Battery safety charging method and charging device

Abstract

The application discloses a battery safety charging method and a charging device. The method comprises the following steps: in the process of direct current charging of a charging target, a disturbance current step change is applied to an output current, and voltage response data caused by the current step change of the charging target is synchronously collected; based on a dynamic correlation relationship between the current step change and the voltage response data, a battery direct current internal resistance detection value of the charging target is calculated; a dynamic direct current internal resistance threshold range matched with attribute characteristics of the charging target is obtained; a overrun proportion index is calculated according to the battery direct current internal resistance detection value and the dynamic direct current internal resistance threshold range; and corresponding graded protection control strategies are executed according to the overrun proportion index. Through active electrical excitation detection and dynamic threshold evaluation, the application realizes the identification of internal hidden dangers of the battery by the charging device, and guarantees the continuity of the charging service on the premise of guaranteeing active safety.

Description

Technical Field

[0001] This invention relates to the field of new energy vehicle charging safety monitoring technology, and in particular to a battery safe charging method and charging equipment. Background Technology

[0002] With the rapid development of new energy vehicles, the number of electric vehicles on the road is increasing year by year, and the scale of charging infrastructure construction is also expanding. As a key connection point between vehicles and the power grid, the operational safety of charging piles directly affects the safety of vehicles, batteries, and the personal and property safety of users. In recent years, fires, explosions, and electric shocks caused by electrical faults during charging, battery thermal runaway, equipment aging, and untimely maintenance have occurred frequently, posing potential risks to the industry's development. Especially in public charging stations, high-power fast charging, and integrated photovoltaic-storage-charging scenarios, the charging power is greater and the operating environment is more complex, placing higher demands on safety monitoring and risk warning. Therefore, establishing a comprehensive new energy vehicle charging safety monitoring system is not only a necessary measure to ensure user charging experience and public safety, but also an important foundation for promoting the sustainable development of the new energy vehicle industry.

[0003] However, current mainstream charging piles primarily operate based on the vehicle's BMS (Battery Management System) charging requests (i.e., current demand) and state of charge. During charging, they only perform start-stop control, failing to effectively monitor and protect against real-time safety conditions within the battery cells (such as abnormal temperature or DC resistance). This lack of monitoring of cell-level safety indicators constitutes a significant risk point in the charging process and makes it difficult to meet the increasingly complex charging safety requirements. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a battery safe charging method and charging device, so as to realize the active safety protection of the battery by the charging device.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A method for safely charging a battery, comprising: During the DC charging process of the charging target, a perturbation current step change is applied to the output current, and the voltage response data of the charging target caused by the current step change is collected simultaneously. Based on the dynamic correlation between the current step change and the voltage response data, the detected value of the battery DC internal resistance of the charging target is calculated. Obtain a dynamic DC internal resistance threshold range that matches the attribute characteristics of the charging target; The over-limit ratio index is calculated based on the detected value of the battery's DC internal resistance and the dynamic DC internal resistance threshold range. Based on the aforementioned over-limit ratio indicator, the corresponding graded protection and control strategy is executed.

[0006] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows: A charging device includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the various steps of the above-described battery safe charging method.

[0007] The beneficial effects of this invention are as follows: By actively applying a step change in the output current during the charging process and simultaneously collecting voltage response data to calculate the detected value of the battery's DC internal resistance, and then combining the dynamic DC internal resistance threshold range matched with the vehicle's attribute characteristics to calculate the over-limit ratio index, a graded protection control strategy is executed accordingly. By using active current excitation to obtain the battery's internal impedance information and introducing a threshold dynamically matched with the vehicle's characteristics as a relative evaluation benchmark, this invention solves the problem in the prior art where charging equipment only acts as a passive energy transmission unit and lacks the ability to independently perceive and evaluate the battery's internal impedance state. This enables the charging equipment to independently and actively verify the battery's safety state, effectively avoiding the safety risks caused by blind spots in the vehicle's battery management system monitoring or the singleness of judgment by using fixed thresholds. It ensures active charging safety while also taking into account the continuity of equipment operation. Attached Figure Description

[0008] Figure 1 A flowchart illustrating the steps of a battery safe charging method provided in an embodiment of the present invention; Figure 2 A flowchart of battery DC internal resistance detection and graded protection provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a charging device provided in an embodiment of the present invention. Detailed Implementation

[0009] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0010] The following describes a battery safe charging method according to the present invention, with reference to the appendix. Figure 1 This includes steps 110 to 150.

[0011] Step 110: During the DC charging process of the charging target, a perturbation current step change is applied to the output current, and the voltage response data of the charging target caused by the current step change is collected simultaneously.

[0012] The charging equipment maintains a connection with the charging target (e.g., an electric vehicle). Unlike traditional charging modes that passively follow BMS commands, the charging equipment acts as an active probe, artificially creating a dynamic change in current (i.e., a perturbation current step change) during the charging process. Due to the internal impedance of the battery, this sudden change in current inevitably leads to a corresponding change in the battery terminal voltage. The charging equipment synchronously collects the voltage response data at this moment through a communication interface or built-in sensors, establishing the original data foundation for the electrical excitation and physical response.

[0013] Step 120: Based on the dynamic correlation between current step change and voltage response data, calculate the detected value of the battery DC internal resistance of the charging target.

[0014] Utilizing Ohm's law in physics, the dynamic correlation is manifested as the ratio of voltage change to current change. The charging device processor uses the current step change and voltage response data to directly calculate the current battery DC internal resistance value through ratio calculation, thus achieving real-time acquisition of the battery's DC internal resistance during charging.

[0015] Step 130: Obtain the dynamic DC internal resistance threshold range that matches the attribute characteristics of the charging target.

[0016] To determine whether the detected internal resistance is abnormal, a reference standard is needed. Considering that the internal resistance benchmarks of batteries vary for different vehicle models and different aging levels, this step does not use a fixed threshold. Instead, it matches a dynamic reference range, i.e., a dynamic DC internal resistance threshold range, based on the attributes of the charging target (such as vehicle model, mileage, etc.).

[0017] Step 140: Calculate the over-limit ratio index based on the battery DC internal resistance detection value and the dynamic DC internal resistance threshold range.

[0018] A quantitative risk assessment is conducted. The measured DC internal resistance value of the battery is compared with the upper limit of the dynamic DC internal resistance threshold range to calculate the degree of deviation from the normal range, i.e., the over-limit ratio. This index transforms the physical resistance value into a logical risk level value.

[0019] Step 150: Execute the corresponding graded protection and control strategy based on the over-limit ratio index.

[0020] Based on the quantified risk level (exceeding the limit ratio), the charging equipment adjusts its control logic and executes corresponding protection actions.

[0021] This application calculates the battery's DC internal resistance detection value by actively applying a step change to the output current during charging and simultaneously collecting voltage response data. Then, it calculates the over-limit ratio index by combining this with a dynamic DC internal resistance threshold range that matches the vehicle's attribute characteristics, and executes a graded protection control strategy accordingly. By using active current excitation to obtain battery internal impedance information and introducing a threshold dynamically matched to vehicle characteristics as a relative evaluation benchmark, this application solves the problem in existing technologies where charging equipment only acts as a passive energy transmission unit and lacks the ability to independently perceive and evaluate the battery's internal impedance state. It achieves independent active verification of the battery's safety state by the charging equipment, effectively avoiding safety risks caused by blind spots in the vehicle's battery management system monitoring or the simplistic use of fixed thresholds for judgment. This ensures active charging safety while maintaining the continuity of equipment operation.

[0022] In one embodiment of this application, step 150, which involves performing graded protection based on the over-limit ratio index, includes steps 151 to 153.

[0023] Step 151: When the detected over-limit ratio is less than or equal to 0, maintain the current normal charging logic.

[0024] At this time, the detected value of the battery's DC internal resistance does not exceed the upper limit of the dynamic DC internal resistance threshold range, indicating that the battery impedance is within the normal statistical range under the same vehicle model and operating conditions. The system determines that it is in a safe state, so it maintains the original charging power output to ensure charging efficiency.

[0025] Step 152: When the over-limit ratio is detected to be greater than 0 and less than or equal to 100%, the output current is reduced to 50% of the original operating current value.

[0026] At this point, although the measured internal resistance exceeded the upper limit of the normal range, the excess was within 100% (i.e., not reaching the severity of doubling). This may indicate slight inconsistency in battery aging or a slight increase in connection impedance, and the risk is relatively controllable. To balance safety and user charging needs, the system adopts a current reduction strategy, lowering the output current to half of the original operating current value before the disturbance was applied. By reducing the current, Joule's law (Q=I) can be applied. 2 Rt significantly reduces heat generation inside the battery and at contact points, preventing heat accumulation from escalating risks while maintaining the continuity of charging services.

[0027] Step 153: When the over-limit ratio is detected to be greater than 100%, immediately stop the output current.

[0028] At this point, the measured internal resistance exceeds 100% of the upper limit of the normal range, indicating a possible serious fault within the battery, such as a micro-short circuit, overheating, or loose connection. Continuing to charge could easily trigger thermal runaway. Therefore, the system executes the highest priority shutdown protection, immediately cutting off power output and physically blocking energy input to ensure absolute safety in extreme circumstances.

[0029] In this way, intelligent decisions are made based on the severity of the proportion of risk quantification indicators exceeding limits, balancing maintaining normal operation, reducing current and suppressing heat, and cutting off power to stop losses. While effectively curbing the risk of battery thermal runaway, the availability of charging services is preserved to the greatest extent, avoiding overprotection and a decline in user experience caused by minor data fluctuations.

[0030] In one embodiment of this application, step 154 ​​is also included, which can be performed when determining the over-limit ratio index in step 153.

[0031] Step 154: When the detected excess ratio is greater than 100%, push a security warning message to the user terminal.

[0032] The charging equipment generates an early warning message containing the fault type and suggested measures, and pushes it to the user's mobile terminal via the communication network.

[0033] In this way, remote communication is used to synchronize the fault status of the charging equipment with the information of the user terminal; this ensures that when the charging equipment performs shutdown protection, the user can obtain specific information about the battery abnormality in real time, so that the user can know the reason for the current charging termination and take corresponding inspection measures.

[0034] In one embodiment of this application, the DC charging process in step 110 includes steps 101 to 103.

[0035] Step 101: Read the charging status parameters.

[0036] The charging equipment reads the BMS data reported by the electric vehicle in real time to obtain the current charging status parameters.

[0037] Step 102: Determine whether the state of charge in the charging state parameters is within the range of 60% to 80%.

[0038] The system performs a numerical range determination on the read state of charge.

[0039] Step 103: If yes, then determine that the charging state parameters meet the preset detection trigger conditions, and apply a perturbation current step change to the output current.

[0040] When the state of charge is in the range of 60% to 80%, the system activates the battery DC internal resistance detection step.

[0041] This method establishes the optimal time window for internal resistance detection. From an electrochemical perspective, when a lithium battery's state of charge (SOC) is between 60% and 80%, its chemical and concentration polarizations are relatively stable. At this point, the ohmic internal resistance measured with applied perturbation best reflects the battery's health. Furthermore, this stage typically falls within the later stages of constant current charging, resulting in stable current output. This approach avoids data errors caused by measurements performed at low or high SOC levels, ensuring the accuracy and reliability of DC resistance detection data, while also enabling seamless, opportunistic detection.

[0042] In one embodiment of this application, step 110 involves applying a perturbation current step change to the output current, including steps 111 to 112.

[0043] Step 111: Control the output current to gradually decrease from the original operating current value during DC charging to the preset minimum test current value according to the preset decreasing rate.

[0044] Instead of directly cutting off the current, the charging device controls the power module to linearly reduce its output current from its current operating current value at a controlled slope (preset rate of decrease) until it reaches a lower value (minimum test current value, such as 0A). This gradual reduction prevents sudden current surges from causing excessive stress on the power grid and the battery's internal chemistry.

[0045] Step 112: After reaching the minimum test current value, control the output current to gradually increase at a preset rate to restore it to the original working current value.

[0046] After a brief or momentary pause at the lowest point, the device controls the current to rise again at a controlled slope (preset rise rate) until it returns to the original charging current level and continues normal charging.

[0047] In this way, an engineering-executable and safe perturbation step is defined. Compared to an ideal hard step signal, this perturbation step, with the current gradually adjusted according to a preset rate, can generate the current difference needed to calculate the internal resistance while avoiding the risks of arcing or relay sticking caused by hard switching. While ensuring the availability of the measured physical quantities, it maximizes the electrical safety of the testing process and the lifespan of the equipment.

[0048] In one embodiment of this application, obtaining the dynamic DC internal resistance threshold range in step 130 includes steps 131 to 132.

[0049] Step 131: If the charging target is an electric vehicle, the vehicle attribute characteristics are determined by collecting the electric vehicle's cumulative mileage, vehicle age, battery type, battery charge-discharge cycle count, and current ambient temperature.

[0050] The charging equipment collects the aforementioned multi-dimensional operating parameters through BMS communication messages or platform data interaction. These parameters are key factors affecting battery internal resistance aging (e.g., vehicle age, mileage, battery type, charge / discharge cycle count, and charging ambient temperature).

[0051] Step 132: Obtain the dynamic DC internal resistance threshold range based on vehicle attribute characteristics.

[0052] The system uses the collected attribute features to find or calculate the corresponding normal internal resistance range.

[0053] In this way, a multi-dimensional battery health profile is constructed. Battery internal resistance is not a static constant, but a variable that changes with aging and environment. By introducing key factors such as mileage and temperature, a single fixed threshold is evolved into a context-aware dynamic threshold. This effectively eliminates interference caused by reasonable increases in internal resistance due to normal battery aging (increased mileage) or environmental changes (low temperature), enabling accurate differentiation between normal degradation and abnormal faults, and significantly reducing the false alarm rate.

[0054] In one embodiment of this application, the process of obtaining the dynamic DC internal resistance threshold range in step 130 further includes steps 133 to 134.

[0055] Step 133: Upload the battery DC internal resistance detection value and vehicle attribute characteristics to the cloud management platform.

[0056] The charging equipment acts as an edge computing node, uploading the collected measured data and vehicle identification tags to the cloud, which has big data processing capabilities.

[0057] Step 134: Receive the dynamic DC internal resistance threshold range issued by the cloud management platform.

[0058] The cloud platform uses massive amounts of historical data from the same vehicle model for training and statistical analysis to calculate the reasonable range under the given conditions and then sends the data to the charging equipment.

[0059] This approach enables a cloud-edge collaborative security monitoring architecture. Leveraging the massive data throughput and machine learning algorithms of the cloud, more accurate group characteristic thresholds can be generated than local static databases. By using large-scale group data of the same vehicle model to calibrate the health assessment standards for individual vehicles, the dynamic DC internal resistance threshold range achieves statistically significant accuracy, solving the problem of data silos for single-point devices.

[0060] In one embodiment of this application, the specific calculation formula for the battery DC internal resistance detection value in step 120 includes step 121.

[0061] Step 121: Using the formula The measured DC internal resistance value of the battery for the charging target is calculated.

[0062] Among them, R measure ΔU represents the measured DC internal resistance (DCR) of the battery, ΔU represents the measured voltage change, and ΔI represents the corresponding current change. Specifically, ΔI is the difference between the original operating current and the minimum test current, and ΔU is the difference in the battery terminal voltage response at the corresponding moment.

[0063] This approach clarifies the calculation rules for physical quantities. Based on the definition of DC internal resistance (the ratio of voltage change to current change), this calculation method eliminates the interference of battery open-circuit voltage (OCV) and directly extracts the ohmic internal resistance characteristics. It provides a simple, robust, and computationally inexpensive method for obtaining internal resistance, suitable for real-time operation in the embedded processor of charging piles, ensuring the real-time nature of the detection results.

[0064] In one embodiment of this application, the specific calculation formula for the over-limit ratio index in step 140 includes step 141.

[0065] Step 141: Using the formula Calculate the percentage of indicators exceeding the limit.

[0066] Where K is the over-limit ratio indicator, and R measure R is the measured value of the battery's DC internal resistance. limit This represents the upper limit of the dynamic DC internal resistance threshold range. The formula calculates the percentage deviation of the measured value from the upper limit.

[0067] In this way, risk is normalized and quantified. By converting absolute resistance differences into relative percentage indicators, the assessment difficulties caused by differences in absolute internal resistance values ​​between different vehicle models and battery specifications are eliminated. This provides a universal and standardized decision-making basis for graded protection strategies, enabling a single protection logic to be adapted to all different specifications of electric vehicles, greatly improving the compatibility and universality of safety monitoring systems.

[0068] In summary, this application actively applies a current step disturbance during DC charging and independently calculates the battery's DC internal resistance using voltage response data. This measured value is then compared with a dynamic threshold range matching vehicle attribute characteristics. Finally, a graded protection strategy, including current reduction or shutdown, is implemented based on the calculated over-limit ratio. By utilizing an active electrical excitation detection mechanism combined with big data dynamic benchmark evaluation, the system physically empowers the charging equipment to independently perceive the battery's internal impedance state, effectively solving the monitoring blind spot problem caused by the charging equipment passively responding to BMS commands in existing technologies. By introducing the dynamic threshold of the same vehicle model under similar operating conditions as a comparison benchmark, the system can statistically eliminate interference from the natural impedance increase caused by normal aging throughout the battery's lifespan, achieving accurate differentiation between normal degradation and abnormal faults. Simultaneously, based on the over-limit ratio gradient protection logic, it can maintain service by reducing current during minor anomalies and decisively shut down power during severe anomalies, thus maximizing the balance between charging facility operating efficiency and user experience while ensuring safety.

[0069] The following combination Figure 2 (A flowchart of a battery DC internal resistance detection and graded protection) The specific implementation logic of this application is explained in detail step by step.

[0070] Step 1: Battery DC internal resistance detection value detection step is executed (corresponding to...) Figure 2 Step S1 corresponds to applying a disturbance current to the output current in step 110 and calculating the battery DC internal resistance detection value in step 120.

[0071] During vehicle charging, the charging equipment monitors the charging status in real time. When the battery's state of charge is detected to be between 60% and 80%, the charging equipment determines that the trigger condition has been met and actively performs a DC resistance (DCR) test. The charging equipment controls the output current to gradually decrease from the current operating current value to a preset minimum test current value (e.g., 0A), and then gradually rises back to the original operating current value, creating a current step disturbance. Simultaneously, the charging equipment, through its communication connection with the BMS, synchronously collects the voltage response data during this current change process. Based on Ohm's law (DCR = ΔU / ΔI), the charging equipment uses the collected current step change and voltage response change to calculate the current DC resistance value of the battery.

[0072] Step 2: Reporting of detection results and features (corresponding) Figure 2 (Step S2) corresponds to obtaining the dynamic DC internal resistance threshold range that matches the attribute characteristics of the charging target in step 130 above.

[0073] The charging device packages the calculated detected value of the battery direct current internal resistance (DCR) and vehicle attribute features (including vehicle model information, cumulative driving mileage, ambient temperature, etc.), and reports them to the cloud management platform via a network.

[0074] Step 3. Dynamic threshold acquisition (corresponding to Figure 2 step S4 in the above), which corresponds to acquiring the dynamic direct current internal resistance threshold range in step 130 described above.

[0075] The cloud management platform retrieves from a massive historical database of vehicles of the same model under similar working conditions (such as the same mileage range and the same temperature interval) according to the reported vehicle attribute features, generates a dynamic direct current internal resistance threshold range using a machine learning algorithm, and delivers the range (especially its upper critical value) to the charging device.

[0076] Step 4. Primary threshold judgment (corresponding to Figure 2 step S3 in the above), which corresponds to calculating the over-limit ratio index in step 140 described above.

[0077] After receiving the threshold, the charging device compares the measured detected value of the battery direct current internal resistance (DCR) with the upper critical value of the threshold range, that is, judges whether the detected value of the battery direct current internal resistance (DCR) exceeds the threshold. In this process, the system essentially calculates the over-limit ratio index K. If the measured value does not exceed the threshold (i.e., K ≤ 0), it is determined that the battery is healthy, the process proceeds to step S5, the normal charging logic is maintained, and the current output strategy is not changed.

[0078] Step 5. Severity classification judgment (corresponding to Figure 2 step S6 in the above), which corresponds to the classification judgment logic in step 150 described above.

[0079] If it is determined that the threshold is exceeded (i.e., K > 0), the system needs to further assess the risk level. At this time, it is judged whether the detected value of the battery direct current internal resistance (DCR) exceeds 100% of the threshold, that is, whether the over-limit ratio index K is greater than 100%.

[0080] Step 6. Current reduction protection execution (corresponding to Figure 2 step S8 in the above), which corresponds to the hierarchical protection control strategy in step 150 described above.

[0081] If it is determined that 100% of the threshold is not exceeded (i.e., 0 < K ≤ 100%), it indicates that although the impedance is abnormal, it has not reached an extremely dangerous level. To balance safety and service, the charging device executes a strategy of reducing the current of the charging pile by 50% to continue charging. Specifically, the output current is controlled to be reduced to 50% of the original working current value before detection, so as to reduce the heating power and maintain the energy replenishment service while suppressing the expansion of risks.

[0082] Step 7. Shutdown protection and early warning (corresponding to Figure 2 In step S7), it corresponds to the hierarchical protection control strategy in step 150 described above.

[0083] If it is determined that the threshold is exceeded by 100% (i.e., K>100%), it indicates that the internal impedance of the battery seriously deviates from the normal level of the same vehicle model, and there is an extremely high risk of thermal runaway or circuit failure. The charging device causes the charging pile to stop charging, and pushes an early warning message to the user terminal. Specifically, the output of the power module is immediately cut off, and safety alarm information is sent to the user terminal.

[0084] Through the above steps, the present application constructs a complete closed-loop safety system with end-cloud collaboration and hierarchical response. The real physical impedance of the battery is obtained by using active perturbation, the group benchmark of the same vehicle model is introduced by cloud comparison, and the quantitative classification of risks is realized by proportional determination. By quantifying the risks into three levels: not exceeding the threshold (K≤0), slightly exceeding the threshold (0<K<100%), and severely exceeding the threshold (K>100%), which respectively correspond to three strategies of normal operation, current reduction and shutdown, it not only effectively blocks major safety accidents caused by missed reports from the BMS on the electric vehicle side, but also avoids unnecessary shutdown caused by slight data fluctuations, achieving a balance between charging safety and service continuity.

[0085] Please refer to Figure 3 , the present invention further provides an electronic device 300, which includes a memory 301, a processor 302, and a computer program stored on the memory 301 and operable on the processor 302. When the processor 302 executes the computer program, the steps of the battery safety charging method as described above are implemented.

[0086] The beneficial effects of the electronic device of the present invention are the same as those of the above method, and will not be repeated here.

[0087] The above are only the embodiments of the present invention, and are not intended to limit the patent scope of the present invention. All equivalent transformations made by using the content of the specification and the accompanying drawings of the present invention, or direct or indirect application in the relevant technical fields, are similarly included in the patent protection scope of the present invention.

Claims

1. A method for safely charging a battery, characterized in that, include: During the DC charging process of the charging target, a perturbation current step change is applied to the output current, and the voltage response data of the charging target caused by the current step change is collected simultaneously. Based on the dynamic correlation between the current step change and the voltage response data, the detected value of the battery DC internal resistance of the charging target is calculated. Obtain a dynamic DC internal resistance threshold range that matches the attribute characteristics of the charging target; The over-limit ratio index is calculated based on the detected value of the battery's DC internal resistance and the dynamic DC internal resistance threshold range. Based on the aforementioned over-limit ratio index, the corresponding graded protection control strategy is executed; The output current is subjected to a perturbation current step change, including: The output current is controlled to gradually decrease from the original operating current value during DC charging to the preset minimum test current value at a preset decreasing rate. After reaching the minimum test current value, the control output current gradually increases at a preset rate to restore the original operating current value.

2. The battery safe charging method according to claim 1, characterized in that, Based on the aforementioned over-limit ratio index, the corresponding graded protection control strategy is implemented, including: When the detected over-limit ratio is less than or equal to 0, maintain the current normal charging logic. When the detected over-limit ratio is greater than 0 and less than or equal to 100%, the control output current is reduced to 50% of the original operating current value; When the over-limit ratio is detected to be greater than 100%, the output current is immediately stopped.

3. The battery safe charging method according to claim 2, characterized in that, Also includes: When the detected excess ratio is greater than 100%, a security warning message is pushed to the user terminal.

4. The battery safe charging method according to claim 1, characterized in that, The step change of the perturbation current applied to the output current during the DC charging process of the target includes: Read the charging status parameters of the charging target; Determine whether the state of charge (SOC) of the charging target is within the range of 60% to 80%. If so, the charging state parameters of the charging target are determined to meet the preset detection trigger conditions, and a perturbation current step change is applied to the output current.

5. A battery safe charging method according to claim 1, characterized in that, The step of obtaining the dynamic DC internal resistance threshold range that matches the attribute characteristics of the charging target includes: If the charging target is an electric vehicle, the vehicle attribute characteristics are determined by collecting the electric vehicle's cumulative mileage, vehicle age, battery type, battery charge-discharge cycle count, and current ambient temperature. The dynamic DC internal resistance threshold range is obtained based on the vehicle attribute characteristics.

6. A battery safe charging method according to claim 5, characterized in that, The step of obtaining the dynamic DC internal resistance threshold range that matches the attribute characteristics of the charging target includes: The battery DC internal resistance detection value and the vehicle attribute characteristics are uploaded to the cloud management platform; Receive the dynamic DC internal resistance threshold range issued by the cloud management platform.

7. A battery safe charging method according to claim 1, characterized in that, The calculated DC internal resistance value of the battery of the charging target is obtained by the following formula: ； Among them, R measure ΔU is the detected value of the battery's DC internal resistance, ΔU is the collected voltage change, and ΔI is the corresponding current change.

8. The method according to claim 1, characterized in that, The over-limit ratio index is calculated based on the detected DC internal resistance value of the battery and the dynamic DC internal resistance threshold range, using the following formula: ； Where K is the over-limit ratio index, and R measure R is the detected value of the battery's DC internal resistance. limit This is the upper limit critical value of the dynamic DC internal resistance threshold range.

9. A charging device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements each step of the battery safe charging method according to any one of claims 1 to 8.

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