Control method and system based on intelligent charging pile cluster

Abstract

The invention discloses a control method and system based on an intelligent charging pile cluster, and relates to the technical field of intelligent charging piles, and the method comprises the following steps: recognizing each stage of battery charging, the battery charging stages including an initial stage, a fast charging stage and a trickle charging stage; after entering the trickle charging stage, acquiring charging current data of the battery in real time; and after the real-time current data is obtained, the current data obtained in the trickle charging stage is analyzed under the detection window, and the abnormal condition of current fluctuation is identified. According to the invention, through real-time analysis of current data and rapid identification and adjustment of abnormal fluctuation, damage to the battery caused by overlarge current is avoided, and especially in a trickle charging stage, the service life of the battery is prolonged and the safety is improved. After the abnormal current fluctuation is controlled, the fuzzy logic and PID control are combined, the nonlinear fluctuation is flexibly coped, the stable current is accurately adjusted, the response capability and the regulation and control precision of the system are improved, and the safety and the high efficiency of the charging process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent charging piles, and in particular to a control method and system based on an intelligent charging pile cluster. Background Art

[0002] Control based on smart charging pile clusters refers to the centralized management and optimized scheduling of multiple charging piles through intelligent technology to improve charging efficiency, save energy and optimize user experience. The system usually achieves real-time monitoring and remote control through the Internet of Things, cloud computing and big data analysis, and can automatically adjust the working status and power distribution of charging piles according to the charging needs of different electric vehicles and the load conditions of the charging network. Smart charging pile cluster control also involves balancing the load pressure of the power grid, preventing local power system overload, and can be linked with new energy power generation systems such as solar or wind power to further improve energy utilization.

[0003] In the control process based on the intelligent charging pile cluster, the system will adjust the output power of the charging pile in real time according to the current battery status of each electric vehicle (such as battery power, temperature, voltage, charging curve, etc.) to optimize the charging process and ensure safety and efficiency. Specifically, the battery of an electric vehicle has different power requirements at different charging stages (such as initial charging, fast charging stage, and trickle charging stage). For example:

[0004] Initial stage: When the battery power of the electric vehicle is low, the system will detect the battery status and allow the charging pile to provide higher power to quickly increase the power. At this time, the output power of the charging pile is higher to achieve fast charging.

[0005] Fast charging stage: When the battery power reaches a certain level, the system will gradually reduce the power according to the battery status to avoid damage to the battery caused by overcharging. The charging power in this stage is higher, but slightly reduced to ensure that the battery is charged within an acceptable range.

[0006] Trickle charging stage: When the battery is nearly full, the system will further reduce the output power of the charging pile and enter the trickle charging stage. The power in this stage is very low, mainly to protect the battery and prevent battery aging due to overcharging.

[0007] The prior art has the following deficiencies:

[0008] During the trickle charging process, if the system cannot stably control the current output, resulting in abnormal current fluctuations, the existing technology cannot effectively deal with this problem. When this happens, it may cause an impact on the inside of the battery, especially when the battery is about to be fully charged. Excessive current or sudden power fluctuations will destroy the electrochemical balance of the battery, causing a sharp drop in battery performance, and even causing an internal short circuit in the battery, causing irreversible damage.

[0009] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0010] The purpose of the present invention is to provide a control method and system based on an intelligent charging pile cluster, which can quickly identify abnormal fluctuations and dynamically adjust power by acquiring and analyzing current data in real time, avoiding damage to the battery due to sudden or excessive current, especially in the sensitive trickle charging stage, preventing battery aging and short circuit, extending battery life, and ensuring charging safety. After the abnormal current fluctuation is controlled, fuzzy logic and PID control are combined, fuzzy logic copes with nonlinear current fluctuations, and PID control accurately adjusts the power in a stable state, thereby improving the system's response capability and control accuracy to complex fluctuations, ensuring a safe and efficient charging process, and enhancing system stability, so as to solve the problems in the above-mentioned background technology.

[0011] In order to achieve the above object, the present invention provides the following technical solution: a control method based on a smart charging pile cluster, comprising the following steps:

[0012] Identify various stages of battery charging, where the battery charging stages include an initial stage, a fast charging stage, and a trickle charging stage;

[0013] After entering the trickle charging stage, the battery charging current data is obtained in real time;

[0014] After obtaining the real-time current data, analyze the current data obtained during the trickle charging stage in the detection window to identify abnormal current fluctuations;

[0015] After initially identifying the abnormal current fluctuation, further obtaining the maximum value of the abnormal fluctuation current in the detection window;

[0016] Compare and analyze the maximum value of abnormal current fluctuation with the upper limit of current during normal battery charging to determine whether the current abnormal current fluctuation exceeds the safety range;

[0017] If the comparison and analysis results show that the maximum value of the abnormally fluctuating current exceeds the upper limit of the current when the battery is normally charged, the charging power is dynamically adjusted according to the maximum value of the abnormally fluctuating current, and the maximum value of the abnormally fluctuating current is reduced by adjusting the charging power output of the charging pile;

[0018] After charging power regulation, ensure that the maximum value of abnormally fluctuating current returns to the power range of normal battery charging;

[0019] When the maximum value of the abnormally fluctuating current is within the normal range, power adjustment is performed based on the real-time current during charging by combining fuzzy logic control and PID control. When nonlinear changes in real-time current are detected, fuzzy logic control is used to flexibly adjust the charging power to handle complex nonlinear situations. When the real-time current during charging is monitored to be stable, PID control is switched to use its precise feedback adjustment mechanism to finely regulate the power to ensure that the entire charging process is carried out in a safe and efficient state.

[0020] Preferably, after acquiring the real-time current data, the current data acquired during the trickle charging stage is analyzed under the detection window to generate a current abnormal fluctuation assessment coefficient, and the abnormal current fluctuation is intelligently assessed through the current abnormal fluctuation assessment coefficient. The current abnormal fluctuation assessment coefficient is compared and analyzed with a preset current abnormal fluctuation assessment coefficient reference threshold to identify abnormal current fluctuations.

[0021] Preferably, the specific steps of analyzing the current data obtained in the trickle charging stage under the detection window to generate the current abnormal fluctuation evaluation coefficient are as follows:

[0022] In the trickle charging stage, the current data of the battery is obtained in real time through a high-precision current sensor, and the collected data is represented by I(t), where I(t) represents the current value at time t, where t=1, 2, 3, ..., T, and T represents the length of the detection window;

[0023] In order to capture the current fluctuation, the instantaneous current change rate at each time point is calculated. The calculation expression is: In the formula, is the instantaneous rate of change of current at time t;

[0024] The instantaneous current change rate is further analyzed, and the energy intensity of the current fluctuation is used to evaluate the potential abnormality of the current fluctuation. The "energy intensity function" is introduced to characterize the energy of the current fluctuation. The calculation expression is:

[0025] ,

[0026] In the formula, It is the second-order derivative of the current, which is used to capture the acceleration characteristics when the current fluctuates violently. α is the adjustment factor, which is used to control the contribution ratio of acceleration to energy intensity. E(t) represents the energy intensity of current fluctuations. t0 represents the starting point of time, t1 represents the current time point, and the upper limit of the integral represents the moment currently being analyzed, which changes with time.

[0027] The current abnormal fluctuation assessment coefficient is calculated based on the current fluctuation energy intensity. The current abnormal fluctuation assessment coefficient is used to intelligently assess the abnormal fluctuation of the current. The calculation expression is:

[0028] ,

[0029] Where λ is an exponential factor used to amplify the impact of current at higher fluctuations, β and ξ are adjustment parameters for controlling the impact of abnormal fluctuations and small fluctuations, and are used to balance the sensitivity of the current abnormal fluctuation evaluation coefficient, and |I(t)| is the absolute value of the current, which serves as a reference for the overall level of current fluctuations.

[0030] Preferably, the current abnormal fluctuation assessment coefficient generated by analyzing the current data obtained in the trickle charging stage under the detection window is compared and analyzed with a preset current abnormal fluctuation assessment coefficient reference threshold to identify abnormal current fluctuations. The specific steps are as follows:

[0031] If the abnormal current fluctuation assessment coefficient is greater than or equal to the abnormal current fluctuation assessment coefficient reference threshold, the current data under the detection window is marked as the abnormal current fluctuation period; if the abnormal current fluctuation assessment coefficient is less than the abnormal current fluctuation assessment coefficient reference threshold, the current data under the detection window is marked as the normal current period.

[0032] Preferably, after initially identifying the abnormal current fluctuation, all current values ​​under the detection window are counted, the acquired current values ​​are used to establish a data set, and the current values ​​in the data set are sorted in order, the maximum current value is screened out, and the maximum current value is marked as I max .

[0033] Preferably, the maximum current value screened out when the current fluctuates abnormally is compared and analyzed with the current upper limit value when the battery is normally charged to determine whether the current current fluctuation exceeds the safety range. The specific steps are:

[0034] If the maximum current value is greater than the upper current limit, a current abnormality signal is generated, indicating that the abnormal current fluctuation under the detection window exceeds the safety range;

[0035] If the maximum current value is less than or equal to the current upper limit value, a normal current signal is generated, indicating that the abnormal current fluctuation under the detection window does not exceed the safety range.

[0036] Preferably, the charging power is dynamically adjusted according to the maximum value of the abnormally fluctuating current, and the maximum value of the abnormally fluctuating current is reduced by regulating the charging power output of the charging pile. The specific steps are as follows:

[0037] Calculate the current deviation between the maximum value of the abnormally fluctuating current and the upper limit of the current when the battery is normally charged, and determine the magnitude of the current exceeding the upper limit. The calculation expression is: ΔI=I max -I limit , where I limit It indicates the upper limit of the current when the battery is normally charged, and ΔI indicates the current deviation between the maximum current and the upper limit of the current;

[0038] According to the current deviation value ΔI, the abnormal current fluctuation is reduced by reducing the power output, and the current adjustment is converted into a power adjustment instruction using the formula. The specific expression is: Among them, P new is the adjusted charging power, P current is the current charging power output;

[0039] The relationship between current, voltage and power is used to calculate the voltage adjustment value to achieve dynamic control of charging power. The specific expression for charging pile voltage output regulation is: Where V new Indicates the voltage adjustment value;

[0040] Continuously monitor the current fluctuation and update the charging power output in real time. In the next detection window, reacquire the current data and dynamically update the charging power by the magnitude of the current exceeding the upper limit. The expression for dynamically updating the charging power is: Where P adjusted It represents the charging power that is further adjusted after dynamic regulation. k is an adjustment coefficient, which is used to make subtle adjustments to the charging power according to the nonlinear effect of the current change rate.

[0041] Preferably, when the maximum value of the abnormally fluctuating current is within the normal range, the current I(t) is obtained in real time during the charging process, and its first-order derivative is calculated. and the second-order derivative like If it is the preset nonlinear change threshold, the system is judged to enter the nonlinear change state and enters the fuzzy logic control;

[0042] After detecting nonlinear current fluctuations, the charging power is adjusted using fuzzy logic control, which is based on the first-order derivative and the second-order derivative The fuzzy inference system outputs the appropriate power adjustment coefficient α(t) and dynamically adjusts the charging power. The specific expression is: fuzzy (t) = P current ·α(t), where α(t) is the output result of fuzzy reasoning, representing the adjustment coefficient of charging power, P fuzzy(t) is the real-time power output under fuzzy logic control, where P current is the current charging power, and α(t) adjusts the charging power according to the current current fluctuation through fuzzy reasoning.

[0043] Preferably, when the current fluctuation monitored in real time tends to be stable and When , δ is the preset stability threshold, it switches to PID control. Under the current stable state, PID control can provide accurate power regulation and maintain steady-state regulation of charging power. The specific expression of charging power regulated by PID is: Where, e(t) is the error between the target current and the actual current, K p , K i , K d are proportional, integral and differential coefficients respectively. ∫e(t)dt represents the cumulative amount of error between the target current and the actual current over time, which is the integral term in the PID controller. PID (t) is the real-time power output under PID control;

[0044] According to the real-time feedback of current fluctuation, the system dynamically switches between fuzzy logic control and PID control. When the current fluctuation returns to a stable state, PID control continues to be used for fine adjustment. If current fluctuation or nonlinear change is detected again, it switches back to fuzzy logic control. The system flexibly switches between the two control mechanisms to ensure that the charging process is both efficient and safe. According to the current fluctuation, the expression of the switching control strategy is:

[0045] A control system based on an intelligent charging pile cluster, comprising a charging stage identification module, a data acquisition module, an abnormality detection module, a maximum value acquisition module, a safety assessment module, a power regulation module, a power range confirmation module and an intelligent control module;

[0046] A charging stage identification module identifies various stages of battery charging, wherein the battery charging stages include an initial stage, a fast charging stage, and a trickle charging stage;

[0047] The data acquisition module acquires the battery charging current data in real time after entering the trickle charging stage;

[0048] The abnormality detection module, after acquiring the real-time current data, analyzes the current data acquired during the trickle charging stage under the detection window to identify abnormal current fluctuations;

[0049] The maximum value acquisition module further acquires the maximum value of the abnormal fluctuation current in the detection window after initially identifying the abnormal current fluctuation;

[0050] The safety assessment module compares and analyzes the maximum value of abnormal current fluctuation with the upper limit of current during normal battery charging to determine whether the current abnormal current fluctuation exceeds the safety range;

[0051] The power regulation module dynamically adjusts the charging power according to the maximum value of the abnormally fluctuating current, and reduces the maximum value of the abnormally fluctuating current by regulating the charging power output of the charging pile, if the comparison and analysis results show that the maximum value of the abnormally fluctuating current exceeds the upper limit of the current when the battery is normally charged;

[0052] The power range confirmation module ensures that the maximum value of abnormally fluctuating current returns to the power range of normal battery charging after charging power regulation;

[0053] The intelligent control module adjusts the power according to the real-time current during the charging process by combining fuzzy logic control and PID control when the maximum value of the abnormally fluctuating current is already within the normal range. When the nonlinear change of the real-time current is detected, the fuzzy logic control is used to flexibly adjust the charging power to handle complex nonlinear situations. When the real-time current during the charging process is monitored to be stable, the PID control is switched to use its precise feedback adjustment mechanism to finely control the power to ensure that the entire charging process is carried out in a safe and efficient state.

[0054] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0055] The present invention can quickly identify abnormal current fluctuations by acquiring and analyzing current data in real time, and automatically adjust power when the maximum abnormal current fluctuation value exceeds the safe range. This process avoids internal damage to the battery caused by sudden or excessive current, especially in sensitive charging stages such as trickle charging, where excessive current may cause the chemical balance inside the battery to be broken, thereby accelerating battery aging and even causing a short circuit. By dynamically adjusting the charging power at each stage, it ensures that the current fluctuation is maintained within a safe range, avoids irreversible damage to battery performance caused by overcharging or sudden current shocks, effectively extends battery life, ensures charging safety, and improves the overall efficiency of the charging system.

[0056] After the abnormal current fluctuation is controlled, the present invention cleverly combines the two adjustment mechanisms of fuzzy logic and PID control to give full play to their respective advantages. Fuzzy logic can provide flexible response capabilities when the current changes nonlinearly, handle complex situations, and avoid subtle fluctuations that traditional control algorithms cannot cope with. When the current tends to stabilize, PID control takes over the system and provides high-precision power regulation through its precise feedback adjustment mechanism. This combination not only improves the system's ability to respond to complex current fluctuations, but also ensures that when the current stabilizes, the charging process can be maintained in the optimal state, thereby taking into account flexibility and precision, effectively improving the stability and overall efficiency of the charging system, and making the charging process safer and more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0058] Figure 1 The present invention is a method flow chart of a control method based on a smart charging pile cluster.

[0059] Figure 2 The module diagram of a control system based on a smart charging pile cluster of the present invention. DETAILED DESCRIPTION

[0060] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0061] The present invention provides Figure 1 A control method based on a smart charging pile cluster is shown, comprising the following steps:

[0062] Identify various stages of battery charging, where the battery charging stages include an initial stage, a fast charging stage, and a trickle charging stage;

[0063] In modern battery management systems (BMS), based on real-time monitoring data such as battery voltage, current, and power, the system can accurately identify when the battery is close to full charge. At this point, the charging enters the trickle charging stage, that is, the charging current begins to decrease significantly and gradually turns to low current charging. The existing technology automatically determines and switches to trickle charging mode by setting a specific voltage or charging percentage threshold (for example, the battery voltage is close to 4.2V or the power reaches more than 90%). Accurately identifying this stage is particularly important for subsequent current monitoring and regulation to ensure charging safety and battery life.

[0064] After entering the trickle charging stage, the battery charging current data is obtained in real time;

[0065] Existing current sensors and battery management systems can collect current, voltage and temperature data in real time during the charging process and transmit them to the central control system for analysis. Especially during the trickle charging stage, the current is usually low, so high-precision sensors are required to capture tiny current changes. Through high-precision current sensors, the system can continuously collect the current value of the battery during charging, providing basic data support for subsequent current fluctuation detection.

[0066] After obtaining the real-time current data, analyze the current data obtained during the trickle charging phase in the detection window to identify abnormal current fluctuations;

[0067] After obtaining the real-time current data, the current data obtained in the trickle charging stage is analyzed in the detection window to generate a current abnormal fluctuation assessment coefficient. The abnormal current fluctuation is intelligently assessed through the current abnormal fluctuation assessment coefficient. The current abnormal fluctuation assessment coefficient is compared and analyzed with a preset current abnormal fluctuation assessment coefficient reference threshold to identify abnormal current fluctuations.

[0068] The specific steps for analyzing the current data obtained during the trickle charging phase under the detection window to generate the current abnormal fluctuation evaluation coefficient are as follows:

[0069] In the trickle charging stage, the current data of the battery is obtained in real time through a high-precision current sensor, and the collected data is represented by I(t), where I(t) represents the current value at time t, where t=1, 2, 3, ..., T, and T represents the length of the detection window;

[0070] In order to capture the current fluctuation, the instantaneous current change rate at each time point is calculated. The instantaneous current change rate can evaluate the severity of the current fluctuation. The calculation expression is: In the formula, is the instantaneous rate of change of current at time t;

[0071] The instantaneous current change rate can be used to preliminarily assess the dramatic current fluctuations. If the ΔI(t) value is large, it means that the current changes dramatically and there may be abnormal fluctuations.

[0072] The instantaneous current change rate is further analyzed, and the energy intensity of the current fluctuation is used to evaluate the potential abnormality of the current fluctuation. The "energy intensity function" is introduced to characterize the energy of the current fluctuation. This is similar to the power spectrum density analysis in signal processing, but a non-traditional calculation method can be used. The calculation expression is:

[0073] ,

[0074] In the formula, It is the second-order derivative of the current (acceleration of the current), which is used to capture the acceleration characteristics when the current fluctuates violently. α is the adjustment factor, which is used to control the contribution ratio of acceleration to energy intensity. The selection of the adjustment factor can be adjusted according to the charging characteristics of different batteries. E(t) represents the energy intensity of current fluctuations, which can comprehensively consider the fluctuation amplitude and fluctuation rate of the current. t0 represents the starting point of time, that is, the time when the integration starts. It can be the starting point of the entire analysis process, usually the initial moment of monitoring in a certain charging process. t1 represents the current time point, the upper limit of the integration. It represents the moment currently being analyzed and changes with time.

[0075] The current abnormal fluctuation assessment coefficient is calculated based on the current fluctuation energy intensity. The current abnormal fluctuation assessment coefficient is used to intelligently assess the abnormal fluctuation of the current. The calculation expression is:

[0076] ,

[0077] Where λ is an exponential factor used to amplify the impact of current under high fluctuations, β and γ are adjustment parameters for controlling the impact of abnormal fluctuations and small fluctuations, and are used to balance the sensitivity of the current abnormal fluctuation evaluation coefficient, and |I(t)| is the absolute value of the current, which serves as a reference for the overall level of current fluctuations.

[0078] The setting criteria for λ are usually related to the charging characteristics and safety requirements of the battery. If the battery is more susceptible to overheating or damage under high current conditions, λ should be set to a higher value to amplify the impact of high current fluctuations and ensure that the system responds faster. When setting λ, it is necessary to test and optimize according to the battery type, charging stage, and safety critical points. For example, for sensitive lithium batteries, λ can be set larger to amplify the impact of current fluctuations at the end of charging, thereby reducing the risk of battery damage.

[0079] β is the weight that directly affects the abnormal assessment of current fluctuations in the formula. Its setting standard is related to the system's tolerance for current fluctuations. Generally, the current fluctuation of the system during charging should not be too large, so the value of β needs to ensure that the system is not too sensitive within the normal current fluctuation range, but also responds accurately to fluctuations beyond the safe range. If the current fluctuation is large and lasts for a long time, β should be set smaller to increase the impact of abnormal fluctuations; on the contrary, if the system has a larger tolerance for fluctuations, β should be set larger to reduce the response to small fluctuations.

[0080] ξ is a parameter used to control the contribution of the instantaneous current rate of change to the evaluation, especially for nonlinear situations. Its setting criteria are related to the frequency and amplitude of current changes. If the current changes during charging are frequent and drastic, the value of ξ should be set smaller to allow for a greater impact of nonlinear fluctuations on system evaluation. This helps to make accurate evaluations in more complex current fluctuation scenarios. For more stable charging environments, ξ can be set larger to reduce the impact of nonlinear fluctuations, thereby avoiding overreaction of the system to minor, non-critical fluctuations.

[0081] The higher the value of the abnormal current fluctuation assessment coefficient, the more serious the abnormal current fluctuation is, because the abnormal current fluctuation assessment coefficient comprehensively considers the fluctuation amplitude and change rate of the current. In the formula, the fluctuation characteristics of the current over a period of time are evaluated by integrating the current change and the second-order derivative of the current (i.e., acceleration). A larger fluctuation amplitude or a drastic change rate will increase the abnormal current fluctuation assessment coefficient, which indicates that the current fluctuations are frequent and large in amplitude, which may cause instability or damage to the battery. Therefore, when the abnormal current fluctuation assessment coefficient is high, it means that the current has experienced abnormal fluctuations beyond the normal range within a certain period of time, reflecting the severity of the fluctuation.

[0082] The current abnormal fluctuation assessment coefficient generated by analyzing the current data obtained in the trickle charging stage under the detection window is compared with the preset current abnormal fluctuation assessment coefficient reference threshold to identify the abnormal current fluctuation. The specific steps are as follows:

[0083] If the abnormal current fluctuation assessment coefficient is greater than or equal to the abnormal current fluctuation assessment coefficient reference threshold, the current data under the detection window is marked as the abnormal current fluctuation period; if the abnormal current fluctuation assessment coefficient is less than the abnormal current fluctuation assessment coefficient reference threshold, the current data under the detection window is marked as the normal current period.

[0084] After initially identifying the abnormal current fluctuation, further obtaining the maximum value of the abnormal fluctuation current in the detection window;

[0085] The maximum value of abnormal fluctuating current is the key data to judge the severity of fluctuation. Through real-time monitoring, the system can record the peak value of current fluctuation, which is the most direct manifestation of abnormal current fluctuation.

[0086] After initially identifying the abnormal current fluctuation, all current values ​​in the detection window are counted, the acquired current values ​​are used to establish a data set, and the current values ​​in the data set are sorted in order to filter out the maximum current value, and the maximum current value is marked as I max .

[0087] Compare and analyze the maximum value of abnormal current fluctuation with the upper limit of current during normal battery charging to determine whether the current abnormal current fluctuation exceeds the safety range;

[0088] The upper current limit of a battery during normal charging refers to the maximum current value that the battery can withstand during safe charging. Exceeding this value may cause the battery to overheat, age, or even be damaged. The setting of the upper current limit should be determined based on the battery specifications, chemical properties, and charging parameters provided by the manufacturer. Usually, the upper current limit of the battery is related to the charging stage. The current allowed in the fast charging stage is larger, while the upper current limit is lower in the trickle charging stage. To ensure safety, the upper current limit usually takes into account a certain safety margin to prevent the battery from being subjected to currents beyond the design range due to instantaneous fluctuations or errors. Therefore, the setting of the upper current limit needs to be combined with the battery's capacity, material, and temperature characteristics to ensure that the battery will not be damaged at each charging stage.

[0089] Compare and analyze the maximum current value screened out when the current fluctuates abnormally with the current upper limit when the battery is charged normally to determine whether the current current fluctuation exceeds the safe range. The specific steps are as follows:

[0090] If the maximum current value is greater than the upper current limit, a current abnormality signal is generated, indicating that the abnormal current fluctuation under the detection window exceeds the safety range;

[0091] If the maximum current value is less than or equal to the current upper limit value, a normal current signal is generated, indicating that the abnormal current fluctuation under the detection window does not exceed the safety range.

[0092] If the comparison and analysis results show that the maximum value of the abnormally fluctuating current exceeds the upper limit of the current when the battery is normally charged, the charging power is dynamically adjusted according to the maximum value of the abnormally fluctuating current, and the maximum value of the abnormally fluctuating current is reduced by adjusting the charging power output of the charging pile;

[0093] According to the maximum value of the abnormally fluctuating current, the charging power is dynamically adjusted, and the maximum value of the abnormally fluctuating current is reduced by adjusting the charging power output of the charging pile. The specific steps are as follows:

[0094] Calculate the current deviation between the maximum value of the abnormally fluctuating current and the upper limit of the current when the battery is normally charged, and determine the magnitude of the current exceeding the upper limit. The calculation expression is: ΔI=I max -I limit , where I limit It indicates the upper limit of the current when the battery is normally charged, and ΔI indicates the current deviation between the maximum current and the upper limit of the current;

[0095] According to the current deviation value ΔI, the abnormal current fluctuation is reduced by reducing the power output, and the current adjustment is converted into a power adjustment instruction using the formula. The specific expression is: Among them, P new is the adjusted charging power, P current is the current charging power output;

[0096] By proportionally reducing the charging power, the current fluctuation can be effectively controlled within a reasonable range.

[0097] The relationship between current, voltage and power is used to calculate the voltage adjustment value to achieve dynamic control of charging power. The specific expression for charging pile voltage output regulation is: Where V new Indicates the voltage adjustment value;

[0098] By regulating the voltage output, the current fluctuation is ensured to be kept below the upper current limit and the charging process is guaranteed to be smooth.

[0099] Continuously monitor the current fluctuation and update the charging power output in real time. In the next detection window, reacquire the current data and dynamically update the charging power by the magnitude of the current exceeding the upper limit. The expression for dynamically updating the charging power is: Where P adjusted represents the charging power that is further adjusted after dynamic regulation, and k is an adjustment coefficient used to make subtle adjustments to the charging power according to the nonlinear effect of the current change rate;

[0100] This step ensures that current fluctuations can be dynamically controlled to avoid damaging the battery due to excessive fluctuations.

[0101] According to the maximum value of the abnormally fluctuating current, the charging power is dynamically adjusted, and the maximum value of the abnormally fluctuating current is reduced by adjusting the charging power output of the charging pile. The main function is to control the abnormal current fluctuation by dynamically adjusting the charging power output of the charging pile to prevent the battery from being damaged by excessive current or excessive fluctuation. When it is detected that the maximum value of the abnormally fluctuating current exceeds the upper limit of the battery's safe current, the amplitude of the current fluctuation can be effectively reduced by adjusting the charging power, avoiding the adverse effects of excessive current on the battery's electrochemical balance, life and safety. This process not only prolongs the service life of the battery, but also ensures the smoothness of the charging process and the safety of the equipment.

[0102] After charging power regulation, ensure that the maximum value of abnormally fluctuating current returns to the power range of normal battery charging;

[0103] After the charging power is regulated, the maximum current value screened out when the current fluctuates abnormally is compared and analyzed with the current upper limit when the battery is charged normally to determine whether the current current fluctuation exceeds the safety range. The specific steps are: if the maximum current is greater than the current upper limit, a charging power regulation failure signal is generated, and the charging power continues to be dynamically adjusted; if the maximum current is less than or equal to the current upper limit, a charging power regulation success signal is generated, and the dynamic adjustment of the charging power is stopped.

[0104] When the maximum value of the abnormally fluctuating current is within the normal range, the power is adjusted according to the real-time current during the charging process, combining fuzzy logic control and PID control. When nonlinear changes in the real-time current are detected, the charging power is flexibly adjusted using fuzzy logic control to handle complex nonlinear situations. When the real-time current during the charging process is monitored to be stable, the PID control is switched to use its precise feedback adjustment mechanism to finely control the power to ensure that the entire charging process is carried out in a safe and efficient state.

[0105] When the maximum value of the abnormally fluctuating current is within the normal range, the current I(t) is obtained in real time during the charging process, and its first-order derivative is calculated. (instantaneous current rate of change) and second-order derivative (acceleration of current). By analyzing the first-order derivative and the second derivative If the current changes rapidly or fluctuates violently (i.e. the second-order derivative value is large), the system is judged to have entered a nonlinear change state and fuzzy logic control is required. The first-order derivative is the instantaneous rate of change of the current, which is used to capture dynamic changes. The second-order derivative is the acceleration of the current change, which indicates the severity of the current fluctuation. (in is the preset nonlinear change threshold), then fuzzy logic control is entered.

[0106] After detecting nonlinear current fluctuations, fuzzy logic control is used to adjust the charging power. Fuzzy logic control is based on the first-order derivative and the second derivative The fuzzy inference system outputs the appropriate power adjustment coefficient α(t) and dynamically adjusts the charging power. The specific expression is: fuzzy (t) = P current ·α(t), where α(t) is the output result of fuzzy reasoning, representing the adjustment coefficient of charging power, P fuzzy (t) is the real-time power output under fuzzy logic control, where P current is the current charging power, and α(t) adjusts the charging power according to the current current fluctuation through fuzzy reasoning.

[0107] When the current fluctuation monitored in real time tends to be stable and When , δ is the preset stability threshold, it switches to PID control. Under the current stable state, PID control can provide accurate power regulation and maintain steady-state regulation of charging power. The specific expression of charging power regulated by PID is: Where, e(t) is the error between the target current and the actual current, K p , K i , K d are proportional, integral and differential coefficients respectively. ∫e(t)dt represents the cumulative amount of error between the target current and the actual current over time, which is the integral term in the PID controller. PID (t) is the real-time power output under PID control.

[0108] According to the real-time feedback of current fluctuation, the system dynamically switches between fuzzy logic control and PID control. When the current fluctuation returns to a stable state, PID control continues to be used for fine adjustment. If current fluctuation or nonlinear change is detected again, it switches back to fuzzy logic control. The system flexibly switches between the two control mechanisms to ensure that the charging process is both efficient and safe. According to the current fluctuation, the expression of the switching control strategy is:

[0109] By combining fuzzy logic control and PID control, refined power regulation is achieved during the charging process to ensure the safety and stability of charging. When the real-time current changes nonlinearly, fuzzy logic control can flexibly adjust the power to cope with complex nonlinear fluctuations and avoid the negative impact of current fluctuations on the battery. When the current tends to stabilize, the system automatically switches to PID control, using its precise feedback adjustment mechanism to make more detailed adjustments to the charging power, maintain the stability of the current, and ensure that the charging process is both efficient and safe. This step prevents damage to the battery from overcharging or current fluctuations through dynamic control.

[0110] The present invention can quickly identify abnormal current fluctuations by acquiring and analyzing current data in real time, and automatically adjust power when the maximum abnormal current fluctuation value exceeds the safe range. This process avoids internal damage to the battery caused by sudden or excessive current, especially in sensitive charging stages such as trickle charging, where excessive current may cause the chemical balance inside the battery to be broken, thereby accelerating battery aging and even causing a short circuit. By dynamically adjusting the charging power at each stage, it ensures that the current fluctuation is maintained within a safe range, avoids irreversible damage to battery performance caused by overcharging or sudden current shocks, effectively extends battery life, ensures charging safety, and improves the overall efficiency of the charging system.

[0111] After the abnormal current fluctuation is controlled, the present invention cleverly combines the two adjustment mechanisms of fuzzy logic and PID control to give full play to their respective advantages. Fuzzy logic can provide flexible response capabilities when the current changes nonlinearly, handle complex situations, and avoid subtle fluctuations that traditional control algorithms cannot cope with. When the current tends to stabilize, PID control takes over the system and provides high-precision power regulation through its precise feedback adjustment mechanism. This combination not only improves the system's ability to respond to complex current fluctuations, but also ensures that when the current stabilizes, the charging process can be maintained in the optimal state, thereby taking into account flexibility and precision, effectively improving the stability and overall efficiency of the charging system, and making the charging process safer and more efficient.

[0112] The present invention provides Figure 2 A control system based on a smart charging pile cluster is shown, comprising a charging stage identification module, a data acquisition module, an abnormality detection module, a maximum value acquisition module, a safety assessment module, a power regulation module, a power range confirmation module and an intelligent control module;

[0113] A charging stage identification module identifies various stages of battery charging, wherein the battery charging stages include an initial stage, a fast charging stage, and a trickle charging stage;

[0114] The data acquisition module acquires the battery charging current data in real time after entering the trickle charging stage;

[0115] The abnormality detection module, after acquiring the real-time current data, analyzes the current data acquired during the trickle charging stage under the detection window to identify abnormal current fluctuations;

[0116] The maximum value acquisition module further acquires the maximum value of the abnormal fluctuation current in the detection window after initially identifying the abnormal current fluctuation;

[0117] The safety assessment module compares and analyzes the maximum value of abnormal current fluctuation with the upper limit of current during normal battery charging to determine whether the current abnormal current fluctuation exceeds the safety range;

[0118] The power regulation module dynamically adjusts the charging power according to the maximum value of the abnormally fluctuating current, and reduces the maximum value of the abnormally fluctuating current by regulating the charging power output of the charging pile, if the comparison and analysis results show that the maximum value of the abnormally fluctuating current exceeds the upper limit of the current when the battery is normally charged;

[0119] The power range confirmation module ensures that the maximum value of abnormally fluctuating current returns to the power range of normal battery charging after charging power regulation;

[0120] The intelligent control module adjusts the power according to the real-time current during the charging process by combining fuzzy logic control and PID control when the maximum value of the abnormally fluctuating current is within the normal range. When the nonlinear change of the real-time current is detected, the fuzzy logic control is used to flexibly adjust the charging power to handle complex nonlinear situations. When the real-time current during the charging process is monitored to be stable, the PID control is switched to use its precise feedback adjustment mechanism to finely control the power to ensure that the entire charging process is carried out in a safe and efficient state.

[0121] A control method based on a smart charging pile cluster provided in an embodiment of the present invention is implemented by the above-mentioned control system based on a smart charging pile cluster. The specific method and process of a control system based on a smart charging pile cluster are detailed in the above-mentioned embodiment of a control method based on a smart charging pile cluster, which will not be repeated here.

[0122] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center containing one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0123] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0124] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0125] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0128] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0129] 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 who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0130] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A control method based on a smart charging pile cluster, characterized in that: The following steps are involved: Identify various stages of battery charging, where the battery charging stages include an initial stage, a fast charging stage, and a trickle charging stage; After entering the trickle charging stage, the battery charging current data is obtained in real time; After obtaining the real-time current data, analyze the current data obtained during the trickle charging stage in the detection window to identify abnormal current fluctuations; After initially identifying the abnormal current fluctuation, further obtaining the maximum value of the abnormal fluctuation current in the detection window; Compare and analyze the maximum value of abnormal current fluctuation with the upper limit of current during normal battery charging to determine whether the current abnormal current fluctuation exceeds the safety range; If the comparison and analysis results show that the maximum value of the abnormally fluctuating current exceeds the upper limit of the current when the battery is normally charged, the charging power is dynamically adjusted according to the maximum value of the abnormally fluctuating current, and the maximum value of the abnormally fluctuating current is reduced by adjusting the charging power output of the charging pile; After charging power regulation, ensure that the maximum value of abnormally fluctuating current returns to the power range of normal battery charging; When the maximum value of the abnormally fluctuating current is within the normal range, power adjustment is performed based on the real-time current during charging by combining fuzzy logic control and PID control. When nonlinear changes in real-time current are detected, fuzzy logic control is used to flexibly adjust the charging power to handle complex nonlinear situations. When the real-time current during charging is monitored to be stable, PID control is switched to use its precise feedback adjustment mechanism to finely regulate the power to ensure that the entire charging process is carried out in a safe and efficient state.

2. A control method based on a smart charging pile cluster according to claim 1, characterized in that: After obtaining the real-time current data, the current data obtained in the trickle charging stage is analyzed in the detection window to generate a current abnormal fluctuation assessment coefficient. The abnormal current fluctuation situation is intelligently evaluated through the current abnormal fluctuation assessment coefficient. The abnormal current fluctuation assessment coefficient is compared and analyzed with the pre-set reference threshold of the abnormal current fluctuation assessment coefficient to identify abnormal current fluctuations.

3. A control method based on a smart charging pile cluster according to claim 2, characterized in that: The specific steps for analyzing the current data obtained during the trickle charging stage under the detection window to generate the current abnormal fluctuation evaluation coefficient are as follows: In the trickle charging stage, the current data of the battery is obtained in real time through a high-precision current sensor, and the collected data is represented by I(t), where I(t) represents the current value at time t, where t=1, 2, 3, ..., T, and T represents the length of the detection window; In order to capture the current fluctuation, the instantaneous current change rate at each time point is calculated. The calculation expression is: In the formula, is the instantaneous rate of change of current at time t; The instantaneous current change rate is further analyzed, and the energy intensity of the current fluctuation is used to evaluate the potential abnormality of the current fluctuation. The "energy intensity function" is introduced to characterize the energy of the current fluctuation. The calculation expression is: ， In the formula, It is the second-order derivative of the current, which is used to capture the acceleration characteristics when the current fluctuates violently. α is the adjustment factor, which is used to control the contribution ratio of acceleration to energy intensity. E(t) represents the energy intensity of current fluctuations. t0 represents the starting point of time, t1 represents the current time point, and the upper limit of the integral represents the moment currently being analyzed, which changes with time. The current abnormal fluctuation assessment coefficient is calculated based on the current fluctuation energy intensity. The current abnormal fluctuation assessment coefficient is used to intelligently assess the abnormal fluctuation of the current. The calculation expression is: ， Where λ is an exponential factor used to amplify the impact of current fluctuations, β and ξ are adjustment parameters for controlling the impact of abnormal fluctuations and small fluctuations, and are used to balance the sensitivity of the current abnormal fluctuation evaluation coefficient, and |I(t)| is the absolute value of the current, which serves as a reference for the overall level of current fluctuations.

4. A control method based on a smart charging pile cluster according to claim 3, characterized in that: The current abnormal fluctuation assessment coefficient generated by analyzing the current data obtained in the trickle charging stage under the detection window is compared with the preset current abnormal fluctuation assessment coefficient reference threshold to identify the abnormal current fluctuation. The specific steps are as follows: If the abnormal current fluctuation assessment coefficient is greater than or equal to the abnormal current fluctuation assessment coefficient reference threshold, the current data under the detection window is marked as the abnormal current fluctuation period; if the abnormal current fluctuation assessment coefficient is less than the abnormal current fluctuation assessment coefficient reference threshold, the current data under the detection window is marked as the normal current period.

5. The control method based on the intelligent charging pile cluster according to claim 1 is characterized in that: After initially identifying the abnormal current fluctuation, all current values ​​in the detection window are counted, the acquired current values ​​are used to establish a data set, and the current values ​​in the data set are sorted in order to filter out the maximum current value, and the maximum current value is marked as I max .

6. The control method based on the intelligent charging pile cluster according to claim 1 is characterized in that: Compare and analyze the maximum current value screened out when the current fluctuates abnormally with the current upper limit when the battery is charged normally to determine whether the current current fluctuation exceeds the safe range. The specific steps are as follows: If the maximum current value is greater than the upper current limit, a current abnormality signal is generated, indicating that the abnormal current fluctuation under the detection window exceeds the safety range; If the maximum current value is less than or equal to the current upper limit value, a normal current signal is generated, indicating that the abnormal current fluctuation under the detection window does not exceed the safety range.

7. A control method based on a smart charging pile cluster according to claim 5, characterized in that: According to the maximum value of the abnormally fluctuating current, the charging power is dynamically adjusted, and the maximum value of the abnormally fluctuating current is reduced by adjusting the charging power output of the charging pile. The specific steps are as follows: Calculate the current deviation between the maximum value of the abnormally fluctuating current and the upper limit of the current when the battery is normally charged, and determine the magnitude of the current exceeding the upper limit. The calculation expression is: ΔI=I max -I limit , where I limit It indicates the upper limit of the current when the battery is normally charged, and ΔI indicates the current deviation between the maximum current and the upper limit of the current; According to the current deviation value ΔI, the abnormal current fluctuation is reduced by reducing the power output, and the current adjustment is converted into a power adjustment instruction using the formula. The specific expression is: Among them, P new is the adjusted charging power, P current is the current charging power output; The relationship between current, voltage and power is used to calculate the voltage adjustment value to achieve dynamic control of charging power. The specific expression for charging pile voltage output regulation is: Where V new Indicates the voltage adjustment value; Continuously monitor the current fluctuation and update the charging power output in real time. In the next detection window, reacquire the current data and dynamically update the charging power by the magnitude of the current exceeding the upper limit. The expression for dynamically updating the charging power is: Where P adjusted It represents the charging power that is further adjusted after dynamic regulation. k is an adjustment coefficient, which is used to make subtle adjustments to the charging power according to the nonlinear effect of the current change rate.

8. The control method based on the intelligent charging pile cluster according to claim 1 is characterized in that: When the maximum value of the abnormally fluctuating current is within the normal range, the current I(t) is obtained in real time during the charging process, and its first-order derivative is calculated. and the second derivative like If it is the preset nonlinear change threshold, the system is judged to enter the nonlinear change state and enters the fuzzy logic control; After detecting nonlinear current fluctuations, the charging power is adjusted using fuzzy logic control, which is based on the first-order derivative and the second derivative The fuzzy inference system outputs the appropriate power adjustment coefficient α(t) and dynamically adjusts the charging power. The specific expression is: fuzzy (t) = P current ·α(t), where α(t) is the output result of fuzzy reasoning, representing the adjustment coefficient of charging power, P fuzzy (t) is the real-time power output under fuzzy logic control, where P current is the current charging power, and α(t) adjusts the charging power according to the current current fluctuation through fuzzy reasoning.

9. A control method based on a smart charging pile cluster according to claim 8, characterized in that: When the current fluctuation monitored in real time tends to be stable and When , δ is the preset stability threshold, it switches to PID control. Under the current stable state, PID control can provide accurate power regulation and maintain steady-state regulation of charging power. The specific expression of charging power regulated by PID is: Where, e(t) is the error between the target current and the actual current, K p , K i , K d are proportional, integral and differential coefficients respectively. ∫e(t)dt represents the cumulative amount of error between the target current and the actual current over time, which is the integral term in the PID controller. PID (t) is the real-time power output under PID control; According to the real-time feedback of current fluctuation, the system dynamically switches between fuzzy logic control and PID control. When the current fluctuation returns to a stable state, PID control continues to be used for fine adjustment. If current fluctuation or nonlinear change is detected again, it switches back to fuzzy logic control. The system flexibly switches between the two control mechanisms to ensure that the charging process is both efficient and safe. According to the current fluctuation, the expression of the switching control strategy is:

10. A control system based on a smart charging pile cluster, used to implement the control method based on a smart charging pile cluster as described in any one of claims 1 to 9, characterized in that: It includes a charging stage identification module, a data acquisition module, an abnormality detection module, a maximum value acquisition module, a safety assessment module, a power regulation module, a power range confirmation module and an intelligent control module; A charging stage identification module identifies various stages of battery charging, wherein the battery charging stages include an initial stage, a fast charging stage, and a trickle charging stage; The data acquisition module acquires the battery charging current data in real time after entering the trickle charging stage; The abnormality detection module, after acquiring the real-time current data, analyzes the current data acquired during the trickle charging stage under the detection window to identify abnormal current fluctuations; The maximum value acquisition module further acquires the maximum value of the abnormal fluctuation current in the detection window after initially identifying the abnormal current fluctuation; The safety assessment module compares and analyzes the maximum value of abnormal current fluctuation with the upper limit of current during normal battery charging to determine whether the current abnormal current fluctuation exceeds the safety range; The power regulation module dynamically adjusts the charging power according to the maximum value of the abnormally fluctuating current, and reduces the maximum value of the abnormally fluctuating current by regulating the charging power output of the charging pile, if the comparison and analysis results show that the maximum value of the abnormally fluctuating current exceeds the upper limit of the current when the battery is normally charged; The power range confirmation module ensures that the maximum value of abnormally fluctuating current returns to the power range of normal battery charging after charging power regulation; The intelligent control module adjusts the power according to the real-time current during the charging process by combining fuzzy logic control and PID control when the maximum value of the abnormally fluctuating current is already within the normal range. When the nonlinear change of the real-time current is detected, the fuzzy logic control is used to flexibly adjust the charging power to handle complex nonlinear situations. When the real-time current during the charging process is monitored to be stable, the PID control is switched to use its precise feedback adjustment mechanism to finely control the power to ensure that the entire charging process is carried out in a safe and efficient state.

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