A charging gun charging control system and method

Abstract

The application discloses a charging gun charging control system and method, and particularly relates to the technical field of new energy automobile charging, and comprises the following steps: collecting a user operation sequence, judging whether a charging intention is possessed; collecting connection parameters such as insertion depth and contact pressure after confirming that the intention is valid, and constructing a current connection state; setting a state confirmation window to continuously sample, judging whether the parameters are stable; if not stable or triggering an oscillation determination logic, then stopping the operation and starting a cooling mechanism; if the operation behavior is consistent with the connection state and is continuously stable, then starting a power supply process to complete charging; the application realizes operation intention recognition by constructing a user action sequence, and improves interaction accuracy; continuously sampling physical parameters based on a time window ensures connection stability; linkage analysis of user behavior and connection state triggers oscillation determination and a cooling mechanism, effectively prevents and controls abnormal operation risks, and guarantees charging safety and reliability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy vehicle charging, more particularly, to a charging gun charging control system and method. BACKGROUND

[0002] With the wide application of new energy vehicles, as an important part of its infrastructure, the use frequency and safety requirements of charging guns are rapidly rising. When users actually use the charging gun to charge, there are often complex situations such as inconsistent action path, non-standard plugging action, and starting power supply attempt without complete insertion. Especially in fast charging, high-power charging or unattended scenarios, if the system lacks a precise judgment mechanism for user behavior and connection stability, it is easy to cause misjudgment of power supply, repeated plugging and unplugging, terminal breakdown, electric arc stretching, and even a series of serious consequences such as contact heating.

[0003] Most of the existing charging gun control systems rely on mechanical switch state, simple electrical signal detection (such as plug insertion, ground confirmation, and conduction detection) as the judgment standard. These judgment methods are usually based on the instantaneous state of a certain type of signal, such as contact closing resistance, microswitch state, CAN signal feedback, etc. However, this type of design ignores the coordination between user's actual behavior logic and physical state, making it difficult to accurately identify edge operation conditions such as non-standard insertion, rapid plugging and unplugging, test-type insertion, and false triggering, leading to a deviation of the system power supply decision from the user's true intention, and posing a safety hazard.

[0004] Some systems use the resistance drop in the plug insertion action as the main basis for judging the success of plugging, but in actual scenarios, the resistance may temporarily meet the standard but is unstable due to factors such as incorrect angle, plug shaking, or contamination of the contact surface, leading to a false judgment of a power supply state. At this time, the user may still be in the process of adjusting the insertion, and the power supply opening may cause unexpected current shock or poor contact heating. Most current charging systems lack modeling analysis of the user's operation behavior as a whole, and cannot identify whether the user has completed a complete and reasonable start-up path, such as plug insertion, code scanning, and static confirmation. When the user skips a certain operation step or performs the sequence incorrectly, the system often cannot distinguish whether the behavior is malicious testing, misoperation, or actual intention, and thus cannot implement effective intervention. Therefore, a charging gun charging control system and method are proposed to solve the above problems. SUMMARY

[0005] To achieve the above purpose, the present application provides the following technical solutions:

[0006] A charging gun charging control method, comprising the following steps:

[0007] Acquire multiple preset action signals triggered by the user and record the occurrence time of each preset action in sequence. By constructing a complete action sequence, determine whether it meets the target behavior pattern for initiating charging, thereby determining whether the user has a valid charging operation intention;

[0008] After identifying that a valid operation intention exists, multiple preset physical connection status parameters are collected to construct the current connection status;

[0009] A fixed time period is set as the status confirmation window. During this window, all physical connection status parameters are continuously sampled to determine whether each parameter remains within the set threshold. If the stability confirmation fails, the current charging attempt is aborted and a connection abnormality prompt is displayed.

[0010] During the status confirmation process, a linkage analysis is performed based on the user behavior intention recognition results and real-time connection status changes. Based on the linkage analysis results, a decision is made as to whether to trigger the status oscillation judgment logic and freeze the current round of operation permissions. At the same time, a cooling-down waiting phase is entered to block potential dangerous behaviors.

[0011] When the user behavior is consistent with the connection status, and all parameters in the status confirmation window are stable and without fluctuation, and the status oscillation judgment logic is not triggered, the power control device is started to supply power, so that the electrical energy is released to the vehicle battery, thereby executing the normal charging process.

[0012] In a preferred embodiment, when acquiring multiple preset action signals, each action signal includes four characteristic parameters: operation trigger time, duration, operation intensity (in Newtons), and trigger sequence number;

[0013] After constructing the action sequence, the dynamic time warping algorithm is used to determine the behavior intention matching. The similarity threshold is set to p, which is between 0 and 1.

[0014] When the matching similarity between the current action sequence and the reference behavior path is greater than or equal to the similarity threshold p, it is determined to be a valid charging intention; when it is less than the similarity threshold p, it is determined to be a non-charging behavior or a test behavior.

[0015] In a preferred embodiment, when using the dynamic time warping algorithm, the shortest path pairing relationship is established between the user behavior time series vector and the reference standard behavior path, and the overall pairing error distance is calculated. The smaller the minimum pairing distance, the closer the current behavior sequence is to the standard behavior.

[0016] The user behavior time sequence vector is a sequence of a set of preset actions of a user in an operation process on a time axis, and is defined as a sequence of operation action identifiers arranged in time sequence, each identifier including three dimensions of action type number, trigger timestamp, and operation duration, which are obtained from a complete action sequence and finally constitute the user behavior time sequence vector;

[0017] Each action matching pair in the algorithm matching process is provided with a weighting item, i.e., an action confidence factor, the value of the confidence factor is set according to user historical behavior characteristics, and is a real number between 0 and 1, representing the consistency confidence strength of the user's behavior on a specific action;

[0018] The final behavior matching score, i.e., the matching similarity, is a normalized value of the weighted pairing distance.

[0019] In a preferred embodiment, the preset physical connection state parameters include insertion depth, contact pressure, terminal resistance, and stability value of the plug in the spatial position, each parameter is continuously sampled at a fixed frequency, the sampling frequency is set to A1 times per second, and the sampling time window is set to A2 milliseconds continuously;

[0020] In the time window, a derivative calculation is performed on the sampling value sequence of each parameter to obtain the change rate of the parameter, each parameter is provided with a corresponding initial stable value, if the change rate of any parameter in the current sampling period exceeds the respective stable threshold value, it is determined that the current connection state is unstable, the stable threshold value is A3 percent of the initial stable value, and a state confirmation failure result is returned, triggering a re-sampling or connection retry logic.

[0021] In a preferred embodiment, when setting the state confirmation time window, the state confirmation time window is initially set to A2 milliseconds, and is dynamically adjusted according to three time window control factors, which are the current environmental temperature T, the resistance change rate R, and the plug spatial displacement standard deviation S;

[0022] The adjustment rules are as follows: when the temperature T is less than B1 degrees Celsius, the resistance change rate R is continuously negatively changed, the average rate absolute value is less than or equal to B2 milliohms per second, and the plug spatial displacement standard deviation S is less than B3 millimeters, the state confirmation time window is extended to A3 milliseconds; if the difference between the maximum and minimum values of R in the current time window is greater than or equal to B4 milliohms, and S is greater than B5 millimeters, it is determined that the fluctuation is violent, the current confirmation window is terminated in advance and a failure state is returned; if the three factors are in the preset intermediate interval, the A2 millisecond window remains unchanged.

[0023] In a preferred embodiment, the sampling frequency within the state confirmation time window is set to A1 times per second. At this frequency, the sliding sampling window length is set to 20 consecutive sampling points. The mean M of the current window is calculated each time the window is updated, and the residual value of each sampling point X is calculated, that is, |XM|. If the residual of a sampling point exceeds 20% of the mean, that is, the condition |XM|>0.2×M is met, it is marked as a disturbance point.

[0024] If more than three disturbance points are marked within the same window period, it is considered a local disturbance behavior and the connection failure logic is immediately triggered, prompting the user to retry the insertion operation;

[0025] At the same time, after each window update cycle ends, the sum of squares of all residuals in the window is calculated. If the value is greater than the preset steady-state judgment threshold, the preset steady-state judgment threshold is determined by the maximum residual square sum of historical charging success windows and is also used as the basis for judging the overall unstable state. If either condition is met, the status confirmation process is terminated and a prompt is returned.

[0026] In a preferred embodiment, in the linkage analysis results, the event frequency F is defined as the number of times N that the connection state switches from a stable connected state to an unstable disconnected state or from an unstable disconnected state to a stable connected state within a unit time t, that is, F=N / t. In the connection state definition, the stable connected state means that all physical connection state parameters remain within the set threshold for more than 200 milliseconds, and the unstable disconnected state means that any parameter exceeds the threshold and lasts for more than 100 milliseconds. If the event frequency F is greater than the abnormal threshold and exceeds the abnormal threshold for two consecutive sampling periods, it is considered to trigger the first oscillation condition;

[0027] The connection recovery time T_r is introduced and defined as the duration between the detection of an unstable disconnection state and the next time the stable state judgment condition is met. If T_r is greater than q times the average connection stability confirmation time T_avg during current device operation, and q is greater than 1, it is considered to have triggered the second oscillation condition. T_avg is calculated as the arithmetic average of the time taken to successfully confirm the stable state for the first ten times;

[0028] When any oscillation condition is continuously met for more than three consecutive judgment cycles, oscillation behavior is considered to exist.

[0029] In a preferred embodiment, the cooling waiting stage is set as follows:

[0030] The initial value of the time period is ten seconds, and is dynamically adjusted according to the following model: W=10+(w1xV)+(w2xH), wherein W is the cooling waiting time, w1 and w2 are preset proportional coefficients, V is the number of current oscillation behaviors, H is the total number of times that the user is identified as abnormal behavior in the last N consecutive charging attempts, and the model output result is limited in the range of 10 to 60 seconds.

[0031] In one preferred embodiment, a charging gun charging control system comprises:

[0032] The behavior recognition module is configured to acquire a plurality of preset action signals triggered by the user, record the occurrence time of each preset action in chronological order, construct a complete action sequence of the user, and determine whether the current operation of the user conforms to the valid behavior characteristics of starting charging in combination with a target behavior path model, so as to determine whether the user has a charging operation intention.

[0033] The connection modeling module is configured to be started after the behavior recognition module determines the valid charging intention, and to collect a plurality of preset physical connection state parameters in real time to construct a current physical connection state model.

[0034] The steady state evaluation module is configured to continuously sample and analyze each parameter output by the connection modeling module in a set time window, to determine whether all parameters continuously remain in a preset stable threshold range, and to immediately terminate the current charging process and output a connection abnormality prompt signal if the detection result does not satisfy the stable standard.

[0035] The linkage discrimination module is configured to acquire the behavior recognition result and the connection modeling data in real time during the steady state evaluation process, to determine whether the user operation matches the physical state through linkage analysis logic, to determine whether to trigger the state oscillation determination logic and freeze the operation permission of the current round, and to enter a cooling control stage to block potential risks.

[0036] The power supply execution module is configured to start the power supply control device to supply power when the user behavior and the connection state are consistent, all parameters in the state confirmation window are stable without fluctuation, and the state oscillation determination logic is not triggered, so that the electric energy is released to the vehicle battery, and the normal charging process is executed.

[0037] The technical effects and advantages of the present application are as follows:

[0038] The application acquires a plurality of preset action signals triggered by a user, and sequentially records the occurrence time of each preset action, thereby constructing a complete operation action sequence, so that whether the current operation behavior of the user conforms to the target behavior mode for starting charging can be judged based on the time sequence. Compared with the traditional single-action trigger logic, the mechanism can significantly improve the determination ability of the user's real operation intention, avoid misjudgment caused by false touch, test behavior or non-standard operation path, and improve the safety of interaction and the accuracy of system response from the source.

[0039] After determining that the user has a valid charging intention, the application further collects a plurality of preset physical connection state parameters, and continuously samples these parameters within a fixed time period to determine whether they are continuously maintained within a set threshold range. By constructing a state confirmation window to evaluate the stability of the connection state in the time dimension, it effectively prevents false entry into the power supply process under the conditions of incomplete plug-in, poor terminal contact or position shaking, ensures that the electric energy release behavior can be performed only after the physical connection has reached a stable and reliable state, and thus improves the overall safety and reliability of the charging operation.

[0040] The application introduces a linkage analysis mechanism in the state confirmation stage, which associates the user behavior intention recognition result with the real-time physical connection state change, and can identify whether there is inconsistency or abnormal fluctuation between the operation behavior and the connection state. Once it is determined that there is a potential risk behavior, the state oscillation determination logic is triggered immediately, the current charging operation permission is frozen, and the cooling waiting stage is entered, so as to avoid repeated attempts by the user in an unstable connection state, effectively block the risk of false power supply or equipment damage caused by state fluctuation, and build a complete safety protection logic from the system control level. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to facilitate the understanding of those skilled in the art, the application will be further described below with reference to the accompanying drawings;

[0042] Figure 1 A schematic diagram of a charging gun charging control method in the application.

[0043] Figure 2 A schematic diagram of a charging gun charging control system in the application. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the application. Obviously, the described embodiments are only a part of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0045] ReferenceFigure 1 Figure 2 The following examples are obtained:

[0046] Example 1: A charging gun charging control method, comprising the following steps:

[0047] Obtain a plurality of preset action signals triggered by the user, and record the occurrence time of each preset action in sequence. By constructing a complete action sequence, it is determined whether it conforms to the target behavior model for starting charging, so as to determine whether the user has a valid charging operation intention. By collecting a series of typical operation actions (such as scanning code, inserting gun, staying, swiping card, etc.) performed by the user when starting to use the charging gun, these operations are combined into a behavior sequence in chronological order, and compared with the set target behavior model. The target model can be derived from the standard use process or large sample historical user data construction. The system compares the time sequence and identifies the behavior characteristics to analyze whether the user is operating according to the normal starting process, thereby effectively distinguishing between invalid clicks, accidental touch behaviors, malicious test behaviors and real charging intentions. Through this mechanism, the system can accurately judge the user's behavior intention before entering the power supply process, improving the accuracy and safety of the subsequent control logic.

[0048] After identifying that the user has a valid operation intention, a plurality of preset physical connection state parameters are collected to construct the current connection state. Once the user's operation behavior is determined to have a charging intention, the system immediately switches to the connection state monitoring stage. In this stage, the key connection parameters between the charging gun and the vehicle socket are collected in real time by sensors and control units. These parameters include but are not limited to insertion depth (reflecting the degree of mechanical connection), contact pressure (judging whether the plug is pressed tightly), resistance stability (reflecting the reliability of conduction), and plug space position stability (judging whether shaking or sliding occurs). The system constructs a current connection state model based on these sample values, which reflects whether the connection physical conditions meet the minimum steady-state standard required for safe power supply, and is one of the core judgment bases for charging safety.

[0049] ​A fixed time period is set as a status confirmation window. During this window, all physical connection status parameters are continuously sampled to determine whether they remain within the set thresholds. If stability verification fails, the current charging attempt is aborted and a connection anomaly notification is displayed. To ensure that the connection status not only meets the instantaneous conditions but also remains stable over time before actual power is supplied, the system sets a fixed status confirmation window, for example, 500 to 1000 milliseconds. During this window, all parameters are continuously sampled at high frequency and compared against preset thresholds in real time. The connection is considered stable only if all parameters remain within the tolerance range throughout the entire time window. If any parameter jumps or fluctuates beyond the threshold, the connection is deemed unstable, and subsequent power supply is immediately terminated, prompting the user to reconnect the charger. This design effectively prevents arcing and power jumps caused by an incomplete plug or poor contact, eliminating power supply risks at the source.

[0050] During the status confirmation process, the system analyzes user behavior intent and real-time connection status changes in a coordinated manner. This analysis determines whether to trigger the status oscillation detection logic, freeze current operation permissions, and enter a cool-down waiting period to prevent potentially dangerous behavior. During the status confirmation process, the system not only independently monitors physical parameters but also dynamically integrates previously identified user behavior intent with current connection status changes. If a user's behavior is confirmed to be intentional, but the physical connection status frequently switches or fluctuates rapidly, the system identifies it as a high-risk mismatch. This triggers the status oscillation detection mechanism to determine whether there are unstable plugging and unplugging, mechanical looseness, or malicious operation. If the oscillation conditions are met, the system aborts the current charging process, freezes operation permissions, and enters a preset cool-down waiting period (e.g., 10-60 seconds) to prevent system load or hardware damage from repeated user attempts.

[0051] When the user behavior is consistent with the connection status, and all parameters in the status confirmation window are stable and without fluctuation, and the state oscillation judgment logic is not triggered, the power control device is started to supply power, so that the electric energy is released to the vehicle battery, thereby executing the normal charging process. After completing the aforementioned behavior recognition, connection detection, stability assessment and risk judgment, the controller will only issue a power start instruction under the triple confirmation conditions of reasonable user behavior, stable physical connection status, and no abnormal risk detected by the system. At this time, the system activates relays, power controllers and other devices to establish a power path, allowing high voltage electricity to be output from the charging pile to the vehicle battery. The entire process maintains closed-loop monitoring to ensure that no dangerous state will be caused by misconnection, misjudgment or external disturbance at the moment of connection. This step is the end point of the entire method flow, which represents the safe and compliant start of the charging task, and also reflects the technical depth of the present invention in the risk management logic of the whole process.

[0052] It should be noted that different letter marks appear several times throughout the text, and the specific values of the A1, A2, A3 and other parameter substitutes can be configured according to the application scenario.

[0053] When obtaining a plurality of preset action signals, each action signal is a specific operation behavior performed by the user during the interaction with the charging gun. The collected data includes four feature parameters: first, the operation trigger time, which is the system recording time when the action is first detected, in milliseconds; second, the duration, which represents the duration of the action from triggering to completion, in milliseconds; third, the operation intensity, which represents the force exerted by the user when performing the action, such as the pushing force when inserting the gun or swiping the card, in Newton; and fourth, the trigger sequence number, which represents the order of the action in the sequence of operation behaviors, used to construct a time-ordered operation flow.

[0054] After collecting the above feature parameters, the system combines all actions in time sequence to form an action sequence, and uses the dynamic time warping algorithm (DTW for short) to match and judge the behavior intention of the action sequence. Dynamic time warping is a calculation method for comparing the similarity of two time series data patterns, supporting non-linear stretching of the time axis, so that it can align and analyze behaviors with different action durations or response speeds. The algorithm establishes all possible pairing paths between the user's current behavior sequence and the predefined reference behavior path, and selects the matching with the smallest path cost as the final result. This path cost is called the overall pairing error distance, which is the core indicator for measuring the similarity between the current behavior and the standard behavior.

[0055] To improve the discrimination of the matching judgment, the system introduces the user behavior time sequence vector in the above path pairing calculation process. The vector is the expression of the operation flow of the user in the charging interaction process on the time axis, composed of multiple action identifiers. Each action identifier is a tuple containing three elements: action type number (reflecting the category of the action in the preset operation set), trigger timestamp (millisecond level), and duration (milliseconds). By extracting and arranging the above tuples from the original action sequence, a complete user behavior time sequence vector is formed, which is one of the inputs of the dynamic time warping algorithm and participates in the calculation.

[0056] During the matching process, to further account for individual behavioral differences among users, each action pairing point is assigned a weighted term, the action confidence factor. This factor is a real-valued value between 0 and 1 that represents the user's behavioral consistency in that action. A higher value indicates a more regular and stable performance of the action. The confidence factor is set based on a user's historical behavior data model. For example, if a user has repeatedly completed the standard process of scanning the code, inserting the gun, and resting the gun, the confidence factor for the insertion action may be set to 0.9 or above. For users who have repeatedly engaged in non-standard behaviors such as prematurely drawing the gun, the confidence factor for such actions may be set to 0.4 or lower.

[0057] After completing the dynamic time warping matching and weighting, the system calculates the final behavior matching score. This matching score is the weighted distance normalized value of the matching path, called matching similarity, which is used to measure the similarity between the current behavior sequence and the reference behavior path in terms of time sequence, action structure, and action stability. The system sets a similarity threshold p (p is a floating point number between 0 and 1, for example, it can be set to 0.85). When the matching similarity of the current behavior sequence is greater than or equal to p, the system determines that the user behavior is a valid charging intention; when the matching similarity is lower than p, the behavior is judged to be a non-charging operation or test behavior and does not enter the power supply process.

[0058] In one embodiment, if a user sequentially scans a code (trigger time 0ms, duration 300ms, force 1 Newton), inserts the charging gun (400ms, 1000ms, 20 Newtons), and remains stationary (1500ms, 5000ms, 0 Newtons), the system generates a time series vector consisting of three action identifiers. This vector is then matched against a standard system-built-in path (e.g., scan code - insert the charging gun - remain stationary) using DTW. If the path error is low and the weighted score exceeds the set threshold p=0.87, the user behavior is considered to have a valid intention to initiate charging.

[0059] The setting of the action confidence factor is established based on the user's historical behavior data model, which includes the user's past behavioral sequence records during the use of the charging gun. The system counts the number of standard executions, the number of abnormal deviation behaviors, and the physical characteristic parameters related to each execution of the user in the established action category to build an individualized action stability scoring model. Among them, the operation intensity is one of the behavioral characteristics and participates in the weight mapping modeling of the action confidence factor. The operation intensity is used as follows: all the collected operation intensity values ​​in the action history record are calculated to account for their proportion in the standard operation intensity range. The standard operation intensity range is pre-set by the system. For example, the recommended intensity range for the gun insertion action is 10 Newtons to 30 Newtons.

[0060] The system performs scoring training based on the following mapping strategy:

[0061] If over 80% of a user's past gun insertion behaviors fall within the recommended range for intensity, and the sequence of behaviors accurately matches the target path, the gun insertion confidence factor is set to 0.9 or higher. If only 40% of the operation intensities meet the recommended range, the confidence factor is set to 0.8. If a high proportion of the operation intensities are insufficient (e.g., <5 Newtons) or excessive (e.g., >50 Newtons), and are often accompanied by non-standard sequence behaviors (e.g., not scanning a QR code before inserting the gun), the confidence factor is set to 0.4 or lower. The intensity of the operation and the consistency of the behavior sequence are jointly input into a machine learning model (e.g., a support vector machine (SVM)), and the model output is an action confidence factor. Extensive discussion of existing technologies is omitted here. This factor value serves as a weighting factor for the current action matching path in the matching algorithm, influencing the final matching score, thereby dynamically adapting to the stability and compliance of different users' operations.

[0062] In one embodiment, a user's average charging pressure during nearly 20 charging attempts was 18 Newtons, with a minimum of 9 Newtons and a maximum of 24 Newtons. Seventeen of these attempts were within the recommended range, with the scan-plug-plug-rest sequence complete. Based on this, the system trained a confidence factor of 0.93 for their charging action. Another user's charging pressure was typically 2-6 Newtons, with frequent instances of scanning without plugging in the charger or immediately unplugging the charger. The system assigned a confidence factor of 0.41 to their charging action.

[0063] The physical characteristic parameters associated with each execution refer to a set of measurement values ​​related to the physical interaction state that are collected by the device system and stored in association with the user's action (such as inserting a gun, scanning a code, swiping a card, or drawing a gun). These parameters include but are not limited to the following:

[0064] Operation intensity (in Newtons): Indicates the force applied by the user to the operating interface (such as the plug, button, and gun body) when performing the action, reflecting their determination and strength characteristics of the operation. Action duration (in milliseconds): The total duration from the start of the action to the end, reflecting whether the operation is clean and smooth or hesitant and repetitive. Insertion depth change (in millimeters): Indicates the changing trend of the depth of the charging gun plug entering the socket during the insertion process, whether it is smoothly inserted to the bottom or reciprocated multiple times. Terminal contact pressure (in Newtons): Reflects the actual mechanical contact compression of the electrical connection part, indicating whether the contact is reliable.

[0065] For example, in a one-time plug-in action, the system records the following physical characteristic parameters: the operation strength is 17 Newtons; the duration is 1200 milliseconds; the insertion depth increases from 0 mm to 27 mm; the initial resistance is 18 mOhm, and the fluctuation rate is 1.5 mOhm / s; the plug position stability standard deviation is 0.12 mm. According to these data, the system combines historical behavior to judge that the operation is a "stable, complete, and high-confidence" plug-in action, and the corresponding action confidence factor is set to 0.91.

[0066] The preset physical connection state parameters include insertion depth, contact pressure, terminal resistance, and plug spatial position stability value. Among them, the insertion depth represents the insertion length of the charging gun plug relative to the vehicle charging socket, with units of millimeters; the contact pressure is the pressing force between the end of the plug and the contact surface of the vehicle socket, with units of Newtons; the terminal resistance is the instantaneous contact resistance between the internal conductive terminal of the plug and the socket terminal, with units of milliohms; the plug spatial position stability value is defined as the Euclidean displacement path sum between consecutive sampled three-dimensional space coordinates of the plug within a set sampling time window, which is used to measure the overall motion amplitude or disturbance degree of the plug within that time period, and then judge whether the plug is in a physically stable state. Specifically, the system continuously samples the spatial position of the plug according to the set sampling frequency, records the coordinate position of the plug in three-dimensional space at each sampling, and then calculates the Euclidean distance between each two adjacent sampling points.

[0067] Each parameter is continuously sampled at a fixed frequency, with a sampling frequency set to A1 times per second, i.e. every (1000 / A1) milliseconds to collect the current value; the sampling time window is set to A2 milliseconds, and within this time window, a total of (A1 x A2) / 1000 samples will be taken for each physical parameter to form a parameter sequence. The sampling frequency A1 and the time window A2 can be configured according to device performance and application scenarios, for example, typical values are A1 = 50 times / second and A2 = 500 milliseconds. Within this time window, the system performs a first derivative calculation on the sequence of each parameter sampling value, which is used to obtain the change rate of the parameter. The calculation method of the first derivative is the difference between the values of the two adjacent sampling points divided by the time interval (increment change in units of time), which represents the trend change direction and amplitude of the parameter, with the same unit as the original parameter (such as the change rate of the insertion depth, with units of millimeters per second).

[0068] Each parameter is provided with a corresponding initial stable value, which is the average value in the sampling data after the device is powered on for the first time or the last state confirmation is successful, and is used as a reference value for state change judgment. The stability threshold is A3% of the initial stable value, and A3 is a stability control parameter, for example, A3=10 indicates that a fluctuation range of ±10% is allowed. In any current sampling period, if the change rate (i.e. the absolute value of the derivative) of a certain parameter exceeds the product of the initial stable value and the stability threshold of the parameter, that is, it satisfies the following condition: |change rate|>stability threshold=initial stable value×A3 / 100, the system immediately determines that the current connection state is unstable. This judgment method judges by trend mutation rather than single-point anomaly, and can identify sudden jitter, contact arc, mechanical looseness and other unstable behaviors generated during plugging. Once the connection state is determined to be unstable, the system immediately suspends the current state confirmation process, returns a state confirmation failure result, and triggers a re-sampling or connection retry logic, i.e. restarts the sampling window and prompts the user to check or re-plug the charging gun to prevent triggering power supply control under poor connection conditions and ensure the safety of the overall system operation.

[0069] For example, in a specific application, the system sets the sampling frequency A1=50 times / second and the time window A2=500 milliseconds, so each parameter is sampled 25 times in each judgment period. The initial stable value of the insertion depth is 26 mm, and if A3 is set to 10, the allowed change rate threshold of the parameter is 2.6 mm / s. If the system detects that the insertion depth decreases from 26 mm to 24 mm in 40 ms between two sampling points, the derivative is (26-24) / 0.04=50 mm / s, which is significantly higher than the threshold, and the system immediately determines that the state is unstable during plugging and terminates the connection judgment process.

[0070] When setting the state confirmation time window, the state confirmation time window is initially set to A2 milliseconds, and A2 is the system's pre-set basic judgment time, which is used to provide sufficient observation time in the initial stage of stability analysis, and is usually in the range of 500-1000 milliseconds, which is used to accommodate short-term fluctuations and observe trends. This time window is not fixed, but is dynamically adjusted according to three time window control factors.

[0071] The three time window control factors are: the current ambient temperature T (in degrees Celsius), the resistance change rate R (in milliohms per second), and the plug spatial displacement standard deviation S (in millimeters). Among them: the ambient temperature T is measured by the built-in temperature sensor of the charging device in real time; the resistance change rate R is the trend change speed of the resistance parameter value sequence in the current sampling window, which can be calculated by the average value of consecutive differences; the plug spatial displacement standard deviation S represents the position standard deviation of the plug in the three-dimensional coordinate system in this time window, which is used to reflect whether the plug has slight jitter or structural looseness.

[0072] The adjustment rules are as follows:

[0073] If the temperature T is less than B1 degrees Celsius, it indicates that the ambient temperature is low; and the resistance change rate R is continuously negatively changed, indicating that the resistance value is steadily decreasing; and the absolute value of its average rate is less than or equal to B2 milliohms per second, indicating that the change trend is stable; at the same time, the plug space displacement standard deviation S is less than B3 millimeters, indicating that the plug movement is very small and stable; at this time, the system judges that the current connection environment is relatively ideal, and the state confirmation time window can be extended to A3 milliseconds to fully confirm the stable connection state;

[0074] If the difference between the maximum and minimum values of R within the current time window is greater than or equal to B4 milliohms, it indicates that the resistance fluctuation is significant, and S is greater than B5 millimeters, indicating that the plug has moved or shaken with a large amplitude in physical position, at which time the system judges that the current connection state fluctuates violently and is not suitable for continuing the confirmation process, and the current confirmation window will be terminated in advance and return to the failure state prompt;

[0075] If the three factors T, R, and S are all in the preset middle interval, i.e., neither reaching the excellent state nor triggering the fault threshold, the original confirmation time window A2 milliseconds is kept unchanged to ensure the neutral judgment logic.

[0076] The sampling frequency within the state confirmation time window is set to A1 times per second, and A1 is the continuous sampling frequency set by the system, for example, a typical value is 50 Hz. At this frequency, the sliding sampling window length is set to twenty consecutive sampling points, forming a moving local data set.

[0077] Each time the sliding window is updated, the system calculates the mean M of all data points in the window, and calculates the residual value of each sampling point X in the window, defined as |X-M|. If the residual of a sampling point exceeds 20% of the mean, the point is marked as a disturbance point. If the number of disturbance points marked in the same window period exceeds three, i.e., more than 3 points are disturbance points in 20 points (disturbance rate greater than 15%), the system determines that the window data has abnormal disturbance behavior, i.e., the local disturbance behavior is established. At this time, the connection failure logic is triggered immediately, and the user is prompted to reinsert the charging gun or adjust the operation. In addition, after each sliding window period ends, the system also calculates the sum of squares of all residual values in the window, denoted as RSS. If the value is greater than a preset steady state judgment threshold (the threshold is set by statistical analysis of the maximum RSS value of each window in many successful charging processes in history), it is considered that the window as a whole fluctuates strongly, constituting an overall unstable state. In the above two judgment methods, if either condition is met, the system considers that the current connection does not meet the steady state requirement, and immediately stops the state confirmation process and returns to the prompt, thereby preventing false judgment or risk discharge behavior due to local vibration or continuous parameter deviation.

[0078] For example, in a specific scenario, the initial time window A2 is set to 600 milliseconds; the temperature T = 7°C, the average rate of change of R = -1.5 milliohms / second, and S = 0.08 mm; when the extension condition is triggered, the window is automatically adjusted to A3 = 1000 milliseconds; if there are four disturbance points in the subsequent sliding window, or RSS = 3200 exceeds the set threshold of 3000, the system immediately terminates the confirmation process.

[0079] In this embodiment of the present invention, the reference threshold parameters B1, B2, B3, B4, and B5 used in the dynamic adjustment of the status confirmation time window for the three control factors T, R, and S must be set based on the actual device operating environment, user behavior fluctuations, and sensor accuracy. Parameter B1 represents the ambient temperature threshold used to determine whether the device has entered a low-temperature state. A recommended setting is 10 degrees Celsius. When the external ambient temperature falls below this value, the response speed of mechanical components may slow down, and the terminal resistance may temporarily be high. The system can accordingly extend the confirmation time to avoid false positives. Parameter B2 represents the upper limit of the resistance change rate, used to determine whether the contact resistance has stabilized. A recommended setting is 2.0 milliohms per second. When the average rate of resistance change is less than or equal to this value, the connection state is considered to be gradually stabilizing, which is conducive to determining whether the device has entered a steady-state state. Parameter B3 represents the upper limit of the standard deviation of the plug's spatial displacement, used to determine whether the plug remains stationary in space. A recommended setting is 0.1 mm. If the jitter amplitude is below this value, the plug has almost no perceptible movement in physical space and is highly stable. Parameter B4 determines whether resistance fluctuations are severe. It is defined as the threshold difference between the maximum and minimum resistance values ​​within the current time window, with a recommended setting of 5 milliohms. Exceeding this range typically indicates poor contact or dynamic interference, and the system must immediately terminate the determination process. Parameter B5 is the upper limit of the standard deviation of the plug's spatial displacement, used to determine whether the plug has experienced significant movement. The recommended value is 0.3 mm. If the plug's stability exceeds this value during the confirmation period, there may be a risk of slippage, loosening, or artificial movement. The above values ​​are recommended configurations based on the characteristics of the charging connector interface of typical EV models, usage scenarios, and the capabilities of existing status recognition technology. They can also be optimized through self-learning by the system based on operating data or set by the manufacturer. Dynamic adjustment of this parameter group allows for precise control of the duration of the status confirmation window, extending the determination period under benign conditions such as low temperatures and mild fluctuations, and promptly terminating the determination process in scenarios such as severe disturbances and high-frequency instability, thereby improving the overall intelligence and safety of connection determination.

[0080] In the linkage analysis result of the present application, the event frequency F is defined as the number N of times of switching of the connection state from the stable on state to the unstable off state, or from the unstable off state to the stable on state within a unit time t, i.e. F = N / t. The unit time t is a preset statistical observation period, in seconds, and is recommended to be set to 5 seconds in actual implementation. Within this time period, each time the connection state switches from "on" to "off unstable", or from "off unstable" to "on", it is counted as one event.

[0081] The connection state is divided into two types: stable on state, which means that all the preset physical connection state parameters collected by the system remain within their respective stable threshold ranges within a continuous 200 ms time window. This state indicates that the connection quality is stable, safe and controllable, and is suitable for power supply operation; unstable off state, which means that any of the above-mentioned physical connection state parameters (including insertion depth, contact pressure, terminal resistance, plug space disturbance index) changes by more than the set threshold, and the duration of the change exceeds 100 ms, indicating that the connection state is unstable, and there may be risks such as shaking, interruption of plugging or temporary poor contact.

[0082] The system statistically judges the state switching frequency within a certain time. If the value of the event frequency F is greater than the set abnormal frequency threshold (for example, set to 0.8 times per second, i.e. more than 0.8 times of state switching per second), and the frequency exceeds the abnormal threshold in two consecutive sampling periods, the system determines that the current connection state is in high-frequency switching behavior, which meets the first oscillation condition. In order to enhance the recognition ability of non-natural state recovery behavior, the system further introduces the connection recovery time T_r, which is defined as the time interval between the detection of the unstable off state and the successful confirmation of entering the stable on state, in milliseconds. This time represents the real duration of the connection from abnormal to normal recovery. In order to exclude short-time jitter misjudgment and premature power supply risk, the system introduces the proportional relationship between T_r and the average confirmation time T_avg as the basis for judging the second oscillation condition. T_avg is the average time used by the system to record the last ten times of successful confirmation of entering the stable on state in the current working period, which is calculated by arithmetic mean.

[0083] If the current connection recovery time T_r is greater than q times of T_avg, and q is an empirical constant greater than 1 (for example, 1.5 or 2), it means that the connection recovery time is much higher than the system's usual judgment time, and it is likely to be caused by non-natural recovery behaviors such as plug loosening, position drift, repeated plug-in, etc. Therefore, the system considers that the second oscillation condition is triggered. The above-mentioned first oscillation condition and second oscillation condition can exist independently, but only when either of the conditions is continuously established for more than three consecutive judgment periods (i.e. for more than three five-second periods), the system finally determines that the current connection state has a significant oscillation behavior. Oscillation behavior is defined as a behavior pattern that presents persistent instability, frequent fluctuations and unnatural recovery process in a short period of time, which is the main risk source of power supply abnormalities or contact accidents. When the system detects that the oscillation behavior is established, it will immediately execute the oscillation behavior control mechanism, suspend the current operation, freeze the user's charging right, and enter the cooling waiting stage to prevent the user from forcibly starting the charging process in an unstable state.

[0084] The cooling waiting stage is set in the following way:

[0085] The initial value of the time period is ten seconds, and it is dynamically adjusted according to the following model: W = 10 + (w1 x V) + (w2 x H), where W is the cooling waiting time, w1 and w2 are preset proportional coefficients, which are non-zero values set according to actual use scenarios, V is the current number of oscillation behaviors, H is the total number of times the user is identified as abnormal behavior in the last N consecutive charging attempts, and the model output is limited to the range of 10 to 60 seconds.

[0086] Specifically, the "current" of the "current number of oscillation behaviors" V refers to the number of times the system has determined that there is an oscillation behavior from the first time the oscillation determination logic is triggered to the current time during the current charging session or within the control stage period. That is, V is the number of oscillation behavior events identified by the system for the same charging attempt within the current plug-in to the current state judgment period. Whenever the connection state continuously meets any of the oscillation conditions for more than three times, the system officially recognizes an oscillation behavior, and V increases by 1. The system maintains an independent oscillation state statistical unit for each plug-in attempt. This statistical unit starts counting from the time the user's plug-in action is first recognized as a valid intention and the physical connection state collection begins, and ends when the current plug-in behavior is finally completed, failed or timed out. The time range is defined as a "charging connection interaction period", and multiple entries into the state confirmation, failure, retry and other stages within this period are included in the cumulative range of V.

[0087] The cooling-down wait phase aims to prevent users from repeatedly attempting to charge when the connection is unstable or exhibits significant oscillation characteristics, thereby preventing unintentional, continuous operation that could lead to hardware wear, improper power supply, or electric shock. By introducing a dynamic cooling-down duration control model, the system automatically weights the cooling-down wait duration W based on the user's current oscillation severity (a higher V indicates more issues in this round) and the consistency of their historical behavior (a higher H indicates greater deviation from the standard). This model supports a certain degree of user-level control, balancing security and user experience. The historical abnormal behavior count H in the model is a long-term metric continuously updated in background behavior data. It represents the total number of times the system identified a user as having engaged in non-standard charging behavior in the last N consecutive charging attempts. N is a set statistical window, generally recommended to be 20 or 50, indicating that the system continuously tracks the user's operation trajectory. The H value is updated as a sliding statistical result.

[0088] After the cooling waiting phase ends, the system will not immediately determine that this round of attempts has failed. Instead, based on the previously identified valid operation intention results, it will restart the physical connection status acquisition process, and perform a new round of continuous sampling and evaluation of multiple preset physical connection parameters such as insertion depth, contact pressure, terminal resistance, and spatial stability. It will reconstruct the current connection state and enter a new round of status confirmation and judgment cycle to identify whether the user has completed the physical correction action and realize a highly robust human-computer interaction control mechanism. If the user performs the operation of re-plugging the charging gun during the cooling waiting phase or afterwards, the system should regard it as the starting point of a new user operation sequence and must re-judge the charging intention, and cannot directly use the previous judgment result.

[0089] In one embodiment, after the user plugs in the gun, it is recognized as a valid intention, but the plug shakes slightly and disconnects continuously. The system determines 3 complete trigger events that meet the oscillation behavior within a connection interaction cycle, and the current number of oscillation behaviors V=3. At the same time, the user was identified as abnormal behavior 5 times in the last 20 charging attempts, that is, H=5. Then the cooling wait time W=10+(0.2×3)+(0.5×5)=10+0.6+2.5=13.1 seconds, which can be rounded up to 14 seconds. If the calculated result exceeds 60 seconds, it is limited to the upper limit; if the calculated result is less than 10 seconds, the minimum value is guaranteed to be the initial value.

[0090] In the charging gun charging control method described in the present invention, "abnormal behavior" refers to the user's operation behavior, connection status, or behavior sequence during a complete charging attempt, which significantly deviates from the expected standard process or system stability judgment logic, and has a certain degree of non-standardization, instability, or potential risk. Abnormal behavior mainly includes the following three judgment scenarios:

[0091] Behavioral path deviation anomalies: When a user's action sequence during the charging gun startup process matches the system's preset target behavior path model, the similarity falls below a set threshold p (e.g., p=0.85), indicating a behavioral intent recognition failure. This anomaly includes, but is not limited to, removing the charger without inserting it after scanning the code, inserting the charger before scanning the code, and not having a clear wait time, among other typical non-startup action paths. For example, if the user action match is only 0.6, the attempt is marked as abnormal.

[0092] Connection stability failure: During the connection confirmation process, if any of the preset physical connection parameters (insertion depth, contact pressure, terminal resistance, and spatial position) fails to meet stability criteria, such as the rate of change exceeding the threshold, the residual disturbance point exceeding the limit, or the sum of squared residuals exceeding the preset steady-state threshold, the system considers the connection to have failed. In particular, if the user attempts to connect multiple times but the status confirmation window is terminated multiple times, each failure counts as an abnormal behavior.

[0093] State oscillation determination is an abnormality: If during the connection process, the system recognizes that the event frequency F is continuously higher than the abnormal threshold, or the connection recovery time T_r is greater than q times T_avg, and any of the above oscillation conditions is continuously met for more than three rounds, and it is determined that "oscillating behavior" exists, the behavior is also classified as abnormal behavior. Each time oscillation behavior is established, it will be recorded as an abnormal record in the background operation behavior log. After each charging attempt is completed, the system will make a unified judgment on whether it constitutes abnormal behavior. If any type of abnormality is met, the attempt will be marked as "abnormal" and used for subsequent cooling wait time calculation and user behavior profile generation.

[0094] Example 2: A charging gun charging control system, comprising:

[0095] The behavior recognition module is used to obtain multiple preset action signals triggered by the user, record the occurrence time of each preset action in chronological order, construct the user's complete action sequence, and combine the target behavior path model to determine whether the user's current action meets the valid behavior characteristics for starting charging, thereby determining whether the user has the intention to charge.

[0096] The connection modeling module is activated after the behavior recognition module determines that the charging intention is valid, and collects multiple preset physical connection status parameters in real time to build a current physical connection status model;

[0097] The steady-state assessment module continuously samples and analyzes the various parameters output by the connection modeling module within a set time window to determine whether all parameters remain continuously within the preset stability threshold range. If the test results do not meet the stability standard, the current charging process is immediately terminated and a connection abnormality prompt signal is output;

[0098] The linkage discrimination module, in the steady state evaluation process, real-time acquisition behavior recognition result and connection modeling data, through linkage analysis logic to judge whether the user operation matches the physical state, and then decide whether to trigger state oscillation determination logic and freeze this round of operation permission, and enter the cooling control stage to block potential risks;

[0099] The power supply execution module, when the user behavior and the connection state remain consistent, and all parameters in the state confirmation window are stable without fluctuation, and the state oscillation determination logic is not triggered, starts the power supply control device to supply power, releases the electric energy to the vehicle battery, and thus executes the normal charging process.

[0100] The above formulas are dimensionless values calculated, the formulas are obtained by collecting a large amount of data to simulate a formula of the most recent real situation, and the preset parameters in the formula are set by a person skilled in the art according to the actual situation.

[0101] It should be understood that the size of the serial number of each process described above in various embodiments of the present application does not mean the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0102] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0103] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0104] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A charging control method for a charging gun, characterized in that: The following steps are involved: Acquire multiple preset action signals triggered by the user and record the occurrence time of each preset action in sequence. By constructing a complete action sequence, determine whether it meets the target behavior pattern for initiating charging, thereby determining whether the user has a valid charging operation intention; After identifying that a valid operation intention exists, multiple preset physical connection status parameters are collected to construct the current connection status; A fixed time period is set as the status confirmation window. During this window, all physical connection status parameters are continuously sampled to determine whether each parameter remains within the set threshold. If the stability confirmation fails, the current charging attempt is aborted and a connection abnormality prompt is displayed. During the status confirmation process, a linkage analysis is performed based on the user behavior intention recognition results and real-time connection status changes. Based on the linkage analysis results, a decision is made as to whether to trigger the status oscillation judgment logic and freeze the current round of operation permissions. At the same time, a cooling-down waiting phase is entered to block potential dangerous behaviors. When the user behavior is consistent with the connection status, and all parameters in the status confirmation window are stable and without fluctuation, and the status oscillation judgment logic is not triggered, the power control device is started to supply power, so that the power is released to the vehicle battery, thereby executing the normal charging process; When setting the status confirmation time window, the status confirmation time window is initially set to A2 milliseconds and is dynamically adjusted based on three time window control factors: the current ambient temperature T, the resistance change rate R, and the standard deviation of the plug spatial displacement S; The adjustment rules are as follows: When the temperature T is less than B1 degrees Celsius, the resistance change rate R is continuously negative, the average absolute value of the rate is less than or equal to B2 milliohms per second, and the standard deviation S of the plug's spatial displacement is less than B3 millimeters, the status confirmation time window is extended to A3 milliseconds. If the difference between the maximum and minimum values ​​of R within the current time window is greater than or equal to B4 milliohms, and S is greater than B5 millimeters, it is determined to be a severe fluctuation, the current confirmation window is terminated early, and the failure status is returned. If all three factors are within the preset middle range, the A2 millisecond window is maintained. The sampling frequency within the state confirmation time window is set to A1 times per second. At this frequency, the sliding sampling window length is set to 20 consecutive sampling points. The mean M of the current window is calculated each time the window is updated, and the residual value of each sampling point X is calculated, that is, |XM|. If the residual of a sampling point exceeds 20% of the mean, that is, the condition |XM|>0.2×M is met, it is marked as a disturbance point. If more than three disturbance points are marked within the same window period, it is considered a local disturbance behavior and the connection failure logic is immediately triggered, prompting the user to retry the insertion operation; At the same time, after each window update cycle ends, the sum of squares of all residuals in the window is calculated. If the sum of squares of all residuals is greater than the preset steady-state judgment threshold, the preset steady-state judgment threshold is determined by the maximum sum of squares of residuals in the historical charging success window and is also used as the basis for judging the overall unstable state. If either condition is met, the status confirmation process is terminated and a prompt is returned.

2. A charging control method for a charging gun according to claim 1, characterized in that: When acquiring multiple preset action signals, each action signal contains four characteristic parameters: operation trigger time, duration, operation intensity, and trigger sequence number; After constructing the action sequence, the dynamic time warping algorithm is used to determine the behavior intention matching. The similarity threshold is set to p, which is between 0 and 1. When the matching similarity between the current action sequence and the reference behavior path is greater than or equal to the similarity threshold p, it is determined to be a valid charging intention; If the similarity is less than the threshold p, it is determined to be a non-charging behavior or a testing behavior.

3. The charging control method for a charging gun according to claim 1, characterized in that: When using the dynamic time warping algorithm, the overall pairing error distance is calculated by establishing a shortest path pairing relationship between the user behavior time series vector and the reference standard behavior path; A user behavior time series vector is a sequence of preset actions expressed on the time axis during the user's operation process. It is defined as a sequence of operation action identifiers arranged in chronological order. Each identifier contains three dimensions: action type number, trigger timestamp, and operation duration. The corresponding identifiers are obtained from the complete action sequence and ultimately constitute the user behavior time series vector. During the algorithm matching process, each action matching pair is assigned a weighted item, namely the action confidence factor. The value of the confidence factor is set based on the user's historical behavior characteristics and is a real number between 0 and 1, indicating the confidence strength of the user's behavior consistency in the preset action. The final behavior matching score, i.e., the matching similarity, is the normalized value of the weighted pairing distance.

4. The charging control method for a charging gun according to claim 1, characterized in that: The preset physical connection status parameters include insertion depth, contact pressure, terminal resistance, and the stability value of the plug in space. Each parameter is continuously sampled at a fixed frequency. The sampling frequency is set to A1 times per second, and the sampling time window is set to A2 milliseconds continuously. Within this time window, a derivative calculation is performed on the sampling value sequence of each parameter to obtain the rate of change of the parameter. Each parameter is set with a corresponding initial stable value. If the change rate of any parameter exceeds its corresponding stable threshold within the current sampling period, the current connection state is determined to be unstable. The stable threshold is A3 percent of the initial stable value.

5. A charging control method for a charging gun according to claim 4, characterized in that: In the linkage analysis results, the event frequency F is defined as the number of times N that the connection state switches from a stable connected state to an unstable disconnected state, or from an unstable disconnected state to a stable connected state, per unit time t. That is, F = N / t. If the event frequency F is greater than the abnormal threshold and exceeds the abnormal threshold for two consecutive sampling periods, it is considered to have triggered the first oscillation condition. The connection recovery time T_r is introduced and defined as the duration between the detection of an unstable disconnection state and the next time the stable state judgment condition is met. If T_r is greater than q times the average connection stability confirmation time T_avg during current device operation, and q is greater than 1, it is considered to have triggered the second oscillation condition. T_avg is calculated as the arithmetic average of the time taken to successfully confirm the stable state for the first ten times; When any oscillation condition is continuously met for more than three consecutive rounds within the preset linkage analysis and judgment period, oscillation behavior is determined to exist.

6. A charging control method for a charging gun according to claim 5, characterized in that: The cooling waiting phase is set as follows: The initial value of the time period is ten seconds and is dynamically adjusted according to the following model: W=10+(w1×V)+(w2×H), where W is the cooling wait time, w1 and w2 are preset proportional coefficients, V is the current number of oscillation behaviors, and H is the total number of times the user has been identified as having abnormal behavior in the last N consecutive charging attempts. The model output result is limited to the range of 10 to 60 seconds.

7. A charging gun charging control system, used to implement a charging gun charging control method according to any one of claims 1 to 6, characterized in that: include: The behavior recognition module is used to obtain multiple preset action signals triggered by the user, record the occurrence time of each preset action in chronological order, construct the user's complete action sequence, and combine the target behavior path model to determine whether the user's current action meets the valid behavior characteristics for starting charging, thereby determining whether the user has the intention to charge. The connection modeling module is activated after the behavior recognition module determines that the charging intention is valid, and collects multiple preset physical connection status parameters in real time to build a current physical connection status model; The steady-state assessment module continuously samples and analyzes the various parameters output by the connection modeling module within a set time window to determine whether all parameters remain continuously within the preset stability threshold range. If the test results do not meet the stability standard, the current charging process is immediately terminated and a connection abnormality prompt signal is output; The linkage discrimination module obtains behavior recognition results and connection modeling data in real time during the steady-state assessment process. It uses linkage analysis logic to determine whether the user operation matches the physical state. It then decides whether to trigger the state oscillation judgment logic and freeze the current round of operation permissions. At the same time, it enters the cooling control phase to block potential risks. The power supply execution module starts the power control device to supply power when the user behavior is consistent with the connection status, all parameters in the status confirmation window are stable and without fluctuation, and the status oscillation judgment logic is not triggered, so that the electric energy is released to the vehicle battery, thereby executing the normal charging process.

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