Smart community charging pile management method, device, equipment and medium

Abstract

The invention relates to an intelligent community charging pile management method and device, equipment and a medium, and the method comprises the steps: obtaining the real-time power utilization state data of a community, determining a corresponding effective charging power interval based on the power utilization state data, building a multi-level charging strategy according to the effective charging power interval, and carrying out the management of the charging pile of the intelligent community. A corresponding charging strategy is matched and issued to the target charging pile, operation data of the target charging pile are dynamically monitored, and the charging power of the target charging pile is adjusted in real time to not exceed a safety load limiting threshold value contained in a preset power grid bearing threshold value; generating and pushing a corresponding exclusive charging mode according to pre-acquired historical use behavior data of the user; based on an intelligent regulation and control mechanism of a cell-level load state and user multi-dimensional information, dynamic perception and hierarchical control of a charging process are realized, the load prediction capability is enhanced, and efficient scheduling and ordered management of charging behaviors in an intelligent cell are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of charging pile management, and in particular to a smart community charging pile management method, device, equipment and medium. BACKGROUND

[0002] At present, in the existing smart community construction, with the continuous increase of the number of electric vehicles, the deployment density of charging piles as basic supporting facilities is increasing, but at the same time, the charging process brings significant challenges to the instantaneous load of the community power distribution system. The traditional charging management mode mainly depends on single pile or static allocation strategy, and lacks the cooperative perception and control mechanism of the overall load state, user behavior difference and energy dynamic change, which is easy to cause local overload, low energy utilization efficiency and uneven user charging experience in peak period, and is difficult to meet the flexible allocation and safety protection demand in multi-user and multi-scene. Therefore, it is urgent to develop a charging management scheme with better adaptability and global perception ability to realize the safe scheduling and efficient utilization of power resources in the community level. SUMMARY

[0003] In order to solve the problem that the traditional charging management mode mainly depends on single pile or static allocation strategy, and is easy to cause local overload, low energy utilization efficiency and uneven user charging experience in peak period, the present application provides a smart community charging pile management method, device, equipment and medium.

[0004] A smart community charging pile management method, the smart community charging pile management method comprises: acquiring real-time power consumption state data of the community, the power consumption state data comprising total power consumption, historical period power consumption fluctuation data, community load state data and a preset power grid bearing threshold; determining a corresponding effective charging power interval based on the power consumption state data, establishing a multi-level charging strategy according to the effective charging power interval, the charging strategy comprising at least a fast charging strategy, a slow charging strategy and a time-sharing reservation strategy; acquiring and matching the corresponding charging strategy according to reservation charging information, a current SOC state value of the vehicle and a user level, and delivering the corresponding charging strategy to a target charging pile, the user level comprising at least a private level and a public level; dynamically monitoring operation data of the target charging pile, the operation data comprising real-time current, real-time voltage, charging operation power and environmental temperature; adjusting the charging power of the target charging pile in real time according to the operation data and the community load state data, so that the charging power does not exceed a safety load threshold included in the preset power grid bearing threshold; recording the load change curve of the target charging pile in the whole charging process, and generating and pushing a corresponding exclusive charging mode according to the pre-acquired user historical use behavior data.

[0005] By adopting the technical scheme, through real-time perception and multi-dimensional data analysis of the overall power consumption state of the community, dynamic hierarchical formulation and intelligent matching of the charging strategy are realized, and the safety and energy efficiency management level of the charging pile operation are effectively improved. By limiting the charging power within the safety threshold of the power grid, and combining with user reservation information, SOC state and use level for differential scheduling, not only the risk of overload of the community power system is avoided, but also the rationality of resource allocation and user charging experience are improved; at the same time, on the basis of continuously recording charging process data and user behavior, a personalized charging mode is formed, and a change from passive charging to active prediction and optimization management is realized, and the stability, self-adaptive ability and intelligent level of the charging system in the smart community are overall enhanced.

[0006] Preferably, in the step of determining the corresponding effective charging power interval based on the power consumption state data, the step comprises: determining a corresponding fluctuation range according to the historical period power fluctuation data; comparing the total power consumption and the preset power grid carrying threshold to generate a corresponding residual available power value, determining an upper limit value of the fluctuation range according to the residual available power value, and screening an effective range of the fluctuation range; dividing the effective range to generate a plurality of level sub-ranges, and establishing a plurality of effective charging power intervals according to the level sub-ranges.

[0007] By adopting the technical scheme, by combining the historical power fluctuation of the community with the current total power consumption, the residual power available for charging is dynamically calculated under the constraint of the carrying capacity of the power grid, and the effective fluctuation interval with real schedulability is screened accordingly, so as to avoid that the power configuration is away from the actual load. Further subdividing the effective range into a plurality of level intervals enables the subsequent charging strategy to accurately match the available power resources under different load conditions, realizes the refinement and hierarchical management of charging scheduling, and improves the energy utilization efficiency and power supply safety of the system in the multi-user concurrent scenario.

[0008] Preferably, in the step of establishing a multi-level charging strategy according to the effective charging power interval, the step comprises: sorting a plurality of the effective charging power intervals according to power size, and identifying a corresponding charging power level for each of the effective charging power intervals; setting a fixed target charging power range and an available time period for each of the charging power levels; associating the target charging power range to different charging strategies respectively, the charging strategies at least including a fast charging strategy, a slow charging strategy and a time-sharing reservation strategy.

[0009] By adopting the technical scheme, the system can establish clear strategy division standards according to different power conditions by sorting and grading the effective charging power interval, and then realize fine management of charging resources. By setting a clear target power range and applicable time period for each power level, the flexibility and controllability of charging scheduling are improved, and the most suitable charging mode can be enabled under different load conditions. Corresponding each power level to a specific strategy type can ensure the stability of the community power system while efficiently responding to and reasonably shunting the diversified charging needs of users, thereby improving the overall operation efficiency of the system and the user charging experience.

[0010] Preferably, in the step of acquiring and matching the corresponding charging strategy to the target charging pile according to the reservation charging information, the current SOC state value of the vehicle and the user level, the step comprises: acquiring the user level; if the user level is a private level, matching the private charging pile corresponding to the private level as the target charging pile; if the user level is a public level, acquiring the historical charging data of the public charging pile corresponding to the public level, determining the corresponding safety evaluation value according to the historical charging data, and determining the public charging pile with the highest safety evaluation value as the target charging pile; acquiring and matching the corresponding charging strategy to the target charging pile according to the reservation charging information and the current SOC state value of the vehicle.

[0011] By adopting the technical scheme, the system can establish clear strategy division standards according to different power conditions by sorting and grading the effective charging power interval, and then realize fine management of charging resources. By setting a clear target power range and applicable time period for each power level, the flexibility and controllability of charging scheduling are improved, and the most suitable charging mode can be enabled under different load conditions. Corresponding each power level to a specific strategy type can ensure the stability of the community power system while efficiently responding to and reasonably shunting the diversified charging needs of users, thereby improving the overall operation efficiency of the system and the user charging experience.

[0012] Preferably, in the step of acquiring and matching the corresponding charging strategy to the target charging pile according to the reservation charging information and the current SOC state value of the vehicle, the step comprises: acquiring the reservation charging information, determining whether there is an emergency charging demand specified according to the reservation charging information, and if there is an emergency charging demand specified, directly matching and issuing the fast charging strategy to the target charging pile; If no emergency charging demand is specified, an initial SOC state value of the vehicle before charging is obtained, and a first SOC threshold and a second SOC threshold are determined according to the initial SOC state value of the vehicle; A current SOC state value of the vehicle is obtained in real time; If the current SOC state value of the vehicle is lower than the first SOC threshold, the fast charging strategy is matched and delivered, and the charging power is dynamically adjusted to the maximum value in the effective charging power interval; If the current SOC state value of the vehicle is at the second SOC threshold, a time length required for full charging is calculated according to the current SOC state value of the vehicle; It is judged whether the remaining reservation time period in the reservation charging information is greater than the time length required for full charging, if not, the fast charging strategy is matched and delivered, and if yes, the slow charging strategy is matched and delivered; If the current SOC state value of the vehicle is higher than the second SOC threshold, it is judged whether there is an economic charging demand in the reservation charging information, if not, the charging strategy when the current SOC state value of the vehicle is at the second SOC threshold is maintained, and if yes, the time reservation strategy is matched and delivered.

[0013] By adopting the above technical solutions, by combining the charging reservation information, the SOC state value and the emergency charging demand of the vehicle, the most suitable charging strategy is intelligently allocated for each user, and the balance between charging efficiency and user demand is ensured. According to the initial SOC value and the real-time SOC state of the vehicle, the charging strategy is dynamically adjusted, when the SOC value is low, the fast charging strategy is preferentially started, and the power is adjusted according to the load condition of the community, so as to ensure the charging speed while not exceeding the system load. When the SOC value approaches the target value, the system intelligently switches to the appropriate charging strategy according to the remaining reservation time and the vehicle charging demand, to avoid battery damage caused by too fast charging, while optimizing the allocation of power resources and avoiding waste. Especially when the SOC value of the vehicle is high, the system can guide the user to select the time reservation strategy by identifying the economic charging demand, and charge in the off-peak period, which not only reduces power consumption, but also optimizes the use of community power resources, and improves the intelligent and personalized management level of the charging process.

[0014] Preferably, in the step of recording the load change curve of the target charging pile in the whole charging process, and generating and pushing the corresponding exclusive charging mode according to the pre-obtained user historical use behavior data, the step comprises: The load change curve of the target charging pile in the whole charging process is recorded, The charging time period preference in the pre-obtained user historical use behavior data is extracted; The load change curve is divided into multiple load intervals on a time axis, the charging time period preference in the user historical use behavior data is associated, and a corresponding target interval is screened out; According to the target interval, a corresponding initial exclusive mode is generated and pushed; Real-time detection is performed on user adjustment operations on the initial exclusive mode, and a corresponding exclusive charging mode is generated and pushed according to the adjustment operations.

[0015] By adopting the technical solution, the load change curve of the target charging pile in the charging process is recorded and analyzed, the historical charging behavior data of the user is combined, the personalized charging mode is intelligently generated and pushed, the charging time period preference of the user is extracted, the load change is matched with the user habit, it is ensured that the charging process can be carried out at the optimal power in the time period expected by the user, and the interference in the peak load period is avoided. The system can also monitor the adjustment of the initial exclusive charging mode by the user in real time, dynamically respond to the personalized demand of the user, continuously optimize the charging mode, improve the user experience, and also more efficiently utilize the power resources, so as to realize intelligent, personalized and efficient charging management.

[0016] In summary, the present application includes at least one of the following beneficial technical effects: The present application introduces an intelligent regulation and control mechanism based on the cell-level load state and multi-dimensional user information, realizes dynamic perception and hierarchical control of the charging process. The system first obtains the current total power consumption, historical fluctuation trend and real-time load state of the cell from a global perspective, and combines the set upper limit of the power grid to reasonably evaluate the power interval available for charging. Then, by dividing the power interval into multiple levels, different charging strategies are constructed, so that the allocation of charging resources is no longer static or uniform, but can be flexibly adjusted according to the current power carrying capacity of the cell. Further, the system accurately matches and pushes the strategy to the target charging pile according to the charging reservation situation of the user, the state of charge (SOC) of the battery and the use level it is in, effectively alleviating the problem of public pile resource shortage and private pile resource waste. During the charging process, the system continuously monitors the operating state of the target pile and dynamically adjusts the charging power based on it, ensuring that the overall load always operates within the safe limit range. Finally, through the recording and analysis of the long-term use behavior of the user, the system can gradually form a personalized charging mode, improve the overall use experience and enhance the load prediction capability, so as to realize efficient scheduling and orderly management of charging behavior in the smart community under the premise of ensuring power supply safety. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is a flowchart of a smart community charging pile management method in an embodiment of the present application.

[0018] Figure 2is an implementation flowchart of step S20 in a smart community charging pile management method in an embodiment of the present application; Figure 3 is another implementation flowchart of step S20 in a smart community charging pile management method in an embodiment of the present application; Figure 4 is an implementation flowchart of step S30 in a smart community charging pile management method in an embodiment of the present application; Figure 5 is an implementation flowchart of step S304 in a smart community charging pile management method in an embodiment of the present application; Figure 6 is an implementation flowchart of step S60 in a smart community charging pile management method in an embodiment of the present application; Figure 7 is a principle block diagram of a smart community charging pile management device in an embodiment of the present application; Figure 8 is a device schematic diagram in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The present application will be further described in detail below with reference to the accompanying drawings.

[0020] In an embodiment, as shown in Figure 1 , the present application discloses a smart community charging pile management method, which includes: S10, acquiring real-time power consumption state data of the community, the power consumption state data including total power consumption, historical period power consumption fluctuation data, community load state data, and a preset power grid carrying threshold; the total power consumption refers to the comprehensive power consumption of all power consumption devices in the community at a certain time, providing a comprehensive perspective of the overall power consumption of the community. The historical period power consumption fluctuation data reflects the fluctuation of power consumption demand in different time periods, providing a basis for power dispatching and load management. The community load state data helps to judge the load level of the current community power grid, which is crucial for determining whether there is a risk of overload. The preset power grid carrying threshold is the maximum carrying capacity of the community power system under safe operation, preventing the occurrence of power grid overload during peak power consumption periods. Through comprehensive analysis of these data, the system can dynamically evaluate the load condition of the current power system and make appropriate charging pile management decisions to ensure the safe and efficient operation of the community power system.

[0021] S20, based on the power consumption state data, determine the corresponding effective charging power interval, and establish a multi-level charging strategy according to the effective charging power interval, the charging strategy at least including fast charging strategy, slow charging strategy and time-sharing reservation strategy; the effective charging power interval is obtained by analyzing the total power consumption of the current cell and the load state data, which represents the range of available charging power of the charging pile without exceeding the power grid load. According to this power range, the system establishes multiple charging strategy levels, among which fast charging strategy, slow charging strategy and time-sharing reservation strategy are the three common strategy types. Fast charging strategy is suitable for periods of light power load, which provides higher power to complete charging quickly; slow charging strategy is suitable for periods of high power load, which has lower charging power to reduce the pressure on the community power grid; time-sharing reservation strategy allows users to choose to charge during low load period, improving the flexibility and efficiency of energy use. Through the setting of these strategies, the system can reasonably allocate the resources of charging piles in the community, avoiding the problem of excessive power grid pressure or long charging waiting time during high load period.

[0022] S30, obtain and match the corresponding charging strategy according to the reservation charging information, the current SOC state value of the vehicle and the user level, and push it to the target charging pile; the user level at least includes private level and public level; the reservation charging information includes the user's charging reservation time, charging duration demand, etc., which can help the system accurately allocate charging resources within the specified time. The current SOC state value of the vehicle refers to the current battery percentage, which is an important basis for determining whether high-power support is needed for the charging strategy. When the SOC is low, the system will prefer to use fast charging strategy to charge quickly; when the SOC is high, the system will choose slow charging strategy to reduce the damage to the battery and avoid unnecessary power waste. The setting of the user level is based on the different needs of users in the community. Private level is usually used for users with fixed charging needs, such as residents or users with exclusive parking spaces, and the system will allocate resources to these users first. Public level is suitable for users without fixed parking spaces or users sharing charging piles, and the system will reasonably schedule according to the availability of public resources. After the comprehensive use of these data, the system can accurately match the most suitable charging strategy and push it to the target charging pile, ensuring that users get the best charging service.

[0023] S40. Dynamically monitor the operating data of the target charging pile, including real-time current, real-time voltage, charging operating power, and ambient temperature. Real-time current and voltage monitoring can help the system understand the operating status of the charging pile in real time and ensure that it is within the normal operating range. If the current or voltage exceeds the predetermined range, the system can issue an alarm and adjust the charging power to ensure safety. Charging operating power is a key parameter that determines the charging speed. Monitoring its changes can help the system adjust the charging strategy to improve charging efficiency. Ambient temperature can also affect the operation of the charging pile. Excessively high or low temperatures may affect charging efficiency or cause safety hazards. Therefore, monitoring the ambient temperature can make timely adjustments to ensure the safety and stability of the charging process.

[0024] S50. Based on the operating data and the cell load status data, the charging power of the target charging pile is adjusted in real time so as not to exceed the safety load limit threshold included in the preset grid load threshold; by dynamically adjusting the power of the charging pile, it is ensured that the carrying capacity of the grid system is not exceeded during the charging process. The system monitors the current cell load status in real time. If it finds that the power consumption is close to or exceeds the preset grid load threshold, the system will automatically reduce the charging power to avoid the problem of overload operation of the grid. In addition, the safety load limit threshold serves as a protection mechanism to ensure that the power of the charging pile will not be too high when the grid load is critical, thereby avoiding potential risks to the power system. This adjustment mechanism ensures the efficient operation of the charging pile and guarantees the safety and stability of the power system.

[0025] S60. Record the load change curve of the target charging pile throughout the charging process, and generate and push the corresponding exclusive charging mode based on the user's historical usage behavior data obtained in advance; the charging pile load change curve is important data reflecting the power fluctuation during the charging process. Recording this curve can help the system analyze the power demand and load changes during the charging process. Combined with the user's historical charging behavior data, the system can calculate each user's most commonly used charging time, charging method, charging speed and other preferences, and generate an exclusive charging mode based on this information. For example, if a user usually charges at a specific time in the evening, the system will give priority to charging during this time and may adopt a lower power slow charging strategy to meet the user's needs. By monitoring and analyzing this data in real time, the system can not only adapt to current charging needs, but also predict users' future charging habits, thereby providing each user with more personalized and efficient charging services.

[0026] In one embodiment, if Figure 2 As shown, in step S20, i.e., the step of determining the corresponding effective charging power range based on the power usage status data, the following steps are included: S2011. Determine the corresponding fluctuation range based on historical power consumption fluctuation data. Historical power consumption fluctuation data refers to the overall power consumption trend of the cell over several past time periods. By analyzing this data, the system can identify the load fluctuations of the cell during different time periods and extract a fluctuation range. This fluctuation range reflects the load changes of the cell under normal use, facilitating the subsequent dynamic adjustment of the charging strategy based on real-time conditions.

[0027] S2012. Compare the total power consumption with the preset grid load threshold, generate the corresponding remaining available power value, determine the upper limit of the fluctuation range based on the remaining available power value, and screen out the effective range of the fluctuation range; based on the remaining available power value, the system determines the upper limit of the fluctuation range to ensure that the power distribution of the charging pile does not exceed the carrying capacity of the grid. After screening out the effective range of the fluctuation range, the system ensures that the distribution of charging power can meet user needs without causing excessive load on the grid. For example, if the grid load threshold is 1000kW, and the current total power consumption of the community is 800kW, the remaining available power is 200kW. The system will ensure that the charging power does not exceed this 200kW available range, thereby avoiding excessive load on the grid.

[0028] S2013. Divide the effective range to generate multiple sub-ranges. Based on these sub-ranges, multiple effective charging power intervals are established. The effective range is the upper limit of the remaining available power, calculated based on the aforementioned calculations. The system divides the effective range into multiple charging power levels, such as high, medium, and low, based on varying power demands and grid load. Each interval corresponds to different charging requirements and strategies, meeting the charging needs of different users. The high-power interval is suitable for users with more urgent charging needs, the low-power interval is suitable for users who require longer charging periods without rushing to complete the charge, and the medium-power interval serves as an intermediate option for load balancing. For example, during high-load periods (such as 6:00 PM to 8:00 PM), the system will prioritize charging in the low-power interval to reduce grid pressure. During low-load periods (such as 2:00 AM to 4:00 AM), the system will allow the use of the high-power interval to improve charging efficiency.

[0029] In one embodiment, if Figure 3 As shown, in step S20, i.e., the step of establishing a multi-level charging strategy according to the effective charging power range, it also includes: S2021. Sort multiple effective charging power intervals according to power size, and identify the corresponding charging power level for each effective charging power interval; the effective charging power interval is an available charging power range calculated by the above steps, and the system sorts these intervals from high to low according to power. The sorted charging power intervals can distinguish different charging power levels according to their different power requirements. For example, during low-load periods, the charging pile can use higher power for fast charging, so the corresponding charging power level is a high power level; while during high-load periods, the charging pile uses lower power for charging to avoid overload, so the corresponding charging power level is a low power level. Through this sorting, the system can better grasp the distribution of different power intervals and ensure the rational allocation of charging resources.

[0030] S2022. Set a fixed target charging power range and available time period for each charging power level; the system specifies the maximum power that the charging pile can provide at that level by setting the target charging power range. For example, the target charging power range for the high power level may be 18-22kW, while the target charging power range for the low power level may be 2-5kW. At the same time, each charging power level also has an available time period, and the system sets charging strategies for different time periods based on the grid load. High power levels are usually used during periods when the grid load is low, such as at night; while low power levels are used during peak grid load periods to reduce pressure on the grid. In this way, the system ensures that charging strategies of different levels can be executed in the most appropriate time periods to optimize the use of power resources.

[0031] S2023. Associate the target charging power range with different charging strategies, which include at least fast charging strategy, slow charging strategy and time-sharing reservation strategy; each charging power level is determined by associating with different charging strategies. For high power levels, the system usually selects a fast charging strategy to provide fast charging services to meet the needs of users who need to be fully charged in a short time. For low power levels, a slow charging strategy is adopted, and the charging process is relatively slow to reduce the burden on the power grid and extend the charging period. The time-sharing reservation strategy allows users to make reservations for charging during low-load periods (such as at night). The system automatically selects the appropriate charging power level for charging based on the user's reservation time. The introduction of this strategy makes the charging process more flexible, and can reasonably allocate charging resources according to user needs and power grid load conditions, thereby improving power utilization efficiency and ensuring power grid security.

[0032] In one embodiment, if Figure 4 As shown, in step S30, i.e., the step of obtaining and matching the corresponding charging strategy to the target charging pile based on the scheduled charging information, the current SOC state value of the vehicle and the user level, includes: S301, obtain the user's own level; the user's own level is a standard for classifying users according to their charging pile usage rights and charging needs in the cell. The classification of user levels can be based on multiple factors, such as whether the user has a dedicated parking space, whether it is a shared user, etc. The private level is usually suitable for resident users who have fixed parking spaces and long-term charging needs, and the public level is suitable for temporary users who do not have a dedicated parking space or users who share charging piles. By obtaining the user's own level, the system can better identify the user's demand type and then decide the specific matching method of the charging strategy to ensure that the charging resources are reasonably allocated.

[0033] S302, if the user's own level is a private level, match the private charging pile corresponding to the private level as the target charging pile; the private charging pile is usually a dedicated charging device provided for users with fixed parking spaces. Private users usually have stable and long-term charging needs, so the system prioritizes private charging piles as target charging piles for charging task allocation. The use of private charging piles is not affected by other users and can provide flexible charging services according to the user's charging habits and needs. For example, if a private user usually charges after 8 pm, the system will automatically allocate a private charging pile for the user and adjust the charging power to avoid conflicts with other users.

[0034] S303, if the user's own level is a public level, obtain the historical charging data of the public charging pile corresponding to the public level, determine the corresponding safety evaluation value according to the historical charging data, and determine the public charging pile with the highest safety evaluation value as the target charging pile; the public charging pile is usually used by users who do not have a fixed parking space or users who share charging piles. When selecting a public charging pile as the target charging pile, the system will obtain the historical charging data of the charging pile, including charging frequency, usage, current and voltage stability, etc. Through analysis of these data, the system calculates the safety evaluation value of each public charging pile, which reflects the stability and safety of the charging pile. The charging pile with a higher safety evaluation value indicates that it is more stable and less likely to fail, so the system prioritizes the charging pile with the highest safety evaluation value as the target charging pile to ensure the safety and stability of public users' charging.

[0035] S304, match and issue a corresponding charging strategy to the target charging pile according to the reservation charging information and the current SOC state value of the vehicle; the reservation charging information usually includes the time period of user reservation charging, the expected charging duration, etc., and the SOC state value reflects the current battery capacity of the electric vehicle. By combining the information of the two, the system can accurately judge the charging demand of the user. If the SOC of the user is low, the system will select a fast charging strategy according to the remaining battery capacity and the reservation time to quickly supplement the battery capacity; if the SOC is high, the system will select a slow charging strategy to reduce battery wear and avoid wasting power resources. In addition, the system will also select a suitable charging strategy according to the type of the target charging pile (private charging pile or public charging pile). For example, during the peak period of public charging piles, the system may prefer to select a time-sharing reservation strategy to avoid resource conflicts caused by multiple users using the charging pile at the same time. By comprehensively considering the reservation charging information, the SOC state value and the type of the charging pile, the system can efficiently and accurately match and issue a suitable charging strategy to ensure a smooth and efficient charging process for the user.

[0036] In an embodiment, as shown in FIG. 4, in step S304, i.e., the step of matching and issuing a corresponding charging strategy to the target charging pile according to the reservation charging information and the current SOC state value of the vehicle, the following steps are included: Figure 5 S3041, obtain the reservation charging information, determine whether there is an emergency charging demand specified according to the reservation charging information, and if there is an emergency charging demand specified, directly match and issue a fast charging strategy to the target charging pile; the reservation charging information includes the specific description of the user's charging demand, such as the charging period, the charging capacity requirement, etc. If the user indicates an emergency charging demand when reserving, the system will prioritize this demand and automatically match and issue a fast charging strategy for the user. This strategy provides higher power to quickly increase the battery capacity, meeting the user's urgent demand for fast charging.

[0037] S3042, if there is no emergency charging demand specified, obtain the initial SOC state value of the vehicle before charging, and determine the first SOC threshold and the second SOC threshold according to the initial SOC state value of the vehicle; the SOC (State of Charge) state value reflects the current battery capacity percentage of the vehicle. The system first obtains the initial SOC state value of the vehicle before charging, and sets two SOC thresholds according to this value. The first SOC threshold usually represents a lower battery capacity level, below which fast charging is needed to avoid excessive battery discharge; the second SOC threshold represents a higher battery capacity level, close to full charge, at which the charging speed can be slowed down to improve battery health and avoid overcharging.

[0038] S3043, obtain the current SOC state value of the vehicle in real time; ​S3044. If the vehicle's current SOC value is lower than the first SOC threshold, the fast charging strategy is matched and issued, and the charging power is dynamically adjusted to the maximum value within the effective charging power range; if the vehicle's SOC value is lower than the first SOC threshold, it means that the battery power is low, and the system will give priority to the fast charging strategy to quickly increase the battery power.

[0039] S3045: If the current SOC value of the vehicle is at a second SOC threshold, calculate the time required for full charging based on the current SOC value of the vehicle; S3046: Determine whether the remaining scheduled time period in the scheduled charging information is greater than the required time for a full charge. If so, match and issue a fast charge strategy. If so, match and issue a slow charge strategy. This is used to determine whether the user has sufficient charging time. If the remaining scheduled charging time period is insufficient to fully charge the battery using slow charging, the system selects a fast charge strategy to shorten the charging time. If sufficient time is left, the system selects a slow charge strategy to reduce the battery's charging burden and extend its life.

[0040] S3047. If the vehicle's current SOC value is higher than the second SOC threshold, determine whether there is an economic charging requirement in the scheduled charging information. If not, maintain the charging strategy for when the vehicle's current SOC value is at the second SOC threshold. If there is an economic charging requirement, match and issue a time-sharing reservation strategy. Economic charging requirement means that the user wishes to charge during periods with lower electricity prices to save costs. If the vehicle's SOC is higher and the user does not specify an economic charging requirement, the system will maintain the current charging strategy based on the existing SOC state. If the user specifies an economic charging requirement, the system will prioritize the time-sharing reservation strategy based on the community's load conditions and electricity price fluctuations, charging during periods with lower electricity prices, thereby reducing charging costs.

[0041] In one embodiment, if Figure 6 As shown, in step S60, that is, recording the load change curve of the target charging pile during the entire charging process, generating and pushing the corresponding exclusive charging mode according to the pre-acquired user historical usage behavior data, the steps include: S601. Record the load change curve of the target charging pile throughout the charging process. The load change curve reflects the changes in the charging pile's power during the charging process. It describes the fluctuations in the power carried by the charging pile in different time periods from the start to the end of charging. By recording this curve in real time, the system can obtain changes in key parameters such as current, voltage, and charging power during the charging process.

[0042] S602, extract the charging time period preference from the pre-acquired user historical usage behavior data; the user historical usage behavior data includes the user's past charging time period, charging frequency, charging duration, etc. information, which reflects the user's charging habits and preferences. By analyzing these historical data, the system can understand the user's charging needs in different time periods. For example, some users may be used to charging at night, while others may prefer to charge during the day. After extracting this information, the system can develop more personalized charging strategies for each user to ensure that the charging process can best meet the user's needs.

[0043] S603, divide the load change curve into multiple load intervals according to the time axis, associate the charging time period preference in the user historical usage behavior data, and screen out the corresponding target interval; the load change curve usually has obvious time sequence characteristics, and the system divides this curve according to the time axis, and divides the different charging processes into multiple load intervals. These intervals represent the power demand in different stages of the charging process. By associating these load intervals with the user's charging time period preference, the system can identify which time period is the best time for the user to charge. For example, if the user is used to charging at night and prefers a low-power charging mode, the system will prefer to select the low-power interval for charging at night to maximize the efficiency and comfort of the user's charging.

[0044] S604, according to the target interval, generate and push the corresponding initial exclusive mode; first, it depends on the accurate division of the target interval and the deep analysis of the user's historical behavior data. The system analyzes the target interval (for example, low load interval, high load interval, etc.) defined in the previous step in detail, and determines the required charging power in combination with the real-time load status of the cell power grid. Specifically, the system will select the appropriate charging strategy based on the upper and lower limits of the power of the target interval, for example, if the target interval falls in the low load period, the system will automatically select the slow charging strategy with lower power to avoid excessive load of the power grid caused by high-power charging. Conversely, in the light load period, the system will select the fast charging strategy with higher power according to the target interval to ensure that the user can quickly charge; next, the system will consider the user's historical use behavior data to extract the user's common charging time period preference and adaptability to charging power. Through these data, the system can generate a personalized charging strategy and automatically generate an exclusive initial charging mode for each user. For example, if the user's historical data shows that he usually chooses to charge from 9 pm to 10 pm, and the power grid load is low at this time, the system will push a slow charging strategy suitable for this period for the user, and ensure that the charging pile charges at an appropriate power during this period to meet the user's charging demand and avoid overloading the power grid; In the process of generating the initial exclusive mode, the system combines these charging time period preferences, power requirements of the target interval, and user charging habits to determine the most appropriate charging power range and allocate the charging power to the target charging pile. The push process transmits this mode to the target charging pile through wireless communication technology to ensure that the charging pile can perform corresponding operations in actual operation according to the pushed charging strategy. This step ensures that the charging demand of each user can be responded in time, and the charging process always remains within the safe range of the community load, avoiding pressure on the power grid.

[0045] S605, real-time detection of user adjustment operation on the initial exclusive mode, generation and push of the corresponding exclusive charging mode according to the adjustment operation; during the charging process, the user may adjust the charging mode according to his own needs, such as changing the charging period, modifying the charging power, etc. The system monitors the user's adjustment operation in real time and dynamically adjusts the charging mode according to these operations. If the user chooses to increase the charging power or adjust the charging time, the system will generate and push the corresponding exclusive charging mode in time according to the new demand.

[0046] It should be understood that the size of the serial number of each step in the above embodiment 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.

[0047] In one embodiment, a smart community charging pile management device is provided, which corresponds one-to-one to a smart community charging pile management method in the above embodiment. Figure 7 As shown, the smart community charging pile management device includes a first acquisition module, a determination module, a second acquisition module, a monitoring module, an adjustment module and a recording module. The functional modules are described in detail as follows: A first acquisition module is used to obtain real-time power consumption status data of a cell, wherein the power consumption status data includes total power consumption, power consumption fluctuation data of historical periods, cell load status data, and a preset grid load threshold; a determination module, configured to determine a corresponding effective charging power interval based on the power usage status data, and establish a multi-level charging strategy according to the effective charging power interval, wherein the charging strategy includes at least a fast charging strategy, a slow charging strategy, and a time-sharing reservation strategy; The second acquisition module is used to obtain and match the corresponding charging strategy to the target charging pile based on the scheduled charging information, the current SOC state value of the vehicle and the user level. The user level includes at least private level and public level; A monitoring module is used to dynamically monitor the operating data of the target charging pile, wherein the operating data includes real-time current, real-time voltage, charging operating power and ambient temperature; An adjustment module, configured to adjust the charging power of the target charging pile in real time according to the operation data and the cell load status data so as not to exceed a safety load limit threshold included in the preset grid load threshold; The recording module is used to record the load change curve of the target charging pile during the entire charging process, and generate and push the corresponding exclusive charging mode based on the user's historical usage behavior data obtained in advance.

[0048] Optionally, the determining module includes: a determination unit, configured to determine a corresponding fluctuation range based on the electricity consumption fluctuation data during the historical period; a comparing unit, configured to compare the total power consumption with the preset grid load threshold, generate a corresponding remaining available power value, determine an upper limit of the fluctuation range according to the remaining available power value, and screen out a valid range of the fluctuation range; a first dividing unit, configured to divide the effective range to generate a plurality of level sub-ranges, and establish a plurality of effective charging power intervals according to the level sub-ranges; Optionally, the determining module further includes: an identification unit, configured to sort the plurality of effective charging power intervals according to power size, and identify a corresponding charging power level for each effective charging power interval; The setting unit is configured to set a fixed target charging power range and an available time period for each charging power level; The association unit is configured to associate the target charging power range to different charging strategies respectively, wherein the charging strategies at least include a fast charging strategy, a slow charging strategy and a time-sharing reservation strategy; Optionally, the second acquisition module comprises: The first acquisition unit is configured to acquire a user level; The matching unit is configured to match a private charging pile corresponding to the private level as a target charging pile if the user level is the private level; The second acquisition unit is configured to acquire historical charging data of a public charging pile corresponding to the public level if the user level is the public level, determine a safety evaluation value according to the historical charging data, and determine a public charging pile with the highest safety evaluation value as the target charging pile; The third acquisition unit is configured to acquire and match a corresponding charging strategy according to reservation charging information and a current SOC state value of a vehicle, and deliver the corresponding charging strategy to the target charging pile; Optionally, the third acquisition unit comprises: The first acquisition sub-unit is configured to acquire reservation charging information, determine whether there is an emergency charging demand, and directly match and deliver the fast charging strategy to the target charging pile if there is an emergency charging demand; The second acquisition sub-unit is configured to acquire an initial SOC state value of a vehicle before charging if there is no emergency charging demand, and determine a first SOC threshold value and a second SOC threshold value according to the initial SOC state value; The third acquisition sub-unit is configured to acquire a current SOC state value of a vehicle in real time; The matching sub-unit is configured to match and deliver the fast charging strategy if the current SOC state value of the vehicle is lower than the first SOC threshold value, and dynamically adjust a charging power to a maximum value in the effective charging power interval; The calculation sub-unit is configured to calculate a time required for full charging according to the current SOC state value of the vehicle if the current SOC state value of the vehicle is at the second SOC threshold value; The first judgment sub-unit is configured to determine whether a remaining reservation time period in the reservation charging information is greater than the time required for full charging, match and deliver the fast charging strategy if the remaining reservation time period is not greater than the time required for full charging, and match and deliver the slow charging strategy if the remaining reservation time period is greater than the time required for full charging; The second judging subunit is configured to determine whether there is an economic charging demand in the pre-order charging information if the current SOC state value of the vehicle is higher than the second SOC threshold value, and keep the charging strategy of the current SOC state value of the vehicle when the current SOC state value is at the second SOC threshold value if there is no economic charging demand, and match and issue the time-sharing pre-order strategy if there is an economic charging demand. Optionally, the recording module comprises: The recording unit is configured to record a load change curve of the target charging pile in a whole charging process, The extraction unit is configured to extract a charging time period preference in the pre-acquired user historical use behavior data. The second dividing unit is configured to divide the load change curve into a plurality of load intervals according to a time axis, associate the charging time period preference in the user historical use behavior data, and filter out a corresponding target interval. The first generating unit is configured to generate and push an initial exclusive mode corresponding to the target interval according to the target interval. The second generating unit is configured to detect a user adjustment operation on the initial exclusive mode in real time, and generate and push a corresponding exclusive charging mode according to the adjustment operation.

[0049] For specific limitations of the smart community charging pile management device, refer to the limitations of the smart community charging pile management method in the foregoing description, which will not be repeated here. Each module in the smart community charging pile management device described above can be realized by software, hardware and combinations thereof, in whole or in part. The above modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in the form of software, so as to call and execute the operations corresponding to the above modules by the processor.

[0050] In one embodiment, a computer device, which can be a server, is provided, and an internal structure diagram of the computer device can be as shown in Figure 8 The computer device comprises a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is configured to communicate with an external terminal through a network connection. The computer program is executed by the processor to implement a smart community charging pile management method.

[0051] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program: S10, acquiring real-time power consumption state data of a cell, the power consumption state data comprising total power consumption, historical period power consumption fluctuation data, cell load state data, and a preset power grid bearing threshold S20, determining a corresponding effective charging power interval based on the power consumption state data, establishing a multi-level charging strategy according to the effective charging power interval, the charging strategy at least comprising a fast charging strategy, a slow charging strategy, and a time-sharing reservation strategy S30, acquiring and matching the corresponding charging strategy to a target charging pile according to reservation charging information, a current SOC state value of a vehicle, and a user level to which the vehicle belongs, the user level at least comprising a private level and a public level S40, dynamically monitoring operation data of the target charging pile, the operation data comprising real-time current, real-time voltage, charging operation power, and environmental temperature S50, adjusting the charging power of the target charging pile in real time according to the operation data and the cell load state data, so that the charging power does not exceed a safety load limit threshold included in the preset power grid bearing threshold S60, recording a load change curve of the target charging pile in a whole charging process, and generating and pushing a corresponding exclusive charging mode according to pre-acquired historical use behavior data of a user In one embodiment, a computer readable storage medium is provided, having a computer program stored thereon, the computer program being executable by a processor to implement the following steps: S10, acquiring real-time power consumption state data of a cell, the power consumption state data comprising total power consumption, historical period power consumption fluctuation data, cell load state data, and a preset power grid bearing threshold S20, determining a corresponding effective charging power interval based on the power consumption state data, establishing a multi-level charging strategy according to the effective charging power interval, the charging strategy at least comprising a fast charging strategy, a slow charging strategy, and a time-sharing reservation strategy S30, acquiring and matching the corresponding charging strategy to a target charging pile according to reservation charging information, a current SOC state value of a vehicle, and a user level to which the vehicle belongs, the user level at least comprising a private level and a public level S40, dynamically monitoring operation data of the target charging pile, the operation data comprising real-time current, real-time voltage, charging operation power, and environmental temperature S50, adjusting the charging power of the target charging pile in real time according to the operation data and the cell load state data, so that the charging power does not exceed a safety load limit threshold included in the preset power grid bearing threshold S60, record the load change curve of the target charging pile in the whole charging process, generate and push a corresponding exclusive charging mode according to the pre-acquired user historical use behavior data Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, the processes of the above-mentioned embodiments can be included. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0052] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is exemplified. In actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0053] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A smart community charging pile management method, characterized in that: The smart community charging pile management method includes: Obtaining real-time power consumption status data for the cell, including total power consumption, power consumption fluctuation data for historical periods, cell load status data, and a preset grid load threshold; Based on the power usage status data, a corresponding effective charging power interval is determined, and a multi-level charging strategy is established according to the effective charging power interval, wherein the charging strategy includes at least a fast charging strategy, a slow charging strategy, and a time-sharing reservation strategy; Obtain and match the corresponding charging strategy to the target charging pile based on the scheduled charging information, the vehicle's current SOC status value and the user level. The user level includes at least private level and public level. Dynamically monitor the operating data of the target charging pile, wherein the operating data includes real-time current, real-time voltage, charging operating power, and ambient temperature; According to the operating data and the cell load status data, the charging power of the target charging pile is adjusted in real time so as not to exceed the safety load limit threshold included in the preset grid load threshold; The load change curve of the target charging pile during the entire charging process is recorded, and the corresponding exclusive charging mode is generated and pushed based on the user's historical usage behavior data obtained in advance.

2. A smart community charging pile management method according to claim 1, characterized in that: The step of determining the corresponding effective charging power range based on the power usage status data includes: Determine the corresponding fluctuation range based on the electricity consumption fluctuation data of the historical period; Comparing the total power consumption with the preset grid load threshold to generate a corresponding remaining available power value, determining an upper limit of the fluctuation range according to the remaining available power value, and screening out a valid range of the fluctuation range; The effective range is divided to generate a plurality of level sub-ranges, and a plurality of effective charging power intervals are established according to the level sub-ranges.

3. A smart community charging pile management method according to claim 1, characterized in that: The step of establishing a multi-level charging strategy according to the effective charging power range includes: sorting the plurality of effective charging power intervals according to power size, and identifying a corresponding charging power level for each effective charging power interval; Setting a fixed target charging power range and available time period for each of the charging power levels; The target charging power range is associated with different charging strategies respectively, and the charging strategies include at least a fast charging strategy, a slow charging strategy and a time-sharing reservation strategy.

4. A smart community charging pile management method according to claim 3, characterized in that: The step of obtaining and matching the corresponding charging strategy to the target charging pile based on the scheduled charging information, the current SOC state value of the vehicle and the user level includes: Get the user level; If the user level is a private level, the private charging pile corresponding to the private level is the target charging pile; If the user level is public, obtaining historical charging data of a public charging pile corresponding to the public level, determining a corresponding safety assessment value based on the historical charging data, and determining the public charging pile with the highest safety assessment value as the target charging pile; Obtain and match the corresponding charging strategy to the target charging pile based on the scheduled charging information and the vehicle's current SOC status value.

5. A smart community charging pile management method according to claim 4, characterized in that: The step of obtaining and matching the corresponding charging strategy to the target charging pile based on the scheduled charging information and the current SOC state value of the vehicle includes: Obtaining scheduled charging information, determining whether an emergency charging requirement is specified based on the scheduled charging information, and if so, directly matching and issuing the fast charging strategy to the target charging pile; If no emergency charging requirement is specified, obtaining an initial SOC state value of the vehicle before charging, and determining a first SOC threshold and a second SOC threshold according to the initial SOC state value of the vehicle; Get the current SOC status value of the vehicle in real time; If the current SOC value of the vehicle is lower than the first SOC threshold, the fast charging strategy is matched and issued, and the charging power is dynamically adjusted to the maximum value within the effective charging power range; If the current SOC state value of the vehicle is within the second SOC threshold, calculating the time required for full charging according to the current SOC state value of the vehicle; Determine whether the remaining scheduled time period in the scheduled charging information is greater than the time required for full charging, and if so, match and issue the fast charging strategy; if so, match and issue the slow charging strategy; If the current SOC state value of the vehicle is higher than the second SOC threshold, it is determined whether there is an economic charging demand in the reserved charging information. If there is no economic charging demand, the charging strategy of maintaining the current SOC state value of the vehicle at the second SOC threshold is maintained. If there is an economic charging demand, the time-sharing reservation strategy is matched and issued.

6. A smart community charging pile management method according to claim 1, characterized in that: The step of recording the load change curve of the target charging pile during the entire charging process and generating and pushing a corresponding exclusive charging mode based on pre-acquired user historical usage behavior data includes: Recording the load change curve of the target charging pile during the entire charging process; Extracting charging time period preferences from pre-acquired user historical usage behavior data; Dividing the load variation curve into multiple load intervals according to the time axis, correlating the charging time period preference in the user's historical usage behavior data, and screening out the corresponding target interval; Generate and push the corresponding initial exclusive mode according to the target interval; The user's adjustment operation on the initial exclusive mode is detected in real time, and a corresponding exclusive charging mode is generated and pushed according to the adjustment operation.

7. A smart community charging pile management device, characterized in that: The smart community charging pile management device includes: A first acquisition module is used to obtain real-time power consumption status data of a cell, wherein the power consumption status data includes total power consumption, power consumption fluctuation data of historical periods, cell load status data, and a preset grid load threshold; a determination module, configured to determine a corresponding effective charging power interval based on the power usage status data, and establish a multi-level charging strategy according to the effective charging power interval, wherein the charging strategy includes at least a fast charging strategy, a slow charging strategy, and a time-sharing reservation strategy; The second acquisition module is used to obtain and match the corresponding charging strategy to the target charging pile based on the scheduled charging information, the current SOC state value of the vehicle and the user level. The user level includes at least private level and public level; A monitoring module is used to dynamically monitor the operating data of the target charging pile, wherein the operating data includes real-time current, real-time voltage, charging operating power and ambient temperature; An adjustment module, configured to adjust the charging power of the target charging pile in real time according to the operation data and the cell load status data so as not to exceed a safety load limit threshold included in the preset grid load threshold; The recording module is used to record the load change curve of the target charging pile during the entire charging process, and generate and push the corresponding exclusive charging mode based on the user's historical usage behavior data obtained in advance.

8. A smart community charging pile management device according to claim 7, characterized in that: The determination module includes: a determination unit, configured to determine a corresponding fluctuation range based on the electricity consumption fluctuation data during the historical period; a comparing unit, configured to compare the total power consumption with the preset grid load threshold, generate a corresponding remaining available power value, determine an upper limit of the fluctuation range according to the remaining available power value, and screen out a valid range of the fluctuation range; a first dividing unit, configured to divide the effective range to generate a plurality of level sub-ranges, and establish a plurality of effective charging power intervals according to the level sub-ranges; The determining module further includes: an identification unit, configured to sort the plurality of effective charging power intervals according to power size, and identify a corresponding charging power level for each effective charging power interval; a setting unit, configured to set a fixed target charging power range and an available time period for each of the charging power levels; an associating unit, configured to associate the target charging power range with different charging strategies, wherein the charging strategies include at least a fast charging strategy, a slow charging strategy, and a time-sharing reservation strategy; The second acquisition module includes: A first obtaining unit is used to obtain the user level; a matching unit, configured to, if the user level is a private level, match a private charging pile corresponding to the private level as a target charging pile; a second acquiring unit, configured to, if the user level is a public level, acquire historical charging data of a public charging pile corresponding to the public level, determine a corresponding safety assessment value based on the historical charging data, and determine the public charging pile with the highest safety assessment value as a target charging pile; The third acquisition unit is used to acquire and match the corresponding charging strategy to the target charging pile based on the scheduled charging information and the current SOC state value of the vehicle; The third acquiring unit includes: A first acquisition subunit is configured to acquire scheduled charging information, determine whether an emergency charging requirement is specified based on the scheduled charging information, and if so, directly match and issue the fast charging strategy to the target charging pile; a second acquisition subunit, configured to, if no emergency charging requirement is specified, acquire an initial SOC state value of the vehicle before charging, and determine a first SOC threshold and a second SOC threshold according to the initial SOC state value of the vehicle; The third acquisition subunit is used to obtain the current SOC state value of the vehicle in real time; a matching subunit, configured to match and issue the fast charging strategy if the current SOC value of the vehicle is lower than the first SOC threshold, and dynamically adjust the charging power to a maximum value within the effective charging power range; a calculation subunit, configured to calculate a time required for full charging according to the current SOC state value of the vehicle if the current SOC state value of the vehicle is at the second SOC threshold; a first judgment subunit, configured to judge whether the remaining reserved time period in the reserved charging information is greater than the time required for full charging, and if so, match and issue the fast charging strategy; and if so, match and issue the slow charging strategy; a second judgment subunit, configured to, if the current SOC state value of the vehicle is higher than the second SOC threshold, determine whether there is an economic charging demand in the scheduled charging information; if not, maintain the charging strategy when the current SOC state value of the vehicle is at the second SOC threshold; and if there is an economic charging demand, match and issue the time-sharing reservation strategy; The recording module includes: A recording unit is used to record the load change curve of the target charging pile during the entire charging process. an extraction unit, configured to extract a charging time period preference from pre-acquired historical user usage behavior data; a second dividing unit, configured to divide the load variation curve into a plurality of load intervals according to a time axis, associate the charging time period preference in the user's historical usage behavior data, and select a corresponding target interval; A first generating unit is configured to generate and push a corresponding initial exclusive mode according to the target interval; The second generating unit is configured to detect in real time the user's adjustment operation on the initial exclusive mode, and generate and push a corresponding exclusive charging mode according to the adjustment operation.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the smart community charging pile management method as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a smart community charging pile management method as described in any one of claims 1 to 6 are implemented.

Images