induced current signal is converted into a voltage signal suitable for subsequent processing by a signal conditioning circuit and then transmitted to a data acquisition device. The data acquisition device samples the voltage signal at a high sampling rate (e.g., 10kHz) and stores the sampled data in a local hard disk, thereby acquiring a complete pulse current beam and providing raw material for subsequent signal processing.

[0027] Step S12: Perform high-frequency noise filtering on the pulse current beam corresponding to the military lithium battery during fast charging, and apply adaptive filtering to adjust the corresponding filtering parameters to remove high-frequency noise and random noise in the pulse current beam, and generate a pulse current beam after high-frequency noise reduction. In this embodiment of the invention, an adaptive filtering algorithm (such as the Least Mean Square (LMS) algorithm) combined with a digital signal processor (DSP) is used to filter high-frequency noise in the pulse current beam corresponding to the fast charging process of a military lithium battery. The collected pulse current beam data is input into the DSP, and a filtering program based on the LMS algorithm is written in the DSP. The LMS algorithm continuously adjusts the filter coefficients to minimize the mean square error between the filter output and the desired signal. In actual operation, a reference signal (usually a clean DC signal or a known low-frequency signal) is set, and the pulse current beam signal is compared with the reference signal. For example, when high-frequency noise exists in the pulse current beam, the LMS algorithm automatically adjusts the filter coefficients based on the error between the two to remove high-frequency noise and random noise. Through continuous iterative calculation, the filtering parameters are continuously optimized, and finally, a pulse current beam after high-frequency noise reduction is generated. For example, if the original pulse current beam contains high-frequency noise at a frequency of 100kHz, after filtering by the LMS algorithm, the high-frequency noise is effectively suppressed, and the pulse current beam becomes smoother.

[0028] Step S13: Perform low-frequency sliding filtering on the pulse current beam after high-frequency noise reduction. By setting a sliding window with a window size of 5, and using the sliding average filtering of the low-frequency noise corresponding to the pulse current beam after high-frequency noise reduction according to the sliding window, a smoothed pulse current beam is obtained. In this embodiment of the invention, a low-frequency sliding filter is performed on the pulse current beam after high-frequency noise reduction using a microcontroller (such as an STM32F407 microcontroller) and its internal computing resources. A sliding filter program is written in the microcontroller, setting a sliding window of size 5. For the pulse current beam data after high-frequency noise reduction, every 5 consecutive data points are sequentially placed into the sliding window. For example, assuming the pulse current beam data after high-frequency noise reduction is [1.2A, 1.3A, 1.4A, 1.1A, 1.5A, 1.3A…], the first 5 data points [1.2A, 1.3A, 1.4A, 1.1A,…] are first placed into the sliding window. 1.5A is placed into a sliding window. The microcontroller sums the data in the window and divides it by the window size of 5 to obtain the moving average, i.e., (1.2+1.3+1.4+1.1+1.5)÷5=1.3A. Then the sliding window moves one data point backward, and the new data point 1.3A is included in the window, while the earliest data point 1.2A is removed. The moving average is calculated again. In this way, the low-frequency noise corresponding to the pulse current beam after high-frequency noise reduction is filtered by moving average, and finally the pulse current beam after smoothing is obtained, which further improves the stability of the signal.

[0029] Step S14: Calculate the pulse control parameters based on the smoothed and filtered pulse current beam to obtain the pulse current amplitude, pulse current frequency, and pulse current duty cycle during the fast charging process.

[0030] In this embodiment of the invention, by utilizing the aforementioned signal processing circuit, microcontroller, and data acquisition card, pulse control parameters are calculated based on the smoothed and filtered pulse current beam. First, the smoothed and filtered pulse current beam is processed by a dedicated signal processing circuit. A comparator and microcontroller determine the zero-crossing point of the pulse current signal, thereby determining the start and end times of each waveform. The pulse period is obtained by calculating the difference between the start and end times. For example, if a pulse waveform starts at 10ms and ends at 15ms, the pulse period is 5ms. The data acquisition card samples the pulse current signal at a sampling rate several times higher than the pulse frequency. The microcontroller finds the maximum and minimum values ​​of the sampled data within each pulse period and calculates the pulse amplitude. For example, if the maximum value is 1.8A and the minimum value is 1.2A, the pulse amplitude is 1.8A - 1.2A = 0.6A. The microcontroller's counting program is set to a unit time of 1 second to count the pulse cycles. If 200 pulse cycles are recorded within 1 second, the pulse current frequency is 200Hz. Using the microcontroller and data acquisition card, the high-level state is determined based on the positive or negative sign of the pulse current signal. The duration of the high level is recorded, and the duty cycle is calculated. For example, if the total time of one pulse cycle is 5ms and the high-level duration is 3ms, the duty cycle is 3ms ÷ 5ms × 100% = 60%. This provides the pulse current amplitude, pulse current frequency, and pulse current duty cycle corresponding to the fast charging process, providing key parameters for precise control of the pulse current.

[0031] Furthermore, step S14 includes the following steps: Step S141: Obtain the zero-crossing point of the corresponding pulse current signal through the smoothed pulse current beam, and determine the start and end times of each waveform in the smoothed pulse current beam based on the zero-crossing point of the pulse current signal. Step S142: Estimate the pulse period based on the start and end times of each waveform in the pulse current beam to obtain the pulse period corresponding to the pulse current beam. Step S143: Obtain the maximum and minimum values ​​of the pulse current signal corresponding to each pulse period of the pulse current beam, and calculate the pulse amplitude based on the maximum and minimum values ​​of the pulse current signal to obtain the pulse current amplitude corresponding to the fast charging process. Step S144: Calculate the number of pulse cycles per unit time using the pulse cycle corresponding to the pulse current beam as the frequency, so as to obtain the pulse current frequency corresponding to the fast charging process. Step S145: Obtain the high-level time of the pulse current beam within one pulse period and the total time of the entire period by using the pulse period corresponding to the pulse current beam. Calculate the corresponding duty cycle based on the ratio between the high-level time and the total time of the entire period to obtain the corresponding pulse current duty cycle during the fast charging process.

[0032] As an embodiment of the present invention, reference Figure 3 As shown, Figure 2 A detailed flowchart of step S14 is shown in this embodiment. Step S14 includes the following steps: Step S141: Obtain the zero-crossing point of the corresponding pulse current signal through the smoothed pulse current beam, and determine the start and end times of each waveform in the smoothed pulse current beam based on the zero-crossing point of the pulse current signal. In this embodiment of the invention, a dedicated signal processing circuit is used to process the smoothed and filtered pulse current beam. This circuit includes components such as comparators. The pulse current signal is input into the comparator and compared with a reference voltage (usually set to 0V). When the pulse current signal changes from a positive value to a negative value or from a negative value to a positive value, a zero-crossing occurs, and the comparator outputs a transition signal. The microcontroller (such as the STM32 series) detects the transition signal output by the comparator and records the time of each transition using its internal timer. For example, at a certain moment, the pulse current signal changes from a positive value to a negative value after passing through 0V, the comparator outputs a transition signal, the microcontroller detects the signal and records the time at that moment. This time is the zero-crossing point of the pulse current signal. By continuously monitoring the transition signal, the start and end times of each waveform in the smoothed and filtered pulse current beam are determined. If a pulse waveform starts from the positive half-cycle, the time recorded when the first zero-crossing point is detected is the start time, and the time recorded when the next zero-crossing point is detected (from the negative half-cycle back to the positive half-cycle) is the end time.

[0033] Step S142: Estimate the pulse period based on the start and end times of each waveform in the pulse current beam to obtain the pulse period corresponding to the pulse current beam. In this embodiment of the invention, the pulse period is estimated by using the calculation program in the microcontroller based on the start and end times of each waveform in the pulse current beam. Taking the STM32 microcontroller as an example, the start time T1 and end time T2 recorded by its timer are used to calculate the duration of a single pulse waveform by calculating T2-T1. For example, if the start time T1 of a pulse waveform is 10ms and the end time T2 is 15ms, then the duration of the pulse waveform is 5ms. For multiple consecutive pulse waveforms, the above operation is repeated to calculate the duration of each pulse waveform. Then, the average of these durations is calculated to obtain the pulse period corresponding to the pulse current beam. Assuming that 10 pulse waveforms are measured continuously, and their durations are 5ms, 5.2ms, 4.9ms, etc., these times are added together and divided by 10 to obtain the average duration, i.e., the pulse period. Finally, the pulse period corresponding to the pulse current beam is obtained.

[0034] Step S143: Obtain the maximum and minimum values ​​of the pulse current signal corresponding to each pulse period of the pulse current beam, and calculate the pulse amplitude based on the maximum and minimum values ​​of the pulse current signal to obtain the pulse current amplitude corresponding to the fast charging process. In this embodiment of the invention, by using a data acquisition card and a microcontroller, the maximum and minimum values ​​of the pulse current signal corresponding to each pulse period of the pulse current beam are obtained. The data acquisition card samples the pulse current signal at a sampling rate several times higher than the pulse frequency and transmits the sampled data to the microcontroller. Within each pulse period, the microcontroller iterates through the sampled data to find the maximum and minimum values. For example, within one pulse period, the pulse current signal data acquired by the data acquisition card is [1.2A, 1.5A, 1.3A, 1.8A...]. The microcontroller iterates through these data, finds the maximum value of 1.8A and the minimum value of 1.2A, and then calculates the pulse amplitude based on the maximum and minimum values ​​of the pulse current signal. Using the formula: Pulse amplitude = maximum value - minimum value, the pulse current amplitude corresponding to the fast charging process is finally obtained, i.e., 1.8A - 1.2A = 0.6A.

[0035] Step S144: Calculate the number of pulse cycles per unit time using the pulse cycle corresponding to the pulse current beam as the frequency, so as to obtain the pulse current frequency corresponding to the fast charging process. In this embodiment of the invention, the counting program in the microcontroller calculates the number of pulse cycles per unit time as the frequency based on the pulse period corresponding to the pulse current beam. For example, if the unit time is set to 1 second, the microcontroller's timer counts the pulse cycles. When a pulse cycle begins, the timer starts counting, and the count increments by 1 after each pulse cycle is completed. At the end of 1 second, the timer's count value is read, which is the number of pulse cycles in 1 second. Assuming that the timer records 200 pulse cycles in 1 second, the corresponding pulse current frequency during the fast charging process is 200Hz. In this way, the pulse current frequency is accurately calculated, providing key parameters for subsequent pulse current regulation.

[0036] Step S145: Obtain the high-level time of the pulse current beam within one pulse period and the total time of the entire period by using the pulse period corresponding to the pulse current beam. Calculate the corresponding duty cycle based on the ratio between the high-level time and the total time of the entire period to obtain the corresponding pulse current duty cycle during the fast charging process.

[0037] In this embodiment of the invention, a microcontroller and a data acquisition card are used to obtain the high-level time of the pulse current beam within one pulse cycle and the total time of the entire cycle by using the pulse cycle corresponding to the pulse current beam. The corresponding duty cycle is calculated based on the ratio between the high-level time and the total time of the entire cycle. The data acquisition card continuously collects the pulse current signal, and the microcontroller determines whether it is in a high-level or low-level state based on the positive or negative value of the pulse current signal. Within one pulse cycle, when the pulse current signal is positive, it is considered to be in a high-level state. A timer is used to record the duration of the high level. For example, if the total time of one pulse cycle is 5ms, the high-level duration is 3ms. Then, according to the formula: Duty Cycle = High-level time ÷ Total cycle time × 100%, the duty cycle is calculated to be 3ms ÷ 5ms × 100% = 60%, thus obtaining the pulse current duty cycle corresponding to the fast charging process, providing an important basis for precise control of the pulse current.

[0038] Furthermore, step S2 includes the following steps: Step S21: Obtain the type, voltage level, and measurement accuracy requirements of the military lithium battery; In this embodiment of the invention, the type, voltage level, and measurement accuracy requirements of the military-grade lithium battery are obtained from its technical documentation, product manual, or internal storage chip. For example, for a certain model of military-grade lithium battery, the technical documentation clearly indicates that the type is a lithium-ion battery pack power supply, the voltage level is 24V, and the measurement accuracy requirement is at the micro-ohm level, such as ±0.1mΩ. This information is then read from the power supply's storage chip interface using a dedicated data reading device, such as an industrial-grade USB data reader, according to a specific data protocol, and transmitted to a control terminal, such as an industrial tablet PC, for use in subsequent steps.

[0039] Step S22: Select an internal resistance tester with micro-ohm level measurement accuracy, adaptability to a wide voltage range including 0-1000V, and anti-interference capability according to the type, voltage level, and measurement accuracy requirements of the military lithium battery, and establish a reliable connection between the positive and negative test lines of the internal resistance tester and the positive and negative terminals of the battery pack during the fast charging process. In this embodiment of the invention, based on the obtained parameters of the military lithium battery, a corresponding internal resistance tester is selected. This tester has micro-ohm-level measurement accuracy, can adapt to a wide voltage range of 0-1000V, and has good anti-interference performance. The internal resistance tester is placed on a stable workbench close to the military lithium battery pack, ensuring good grounding. Matching positive and negative test leads are used. The test leads use high-purity copper cores to reduce resistance and have good insulation. One end of the positive test lead is firmly connected to the positive output port of the internal resistance tester, and the other end is tightly clamped to the positive terminal of the battery pack during fast charging using a special alligator clip, ensuring good contact and no loosening or oxide layer affecting conductivity. Similarly, the negative test lead is connected to the negative output port of the internal resistance tester and the negative terminal of the battery pack in the same way to establish a reliable electrical connection, preparing for subsequent measurements.

[0040] Step S23: Obtain the usage frequency corresponding to the military lithium battery, set the corresponding measurement cycle according to the usage frequency corresponding to the military lithium battery, and inject an AC current between 1kHz and 10kHz into the battery pack by starting the positive and negative terminals of the internal resistance tester when the battery pack is not charging or discharging within the corresponding measurement cycle, and measure the AC voltage response at the corresponding terminals to generate the AC voltage for measuring the internal resistance of the military battery. In this embodiment of the invention, the corresponding operating frequency information of the military lithium battery is obtained from its user manual or control system. Assuming the operating frequency of the power supply is 50Hz, the measurement cycle is set based on this frequency. Since the power supply experiences charging and discharging fluctuations during use, to ensure measurement accuracy, the measurement is performed when the battery pack is in a non-charging / discharging state. A control program is written, and a timer is set on the industrial tablet PC. Based on the power supply's operating frequency, the measurement cycle is set to 20ms (1÷50Hz=20ms). Within each measurement cycle, the timer triggers the internal resistance tester. When the battery pack is detected to be in a non-charging / discharging state, the positive and negative terminals of the internal resistance tester inject an AC current with a frequency between 1kHz and 10kHz into the battery pack, for example, an AC current with a frequency of 5kHz. Simultaneously, the internal resistance tester measures the AC voltage response at the corresponding terminals of the battery pack. If the measured AC voltage is 0.5V, this measurement data is transmitted to the industrial tablet PC and recorded, generating the military battery internal resistance measurement AC voltage.

[0041] Step S24: Based on the injected AC current and the AC voltage of the military battery internal resistance measurement, perform AC polarization measurement on the corresponding battery pack during the fast charging process to obtain the internal resistance of the military lithium battery.

[0042] In this embodiment of the invention, AC voltage is measured based on the injected AC current and the measured internal resistance of the military battery. Ohm's law is used to perform polarized AC measurement calculations of the internal resistance on an industrial tablet computer. Given that the injected AC current is I (e.g., 1A) and the measured AC voltage is U (e.g., 0.5V), the internal resistance of the battery pack is calculated as R = U÷I = 0.5V÷1A = 0.5Ω according to the formula R = U÷I. Considering the measurement accuracy of the internal resistance tester and potential interference factors, statistical analysis is performed on multiple measurement data, such as 10 consecutive measurements to obtain 10 calculated internal resistance values. Then, the average, standard deviation, and other statistical quantities of these values ​​are calculated to improve measurement accuracy. Finally, the accurate internal resistance of the military lithium battery is obtained. For example, after statistical analysis, the internal resistance of the military lithium battery is determined to be 0.495Ω, providing an important basis for subsequent pulse current regulation and power supply performance evaluation.

[0043] Furthermore, step S24 includes the following steps: Step S241: Obtain the electrochemical characteristics of the military lithium battery pack by the corresponding battery pack during the fast charging process; In this embodiment of the invention, the electrochemical characteristics of the battery pack during the fast charging process are tested using specialized electrochemical testing equipment. The working electrode, reference electrode, and counter electrode of the electrochemical workstation are connected to the positive and negative electrodes of the battery pack and their corresponding test points in a prescribed manner. Various electrochemical tests, such as open-circuit potential testing and cyclic voltammetry testing, are performed using the workstation's built-in testing program. For example, in the open-circuit potential test, the change in the open-circuit potential of the battery pack at different time points is recorded, reflecting the thermodynamic characteristics of its electrode reactions. In the cyclic voltammetry test, a triangular wave voltage with a specific voltage scan rate is applied to obtain the current-voltage curve. The redox reaction characteristics and electrode reaction kinetic parameters of the battery pack are analyzed from the curve. These test data are then processed and analyzed to ultimately obtain the electrochemical characteristics corresponding to the military-grade lithium battery pack, such as the battery's electrode reaction activation energy and diffusion coefficient.

[0044] Step S242: Obtain the AC circuit connection structure between the battery pack and the internal resistance tester of the military lithium battery, and establish a mathematical relationship model between the battery internal resistance, polarization resistance and AC current and AC voltage based on the AC circuit connection structure and the corresponding electrochemical characteristics of the military lithium battery pack. In this embodiment of the invention, the AC circuit connection structure between the battery pack and the internal resistance tester of the military lithium battery is obtained by using circuit analysis software such as Multisim. The actual circuit connection, including the output port of the internal resistance tester, positive and negative test lines, and positive and negative terminals of the battery pack, is built in Multisim software according to the same topology. Based on the basic principles of AC circuits and combined with the electrochemical characteristics of the military lithium battery pack, such as the equivalent circuit model of electrode reactions (including battery internal resistance, polarization resistance, etc.), Kirchhoff's laws and Ohm's law are used to establish a mathematical relationship model between battery internal resistance (Rb), polarization resistance (Rp), AC current (I), and AC voltage (U). For example, for a simple equivalent circuit model, the following relationship can be established: U = I * (Rb + Rp) + voltage components caused by other electrochemical polarization (determined according to specific electrochemical characteristics), providing a theoretical basis for subsequent data processing and internal resistance calculation.

[0045] Step S243: Use the AC voltage measured by the internal resistance of the military battery as the input to the mathematical relationship model, and separate the voltage components caused by the internal resistance and polarization resistance of the battery through Fourier transform and impedance calculation. In this embodiment of the invention, by installing professional signal analysis software, such as MATLAB, on an industrial tablet computer, the previously measured AC voltage data of the internal resistance of the military battery is imported into the MATLAB software. Using the Fourier transform function in MATLAB's signal processing toolbox, the AC voltage signal is Fourier transformed, converting the time-domain signal into a frequency-domain signal. By analyzing the spectral characteristics of the frequency-domain signal and combining it with the impedance calculation formula of the AC circuit (Z=U / I), the voltage components caused by the battery internal resistance and polarization resistance are separated according to the voltage and current relationship at different frequencies. For example, at a specific frequency, based on the AC circuit model and the spectrum data after the Fourier transform, the voltage component Urb caused by the battery internal resistance and the voltage component Urp caused by the polarization resistance are calculated. For the AC circuit, the AC voltage U, AC current I, battery internal resistance Rb, and polarization resistance Rp are known, and the total impedance Z=Rb+Rp (ignoring the influence of other reactances), according to Ohm's law U=I×Z. After performing a Fourier transform on the measured AC voltage U, the voltage signal is decomposed into different frequency components. At a specific frequency, by analyzing the contribution of different components in the AC circuit model to the voltage, and using the impedance calculation formula Z=U / I, combined with the known injected AC current I and the voltage response U at that frequency, Urb and Urp are calculated separately in the following way: Assuming that the total impedance of the AC circuit at a certain frequency is Z_total, Z_total=U / I can be calculated based on the measured AC voltage U and injected AC current I. Since the total impedance Z_total=Rb+Rp, let the impedance corresponding to the battery internal resistance Rb be Zrb, and the impedance corresponding to the polarization resistance Rp be Zrp, and Z_total=Zrb+Zrp. At this frequency, according to the relationship between resistance and impedance in the AC circuit, the voltage component Urb caused by the battery internal resistance is Urb=I×Zrb, and the voltage component Urp caused by the polarization resistance is Urp=I×Zrp, providing data support for subsequent calculation of AC impedance amplitude and phase angle.

[0046] Step S244: Calculate the AC impedance amplitude and phase angle required for the battery internal resistance to generate polarized AC based on the corresponding voltage components caused by the battery internal resistance and polarization resistance. In this embodiment of the invention, based on the previously separated voltage components caused by the battery's internal resistance and polarization resistance, a calculation program is written in MATLAB software to calculate the AC impedance amplitude (|Z|) and phase angle (θ) required for the battery's internal resistance to generate polarized AC, according to the impedance definition of an AC circuit. The formula for calculating the AC impedance amplitude is |Z| = The phase angle is calculated using the formula θ = arctan(Urp / Urb). Assuming the injected AC current I is 1A, the voltage component Urb caused by the isolated battery internal resistance is 0.3V, and the voltage component Urp caused by the polarization resistance is 0.4V, then the AC impedance amplitude |Z| = = 0.5Ω, phase angle θ = arctan (0.4 / 0.3) ≈ 53.13°. These key parameters are obtained through precise calculation and are used to accurately analyze the internal resistance polarization of the battery.

[0047] Step S245: Based on the AC impedance amplitude and phase angle required to generate polarized AC based on the battery internal resistance, perform internal resistance polarized AC measurement on the injected AC current and the corresponding voltage component caused by the battery internal resistance to obtain the internal resistance of the military lithium battery.

[0048] In this embodiment of the invention, a calculation program running on an industrial tablet PC is used to measure the internal resistance polarization AC based on the AC impedance amplitude and phase angle required to generate polarization AC based on the battery's internal resistance. This measurement is performed on the injected AC current and the corresponding voltage component caused by the battery's internal resistance to obtain the internal resistance of the military lithium battery. According to Ohm's law and phase relationship of AC circuits, combined with the previously established mathematical relationship model, the calculation parameters are gradually adjusted through iterative calculation to make the calculation results more accurate. For example, through multiple iterative calculations, considering factors such as the frequency change of AC current and the mutual influence of battery internal resistance and polarization resistance, the internal resistance R of the battery pack is calculated according to the formula R = U÷I. Considering the measurement accuracy of the internal resistance tester and possible interference factors, statistical analysis is performed on the multiple measurement data. For example, 10 consecutive measurements are taken to obtain 10 internal resistance calculation values. Then, the average value, standard deviation, and other statistical quantities of these values ​​are calculated to finally obtain the accurate internal resistance of the military lithium battery. Assuming that after multiple iterative calculations, the internal resistance of the military lithium battery is determined to be 0.48Ω, this provides accurate battery internal resistance data for subsequent pulse current regulation, so as to achieve a more efficient and stable fast charging process.

[0049] Furthermore, step S3 includes the following steps: Step S31: Estimate the battery interference probability of the corresponding battery pack during fast charging based on the internal resistance of the military lithium battery to generate the interference probability of the military fast charging battery. In this embodiment of the invention, a pre-built database of the relationship between battery internal resistance and interference probability is used to estimate the battery interference probability of the corresponding battery pack during fast charging based on the internal resistance of military lithium batteries. This database is accumulated from a large amount of experimental data and covers the probability statistics of interference of different types of military batteries under various internal resistance states. For example, for a specific model of lithium-ion battery pack, when the internal resistance is in the range of 0.4-0.5Ω, the probability of charging interference is 15%. A query program is written on an industrial tablet computer, and the previously obtained internal resistance of military lithium batteries (assumed to be 0.48Ω) is used as the query condition to perform precise matching in the database. If there is no completely matching internal resistance value in the database, the interference probability is estimated by linear interpolation. For example, if the database records that the interference probability is 10% when the internal resistance is 0.4Ω and 20% when the internal resistance is 0.5Ω, the interference probability corresponding to the internal resistance of 0.48Ω can be calculated by linear interpolation to be approximately 18%, thereby generating the interference probability of military fast charging batteries.

[0050] Step S32: Based on the interference probability of military fast-charging batteries, perform battery health interval mapping on the corresponding battery pack during fast charging to obtain the battery pack health interval corresponding to military lithium batteries. In this embodiment of the invention, professional battery health assessment software, such as BatteryLifePro, is used to map the battery health range of the corresponding battery pack during fast charging based on the interference probability of military fast-charging batteries. This yields the battery pack health range corresponding to the military lithium battery. The software incorporates multiple battery health assessment models, using the interference probability as a key input parameter. The software sets relevant parameters such as battery type (e.g., lithium-ion battery) and fast charging mode, and imports the previously generated interference probability of the military fast-charging battery (e.g., 18%). Based on the built-in models, the software maps the interference probability to the corresponding battery health range. For example, when the interference probability is in the range of 10%-20%, the corresponding battery health range is "good-average". By analyzing the correlation between the interference probability and the battery health status, combined with extensive experimental data and theoretical models, the software determines the battery pack health range, providing a foundation for subsequent health status assessments. Step S33: Calculate the trend of change of the internal resistance of the military lithium battery over a period of time using the moving average method to obtain the trend of change of the internal resistance of the military battery. In this embodiment of the invention, the internal resistance of a military lithium battery is calculated over a period of time using the Python programming language and the pandas library. Assuming that the internal resistance of the military lithium battery was measured every hour over the past week, a total of 168 internal resistance data points were obtained. These data were organized into time series data and stored in a pandas DataFrame structure. By setting the moving average window size, such as 12 (representing 12 hours), the pandas rolling function was used to calculate the moving average. For example, for the 13th data point, the average of the previous 12 data points was calculated as the moving average for that point. By iterating through all data points, a series of moving averages were obtained. These moving averages constitute the changing trend of the military battery's internal resistance over a period of time. The calculation results were plotted as a line graph to visually display the change in internal resistance over time, allowing for analysis of its changing trend, such as observing a gradual increase or stabilization of the internal resistance.

[0051] Step S34: Based on the battery pack health range corresponding to the military lithium battery, assess the health status of the internal resistance change trend of the military battery to obtain the battery pack health status corresponding to the military lithium battery, including normal charging status and battery aging status.

[0052] In this embodiment of the invention, by utilizing pre-set battery health status assessment rules, the health status of military lithium batteries is assessed based on the battery pack health range corresponding to the military battery, and an assessment program is written on an industrial tablet computer. The previously obtained battery pack health range (e.g., "Good-Average") and the previously obtained internal resistance change trend of the military battery (e.g., internal resistance gradually increasing) are used as inputs. For example, if the battery pack health range is "Good-Average" and the internal resistance change trend is gradually increasing beyond a certain threshold (e.g., the internal resistance increase exceeds 10% within one month), the battery pack is determined to be in an aging state according to the assessment rules. If the battery pack health range is "Good" and the internal resistance change trend remains relatively stable, the battery pack is determined to be in a normal charging state. By comparing the health range and internal resistance change trend with the preset rules, the health status of the military lithium battery corresponding to the battery pack is accurately assessed, providing an important basis for subsequent pulse current regulation and ensuring the safety and stability of the fast charging process.

[0053] Furthermore, step S31 includes the following steps: By acquiring the corresponding voltage, temperature, humidity, electromagnetic interference, charge / discharge cycles, internal chemical reaction rate, internal pulse ion migration characteristics, and electrode material stability characteristics of the battery pack during the fast charging process, a set of internal interference factors corresponding to the battery pack can be obtained. In this embodiment of the invention, multiple sensors are used to collect data on the battery pack during the fast charging process to obtain corresponding voltage, temperature, humidity, electromagnetic interference, charge / discharge cycles, internal chemical reaction rate, internal pulse ion migration characteristics, and electrode material stability characteristics. High-precision voltage sensors are connected to the positive and negative terminals of the battery pack to monitor voltage changes in real time. A thermistor temperature sensor is installed on the battery casing to measure battery temperature. A humidity sensor monitors ambient humidity, and an electromagnetic interference tester is used to detect the intensity of electromagnetic interference around the battery pack. The number of charge / discharge cycles is recorded through the battery management system (BMS). For the internal chemical reaction rate, specific electrochemical testing methods, such as chronoamperometry, are used to measure the change of current over time to estimate the chemical reaction rate. Electrochemical impedance spectroscopy (EIS) is used with a frequency response analyzer to analyze the internal pulse ion migration characteristics. X-ray diffraction (XRD) is used to detect changes in the crystal structure of the electrode materials and evaluate the stability characteristics of the electrode materials. The data collected by these sensors and devices are organized to form a set of internal interference factors of the battery.

[0054] Preferably, based on the internal resistance of military lithium batteries, battery interference correlation mining is performed on each interference factor in the battery internal interference factor set corresponding to the battery pack, so as to mine and analyze the potential correlation between battery internal resistance and each interference factor, as well as the interaction relationship between each interference factor. In this embodiment of the invention, a data mining algorithm, such as the Apriori association rule mining algorithm, is used on an industrial tablet PC to perform battery interference correlation mining on the various interference factors within the battery internal interference factor set corresponding to the battery pack, based on the internal resistance of military lithium batteries. The previously obtained internal resistance data of military lithium batteries and the collected internal interference factor data of batteries are organized into a transaction dataset. For example, internal resistance data, voltage data, temperature data, etc., are arranged into records in chronological order. In the Python environment, the Apriori algorithm is implemented using the apyori library, and minimum support and minimum confidence are set, such as minimum support set to 0.2 and minimum confidence set to 0.5. The algorithm scans the transaction dataset to mine the potential correlation between battery internal resistance and various interference factors, as well as the interaction relationships between various interference factors. For example, it is found that when the battery internal resistance exceeds 0.5Ω, there is a 60% probability that the battery temperature will rise above 30°C, and when the battery temperature rises, there is a 70% probability that the internal chemical reaction rate of the battery will accelerate. This clarifies the correlation between various factors, and finally obtains the potential correlation between battery internal resistance and various interference factors, as well as the interaction relationships between various interference factors.

[0055] Preferably, based on the potential correlation between the battery internal resistance and various interference factors, as well as the interaction relationship between various interference factors, an interference propagation network is constructed between the internal resistance of the military lithium battery and various interference factors in the set of internal interference factors of the battery. The internal resistance of the military lithium battery and various interference factors are regarded as nodes in the network, and the potential correlation and interaction relationship are regarded as edges between nodes. At the same time, an initial occurrence probability value is assigned by considering the occurrence probability of each interference factor and its attenuation characteristics during propagation, so as to generate an interference correlation network between the battery internal resistance and various interference factors. In this embodiment of the invention, network analysis software, such as Gephi, is used to construct an interference propagation network between the internal resistance of the military lithium battery and various interference factors, based on the potential correlation between the battery's internal resistance and various interference factors, as well as the interaction relationships between these interference factors. In Gephi, the internal resistance of the military lithium battery and various interference factors are considered as nodes in the network. For example, the battery's internal resistance, voltage, temperature, and humidity are created as nodes, and the previously discovered potential correlations and interaction relationships are considered as edges between nodes. For instance, if a correlation is found between the battery's internal resistance and temperature, an edge is created between the battery's internal resistance node and the temperature node. The probability of occurrence for each interference factor is set through historical data statistics or expert experience. For example, based on a large amount of experimental data, the probability of battery temperature rising is 0.3. Considering the attenuation characteristics during propagation, an attenuation coefficient, such as 0.8, is set for each edge. By setting the attributes of nodes and edges, each node is given an initial probability value, generating an interference correlation network between the battery's internal resistance and various interference factors, which intuitively displays the correlation and propagation relationships between the factors.

[0056] Preferably, the interference propagation path corresponding to the battery internal resistance is determined based on the interference correlation network between the battery internal resistance and various interference factors, and the battery interference probability is estimated based on the interference propagation path and the corresponding initial occurrence probability value on the path, so as to generate the interference probability of military fast charging battery.

[0057] In this embodiment of the invention, the path search function of Gephi software is used to determine the interference propagation path related to the battery internal resistance based on the interference correlation network between the battery internal resistance and various interference factors. For example, in the interference correlation network, all possible paths from the battery internal resistance node to other interference factor nodes are searched. For each path, the battery interference probability is calculated based on the initial occurrence probability value and the edge attenuation coefficient on the path. Assuming a path from the battery internal resistance node to the temperature node and then to the chemical reaction rate node, the initial occurrence probability of the battery internal resistance node is 1 (because the internal resistance data is known), the edge attenuation coefficient from the battery internal resistance to the temperature node is 0.8, the initial occurrence probability of the temperature node is 0.3, the edge attenuation coefficient from the temperature to the chemical reaction rate node is 0.9, and the initial occurrence probability of the chemical reaction rate node is 0.2. Then the battery interference probability of this path is 1 × 0.8 × 0.3 × 0.9 × 0.2 = 0.0432. By calculating the battery interference probability of all relevant paths and conducting comprehensive analysis, such as taking the maximum value or weighted average, the interference probability of military fast-charging batteries is finally generated, providing a basis for subsequent battery health assessment and pulse current regulation.

[0058] Furthermore, the health status assessment in step S34 specifically means that if the internal resistance of the military battery continues to rise over a period of time and exceeds the corresponding battery pack health range, then the health status of the battery pack corresponding to the military lithium battery is determined to be that the battery is in an aging state; otherwise, it is determined to be in a normal charging state.

[0059] Furthermore, step S4 includes the following steps: Step S41: When the health status of the battery pack corresponding to the military lithium battery is determined to be normal charging state, the pulse current amplitude is adjusted to 60%-80% of the maximum charging current according to the rated capacity and charging time requirements of the battery pack corresponding to the military lithium battery, and the pulse frequency is adjusted to 500Hz-1000Hz. At the same time, the pulse current duty cycle is dynamically adjusted according to the charging stage of the battery pack. In the early stage of charging, the pulse current duty cycle can be set to 40%-50%, and when the remaining power is 90%-99% and it is about to be fully charged, the pulse current duty cycle is gradually reduced to 20%-30%, thus generating the pulse current control strategy corresponding to the normal charging state. In this embodiment of the invention, the battery pack health status information is obtained by utilizing the battery management system (BMS) of a military lithium battery. When the battery pack health status is determined to be in a normal charging state, its rated capacity is obtained according to the battery pack's product manual or technical documents. For example, the rated capacity of a certain lithium-ion battery pack is 50Ah. Simultaneously, the charging time requirement is specified, assuming that charging must be completed within 2 hours. A programmable power controller is used to regulate the pulse current. Based on the battery pack's maximum charging current, such as 10A, the pulse current amplitude regulation range is calculated to be 6A (10A × 60%) to 8A (10A × 80%). The corresponding amplitude parameters are set in the programmable power controller. For the pulse frequency, it is set in the range of 500Hz-1000Hz, for example, 800Hz. The pulse current duty cycle is dynamically adjusted according to the charging stage. In the early stage of charging, the duty cycle is set to 40%-50% by the controller, such as 45%. As the charging progresses and approaches full charge, the duty cycle is gradually reduced to 20%-30% by the controller. For example, when the remaining power is 90%, the duty cycle is adjusted to 25%. Through this operation, the pulse current control strategy corresponding to the normal charging state is finally generated to ensure that the charging process is efficient and stable.

[0060] Step S42: When the health status of the military lithium battery pack is determined to be that the battery is in an aging state, the pulse current amplitude is reduced by 20%-30% compared to the normal charging state to reduce the internal heat generation and polarization reaction of the battery pack. The pulse frequency is increased to 1.2-1.5 times that of the normal charging state to improve the ion transport efficiency inside the battery pack by using high-frequency pulses. The pulse current duty cycle is reduced to 70%-80% of the normal charging state through diffusion regulation between internal pulse ions. This generates the pulse current regulation strategy corresponding to the aging state of the battery.

[0061] In this embodiment of the invention, the battery health status of the military lithium battery is determined to be aging by using a battery management system (BMS). To reduce internal heat generation and polarization reactions, a programmable power controller is used to regulate the pulse current amplitude. Given that the pulse current amplitude range under normal charging conditions is 6A-8A, the amplitude range after a 20%-30% reduction compared to the normal state is calculated. Taking the normal amplitude of 7A as an example, a 20% reduction results in 5.6A (7A × 80%), and a 30% reduction results in 4.9A (7A × 70%). A new amplitude parameter is set within this range in the programmable power controller, such as 5.2A. For the pulse frequency, assuming it is 800Hz under normal charging conditions, it is increased to 1.2-1.5Hz. The frequency range is 960Hz (800Hz × 1.2) to 1200Hz (800Hz × 1.5), set to 1000Hz in the controller. The pulse current duty cycle is determined by using professional electrochemical testing equipment to obtain the pulse ion concentration, electrode spacing, and electrolyte conductivity inside the battery pack. Ion diffusion analysis is performed using computational chemistry software Materials Studio. Based on the diffusion path, speed, and direction, the duty cycle is reduced to 70%-80% of the normal charging state using a pulse current control device. Assuming an initial duty cycle of 45% under normal charging conditions, the adjusted duty cycle is 31.5% (45% × 70%) to 36% (45% × 80%). For example, setting it to 33% generates a pulse current control strategy corresponding to the aging state of the battery, improving the charging performance of the aging battery.

[0062] Furthermore, the reduction of the pulse current duty cycle to 70%-80% of the normal charging state through diffusion regulation between internal pulse ions in step S42 includes the following steps: Obtain the internal pulse ion concentration, electrode spacing, and electrolyte conductivity of the battery pack in a military lithium battery. In this embodiment of the invention, key parameters of the military lithium battery pack are measured using specialized electrochemical testing equipment. For the internal pulse ion concentration, ion-selective electrode (ISE) technology is employed, such as using a fluoride ion-selective electrode to measure the fluoride ion concentration in the battery pack. The fluoride ion-selective electrode and the reference electrode are immersed together in the electrolyte of the battery pack. By measuring the potential difference between the electrodes and calculating the fluoride ion concentration according to the Nernst equation, the fluoride ion concentration is determined. For the electrode spacing, a high-precision laser rangefinder is used. With the battery pack disassembled, the transmitter and receiver of the laser rangefinder are aligned with the positive and negative electrode surfaces of the battery pack, respectively, to measure the distance between the electrodes. For the electrolyte conductivity, the electrodes of a conductivity meter are immersed in the electrolyte. The conductivity meter measures the relationship between the current and voltage in the electrolyte and calculates the electrolyte conductivity according to Ohm's law. These measured data are recorded to provide basic data for subsequent ion diffusion analysis.

[0063] Preferably, ion diffusion analysis is performed on the internal pulse ions corresponding to the battery pack in the military lithium battery based on the internal pulse ion concentration, electrode spacing and electrolyte conductivity, so as to obtain the diffusion path, diffusion rate and diffusion direction of the internal pulse ions in the electrolyte. In this embodiment of the invention, computational chemistry software, such as Materials Studio, is used to perform ion diffusion analysis on the internal pulse ions corresponding to the battery pack in a military lithium battery, based on the internal pulse ion concentration, electrode spacing, and electrolyte conductivity. In Materials Studio, a microscopic model of the battery pack is constructed, using the previously obtained internal pulse ion concentration as the initial ion distribution condition in the model, setting the electrode spacing as the geometric parameter of the model, and inputting the electrolyte conductivity as the physical property parameter of the model. The software uses molecular dynamics simulation methods to simulate the trajectory of ions in the electrolyte by solving Newton's equations of motion. During the simulation, factors such as the interaction forces between ions and collisions between ions and electrolyte molecules are considered. For example, for the diffusion simulation of lithium ions in carbonate electrolytes, the software calculates the position information of lithium ions at different times to obtain their diffusion path. By analyzing the relationship between the displacement and time of ions over a period of time, the diffusion rate is calculated, and the diffusion direction is determined based on statistical analysis of the ion movement direction. The simulated diffusion path, diffusion rate, and diffusion direction data are exported for subsequent pulse current regulation.

[0064] Preferably, the duty cycle of the corresponding pulse current is reduced to 70%-80% of that under normal charging conditions by diffusion regulation between the internal pulse ions, based on the diffusion path, diffusion rate and diffusion direction of the internal pulse ions in the electrolyte.

[0065] In this embodiment of the invention, a pulse current control device, such as a programmable power controller, is used to regulate the pulse current duty cycle based on the diffusion path, diffusion rate, and diffusion direction of internal pulse ions in the electrolyte. Assuming the pulse current duty cycle under normal charging conditions is 50%, analysis of ion diffusion reveals that excessively fast ion diffusion may lead to uneven internal battery reactions. In this case, the pulse current duty cycle needs to be reduced. The pulse current control device is connected to the charging circuit of a military lithium battery. By programming and setting the device's control parameters, the required reduction in duty cycle is calculated based on the diffusion analysis results. For example, based on the ion diffusion direction and speed, it is determined that the duty cycle needs to be reduced to 75% of the normal state. A new duty cycle parameter is set in the pulse current control device, causing the device to output a pulse current according to the new duty cycle to charge the battery pack. By real-time monitoring of ion diffusion and the charging status of the battery pack, the duty cycle is continuously adjusted to ensure precise control of the pulse current duty cycle within the target range of 70%-80%, guaranteeing the stability of internal ion diffusion and charging efficiency during fast charging.

[0066] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0067] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A pulse current regulation method for fast charging of military special power supplies, characterized in that, Includes the following steps: Step S1: Obtain the pulse current beam corresponding to the military lithium battery during fast charging, and calculate the pulse control parameters based on the pulse current beam corresponding to the military lithium battery during fast charging to obtain the pulse current amplitude, pulse current frequency and pulse current duty cycle corresponding to the fast charging process. Step S2: Obtain the type, voltage level, and measurement accuracy requirements of the military lithium battery, and perform internal resistance polarization AC measurement on the corresponding battery pack during fast charging based on the type, voltage level, and measurement accuracy requirements of the military lithium battery to obtain the internal resistance of the military lithium battery. Step S3: Estimate the battery interference probability of the corresponding battery pack during fast charging based on the internal resistance of the military lithium battery to generate the interference probability of the military fast charging battery; perform a health interval mapping evaluation on the corresponding battery pack based on the interference probability of the military fast charging battery to obtain the health status of the battery pack corresponding to the military lithium battery, including the normal charging state and the aging state of the battery. Step S4: Based on the health status of the battery pack corresponding to the military lithium battery, perform pulse current regulation analysis on the pulse current amplitude, pulse current frequency and pulse current duty cycle corresponding to the pulse current beam during the fast charging process, and generate pulse current regulation strategies for the military lithium battery under different states.

2. The pulse current regulation method for fast charging of military special power supplies according to claim 1, characterized in that, Step S1 includes the following steps: Step S11: Obtain the pulse current beam corresponding to the military lithium battery during fast charging; Step S12: Perform high-frequency noise filtering on the pulse current beam corresponding to the military lithium battery during fast charging, and apply adaptive filtering to adjust the corresponding filtering parameters to remove high-frequency noise and random noise in the pulse current beam, and generate a pulse current beam after high-frequency noise reduction. Step S13: Perform low-frequency sliding filtering on the pulse current beam after high-frequency noise reduction. By setting a sliding window with a window size of 5, and using the sliding average filtering of the low-frequency noise corresponding to the pulse current beam after high-frequency noise reduction according to the sliding window, a smoothed pulse current beam is obtained. Step S14: Calculate the pulse control parameters based on the smoothed and filtered pulse current beam to obtain the pulse current amplitude, pulse current frequency, and pulse current duty cycle during the fast charging process.

3. The pulse current regulation method for fast charging of military special power supplies according to claim 2, characterized in that, Step S14 includes the following steps: Step S141: Obtain the zero-crossing point of the corresponding pulse current signal through the smoothed pulse current beam, and determine the start and end times of each waveform in the smoothed pulse current beam based on the zero-crossing point of the pulse current signal. Step S142: Estimate the pulse period based on the start and end times of each waveform in the pulse current beam to obtain the pulse period corresponding to the pulse current beam. Step S143: Obtain the maximum and minimum values ​​of the pulse current signal corresponding to each pulse period of the pulse current beam, and calculate the pulse amplitude based on the maximum and minimum values ​​of the pulse current signal to obtain the pulse current amplitude corresponding to the fast charging process. Step S144: Calculate the number of pulse cycles per unit time using the pulse cycle corresponding to the pulse current beam as the frequency, so as to obtain the pulse current frequency corresponding to the fast charging process. Step S145: Obtain the high-level time of the pulse current beam within one pulse period and the total time of the entire period by using the pulse period corresponding to the pulse current beam. Calculate the corresponding duty cycle based on the ratio between the high-level time and the total time of the entire period to obtain the corresponding pulse current duty cycle during the fast charging process.

4. The pulse current regulation method for fast charging of military special power supplies according to claim 1, characterized in that, Step S2 includes the following steps: Step S21: Obtain the type, voltage level, and measurement accuracy requirements of the military lithium battery; Step S22: Select an internal resistance tester with micro-ohm level measurement accuracy, adaptability to a wide voltage range including 0-1000V, and anti-interference capability according to the type, voltage level, and measurement accuracy requirements of the military lithium battery, and establish a reliable connection between the positive and negative test lines of the internal resistance tester and the positive and negative terminals of the battery pack during the fast charging process. Step S23: Obtain the usage frequency corresponding to the military lithium battery, set the corresponding measurement cycle according to the usage frequency corresponding to the military lithium battery, and inject an AC current between 1kHz and 10kHz into the battery pack by starting the positive and negative terminals of the internal resistance tester when the battery pack is not charging or discharging within the corresponding measurement cycle, and measure the AC voltage response at the corresponding terminals to generate the AC voltage for measuring the internal resistance of the military battery. Step S24: Based on the injected AC current and the AC voltage of the military battery internal resistance measurement, perform AC polarization measurement on the corresponding battery pack during the fast charging process to obtain the internal resistance of the military lithium battery.

5. The pulse current regulation method for fast charging of military special power supplies according to claim 4, characterized in that, Step S24 includes the following steps: Step S241: Obtain the electrochemical characteristics of the military lithium battery pack by the corresponding battery pack during the fast charging process; Step S242: Obtain the AC circuit connection structure between the battery pack and the internal resistance tester of the military lithium battery, and establish a mathematical relationship model between the battery internal resistance, polarization resistance and AC current and AC voltage based on the AC circuit connection structure and the corresponding electrochemical characteristics of the military lithium battery pack. Step S243: Use the AC voltage measured by the internal resistance of the military battery as the input to the mathematical relationship model, and separate the voltage components caused by the internal resistance and polarization resistance of the battery through Fourier transform and impedance calculation. Step S244: Calculate the AC impedance amplitude and phase angle required for the battery internal resistance to generate polarized AC based on the corresponding voltage components caused by the battery internal resistance and polarization resistance. Step S245: Based on the AC impedance amplitude and phase angle required to generate polarized AC based on the battery internal resistance, perform internal resistance polarized AC measurement on the injected AC current and the corresponding voltage component caused by the battery internal resistance to obtain the internal resistance of the military lithium battery.

6. The pulse current regulation method for fast charging of military special power supplies according to claim 1, characterized in that, Step S3 includes the following steps: Step S31: Estimate the battery interference probability of the corresponding battery pack during fast charging based on the internal resistance of the military lithium battery to generate the interference probability of the military fast charging battery. Step S32: Based on the interference probability of military fast-charging batteries, perform battery health interval mapping on the corresponding battery pack during fast charging to obtain the battery pack health interval corresponding to military lithium batteries. Step S33: Calculate the trend of change of the internal resistance of the military lithium battery over a period of time using the moving average method to obtain the trend of change of the internal resistance of the military battery. Step S34: Based on the battery pack health range corresponding to the military lithium battery, assess the health status of the internal resistance change trend of the military battery to obtain the battery pack health status corresponding to the military lithium battery, including normal charging status and battery aging status.

7. The pulse current regulation method for fast charging of military special power supplies according to claim 6, characterized in that, Step S31 includes the following steps: By acquiring the corresponding voltage, temperature, humidity, electromagnetic interference, charge / discharge cycles, internal chemical reaction rate, internal pulse ion migration characteristics, and electrode material stability characteristics of the battery pack during the fast charging process, a set of internal interference factors corresponding to the battery pack can be obtained. Based on the internal resistance of military lithium batteries, battery interference correlation mining is performed on the various interference factors in the battery internal interference factor set corresponding to the battery pack, in order to mine and analyze the potential correlation between battery internal resistance and various interference factors, as well as the interaction relationship between various interference factors. Based on the potential correlation between the battery internal resistance and various interference factors, as well as the interaction between various interference factors, an interference propagation network is constructed between the internal resistance of military lithium batteries and various interference factors within the set of internal interference factors. The internal resistance of military lithium batteries and various interference factors are regarded as nodes in the network, and the potential correlation and interaction are regarded as edges between nodes. At the same time, an initial occurrence probability value is assigned by considering the occurrence probability of each interference factor and its attenuation characteristics during propagation, so as to generate an interference correlation network between the battery internal resistance and various interference factors. Based on the interference correlation network between the battery internal resistance and various interference factors, the interference propagation path corresponding to the battery internal resistance is determined, and the battery interference probability is estimated based on the interference propagation path and the corresponding initial occurrence probability value on the path, so as to generate the interference probability of military fast charging battery.

8. The pulse current regulation method for fast charging of military special power supplies according to claim 6, characterized in that, The health status assessment mentioned in step S34 specifically means that if the internal resistance of the military battery continues to rise over a period of time and exceeds the corresponding battery pack health range, then the health status of the battery pack corresponding to the military lithium battery is determined to be that the battery is in an aging state; otherwise, it is determined to be in a normal charging state.

9. The pulse current regulation method for fast charging of military special power supplies according to claim 1, characterized in that, Step S4 includes the following steps: Step S41: When the health status of the battery pack corresponding to the military lithium battery is determined to be normal charging state, the pulse current amplitude is adjusted to 60%-80% of the maximum charging current according to the rated capacity and charging time requirements of the battery pack corresponding to the military lithium battery, and the pulse frequency is adjusted to 500Hz-1000Hz. At the same time, the pulse current duty cycle is dynamically adjusted according to the charging stage of the battery pack. In the early stage of charging, the pulse current duty cycle can be set to 40%-50%, and when the remaining power is 90%-99% and it is about to be fully charged, the pulse current duty cycle is gradually reduced to 20%-30%, thus generating the pulse current control strategy corresponding to the normal charging state. Step S42: When the health status of the military lithium battery pack is determined to be that the battery is in an aging state, the pulse current amplitude is reduced by 20%-30% compared to the normal charging state to reduce the internal heat generation and polarization reaction of the battery pack. The pulse frequency is increased to 1.2-1.5 times that of the normal charging state to improve the ion transport efficiency inside the battery pack by using high-frequency pulses. The pulse current duty cycle is reduced to 70%-80% of the normal charging state through diffusion regulation between internal pulse ions. This generates the pulse current regulation strategy corresponding to the aging state of the battery.

10. The pulse current regulation method for fast charging of military special power supplies according to claim 9, characterized in that, The reduction of the pulse current duty cycle to 70%-80% of that under normal charging conditions through diffusion regulation between internal pulse ions in step S42 includes the following steps: Obtain the internal pulse ion concentration, electrode spacing, and electrolyte conductivity of the battery pack in a military lithium battery. Ion diffusion analysis was performed on the internal pulse ions in the battery pack of military lithium batteries based on the internal pulse ion concentration, electrode spacing and electrolyte conductivity, so as to obtain the diffusion path, diffusion rate and diffusion direction of the internal pulse ions in the electrolyte. Based on the diffusion path, diffusion rate, and diffusion direction of the internal pulse ions in the electrolyte, the duty cycle of the corresponding pulse current is reduced to 70%-80% of that under normal charging conditions through diffusion regulation between the internal pulse ions.

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