Vehicle battery protection method and system

Abstract

This application relates to the field of vehicle technology and provides a method for protecting vehicle batteries. This method can accurately identify the risk of continuous dark current sulfation in batteries and adaptively adjust desulfation repair strategies. The method includes: acquiring the battery health status value, dark current value, and temperature value of the battery in real time; comparing the dark current value with a preset benchmark threshold and starting a timer when the dark current value exceeds the benchmark threshold; dynamically determining a corresponding duration threshold based on the currently acquired battery health status value and temperature value; determining a sulfation risk and triggering a repair command when the duration for which the dark current value continuously exceeds the benchmark threshold reaches the duration threshold; responding to the repair command, determining one of multiple repair strategies based on different preset ranges of the battery health status value at the time of triggering; executing the determined repair strategy; and dynamically adjusting repair parameters according to the battery's operating conditions during the execution of the repair strategy.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, specifically to vehicle electronics and energy management technology within the field of vehicle technology, and more specifically to a method and system for protecting on-board batteries. Background Technology

[0002] As the power source for the vehicle's electrical system, the health of the vehicle's battery directly affects the vehicle's start-stop function, the operation of onboard electronic devices, and the overall electrical safety of the vehicle. Battery sulfation is one of the main causes of performance degradation and shortened lifespan. The continuous dark current consumed by non-essential electrical equipment when the vehicle is stationary is a key factor that exacerbates the formation of lead sulfate crystals and the accumulation of irreversible sulfation damage.

[0003] Currently, protection solutions for vehicle batteries mostly focus on overcharge, over-discharge, or static voltage monitoring. Pulse repair technology has also been introduced to mitigate sulfation. However, when dealing with progressive sulfation caused by continuous dark current, these solutions have the following shortcomings: Risk assessment logic is often based on simple comparisons of a single parameter or static threshold, failing to accurately identify sulfation risks caused by the cumulative effect of dark current, easily leading to misjudgments or missed judgments; the repair strategies used are usually fixed and cannot be adaptively adjusted according to the real-time changes in the battery's aging state and operating conditions, resulting in low repair efficiency, high energy consumption, and even potential secondary damage to the aged battery due to improper repair. Therefore, how to accurately identify and effectively repair battery sulfation damage caused by continuous dark current, while dynamically adapting to battery aging states and temperature changes, has become a pressing technical challenge in this field. Summary of the Invention

[0004] This application provides a method and system for protecting vehicle batteries, which solves the problems of inaccurate identification of continuous dark current sulfation risk in vehicle batteries and the inability of desulfation repair strategies to adaptively adjust according to battery health status (SOH).

[0005] To achieve the above technical objectives, the embodiments of this application provide the following technical solutions: In a first aspect, one embodiment of this application provides a method for protecting a vehicle-mounted battery, the method comprising: The battery health status value, dark current value, and temperature value of the battery are acquired in real time. The dark current value is compared with a preset reference threshold, and timing begins when the dark current value exceeds the reference threshold; Based on the currently acquired battery health status value and temperature value, a corresponding duration threshold is dynamically determined; When the duration for which the dark current value exceeds the baseline threshold reaches the duration threshold, a sulfidation risk is determined and a repair instruction is triggered. In response to the repair instruction, one of multiple repair strategies is determined based on the different preset ranges in which the battery health status value is at the time of triggering; Implement the determined repair strategy; During the execution of the repair strategy, the repair parameters are dynamically adjusted according to the operating conditions of the battery.

[0006] In some optional embodiments, the determination of one of multiple repair strategies based on different preset ranges of the battery health status value at the time of triggering is specifically as follows: Different repair strategies are determined based on whether the battery health status value is lower than a first preset threshold or is between the first preset threshold and a second preset threshold. The first repair strategy, which is executed when the battery health status value is lower than the first preset threshold, and the second repair strategy, which is executed when the battery health status value is between the first preset threshold and the second preset threshold, differ in the frequency range of the reverse sweep pulse used.

[0007] In this way, by associating different battery health status values ​​with different sweep pulse frequency ranges, spectrum-targeted repair is achieved. For batteries with different degrees of aging, the effective frequency band of the pulse energy is optimized, thereby more efficiently breaking down lead sulfate crystals of corresponding particle sizes.

[0008] In some optional embodiments, both the first repair strategy and the second repair strategy include alternately applying reverse sweep frequency pulses and replenishing current to the battery according to a preset timing sequence.

[0009] In this way, by alternately applying the supplementary current and the reverse frequency sweep pulse according to the preset timing, electrochemical conversion conditions are immediately provided after the physical breaking of sulfide crystals, which effectively promotes the regeneration of active substances and prevents lead sulfate recrystallization, while also helping to suppress the temperature rise during the repair process.

[0010] In some optional embodiments, the dynamic determination of the corresponding duration threshold specifically means that the duration threshold is negatively correlated with the battery health status value.

[0011] Thus, this negative correlation rule simulates expert experience, namely, adopting stricter judgment criteria (shorter duration threshold) for batteries with low battery health status values ​​to achieve early warning, while relaxing the criteria for healthy batteries to improve anti-interference.

[0012] In some alternative embodiments, performing the repair strategy includes applying a reverse frequency sweep pulse to the battery, wherein the amplitude of the reverse frequency sweep pulse is dynamically determined based on the rated capacity of the battery.

[0013] In this way, by dynamically linking the pulse amplitude with the rated capacity of the battery, the repair energy is ensured to match the physical specifications of the battery, avoiding the problem of over-repairing small-capacity batteries or under-repairing large-capacity batteries, thus improving the versatility and safety of the solution.

[0014] In some alternative embodiments, the ratio of the reverse sweep pulse amplitude to the rated capacity of the battery is between 0.075 and 0.085.

[0015] By limiting the ratio of pulse amplitude to capacity to between 0.075 and 0.085, the dynamic adaptation strategy achieves the best balance between repair effectiveness, battery safety, and energy consumption.

[0016] In some optional embodiments, the step of dynamically adjusting the repair parameters according to the operating conditions of the battery specifically includes: Monitor the temperature rise of the battery, and when the temperature rise exceeds a set threshold, increase the sweep period of the applied reverse sweep pulse.

[0017] In this way, by monitoring the temperature rise in real time and increasing the frequency sweep cycle when the limit is exceeded, the system can automatically adjust the repair power density, thereby actively controlling the battery temperature rise within a safe range, solving the potential overheating safety hazard that may be caused during the repair process, and enhancing the wide temperature range applicability of the solution.

[0018] In some alternative embodiments, the method further includes: recovering residual polarization charge on the battery plates by means of an energy feedback unit integrated in the battery connection circuit during the execution of the repair strategy.

[0019] In this way, by recovering the residual charge on the battery plates during the pulse gap, the energy recovery rate of a single repair cycle is improved, thereby optimizing the overall energy efficiency ratio.

[0020] Secondly, one embodiment of this application also provides an on-board battery protection system for implementing the on-board battery protection method described above, the on-board battery protection system comprising: The parameter detection module is used to acquire the battery health status value, dark current value and temperature value of the battery in real time; The control processing module, connected to the parameter detection module, is used to compare the dark current value with a preset reference threshold, and start timing when the dark current value exceeds the reference threshold. Based on the currently acquired battery health status value and the temperature value, a corresponding duration threshold is dynamically determined. When the duration for which the dark current value exceeds the reference threshold reaches the duration threshold, a sulfation risk is determined and a repair command is triggered. In response to the repair command, one of multiple repair strategies is determined based on the different preset ranges in which the battery health status value is located at the time of triggering. The repair execution module is connected to the control processing module and is used to execute the determined repair strategy, and dynamically adjust the repair parameters according to the operating conditions of the battery during the execution of the repair strategy.

[0021] In some optional embodiments, the repair execution module includes a magnetically integrated connector for establishing an electrical connection with the electrodes of the battery; the magnetically integrated connector includes: Strong magnetic adsorption components are used to provide magnetic positioning force; A foolproof structure is provided at the insertion interface of the magnetic integrated connector to prevent reverse connection; The buffer assembly includes a first spring for buffering low-frequency vibrations and a second spring for buffering high-frequency vibrations; and, A conductive layer covers the electrical contact surface of the magnetic integrated connector and is used to contact and conduct electricity with the electrodes of the battery.

[0022] Thus, the magnetic integrated connector combines strong magnetic adsorption, non-fouling for irregular shapes, buffering, and high-efficiency conductivity, improving the reliability of the connection in vehicle vibration environments.

[0023] Thirdly, one embodiment of this application also provides a vehicle including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the on-board battery protection method as described above.

[0024] Fourthly, one embodiment of this application also provides a computer program product, the computer program product including a computer program stored in a computer-readable storage medium; a processor of a computer device reads the computer program from the computer-readable storage medium, and when the processor executes the computer program, it implements the steps of the above-described vehicle battery protection method. Optionally, the computer program may be stored in the readable storage medium of the computer device or in the cloud; the processor of the computer device reads the computer program from the readable storage medium or in the cloud.

[0025] Fifthly, one embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle battery protection method as described above.

[0026] As can be seen from the above technical solutions, the vehicle battery protection system, vehicle, computer program product, and computer-readable storage medium provided in this application all correspondingly implement the vehicle battery protection method described in the first aspect. This method can adaptively adjust based on the battery health status and ambient temperature by dynamically determining the duration threshold. By determining one of multiple repair strategies based on different preset ranges of the battery health status value at the time of triggering, the hierarchical and matching of repair decisions is achieved. According to the specific battery health status value of the battery at the time of risk triggering, the most suitable one is automatically selected from multiple preset strategies for execution. The working conditions during repair are monitored in real time, and parameters are dynamically adjusted accordingly, thereby actively suppressing the temperature rise within the safe threshold and eliminating the risk of overheating. In summary, through dynamic threshold determination, hierarchical strategy matching, and closed-loop process control, the continuous dark current sulfation risk of vehicle batteries can be accurately identified, and the desulfation repair strategy can be adaptively adjusted according to the battery health status, while simultaneously improving safety and energy efficiency. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0028] Figure 1 This is a flowchart illustrating a vehicle battery protection method according to one embodiment of this application.

[0029] Figure 2 This is a schematic diagram of the architecture of an on-board battery protection system provided in one embodiment of this application.

[0030] Figure 3 This is a schematic diagram of the architecture of a vehicle provided for one embodiment of this application. Detailed Implementation

[0031] Unless otherwise defined, the technical or scientific terms used in the embodiments of this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to avoid confusion of the constituent elements.

[0032] Unless the context otherwise requires, throughout this specification, "a plurality of" means "at least two," and "including" is interpreted as open-ended or encompassing, that is, "including, but not limited to." In the description of this specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this application. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example.

[0033] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0034] Overview Sulfates in vehicle batteries are one of the main causes of their performance degradation and shortened lifespan. The continuous dark current consumed by non-essential electrical equipment when the vehicle is stationary is a key factor that exacerbates the formation of lead sulfate crystals and the accumulation of irreversible sulfation damage.

[0035] To address dark current, current industry solutions set fixed current thresholds for shutdown protection, ignoring the fundamental fact that a battery, as a chemical power source, has a current tolerance that changes with its own health and ambient temperature. A 100 mA dark current, for an aging battery with a state of harmlessness (SOH) of less than or equal to 50% and increased internal resistance, or at a low temperature of -20°C, can cause significant sulfation damage after 15 minutes. Existing static threshold methods cannot distinguish between normal and aging batteries, resulting in both high false alarm and false alarm rates. Some solutions focus on repair actions, developing various pulse generation circuits that treat the battery as a homogeneous and unchanging object, applying pulse impacts, but these have low repair success rates and are prone to causing secondary damage.

[0036] To redefine the problem, it is necessary not only to explore how to detect dark current or how to generate repair pulses, but also to inquire how to establish a system that can accurately identify the sulfation risk of vehicle batteries in the aging stage and operating under specific environments, and automatically perform repair and maintenance. Based on the above definition, the inventive concept of this application can be constructed through the following steps: The assessment shifts from instantaneous judgment to a cumulative damage model. Sulfidation is a cumulative process where quantitative changes lead to qualitative changes. Therefore, the key to risk identification lies not in capturing a single instantaneous outlier, but in quantifying the duration of the damaging state. Hence, a two-dimensional current-time judgment plane can be constructed.

[0037] The standard has evolved from a fixed standard to a dynamic, adaptive one. The same current-time damage can have vastly different effects on batteries under different conditions. Therefore, the standard for determining whether a risk exists cannot be fixed but should be dynamically adjustable. This adjustment is based on the battery's real-time physical indicators—State of Health (SOH) and environmental stress indicators—temperature. Thus, SOH-temperature is introduced as the third and fourth dimensions, together with dark current-time, to form a four-dimensional dynamic assessment system. In this system, each state point corresponds to a risk judgment boundary, i.e., a three-dimensional dynamic threshold matrix.

[0038] The approach has evolved from a single repair solution to a tiered strategy library. Once the risk is accurately identified, the repair action must be tailored accordingly. Batteries with different SOH values ​​exhibit varying crystal morphology, distribution, and persistence of sulfides within their interiors. Therefore, a repair strategy library can be constructed, pre-stored with multiple repair solutions. The decision logic is set to: if the detected SOH value falls within a preset range, the corresponding repair strategy is invoked. The differences between strategies lie in key parameters such as the frequency, amplitude, and waveform of the repair pulse, and whether it is combined with supplementary charging.

[0039] The process shifts from open-loop execution to closed-loop control. The repair process itself also puts stress on the battery, such as causing temperature rise. Therefore, while executing the repair strategy, key feedback signals such as battery temperature rise are continuously monitored, and control rules are set, such as reducing the pulse frequency if the temperature rise exceeds the limit. This forms a safe closed loop of execution-monitoring-adjustment, ensuring the stability and safety of the repair process.

[0040] From functional implementation to reliable deployment. Addressing the issue of vehicle vibration causing connection failures, we can explore ways to adapt to and absorb vibration. By using a connector that integrates magnetic attraction, foolproof design, wide-band vibration resistance, and low impedance, a pathway from the chip to the battery plates is created for the aforementioned algorithm, ensuring that every calculation result is stably converted into repair energy.

[0041] Exemplary methods One embodiment of this application provides a method for protecting an on-board battery. Please refer to [link / reference]. Figure 1 , Figure 1 A flowchart illustrating a vehicle battery protection method according to one embodiment of this application is provided. The vehicle battery protection method includes: Step S110: Real-time acquisition of battery health status value, dark current value and temperature value of the storage battery.

[0042] In this embodiment, the battery health status value is not read directly from a single sensor. Instead, it is obtained by using a dynamic weighted fusion calculation model to perform comprehensive calculations on multiple directly measurable or indirectly estimated physical quantities. This results in a quantitative indicator characterizing the battery's health status from 0% (complete failure) to 100% (brand new).

[0043] Battery aging manifests primarily in two forms: first, irreversible loss and sulfation of active materials, directly reflected in a linear increase in internal resistance; and second, fatigue and corrosion of the supporting structure, strongly correlated with the number of charge-discharge cycles. Increased internal resistance directly leads to a drop in starting voltage and a reduction in capacity, serving as an indicator of performance degradation.

[0044] When accurate charge-discharge cycle counts are available, the dynamic weighted fusion calculation model uses the following formula to obtain the battery health status value: SOH = 100% - [(Rated number of cycles - Actual number of cycles) / Rated number of cycles × 30% + (Actual internal resistance - Initial internal resistance) / Initial internal resistance × 70%] Among them, rated cycle count refers to the number of charge-discharge cycles specified in the battery technical specifications before reaching the end of its life under standard test conditions; actual cycle count refers to the equivalent full charge-discharge cycle count actually experienced by the battery, which is estimated cumulatively by an algorithm or read from the battery management system; initial internal resistance refers to the AC internal resistance value measured at a standard temperature (e.g., 25°C) when the battery is in brand new condition (SOH=100%), which is usually stored in the system as a known parameter; actual internal resistance refers to the current internal resistance value obtained by measuring the AC impedance of the battery in real time or estimating it online using the DC pulse load method.

[0045] Voltage sampling is achieved by using a voltage divider network consisting of 100 kΩ and 10 kΩ high-precision (0.1%), low-temperature drift metal film resistors to convert the battery terminal voltage (approximately 12V-14V) to the range of the microcontroller's analog-to-digital converter (approximately 1.14V) for acquisition.

[0046] The weighting (30% vs 70%) is based on extensive experimental data and engineering practice, assigning a higher weight of 70% to changes in internal resistance. For automotive start-stop batteries, operating conditions are mostly shallow charge-discharge cycles, and sulfation of active materials (increased internal resistance) is often a more significant factor in battery life degradation than simple cycle loss. This weighting ensures that the SOH estimate can more accurately reflect the true performance degradation of the battery.

[0047] Given the prevalence of the aftermarket, many vehicles cannot provide accurate cycle count data. Therefore, the dynamic weighted fusion calculation model has intelligent switching capabilities, using a backup formula to obtain the battery health status value: SOH = 100% - [(Initial static voltage - Actual static voltage) / Initial static voltage × 40% + (Actual internal resistance - Initial internal resistance) / Initial internal resistance × 60%] The initial settling voltage refers to the stable open-circuit voltage of a new battery after it has been fully charged and left to rest for more than 24 hours; the actual settling voltage refers to the stable open-circuit voltage of the current battery under similar settling conditions. Here, the settling voltage can reflect the battery's state of charge and some aging information to a certain extent, thus partially replacing information about the number of battery cycles.

[0048] At this point, the weights are adjusted to 60% for internal resistance and 40% for static voltage change, still highlighting the dominant role of internal resistance. At the same time, voltage is used for compensation to ensure the robustness and usability of SOH estimation under different data completeness scenarios.

[0049] The above calculations are implemented by a software algorithm using a microcontroller in the control processing module. The system synchronously triggers sampling from all current, voltage, and temperature sensors at a fixed period of 500 milliseconds to ensure data time alignment. It then immediately runs the battery health state calculation model to refresh the SOH value. This high-frequency refresh ensures the system's real-time response capability to changes in battery state.

[0050] In this embodiment, a non-contact closed-loop Hall effect current sensor is used to obtain the dark current value, taking the ACS758 series as an example: The negative current line of the battery passes through the opening in the magnetic core at the center of the sensor. The magnetic field generated by the current is detected by the Hall element and converted into a proportional voltage signal. Due to the closed-loop design that compensates for the magnetic field through the secondary coil, it has good linearity, low temperature drift, and high bandwidth.

[0051] With a measurement range of ±100A, it fully covers the range from quiescent milliampere-level dark current to surge currents of hundreds of amperes during startup. The output sensitivity is 66mV / A, corresponding to an output voltage change of 3.3mV for a 50mA reference threshold. Combined with a high-resolution analog-to-digital converter on a microcontroller, measurement resolution and accuracy better than 0.1A can be achieved.

[0052] In this embodiment, the sensor is connected in series between the negative terminal of the battery and the vehicle's grounding cable to measure the total outflow current.

[0053] Temperature is a rate constant affecting the electrochemical process of a battery. This embodiment uses a surface-mount NTC (negative temperature coefficient) thermistor with fast response and high accuracy. The model must meet the automotive-grade requirements, i.e., it can operate at -40℃ to 125℃.

[0054] The sensor probe is attached to the center of the side of the battery casing using highly thermally conductive silicone grease or adhesive. This central location best reflects the average temperature of the electrolyte inside the battery. Good thermal coupling is a prerequisite for ensuring measurement accuracy.

[0055] An NTC thermistor and a precision reference resistor form a voltage divider circuit, converting the resistance-temperature relationship into a voltage-temperature relationship, which is then input to an analog-to-digital converter. The software performs table lookup or formula calculations to obtain the real-time temperature value with an accuracy of ±0.5℃.

[0056] Step S120: Compare the dark current value with a preset reference threshold, and start timing when the dark current value exceeds the reference threshold.

[0057] Based on extensive surveys of dark current and verification through vulcanization experiments on numerous vehicle models, this embodiment sets the baseline threshold at 50 mA. This value is lower than the 100 mA threshold of existing common solutions, aiming to detect vulcanization risks earlier. Most dark current leaks leading to progressive vulcanization typically fall within the 50 mA-200 mA range. Choosing 50 mA as the baseline allows the system to enter a monitoring state at the initial stage of damage accumulation, reflecting a prevention-oriented strategy.

[0058] The baseline threshold needs to be higher than the self-test or capacitor discharge current of most harmless systems when the vehicle is stationary, while being lower than the level of clearly harmful continuous leakage current. Through experimental verification, 50 mA can achieve the optimal balance between sensitivity and immunity, which is the basis for subsequent accurate judgment.

[0059] The comparison between the dark current value and the reference threshold is completed collaboratively by the parameter detection module and the control processing module. Specifically, the high-precision Hall current sensor outputs an analog voltage signal proportional to the dark current value at a period of 500ms. This analog voltage signal is sampled by an analog-to-digital converter and converted into a digital quantity that can be processed by the microcontroller.

[0060] In the control processing module, the software algorithm executes the following process: Read the digital value of dark current I in the current sampling period sample .

[0061] Will I sample With the reference threshold constant I stored in memory threshold (Corresponding to 50 mA) for comparison.

[0062] Produce a boolean output: Flag Exceed =(I sample >I threshold If the value is true, it indicates that the current instantaneous dark current has exceeded the baseline.

[0063] Starting the timer is not simply a stopwatch function, but a controlled state management process, as follows: In microcontroller unit software, a software timer variable, Timer, is typically defined. Cumulative This is used to accumulate the duration of the current dark current exceeding the standard.

[0064] When Flag Exceed The system considers the rising edge of a false-to-true transition to a true-to-false event as the start of a new risk event. At this point, the system executes the Timer. Cumulative =0 (clear) and start accumulating immediately. For example, when the sampling period of 500ms arrives, the Timer... Cumulative Increase by 0.5.

[0065] In real-world automotive environments, dark current may exhibit minute fluctuations. To prevent frequent start-stop cycles of the timer due to slight current fluctuations near the threshold, algorithms typically introduce a hysteresis interval or a short-term neglect mechanism. For example, a true drop in dark current is only considered valid and timing may be paused if the dark current remains below the threshold for 2-3 consecutive sampling periods (i.e., 1-1.5 seconds); otherwise, brief fluctuations will not interrupt the accumulation.

[0066] Once the timer starts, Timer Cumulative The value will be retained until the dynamic threshold is reached or the value is cleared by a reset command at the end of a complete repair cycle. Even if the dark current returns to normal after exceeding the limit for 25 minutes, the timer will retain its current value as long as the dynamic threshold is not reached, waiting for the next dark current exceedance to continue accumulating.

[0067] Here, through high-sensitivity reference threshold setting, reliable analog-to-digital conversion and comparison, and interference-resistant timing management, potentially risky dark current states are identified and marked from the continuous time stream, providing accurate and stable cumulative time input for subsequent dynamic duration determination based on battery health status values ​​and temperature.

[0068] Step S130: Based on the currently acquired battery health status value and temperature value, dynamically determine a corresponding duration threshold.

[0069] The input for this step depends on the battery health status value and temperature value synchronously collected in step S110.

[0070] The system has a pre-stored SOH-temperature-duration threshold mapping model that has been calibrated through a large number of experiments. This model is stored in the memory of the control processing module in the form of a lookup table or algorithm function.

[0071] Referring to Table 1, the core rules of the dynamic threshold matrix have been clearly quantified under the reference temperature conditions: Table 1: Correspondence Table of SOH-Temperature-Duration Threshold Mapping Model Temperature, as a key variable, is used to adjust the aforementioned baseline threshold in real time, as detailed below: When the temperature is below -20℃, the battery's internal resistance increases sharply, the electrolyte activity decreases, and the harmfulness of the same dark current increases significantly. At this time, the dynamic algorithm will activate a low-temperature sensitive strategy, which can directly use the 25-minute threshold corresponding to the SOH < 60% range, ignoring the current actual SOH value, or multiply the threshold of the current SOH range by a compensation coefficient less than 1.

[0072] In a more refined model, this mapping could be a continuous function based on SOH and temperature, or a high-resolution lookup table. For example, the system could interpolate between adjacent SOH-threshold curves based on real-time temperature, making the threshold more accurate in response to temperature variations.

[0073] In the control processing module, the threshold is dynamically determined according to the following process: Obtain the latest sampled and calculated SOH current and Temp current .

[0074] First, determine Temp. current If the temperature is below the low temperature compensation threshold, then the preset low temperature protection threshold will be output directly.

[0075] If the temperature is normal, then use SOH. current The index is used to query the pre-stored SOH-threshold mapping table. Since SOH is a continuous value, the query process involves: directly determining SOH. current If the battery health status falls within a preset range in Table 1 above, return the corresponding dynamic duration threshold T. dynamic_threshold The system can store denser SOH-threshold correspondence points, when SOH current When the threshold lies between two storage points, a more accurate threshold is calculated using linear interpolation to improve adaptability; the final calculated or queried T... dynamic_threshold The output serves as the criterion for judgment in step S140.

[0076] Here, by binding the time threshold to real-time SOH, older batteries receive strict protection, while newer batteries are spared from interference, thereby reducing the false trigger rate to below 0.3%. By introducing temperature compensation, the system can automatically identify extreme environments and adjust the protection strategy, ensuring protection effectiveness across the entire temperature range from -40℃ to 85℃ and improving the robustness of the solution.

[0077] Step S140: When the duration of the dark current value exceeding the baseline threshold reaches the duration threshold, a sulfidation risk is determined and a repair instruction is triggered.

[0078] During system operation, two logical conditions need to be continuously and in parallel monitored: Condition A: Whether the dark current value is consistently higher than the 50 mA reference threshold. Here, if the dark current occasionally falls below the threshold during the timing period, the timer may be paused or reset, depending on the specific algorithm optimization. Condition B: Whether the accumulated value of the timer starting from step S120 has reached or exceeded the duration threshold dynamically calculated by step S130 based on the latest SOH and temperature.

[0079] The system makes a final decision only when both conditions A and B are true: determining that the battery is suffering from continuous dark current damage, i.e., there is a risk of sulfation. At this point, the system generates a definite repair command signal. This dual-gate determination mechanism, which combines a baseline threshold with dynamic duration, effectively distinguishes between harmless long pulses such as the communication current of the gateway module lasting tens of seconds when the vehicle is locked and the current of the delayed shutdown of the air conditioning fan, and DC leakage current lasting tens of minutes or more caused by actual line leakage or module failure. Testing has verified that this dual-gate determination mechanism controls the system's false trigger rate to below 0.3%, achieving a reliability improvement of over 30 times compared to the 10%-15% false trigger rate of the static threshold scheme.

[0080] Step S150: In response to the repair command, determine one of multiple repair strategies based on the different preset ranges in which the battery health status value is at the time of triggering.

[0081] Once the risk is accurately identified (i.e., the three-dimensional dynamic threshold matrix of SOH-dark current-temperature determines that the triggering conditions are met), the system immediately and seamlessly switches from monitoring mode to the hierarchical and adaptive repair phase.

[0082] The system firmware pre-stores a strategy library containing multiple complete repair processes. Each strategy is a deeply optimized independent program module that not only defines the intensity and duration of the repair but also precisely specifies the detailed parameters and action sequence of the entire repair process. These parameters and sequences are specifically designed based on the physicochemical characteristics of batteries with different degrees of sulfation.

[0083] Once a repair command is triggered, the system immediately locks the battery health status value at the moment of triggering, ensuring the transient nature and objectivity of the decision-making benchmark and avoiding policy mismatch caused by continued changes in battery status during the decision-making process. Subsequently, the main control unit matches and calls the corresponding preset policy from the policy library based on which preset interval the locked battery health status value falls into. This mapping relationship is the basis for the system's adaptive behavior, and its core decision-making logic is as follows: If the SOH is locked below 60%, the system determines that the battery is in a state of severe sulfation or deep aging. At this time, the first repair strategy is invoked: a low-frequency sweep of 1kHz-5kHz is used to decompose large-size crystals, a high-amplitude pulse current corresponding to 0.08 times the rated capacity (e.g., 8A for a 100Ah battery) is applied, and a 2s replenishment + 0.5s pulse enhancement synergy sequence is executed. At the same time, the dark current monitoring threshold is most sensitive in this state (triggered after 25 minutes), and regardless of whether the temperature is below -20℃, the synergy mode including replenishment will be forcibly activated, aiming to strongly impact and transform the materials of the severely sulfated plates.

[0084] If the system locks in a state where 60% ≤ SOH < 80%, it determines that the battery is in a state of moderate sulfation or clear degradation. At this point, the second repair strategy is invoked: a frequency sweep is performed using the 5kHz-8kHz band, with the pulse amplitude dynamically calculated based on the capacity, executing standard coordinated timing. The dark current trigger reference duration for this setting is 30 minutes, which is the reference setting in the three-dimensional matrix.

[0085] If the State of Harm (SOH) is locked at ≥80%, the system determines that the battery is in good health, and this trigger is caused by non-persistent dark current loss. At this point, the third repair strategy is invoked for minimal intervention and preventative maintenance. The main actions are simply logging the event and automatically increasing subsequent monitoring frequency, or executing maintenance repair pulses at low intensity, such as using higher frequency, narrower pulse widths to create disturbances. The aim is to slightly suppress potential early sulfation nuclei without increasing the battery's burden. The dark current trigger threshold is also extended to 40 minutes, reducing false triggering interference from healthy batteries.

[0086] The differences between each strategy go beyond simple scaling of pulse frequency and intensity; rather, they involve the coordinated setting of parameters across the entire pulse-power-temperature-monitoring chain. Deep repair strategy: Maximum energy input, more frequent frequency sweep cycles, and the most stringent temperature rise monitoring and control closed loop to prevent overheating risks during the repair process. For example, when the temperature rise is ≥2℃, the frequency sweep cycle is automatically adjusted to 3 times / 2 seconds. Standard repair strategy: All parameters are at an optimized balance point, aiming to ensure the best ratio of energy consumption to safety while repairing efficiently.

[0087] Mild maintenance strategy: Apply almost no significant electrical stress, focusing primarily on monitoring and recording.

[0088] This step, through transient SOH locking, interval mapping, and invoking preset strategy modules, ensures that the intensity, method, and energy input of the repair action are strictly matched with the current sulfation level of the battery. It provides corresponding treatment solutions for batteries in different health states, thereby achieving a balance between maximizing life extension and minimizing unnecessary losses.

[0089] Step S160: Execute the determined repair strategy.

[0090] Based on the selected repair strategy, the system immediately configures and activates the reverse desulfurization control module, generating a series of specific electrical excitations at both ends of the battery: Dynamic frequency adaptation: The pulse frequency strictly follows the settings in the strategy library and performs frequency sweeping within the range of 1kHz-10kHz.

[0091] Amplitude-capacity matching: The pulse current amplitude is not a fixed value, but is dynamically calculated according to the formula of battery rated capacity × 0.08.

[0092] Precise waveform control: Generates sharp, narrow pulses with widths ranging from 50μs to 200μs.

[0093] To address the disconnect between the mechanical breakage and electrochemical conversion processes of sulfide crystallization, which leads to low efficiency in lead sulfate microcrystal recrystallization and active material regeneration, the execution process follows a replenishment-pulse coordinated timing sequence. When the repair strategy selected by the system based on the battery health status value at the time of triggering the repair command includes replenishment-coordinated operation requirements, the system will perform the following operations: During the intervals between pulse sequences, the battery is briefly recharged with a small current of approximately 0.1C; This electro-energizing process aims to transform the tiny lead sulfate particles that have been broken up and detached from the electrode by the pulse into reversible active substances in the electrolyte, effectively preventing their recrystallization and adhesion. This closes the loop between the physical breaking and chemical transformation processes, achieving a repair success rate of 89.1%, which is higher than the 54.6% of traditional technologies.

[0094] The entire execution process is under multiple real-time monitoring and feedback adjustments, including temperature rise monitoring and regulation, energy feedback utilization, and connection assurance, as detailed below: The NTC temperature sensor continuously monitors the battery temperature rise. Once a preset safety threshold of ≥2℃ is detected, the main control unit will immediately adaptively adjust the sweep frequency cycle.

[0095] The energy feedback unit integrated in the desulfurization module starts working. The energy feedback unit can recover the residual charge generated by the polarization effect on the plate during the pulse gap and feed it back to the system power supply or for replenishment.

[0096] All high-voltage and high-frequency pulse signals are transmitted through the magnetically integrated module.

[0097] This step involves dynamic pulse generation, coordinated charge conversion, real-time temperature rise control, and energy recycling. It can be fine-tuned based on real-time feedback during execution, thereby completing the repair of battery sulfation damage.

[0098] Step S170: During the execution of the repair strategy, the repair parameters are dynamically adjusted according to the battery's operating conditions.

[0099] While executing the repair strategy determined in step S160, the multi-parameter detection module does not stop working, but instead synchronously collects the real-time temperature, terminal voltage and pulse current feedback of the battery at a higher frequency. These data constitute the basis for dynamic adjustment decisions.

[0100] The system continuously calculates the battery temperature rise ΔT relative to the start of the repair.

[0101] The system's built-in adjustment logic primarily targets and intervenes in real-time on the most critical variables during the repair process: When the battery temperature rise is detected to be ≥2℃ in real time, the system immediately determines that there is an overheating risk. The main control unit will automatically adjust the sweep frequency cycle of the reverse pulse, which directly reduces the energy input per unit time and the intensity of the plate reaction.

[0102] In this way, by controlling the temperature rise during the repair process, the battery temperature is kept within a safe range, thus effectively avoiding the risks of electrolyte water loss, plate expansion, or even thermal runaway caused by overheating.

[0103] During the charging-pulse coordinated cycle, the system monitors the voltage rise rate during the charging phase. If the voltage rises too quickly, it indicates that the battery's accepting capacity is limited or it is close to being fully charged. The system can then dynamically fine-tune the charging current or shorten the charging time. Conversely, it can moderately increase the charging current.

[0104] Dynamic adjustment is not limited to parameter fine-tuning, but also involves adaptive switching of the repair strategy level: When executing the standard repair strategy, if the system detects a very weak battery voltage response and a lack of significant reduction in internal resistance during repair, combined with temperature change trends, it can comprehensively determine that the initial SOH estimate may be inaccurate or that sulfation is stubborn. If there is still no improvement after a period of time, the system automatically and smoothly transitions to the stronger parameters of the deep repair strategy to cope with more complex sulfation states.

[0105] In summary, this application's embodiments enable adaptive adjustment based on battery health status and ambient temperature by dynamically determining the duration threshold. By selecting one of multiple repair strategies from different preset ranges based on the battery health status value at the trigger point, a tiered and matched repair decision is achieved. Based on the specific battery health status value at the risk trigger point, the most suitable strategy is automatically selected from a variety of preset options. Real-time monitoring of the repair process and dynamic parameter adjustments proactively suppress temperature rise within a safe threshold, eliminating overheating risks. In conclusion, through dynamic threshold determination, tiered strategy matching, and closed-loop process control, the continuous dark current sulfation risk of vehicle batteries can be accurately identified, and the desulfation repair strategy can be adaptively adjusted based on the battery health status, simultaneously improving both safety and energy efficiency.

[0106] In some optional embodiments, the determination of one of multiple repair strategies based on different preset ranges of the battery health status value at the time of triggering is specifically as follows: Different repair strategies are determined based on whether the battery health status value is lower than a first preset threshold or is between the first preset threshold and a second preset threshold. The first repair strategy, which is executed when the battery health status value is lower than the first preset threshold, and the second repair strategy, which is executed when the battery health status value is between the first preset threshold and the second preset threshold, differ in the frequency range of the reverse sweep pulse used.

[0107] In this embodiment, based on the boundaries that clearly distinguish different sulfation stages determined by a large number of battery aging curves and sulfide analysis experiments, the first preset threshold and the second preset threshold are quantified as 60% and 80%, respectively. Based on this, the system's built-in repair strategy library contains at least the following three strategies, and their calling logic is as follows: When the system triggers a repair command, if the locked real-time SOH value is less than 60%, the first repair strategy (corresponding to deep protection mode) is invoked. At this time, the battery has entered a deep aging period, with a large amount of sulfation of the active material on the plates. There is a high probability that there are many highly crystalline lead sulfate crystals inside. These large-particle crystals have high mechanical strength and low resonant frequency.

[0108] The reverse frequency sweep pulse used in this strategy focuses on the low-frequency range, specifically set from 1kHz to 5kHz. According to crystal resonance theory, the inherent mechanical resonance frequencies of larger-diameter lead sulfate crystals are mainly distributed in the mid-to-low frequency region. By concentrating the energy of the frequency sweep pulse in the 1kHz-5kHz range, the system can maximize the coupling and superposition of the pulse waveform's spectral components with the resonance frequency band of these stubborn crystals, thereby inducing intense mechanical vibration and stress within the crystals with the highest energy conversion efficiency, achieving efficient fragmentation.

[0109] When the system triggers a repair command, if the locked real-time SOH value meets the condition of 60%≤SOH<80%, the second repair strategy (corresponding to the standard protection mode) is invoked. At this time, the battery is in the stage of moderate aging or early sulfation, and the sulfides on the plates may be mainly medium-sized crystals, accompanied by some newly formed small-sized crystals.

[0110] The strategy employs a reverse frequency sweep pulse, with a sweep frequency range covering the mid-frequency band, specifically set from 5kHz to 8kHz. This range is designed to effectively handle medium-sized sulfides while also addressing some smaller or slightly larger crystals, thus tackling the sulfidation problem with a relatively wide particle size distribution within batteries during the early to mid-stages of aging.

[0111] When the system triggers a repair command, if the real-time SOH value is locked at ≥80%, the third repair strategy (corresponding to the tolerance monitoring mode) is invoked. At this time, the battery is relatively healthy, and sulfation may only be in its early or trace stages. In this state, the system enters monitoring and logging mode and marks this event as a low-risk warning. Alternatively, a high-frequency (above 8kHz) maintenance pulse is executed to slightly disturb the electrode surface and prevent the formation of crystal nuclei; its energy input is very small.

[0112] In summary, through the correlation mapping mechanism between SOH value and frequency sweep interval, the system infers the particle size distribution characteristics of sulfide crystals based on the battery health status value, and then automatically matches the optimal frequency sweep interval with concentrated spectral energy to achieve targeted decomposition. Extensive comparative experimental data show that this precise frequency matching increases the overall decomposition efficiency of lead sulfate crystals from approximately 54.6% using traditional fixed-frequency pulse technology to over 89%, with a corresponding increase in repair success rate to 89.1%. Furthermore, this basic frequency interval can be further adaptively fine-tuned for batteries with different chemical systems to maximize performance in specific scenarios: for example, for porous AGM (adsorbed glass fiber separator) batteries, the optimal resonant frequency may be slightly off, and the system can focus on 3kHz-7kHz; for LFP (lithium iron phosphate) batteries using different electrolytes, it can focus on 5kHz-10kHz. This parameter self-optimization based on battery type allows for adaptation to the three mainstream automotive battery types—lead-acid, AGM, and LFP—without any manual settings.

[0113] In some optional embodiments, both the first repair strategy and the second repair strategy include alternately applying reverse sweep frequency pulses and replenishing current to the battery according to a preset timing sequence.

[0114] First, the system control repair execution module applies a stable small current to the battery for 2.0 seconds to replenish it. The intensity of this replenishing current is usually set to 0.1C.

[0115] Immediately after the precise 2.0-second stop of the replenishment current, the system applies a high-intensity reverse frequency sweep pulse sequence with a duration of 0.5 seconds without delay. This 0.5-second window is for concentrated energy release and physical destruction. The pulse width is controlled between 50 and 200 microseconds to generate rich high-order harmonics. The pulse amplitude is dynamically determined based on the capacity, and the pulse frequency is rapidly scanned within the range specified by the current strategy (e.g., 1k-5kHz or 5k-8kHz) at a sweep frequency cycle of 3 times per 1.5 seconds.

[0116] Within a 0.5-second pulse window, the reverse sweep pulse, with its Fourier spectrum components covering the set frequency band, mechanically resonates with lead sulfate crystals of different particle sizes. This resonance generates large shear and tensile stresses inside the crystals, physically crushing them into submicron-sized or smaller particles.

[0117] Immediately following the pulse, the fragmented lead sulfate crystals possess a high specific surface area and high reactivity. At this point, continuous low-current charging provides a stable electron flow and suitable electrode potential. Under these electrochemical conditions, the crystals more readily undergo reduction reactions, transforming into electrochemically active lead dioxide, thus returning to the battery's active material matrix and participating in normal charge-discharge cycles.

[0118] The tightly coupled timing of the electro-pulse reaction in this embodiment interrupts the recrystallization process from a reaction kinetic perspective. Immediate or continuous electro-pulse application after crushing provides a conversion pathway for the microcrystals towards the active material. Within the 2.5-second cycle, only 0.5 seconds are high-peak-power pulses, while the remaining 2 seconds are low-power electro-pulse application or preparation. This duty cycle naturally moderates the total heat generation during the repair process. Simultaneously, due to the high conversion efficiency, energy is avoided from being wasted in ineffective repeated crushing-recrystallization cycles, thus inherently possessing energy-saving effects.

[0119] In some optional embodiments, the dynamic determination of the corresponding duration threshold specifically means that the duration threshold is negatively correlated with the battery health status value.

[0120] The negative correlation is specifically manifested as follows: the lower the real-time SOH value of the battery (the worse its health status), the shorter the threshold for continuous dark current triggering set by the system; conversely, the higher the SOH value, the longer the duration threshold.

[0121] Example of quantization mapping relationship: When SOH < 60% (severe battery aging), the dark current duration threshold is set to ≤ 25 minutes.

[0122] When 60%≤SOH<80% (moderate battery aging), the dark current duration threshold is set to 30 minutes (baseline value).

[0123] When SOH ≥ 80% (battery condition is good), the dark current duration threshold is extended to ≥ 40 minutes.

[0124] For low-SOH (slow-aging) batteries, a significant amount of internal active material has been lost, internal resistance has increased, and the electrochemical system is fragile. The same amount of dark current results in a higher percentage of lead sulfate deposition per unit time, leading to faster and more severe sulfation damage. Therefore, the system must adopt a more sensitive monitoring strategy and shorten the judgment time to initiate timely repair intervention before further damage deteriorates, preventing irreversible capacity decay.

[0125] For high SOH (healthy) batteries, the internal active materials are sufficient and the internal resistance is low, providing a strong buffer against short-term, occasional dark current interference. Excessive triggering for repair may cause unnecessary energy consumption and micro-interference. Therefore, the system adopts a more lenient monitoring strategy, extending the judgment time. This effectively filters out normal, brief power consumption after the vehicle is turned off, reducing the false trigger rate to a low level and avoiding excessive intervention in healthy batteries.

[0126] In this embodiment, the negative correlation logic is deeply integrated with the SOH quantification model, the repair strategy library, and the three-dimensional linkage system of temperature parameters. Specifically, the SOH value upon which the dynamic threshold adjustment depends comes from the aforementioned dynamic weight fusion calculation model. Shorter duration thresholds trigger stronger deep repair strategies, while longer thresholds only trigger mild maintenance strategies, with trigger sensitivity precisely matched to repair intensity. At extreme low temperatures (e.g., <-20℃), even with high SOH, the system may employ a more sensitive threshold setting to address the issues of decreased battery reactivity and increased sulfation at low temperatures. The negative correlation between the duration threshold and the battery health status value enables the system to dynamically adjust monitoring sensitivity based on the battery's SOH strength, thereby achieving precision in both the prevention and treatment phases of battery life management.

[0127] In some optional embodiments, performing the repair strategy includes applying a reverse frequency sweep pulse to the battery, the amplitude of which is dynamically determined based on the battery's rated capacity. The ratio of the reverse frequency sweep pulse amplitude to the battery's rated capacity is between 0.075 and 0.085.

[0128] Reverse refers to the direction of the pulsed current being opposite to the direction of the regular charging current. During the repair phase, the device causes current to flow into the positive terminal and out of the negative terminal of the battery, forming a reverse electric field. This reverse high-voltage pulse acts on the lead sulfate crystals on the plates, utilizing their electrostriction and resonance effects to physically destroy the crystal lattice structure, causing them to detach from the plates and laying the foundation for subsequent chemical transformation.

[0129] A swept-frequency pulse refers to a pulse signal whose frequency is not fixed, but rather varies cyclically within a predetermined range (e.g., 1kHz to 10kHz) at a certain period (e.g., 3 times / 1.5 seconds). Lead sulfate crystals formed inside a battery have a wide particle size distribution, and crystals of different sizes have their inherent mechanical resonant frequencies. A single, fixed-frequency pulse can only effectively break up crystals of a specific resonant size. Sweeped-frequency technology, through a continuously changing frequency spectrum, can cover a wider range of particle sizes, improving adaptability to different sulfation states and breaking efficiency.

[0130] Rated capacity (unit: Ah) is the nominal value of the amount of electricity that a battery can discharge under standard conditions. As the only input variable for dynamically determining the pulse amplitude, the main consideration is that the larger the capacity of the battery, the larger its plate area, and the stronger the current required to establish a sufficiently strong reverse electric field in the entire plate area in order to achieve a uniform and effective repair effect.

[0131] Dynamic determination means that the pulse amplitude is not fixed in advance, but is calculated in real time by a built-in algorithm based on the rated capacity of the currently connected battery when the system is working.

[0132] The system dynamically sets the sweep pulse amplitude according to the following formula: Pulse amplitude (peak current, unit: A) = Battery rated capacity (unit: Ah) × Fixed proportional coefficient K The fixed proportional coefficient K is an optimized and verified constant, ranging from 0.075 to 0.085, with an optimal K=0.08. For a battery with a rated capacity of 60Ah, the suitable pulse amplitude is: 60Ah × 0.08 = 4.8A. For a battery with a rated capacity of 100Ah, the suitable pulse amplitude is: 100Ah × 0.08 = 8A.

[0133] The ratio range of 0.075-0.085 is set based on the physical principles of the electrochemical reactions of the battery plates and extensive experimental verification, as detailed below: The rated capacity of a battery reflects the total effective area and active material mass of its internal plates; a larger capacity means a larger plate area. To generate a sufficiently strong reverse electric field on a large plate area to effectively break up lead sulfate crystals, the pulse amplitude needs to be increased proportionally.

[0134] The lower limit is set at 0.075 to ensure that the pulsed electric field strength is sufficient to overcome the dielectric strength of lead sulfate crystals and achieve effective fragmentation. If the ratio is too low, the electric field strength will be insufficient, resulting in low repair efficiency.

[0135] The upper limit is set at 0.085 to prevent excessive pulse current from causing excessive gas evolution, shedding of active material from the electrode plates, or harmful temperature rise. This upper limit sets a safety boundary for the repair process.

[0136] By setting the ratio of the reverse sweep pulse amplitude to the battery's rated capacity to between 0.075 and 0.085, the pulse energy can maximize its effect on sulfide decomposition while keeping the stress on the battery body within a safe range.

[0137] In some optional embodiments, the step of dynamically adjusting the repair parameters according to the operating conditions of the battery specifically involves: monitoring the temperature rise of the battery, and increasing the sweep period of the applied reverse sweep pulse when the temperature rise exceeds a set threshold.

[0138] During the execution of the repair strategy, the temperature rise ΔT of the battery during the repair period is monitored in real time. The temperature rise ΔT is defined as the difference between the current temperature value and the initial temperature value of the battery recorded when the repair strategy is started.

[0139] The real-time monitored temperature rise ΔT is compared with a preset safe temperature threshold. Preferably, the safe temperature threshold is 2°C. When it is determined that the temperature rise ΔT reaches or exceeds the safe temperature threshold, a parameter adjustment trigger signal is generated.

[0140] In response to a parameter adjustment trigger signal, the sweep period of the reverse sweep pulse being applied to the battery is automatically increased. Specifically, the sweep period is defined as the time to complete one full frequency scan cycle. In normal operating mode without adjustment trigger, the system uses a first sweep period, for example, completing 3 sweep cycles every 1.5 seconds. When adjustment is triggered, the system switches the sweep period from the first sweep period to a longer second sweep period, for example, completing 3 sweep cycles every 2.0 seconds.

[0141] By extending the frequency sweep cycle, the pulse energy density applied to the battery per unit time is reduced, thereby slowing down the electrochemical reaction rate and ohmic heat generation rate inside the battery, effectively suppressing the battery temperature rise. The dynamic adjustment process constitutes a real-time closed-loop control system, in which the battery temperature serves as the feedback signal and the frequency sweep cycle as the controlled variable. This closed-loop control continues to run until the repair process ends or the temperature rise ΔT falls below the safe temperature threshold. The dynamic adjustment function is achieved collaboratively by the main control unit and the temperature sensing unit in the multi-parameter detection module. This closed-loop dynamic adjustment mechanism effectively solves the safety hazards caused by the lack of temperature rise control. It forcibly controls the battery temperature rise during the repair process within the preset safe threshold, avoiding the risks of electrolyte water loss, plate deformation, or even thermal runaway due to overheating.

[0142] In some alternative embodiments, during the execution of the determined repair strategy, when the reverse sweep pulse is in a shutdown gap or a specific electrical window, residual polarization charge generated on the battery plates due to high-frequency pulse excitation is recovered through an energy feedback unit integrated in the battery connection circuit.

[0143] The detailed implementation method is described below: In terms of circuit topology, the operation of the energy feedback unit is synchronously and precisely controlled by the main control unit. According to a preset pulse timing sequence, the main control unit generates an energy recovery enable signal after the falling edge of each reverse-peaked narrow pulse. This energy recovery enable signal controls the high-speed switching devices in the energy feedback unit to turn on within a microsecond-level delay window after the pulse is turned off. At this time, due to the polarization effect, the terminal voltage of the battery plates is higher than the static open-circuit voltage of the battery, forming a potential difference.

[0144] The energy feedback unit includes a synchronous rectified recovery circuit composed of an inductor and a power switch. When the recovery window is open, the circuit provides a controlled low-impedance path for the aforementioned potential difference, guiding the residual charge on the battery plates to flow out in the form of current. The outflowing charge is preferentially directed to a low-voltage, high-capacity energy storage capacitor for buffering. Subsequently, a high-efficiency DC-DC buck converter regulates the energy stored in the capacitor, converting it into a stable DC voltage. This energy is directly fed back to the device's internal power bus to power internal circuits such as the multi-parameter detection module and the main control unit; or, in subsequent low-current charging phases, it serves as a supplementary energy source to assist external power in injecting charging current into the battery, thereby achieving closed-loop energy utilization.

[0145] By recovering polarization energy, the overall energy recovery rate of a single repair cycle reaches 34.7%, driving the overall energy efficiency ratio of the device to 1.92 Wh / Ah·cycle. Compared to traditional devices without energy recovery design, the overall energy utilization rate of this embodiment is improved by more than 30%. This energy feedback mechanism is applied to pulse repair of vehicle batteries, transforming the repair process from energy consumption to partial energy recycling.

[0146] Exemplary System In one exemplary embodiment of this application, an on-board battery protection system 200 is also provided; please refer to [link to relevant documentation]. Figure 2 , Figure 2 This is a schematic diagram of the architecture of an on-board battery protection system provided in one embodiment of this application. The on-board battery protection system 200 includes a parameter detection module 210, a control processing module 220, and a repair execution module 230. The parameter detection module 210 is used to acquire the battery health status value, dark current value, and temperature value of the battery in real time. The control processing module 220 is connected to the parameter detection module 210 and is used to compare the dark current value with a preset benchmark threshold. When the dark current value exceeds the benchmark threshold, a timer is started. Based on the currently acquired battery health status value and temperature value, a corresponding duration threshold is dynamically determined. When the duration for which the dark current value continuously exceeds the benchmark threshold reaches the duration threshold, a sulfation risk is determined and a repair command is triggered. In response to the repair command, one of multiple repair strategies is determined based on different preset ranges of the battery health status value at the time of triggering. The repair execution module 230 is connected to the control processing module 220 and is used to execute the determined repair strategy. During the execution of the repair strategy, the repair parameters are dynamically adjusted according to the battery's operating conditions.

[0147] The parameter detection module 210 includes a dark current detection submodule with a rated measurement range of ±100A, fully meeting the measurement requirements for vehicle starting peak current and stationary dark current, and a sensitivity of 66mV / A. Within the ±50A range, the nonlinearity error of the dark current detection submodule is less than ±1.5%, and its operating temperature range is -40℃ to 85℃, meeting automotive-grade requirements.

[0148] The parameter detection module 210 also includes a temperature detection submodule and a voltage acquisition and SOH calculation auxiliary submodule. The temperature detection submodule uses a surface-mount NTC thermistor, which is connected in series with a 10 kΩ metal film resistor with an accuracy of 1% and a temperature drift of 50 ppm / ℃ to form a voltage divider circuit. A reference voltage (e.g., 3.3V) is applied, and the voltage at the voltage divider point changes with temperature. This voltage signal is filtered and then sent to another analog-to-digital converter channel. The voltage acquisition and SOH calculation auxiliary submodule adopts a high-impedance design to avoid loading the battery. It consists of two metal film resistors with an accuracy of 0.1% and a temperature drift of 25 ppm / ℃ connected in series, for example, a 100 kΩ and a 10 kΩ resistor in series. The series resistor combination divides the battery terminal voltage to the safe input range of the microcontroller's analog-to-digital converter. A filter capacitor and a transient voltage suppression diode are connected after the voltage divider point to filter out noise and prevent voltage spikes caused by load drops from damaging the analog-to-digital converter.

[0149] The control processing module 220 includes a microcontroller unit, an analog-to-digital converter, a timer / counter, general-purpose input / output, and a memory. Its main software modules include: sensor data acquisition and preprocessing driver, battery health state estimation engine, three-dimensional dynamic threshold matrix logic, and safety monitoring and closed-loop control tasks.

[0150] In the sensor data acquisition and preprocessing driver, the analog-to-digital converter is triggered to sample synchronously with a period of 500ms, and the raw data is subjected to digital filtering, scaling transformation and calibration compensation, repair strategy management and scheduler, PWM and digital output control.

[0151] The battery health state estimation engine can run the aforementioned dynamic weighted fusion calculation model in real time, and calculate and update the SOH value online based on available data sources.

[0152] The three-dimensional dynamic threshold matrix logic is the complete logic for implementing steps S120-S140. It includes continuously comparing the dark current with the 50 mA threshold, managing a high-precision software timer, querying the corresponding dynamic time threshold based on the current SOH and temperature, and making the final risk decision.

[0153] The repair strategy manager and scheduler is used to maintain the repair strategy library. After receiving a repair instruction, it calls the corresponding strategy function according to the SOH value at the time of triggering. The scheduler is responsible for managing the power-up pulse timing state machine.

[0154] The PWM and digital output control dynamically configures the timer according to the parameters of the selected strategy, generates PWM waveforms with specific frequencies, sweep modes and duty cycles, and controls digital signals such as the enable of the power supply circuit and the energy feedback switch.

[0155] The safety monitoring and closed-loop control task continuously calculates the temperature rise ΔT, and when ΔT≥2℃, dynamically modifies the period register value of the PWM timer to achieve safety control by increasing the sweep frequency period.

[0156] The repair execution module 230 converts the weak digital / analog commands issued by the control processing module 220 into physical processes that can act on the battery. The repair execution module 230 includes a power drive and energy management submodule, a reverse frequency sweep pulse generation circuit, a charging current generation circuit, an energy feedback unit, and a magnetic integrated connector.

[0157] The reverse sweep pulse generation circuit is preferably implemented using a half-bridge topology. The core of this circuit consists of two power MOSFETs (preferably IRF3205) and their dedicated driver chip (preferably IR2104). In this topology, the two MOSFETs are alternately turned on under the control of the driver chip. Specifically, when the upper MOSFET is on and the lower MOSFET is off, the positive terminal of the battery is connected to the output node through the upper MOSFET, the pulse transformer, or directly, applying a positive voltage to the battery itself. When the lower MOSFET is on and the upper MOSFET is off, a reverse loop is formed, thereby generating the required reverse pulse across the battery terminals.

[0158] The driver chip receives a PWM control signal from the main control unit. The frequency and duty cycle of this PWM control signal are precisely calculated and dynamically adjusted to determine the following key characteristics of the final output pulse: The pulse base frequency and sweep frequency pattern are controlled by the PWM frequency to achieve a preset sweep frequency within the range of 1kHz to 10kHz, with a typical sweep frequency period of 3 times / 1.5 seconds. The frequency range is designed using Fourier spectrum resonance to match the resonance points of lead sulfate crystals with different particle sizes, and can be optimized for different battery types such as AGM, LFP, and lead-acid to improve adaptability to specific scenarios.

[0159] The width of the output pulse is precisely controlled within a narrow pulse range of 50μs to 200μs by adjusting the duty cycle of the PWM signal to form an efficient spiked pulse waveform.

[0160] The pulse current amplitude is dynamically adapted by the duty cycle of the PWM signal and the circuit operating voltage. The core calculation basis is the rated capacity of the battery × 0.08. For example, for 60Ah, 70Ah and 100Ah batteries, the target pulse amplitude is dynamically adapted to 4.8A, 5.6A and 8A respectively.

[0161] To ensure safety and efficiency, the frequency sweep period is not fixed. The system monitors the battery temperature rise in real time. When the temperature rise exceeds 2°C, the main control unit will automatically adjust the timing of the PWM signal, thereby dynamically increasing the frequency sweep period, for example, from 3 times / 1.5 seconds to 3 times / 2 seconds, to reduce the energy input per unit time and achieve closed-loop temperature rise control.

[0162] To achieve amplitude control of capacity × 0.08, one of the following methods can be selected: 1) Adjusting the bus voltage: Use an adjustable DC-DC step-down module to power the half-bridge circuit. The microcontroller unit controls the output voltage of the module through DAC or PWM, thereby changing the peak voltage of the pulse, and then determining the current amplitude through the load; 2) Multi-stage parallel connection and switching control: Connect multiple identical MOSFETs in parallel. The microcontroller unit controls the number of parallel connections to effectively change the on-resistance, thereby adjusting the current amplitude.

[0163] For scenarios requiring stable small currents, such as power replenishment, the current generation circuit employs a linear constant current source solution. For example, an operational amplifier and a power MOSFET can be used to construct a voltage-controlled current source. The microcontroller unit outputs a precise voltage reference via a DAC; this voltage, divided by the resistance of a sampling resistor, determines the magnitude of the constant current. This approach results in low ripple and precise control.

[0164] The energy recovery unit is integrated between the output node of the half-bridge and the power bus. Between the midpoint of the half-bridge and the positive bus, a buck-boost or flyback topology consisting of a power inductor, a fast recovery diode, and a controlled MOSFET is connected. When energy recovery is needed, the microcontroller unit controls the MOSFET to operate in a high-frequency switching mode, pumping the inductor current into the bus capacitor to achieve energy recovery.

[0165] The magnetic integrated connector facilitates easy installation while achieving zero-fluctuation contact under vibration to ensure efficient transmission of repair pulses. It includes a strong magnetic adsorption component, a foolproof structure, a buffer component, and a conductive layer.

[0166] The strong magnetic adsorption assembly uses sintered NdFeB permanent magnets. The magnets are radially magnetized and designed to concentrate the magnetic field onto the contact surface, providing a vertical adsorption force of at least 8 kgf, allowing the connector to firmly attach to the battery terminals. At the interface between the connector and the electrodes, there is an asymmetrical pear-shaped guide groove and a matching contact arrangement. For example, the upper width of the guide groove is 8 mm, and the lower width is 12 mm, forming a trapezoid. The corresponding metal contact plate is also trapezoidal. Only when the connector is aligned with the electrodes in the correct orientation can the contact plate fully embed into the guide groove and completely adhere to the electrode surface. Any attempt to insert in the wrong direction or at an incorrect angle will fail due to the interference of the physical shape, eliminating the risk of short circuits caused by accidental reversal of the positive and negative terminals.

[0167] In this embodiment, the buffer assembly is a dual-spring wide-frequency vibration damping system. The first-stage spring, a low-frequency, large-stroke compression coil spring with a stroke of approximately 5 mm, is installed between the connector body and internal moving parts. It primarily handles low-frequency (0.5Hz-2Hz), large-amplitude impacts and low-frequency swaying generated when the vehicle travels over potholes and speed bumps. Through its large deformation, it absorbs and dissipates the energy of these low-frequency impacts, preventing the connector from rigidly colliding or detaching. The second-stage spring, a high-frequency, low-pressure buffer, is a precision spring with an elastic coefficient of 0.5 N / mm, directly linked to the electrical contacts. It primarily handles continuous high-frequency (2Hz-10Hz), small-amplitude vibrations generated by engine idling and minor road bumps. It provides stable and smooth contact pressure, ensuring that the electrical contacts remain firmly against the battery electrode surface, preventing momentary separation or fluctuations in contact pressure due to high-frequency vibrations. These two springs, mechanically connected in parallel or series, constitute a composite vibration isolation system that effectively covers the entire frequency range of vehicle vibrations, minimizing the impact of external vibrations on the electrical contact interface.

[0168] The conductive layer is a low-resistance gold-plated layer. Gold has good conductivity, excellent oxidation resistance, and corrosion resistance, which helps to increase the effective contact area. Through optimized electroplating process, the contact resistance of the gold-plated contacts is controlled to be less than or equal to 5mΩ. More importantly, after a 24-hour composite vibration test simulating the most severe road vibration environment, the fluctuation range of this contact resistance is less than ±0.15mΩ. The repair pulse has very low energy loss during transmission, the transmission efficiency is improved by more than 83%, and the connection status is stable and reliable.

[0169] Exemplary control terminal In one exemplary embodiment of this application, a vehicle is also provided, see [link to example]. Figure 3 , Figure 3 This application provides a schematic diagram of a vehicle architecture, the vehicle including: a memory and a processor, the memory storing a computer program, the processor executing the computer program to perform the steps in the on-board battery protection method according to various embodiments of this application described above.

[0170] The vehicle includes a processor, memory, network interface, and input devices connected via a system bus. The vehicle's processor provides computing and control capabilities. The vehicle's memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The vehicle's network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it follows the steps of the on-board battery protection method according to various embodiments of this application as described in the above embodiments.

[0171] The processor may include the main processor, as well as baseband chips, modems, etc.

[0172] It is understood that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0173] It is understood that the memory in the embodiments of this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may be random access memory (RAM). It should be noted that the memory in the devices and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0174] Input devices may include devices that receive data and information input by the user, such as keyboards, mice, cameras, scanners, light pens, voice input devices, touch screens, pedometers, or gravity sensors.

[0175] Output devices may include devices that allow information to be output to the user, such as displays, printers, speakers, etc.

[0176] The communication interface may include any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.

[0177] The vehicle may also include a display component and a voice component. The display component may be an LCD screen or an e-ink screen. The vehicle's input device may be a touch layer covering the display component, or a button, trackball, or touchpad set on the vehicle body, or an external keyboard, touchpad, or mouse, etc.

[0178] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the vehicle to which the present application is applied. A specific vehicle may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0179] Exemplary computer program products and storage media In addition to the methods and devices described above, the vehicle battery protection method provided in the embodiments of this application can also be a computer program product, which includes computer program instructions. When the computer program instructions are run by a processor, the processor causes the processor to perform the steps in the vehicle battery protection method according to various embodiments of this application as described in the "Exemplary Methods" section above.

[0180] The aforementioned computer program product can be implemented through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied in a computer storage medium; in another optional embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0181] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0182] Furthermore, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor of the steps in the vehicle battery protection method according to various embodiments of this application as described in the "Exemplary Methods" section above.

[0183] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0184] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0185] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the solutions provided in the embodiments of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for protecting a vehicle-mounted battery, characterized in that, include: The battery health status value, dark current value, and temperature value of the battery are acquired in real time. The dark current value is compared with a preset reference threshold, and timing begins when the dark current value exceeds the reference threshold; Based on the currently acquired battery health status value and temperature value, a corresponding duration threshold is dynamically determined; When the duration for which the dark current value exceeds the baseline threshold reaches the duration threshold, a sulfidation risk is determined and a repair instruction is triggered. In response to the repair instruction, one of multiple repair strategies is determined based on the different preset ranges in which the battery health status value is at the time of triggering; Implement the determined repair strategy; During the execution of the repair strategy, the repair parameters are dynamically adjusted according to the operating conditions of the battery.

2. The vehicle-mounted battery protection method according to claim 1, characterized in that, The method of determining one of multiple repair strategies based on the different preset ranges of the battery health status value at the time of triggering is as follows: Different repair strategies are determined based on whether the battery health status value is lower than a first preset threshold or is between the first preset threshold and a second preset threshold. The first repair strategy, which is executed when the battery health status value is lower than the first preset threshold, and the second repair strategy, which is executed when the battery health status value is between the first preset threshold and the second preset threshold, differ in the frequency range of the reverse sweep pulse used.

3. The vehicle-mounted battery protection method according to claim 2, characterized in that, Both the first repair strategy and the second repair strategy include alternately applying reverse sweep frequency pulses and replenishing current to the battery according to a preset timing sequence.

4. The vehicle-mounted battery protection method according to claim 1, characterized in that, The dynamic determination of the corresponding duration threshold specifically means that the duration threshold is negatively correlated with the battery health status value.

5. The vehicle-mounted battery protection method according to claim 1, characterized in that, The repair strategy includes applying a reverse frequency sweep pulse to the battery, wherein the amplitude of the reverse frequency sweep pulse is dynamically determined based on the rated capacity of the battery.

6. The vehicle-mounted battery protection method according to claim 5, characterized in that, The ratio of the reverse sweep pulse amplitude to the rated capacity of the battery is between 0.075 and 0.

085.

7. The vehicle-mounted battery protection method according to claim 1, characterized in that, The specific steps of dynamically adjusting the repair parameters based on the battery's operating conditions are as follows: Monitor the temperature rise of the battery, and when the temperature rise exceeds a set threshold, increase the sweep period of the applied reverse sweep pulse.

8. The vehicle-mounted battery protection method according to claim 1, characterized in that, The method further includes: during the execution of the repair strategy, recovering residual polarization charge on the battery plates through an energy feedback unit integrated in the battery connection circuit.

9. A vehicle-mounted battery protection system for implementing the vehicle-mounted battery protection method according to any one of claims 1 to 8, characterized in that, The on-board battery protection system includes: The parameter detection module is used to acquire the battery health status value, dark current value and temperature value of the battery in real time; The control processing module, connected to the parameter detection module, is used to compare the dark current value with a preset reference threshold, and start timing when the dark current value exceeds the reference threshold. Based on the currently acquired battery health status value and the temperature value, a corresponding duration threshold is dynamically determined. When the duration for which the dark current value exceeds the reference threshold reaches the duration threshold, a sulfation risk is determined and a repair command is triggered. In response to the repair command, one of multiple repair strategies is determined based on the different preset ranges in which the battery health status value is located at the time of triggering. The repair execution module is connected to the control processing module and is used to execute the determined repair strategy, and dynamically adjust the repair parameters according to the operating conditions of the battery during the execution of the repair strategy.

10. The vehicle-mounted battery protection system according to claim 9, characterized in that, The repair execution module includes a magnetic integrated connector for establishing an electrical connection with the electrodes of the battery; the magnetic integrated connector includes: Strong magnetic adsorption components are used to provide magnetic positioning force; A foolproof structure is provided at the insertion interface of the magnetic integrated connector to prevent reverse connection; The buffer assembly includes a first spring for buffering low-frequency vibrations and a second spring for buffering high-frequency vibrations; and, A conductive layer covers the electrical contact surface of the magnetic integrated connector and is used to contact and conduct electricity with the electrodes of the battery.

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