Charging control method and system of charging pile

Abstract

The invention discloses a charging control method and system for a charging pile, and belongs to the technical field of vehicle charging, and the method comprises the steps: obtaining charging data of a vehicle connected with the charging pile and an electricity price preferential time range of a region where the charging pile is located, generating a charging strategy feature vector, and drawing up a charging mode of the current charging pile; if the charging mode is set to be a slow charging mode, acquiring driving data of a vehicle connected with the charging pile, generating a vehicle travel event period map, and generating a vehicle predicted use time point; obtaining the current residual charge quantity of the vehicle battery and the predicted power consumption rate corresponding to the predicted use time point of the vehicle; establishing a vehicle charging analysis model, and generating a predicted charge quantity of the vehicle; generating a charging power set value of the charging pile according to the predicted charge quantity of the vehicle and the predicted use time point of the vehicle; controlling the charging power of the charging pile according to the charging power set value of the charging pile; according to the invention, the charging cost of the user can be reduced, the vehicle demand of the user is ensured, and the user satisfaction is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle charging, and particularly relates to a charging control method and system for a charging pile. Background Art

[0002] In the context of the rapid development of electric vehicles, as a key facility for energy replenishment of electric vehicles, the intelligence and efficiency of charging piles have become the focus of the industry.

[0003] Most traditional charging piles adopt a fixed charging mode. That is, after the user initiates a charging request, the charging pile starts charging at a preset power until the battery is full or the user manually stops.

[0004] However, although the traditional charging mode is simple and direct, it does not comprehensively consider the time-of-use electricity price strategy and the user's vehicle usage habits, resulting in higher charging costs or unreasonable power planning. For example, the user may charge during non-preferential periods, resulting in excessive charging costs, or delay charging in order to wait for low-price electricity, and ultimately the power cannot meet the travel demand due to insufficient time. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a charging control method and system for a charging pile, which solves the above problems.

[0006] To achieve the above object, the present invention is realized through the following technical solutions: A charging control method for a charging pile, comprising the following steps: Obtain the charging data of the vehicle connected to the charging pile and the time range of electricity price discounts in the area where the charging pile is located, and generate a charging strategy feature vector; wherein, the charging data includes the start charging time point and the estimated charging duration; According to the charging strategy feature vector, formulate the charging mode of the current charging pile; the charging mode includes the user-set mode and the slow charging mode; If the charging mode is formulated as the slow charging mode, obtain the driving data of the vehicle connected to the charging pile, and generate a vehicle travel event cycle map; the driving data includes the vehicle usage time and the driving mileage corresponding to the vehicle usage time; Generate a predicted vehicle usage time point according to the vehicle travel event cycle map and the start charging time point; Obtain the current remaining charge of the vehicle battery and the estimated power consumption rate corresponding to the predicted vehicle usage time point, establish a vehicle charging analysis model, and generate the estimated charge to be filled into the vehicle; Among them, the expression of the vehicle charging analysis model is: ;

[0007] In the expression, represents the estimated charge to be filled into the vehicle, L timerepresents the average driving mileage corresponding to the moment in the vehicle travel event cycle spectrum, P avg represents the predicted power consumption rate corresponding to the predicted vehicle usage time point, T represents the weather temperature factor, and Q0 represents the remaining charge of the current vehicle; the predicted power consumption rate P corresponding to the predicted vehicle usage time point avg refers to the average value of the power consumption rates corresponding to all the predicted vehicle usage time points in the analysis period; the power consumption rate refers to the consumption speed of the vehicle's charge Generate the charging power setting value of the charging pile according to the predicted charge to be input into the vehicle and the predicted vehicle usage time point Control the charging power of the charging pile according to the charging power setting value of the charging pile

[0008] Based on the above technical solutions, the present invention also provides the following optional technical solutions In a further technical solution, obtaining the charging data of the vehicle connected to the charging pile and the electricity price discount time range in the area where the charging pile is located, and generating a charging strategy feature vector, specifically including the following steps Obtain the start charging time point of the vehicle connected to the charging pile, the electricity price discount time range, and the predicted charging duration of the vehicle connected to the charging pile; the predicted charging duration refers to the duration required to fully charge the battery of the vehicle Generate a start charging time score according to the start charging time point of the vehicle connected to the charging pile and the electricity price discount time range Generate a vehicle charging duration score according to the predicted charging duration of the vehicle connected to the charging pile Generate a charging strategy feature vector according to the start charging time score and the vehicle charging duration score

[0009] In a further technical solution, the specific generation method of the start charging time score is as follows Compare the start charging time point of the vehicle connected to the charging pile with the electricity price discount time range. If the start charging time point of the vehicle connected to the charging pile is not within the electricity price discount time range, mark this start charging time point as an off-peak time point When the start charging time point of the vehicle connected to the charging pile is an off-peak time point, it is necessary to adjust the charging strategy Perform a difference processing on the off-peak time point and the near endpoint of the electricity price discount time range in the time sequence to generate an off-peak time escape amount Perform a ratio processing on the off-peak time escape amount and the total number of time points in a single cycle time sequence to generate a start charging time score Among them, the specific generation method of the vehicle charging duration score is as follows Generate the charging time range required for the vehicle connected to the charging pile according to the predicted charging duration of the vehicle connected to the charging pile Generate a time range overlap value according to the charging time range required by the vehicle connected to the charging pile and the electricity price discount time range; Perform a difference process on the time range overlap value and the time range overlap threshold to generate a time range overlap difference; Perform a ratio process on the time range overlap difference and the time range overlap threshold to generate a vehicle charging duration score; Among them, the generation method of the time range overlap value is specifically as follows: Compare each time point in the charging time range required by the vehicle connected to the charging pile with all time points in the electricity price discount time range; If the time point in the charging time range required by the vehicle connected to the charging pile is the same as the time point in the electricity price discount time range, mark this time point as an overlapping time point; Obtain the total number of all overlapping time points, and perform a ratio process on the total number of all overlapping time points and the total number of time points in the charging time range required by the vehicle connected to the charging pile to generate a time range overlap value; Among them, the generation method of the charging strategy feature vector is specifically as follows: Through the formula ;

[0010] Generate a charging strategy feature vector f; In the formula, C start represents the start charging time score, C duration represents the vehicle charging duration score, a1 and a2 are weight coefficients, and a1 + a2 = 1.

[0011] For a further technical solution, the charging mode of the current charging pile is determined according to the charging strategy feature vector, specifically as follows: Compare the charging strategy feature vector with the charging strategy feature vector threshold; If the charging strategy feature vector is less than or equal to the charging strategy feature vector threshold, it means that the smaller the charging strategy feature vector, the higher the tendency to set this charging as the slow charging mode, then determine the charging mode of the current charging pile as the slow charging mode; If the charging strategy feature vector is greater than the charging strategy feature vector threshold, it means that the larger the charging strategy feature vector, the lower the tendency to set this charging as the slow charging mode, then determine the charging mode of the current charging pile as the user-set mode.

[0012] For a further technical solution, if the charging mode is determined as the slow charging mode, obtain the driving data of the vehicle connected to the charging pile and generate a vehicle travel event cycle map, which specifically includes the following steps: If the charging mode is determined to be the slow charging mode, obtain the start charging time point of the vehicle connected to the charging pile, the electricity price preferential time range, and the estimated charging duration of the vehicle connected to the charging pile; Generate a usage frequency distribution map of the vehicle usage time according to the vehicle usage time; Generate a driving mileage distribution map corresponding to the vehicle usage time according to the driving mileage corresponding to the vehicle usage time; Merge the usage frequency distribution map of the vehicle usage time and the driving mileage distribution map corresponding to the vehicle usage time to generate a vehicle travel event cycle map.

[0013] For a further technical solution, the specific generation method of the usage frequency distribution map of the vehicle usage time is as follows: Set an analysis period, evenly divide the analysis period into several analysis sub-periods according to a single time series cycle period, obtain the vehicle usage time within the analysis sub-period, and perform data processing on the vehicle usage time to obtain the vehicle usage time; Obtain the number of vehicle usage times corresponding to each moment in a single time series cycle period; Perform a ratio process on the number of vehicle usage times corresponding to each moment in the time series cycle period and the total number of vehicle usage times to generate the vehicle usage frequency of a single moment in the time series cycle period; Generate a usage frequency distribution map of the vehicle usage time according to the vehicle usage frequency of a single moment in all time series cycle periods in the analysis period; Among them, the generation method of the driving mileage distribution map corresponding to the vehicle usage time is: Obtain the driving mileage of the vehicle usage time corresponding to each moment in a single time series cycle period, and mark it as the driving mileage corresponding to the moment; Perform an average process on all the driving mileages corresponding to the moments in the sub-period to generate the average driving mileage corresponding to the moment; Generate a driving mileage distribution map corresponding to the vehicle usage time according to all the average driving mileages corresponding to the moments.

[0014] For a further technical solution, the specific generation method of the predicted vehicle usage time point is as follows: Compare the vehicle usage frequency of a single moment in the time series cycle period in the vehicle travel event cycle map with a frequency threshold; If the vehicle usage frequency of a single moment in the time series cycle period in the vehicle travel event cycle map is less than the frequency threshold, it means that the smaller the vehicle usage frequency of a single moment in the time series cycle period in the vehicle travel event cycle map, the lower the possibility of the vehicle being used at this moment, then mark this moment as a moment with a lower vehicle travel possibility; If the vehicle usage frequency at a single moment in the time sequence cycle of the vehicle travel event cycle graph is greater than or equal to the frequency threshold, it means that the greater the vehicle usage frequency at a single moment in the time sequence cycle of the vehicle travel event cycle graph, the greater the possibility of vehicle usage at that moment. Then, mark that moment as a moment with a relatively high vehicle travel possibility; Sort all the moments with relatively high vehicle travel possibilities in chronological order to generate a set of moments with relatively high vehicle travel possibilities; Taking the time sequence as the direction and starting from the start charging time, obtain the first moment with a relatively high vehicle travel possibility in the set of moments with relatively high vehicle travel possibilities, which is the predicted vehicle usage time point.

[0015] For a further technical solution, the specific way to obtain the weather temperature factor is as follows: Obtain the current weather temperature and compare it with the minimum value of the battery standard operating temperature range; If the current weather temperature is less than the minimum value of the battery standard operating temperature range, mark the current weather temperature as an abnormal weather temperature; Perform a difference processing on the abnormal weather temperature and the minimum value of the battery standard operating temperature range to generate a temperature difference; Perform a ratio processing on the temperature difference and the minimum value of the battery standard operating temperature range to generate the weather temperature factor.

[0016] For a further technical solution, generating the charging power setting value of the charging pile according to the expected charge amount of the vehicle and the predicted vehicle usage time point is specifically as follows: Through the formula ;

[0017] Generate the charging power setting value P of the charging pile sct ; In the formula, represents the expected charge amount of the vehicle, t use represents the predicted vehicle usage time point, t start represents the start charging time point.

[0018] The charging control system of the charging pile, this system includes: The charging strategy feature analysis unit is used to obtain the charging data of the vehicle connected to the charging pile and the electricity price preferential time range of the area where the charging pile is located, and generate a charging strategy feature vector; among them, the charging data includes the start charging time point and the expected charging duration; The charging mode formulation module is used to formulate the charging mode of the current charging pile according to the charging strategy feature vector; A vehicle travel time period spectrum construction unit. If the charging mode is determined to be the slow charging mode, the vehicle travel time period spectrum construction unit is used to obtain the driving data of the vehicle connected to the charging pile and generate a vehicle travel event period spectrum; the driving data includes the vehicle usage time and the driving mileage corresponding to the vehicle usage time. A vehicle usage prediction module, which is used to generate a predicted vehicle usage time point according to the vehicle travel event period spectrum and the start charging time point. A vehicle charging analysis module, which is used to obtain the current remaining charge amount of the vehicle battery and the predicted power consumption rate corresponding to the predicted vehicle usage time point, establish a vehicle charging analysis model, and generate the predicted charge amount to be charged into the vehicle. A charging pile charging power analysis module, which is used to generate a set value of the charging power of the charging pile according to the predicted charge amount to be charged into the vehicle and the predicted vehicle usage time point. A charging pile charging power control module, which is used to control the charging power of the charging pile according to the set value of the charging power of the charging pile. Among them, the charging strategy feature analysis unit specifically includes: A data acquisition module, which is used to obtain the start charging time point of the vehicle connected to the charging pile, the electricity price preferential time range, and the predicted charging duration of the vehicle connected to the charging pile; the predicted charging duration refers to the duration required to fully charge the charge amount of the vehicle battery. A start charging time analysis module, which is used to generate a start charging time score according to the start charging time point of the vehicle connected to the charging pile and the electricity price preferential time range. A vehicle charging duration analysis module, which is used to generate a vehicle charging duration score according to the predicted charging duration of the vehicle connected to the charging pile. A charging strategy feature vector generation module, which is used to generate a charging strategy feature vector according to the start charging time score and the vehicle charging duration score. Among them, the vehicle travel time period spectrum construction unit specifically includes: A vehicle usage frequency analysis module, which is used to obtain the vehicle usage time and generate a usage frequency distribution map of the vehicle usage time. A vehicle driving mileage analysis module, which is used to obtain the driving mileage corresponding to the vehicle usage time and generate a driving mileage distribution map corresponding to the vehicle usage time. A vehicle travel event period spectrum generation module, which is used to merge the usage frequency distribution map of the vehicle usage time and the driving mileage distribution map corresponding to the vehicle usage time to generate a vehicle travel event period spectrum.

[0019] The present invention provides a charging control method and system for a charging pile, which has the following beneficial effects compared with the prior art: The present invention can not only adjust the charging mode of the charging pile when the vehicle charges during the low - price period of electricity by judging the relationship between the charging time and the electricity price preferential time range, thereby reducing the user's charging cost. At the same time, the present invention also combines the frequently used time and the corresponding driving mileage of the user's vehicle to dynamically adjust the charging power of the charging pile. On the premise of ensuring the vehicle - using demand, it preferentially uses the low - price period for efficient charging, achieving the reduction of the user's charging cost while improving the user's satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flowchart of the charging control method for the charging pile provided by the present invention.

[0021] Figure 2 It is a flowchart of step S1 provided by the present invention.

[0022] Figure 3 It is a flowchart of step S3 provided by the present invention.

[0023] Figure 4 It is a block diagram of the charging control system of the charging pile provided by the present invention.

[0024] Figure 5 It is a block diagram of the charging strategy feature analysis unit provided by the present invention.

[0025] Figure 6 It is a block diagram of the vehicle travel time period spectrum construction unit provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0027] The following describes the specific implementation of the present invention in detail with reference to specific embodiments.

[0028] As Figure 1 shown, the present invention provides a charging control method for a charging pile, including the following steps: S1: Obtain the charging data of the vehicle connected to the charging pile and the electricity price preferential time range of the area where the charging pile is located, and generate a charging strategy feature vector; wherein, the charging data includes the start charging time point and the estimated charging duration; S2: Draw up the charging mode of the current charging pile according to the charging strategy feature vector; the charging mode includes the user - set mode and the slow - charging mode; S3: If the charging mode is determined to be the slow charging mode, obtain the driving data of the vehicle connected to the charging pile, and generate a vehicle travel event cycle map; the driving data includes the vehicle usage time and the driving mileage corresponding to the vehicle usage time. S4: Generate a predicted vehicle usage time point according to the vehicle travel event cycle map and the start charging time point. S5: Obtain the current remaining charge of the vehicle battery and the predicted power consumption rate corresponding to the predicted vehicle usage time point, establish a vehicle charging analysis model, and generate the predicted charge amount to be charged into the vehicle. Among them, the expression of the vehicle charging analysis model is: ;

[0029] In the expression, represents the predicted charge amount to be charged into the vehicle, L time represents the average driving mileage corresponding to the time in the vehicle travel event cycle map, P avg represents the predicted power consumption rate corresponding to the predicted vehicle usage time point, T represents the weather temperature factor, Q0 represents the current remaining charge of the vehicle; the predicted power consumption rate P corresponding to the predicted vehicle usage time point avg refers to the average value of the power consumption rates corresponding to all the predicted vehicle usage time points in the analysis period; the power consumption rate refers to the consumption speed of the vehicle charge amount. It should be noted that the unit of the power consumption rate is corresponding to the unit of the average driving mileage corresponding to the time in the vehicle travel event cycle map; for example, if the unit of the power consumption rate is 20 kWh / 100 km, then the unit of the average driving mileage corresponding to the time in the vehicle travel event cycle map should be nkm, where n is a specific number and km is the unit. S6: Generate a charging power setting value for the charging pile according to the predicted charge amount to be charged into the vehicle and the predicted vehicle usage time point. S7: Control the charging power of the charging pile according to the charging power setting value of the charging pile.

[0030] As Figure 2 shown, as a preferred embodiment of the present invention, the S1 specifically includes the following steps: S10. If the charging mode is determined to be the slow charging mode, obtain the start charging time point of the vehicle connected to the charging pile, the electricity price discount time range, and the predicted charging duration of the vehicle connected to the charging pile; the predicted charging duration refers to the duration required for the charge amount of the vehicle battery to be fully charged. It should be noted that the duration required for the charge amount of the vehicle battery to be fully charged is the predicted duration required for the vehicle to be fully charged (from the current remaining charge to the maximum value of the vehicle charge amount) under the standard charging of the charging pile (the charging pile has no abnormality and the charging power of the charging pile is the maximum safe power). This technology is an existing technology and will not be elaborated here. In addition, the time point is numerical data, and its value is obtained by converting time; for example, if the start charging time of the vehicle connected to the charging pile is 9:00 am, then the value of the time point is 9; at the same time, the time points mentioned in the present invention are all numerical data, and the conversion method is the same, and will not be elaborated hereinafter; S11. Generate a start charging time score according to the start charging time point of the vehicle connected to the charging pile and the electricity price preferential time range; S12. Generate a vehicle charging duration score according to the estimated charging duration of the vehicle connected to the charging pile; S13. Generate a charging strategy feature vector according to the start charging time score and the vehicle charging duration score.

[0031] As a preferred embodiment of the present invention, the generation method of the start charging time score is specifically as follows: Compare the start charging time point of the vehicle connected to the charging pile with the electricity price preferential time range. If the start charging time point of the vehicle connected to the charging pile is not within the electricity price preferential time range, mark this start charging time point as an off-valley time point; When the start charging time point of the vehicle connected to the charging pile is an off-valley time point, it is necessary to adjust the charging strategy; If the start charging time point of the vehicle connected to the charging pile is within the electricity price preferential time range, mark this start charging time point as an on-valley time point; When the start charging time point of the vehicle connected to the charging pile is an on-valley time point, perform the optimal charging strategy; The optimal charging strategy refers to the optimal charging mode of the charging pile. If the user specifies its charging mode, then charge according to the charging mode specified by the customer; Exemplarily, the electricity price preferential time range in the area where the charging pile is located is from 10:00 pm to 6:00 am the next day. If the user does not specify a charging mode when charging the vehicle within this time range, the charging pile runs the optimal charging mode by itself (the charging mode under normal conditions of the charging pile, which specifically needs to be determined according to data such as the model of the charging pile). If the user specifies a charging mode (not exceeding the function range of the charging pile) when charging the vehicle within this time range, the charging mode of the charging pile shall be subject to the mode specified by the user; Perform a difference process on the off-valley time point and the proximal end point of the electricity price preferential time range in time sequence to generate an off-valley time escape amount; The proximal end point of the electricity price preferential time range in time sequence refers to the start time point of the electricity price preferential time range in time sequence, and time sequence means in the direction of time passing; It should be noted that the near-end point of the electricity price preferential time range in the time sequence is a fixed value (for example, starting at 10 pm every day); in real life, when the time is in hours as the time point, a cycle will be formed, and the electricity price preferential time range is a part of the cycle. The start charging time point of the vehicle connected to the charging pile will repeatedly enter this cycle, and there will be a time distance difference between this time point and the start time point of the electricity price preferential time range in the time sequence, that is, the valley-out time escape amount; For the near-end point of the electricity price preferential time range in the time sequence, the present invention provides an embodiment. If the electricity price preferential time range in the area where the charging pile is located is from 10 pm to 6 am the next morning, and the start charging time point of the vehicle connected to the charging pile is 9 pm, then the near-end point of the electricity price preferential time range in the time sequence is the time point represented by 10 pm. If the start charging time point of the vehicle connected to the charging pile is 9 am, then the near-end point of the electricity price preferential time range in the time sequence is also the time point represented by 10 pm; In addition, when performing the difference processing, the time points converted in time between the valley-out time point and the near-end point of the electricity price preferential time range in the time sequence must be of the same standard; for example, if the start charging time point of the vehicle connected to the charging pile is 10 pm on the same day, and the near-end point of the electricity price preferential time range in the time sequence is 1 am the next day, then when converting 1 am the next day into a time point, it needs to be based on the same day, that is, the time point is 25 (one day is 24 hours, and the next day needs to add the total time point of one day, that is, 25); Perform a ratio processing on the valley-out time escape amount and the total number of time points in a single cycle time sequence to generate a start charging time score; It should be noted that in actual applications, a single cycle time sequence generally refers to one day, and the total number of time points in a single cycle time sequence refers to the sum of the number of time points included in a single cycle time sequence; for example, if the time points are divided by hours, the total number of time points in a single cycle time sequence is 24.

[0032] As a preferred embodiment of the present invention, the generation method of the vehicle charging duration score is specifically as follows: Generate the charging required time range of the vehicle connected to the charging pile according to the estimated charging duration of the vehicle connected to the charging pile; Generate a time range overlap value according to the charging required time range of the vehicle connected to the charging pile and the electricity price preferential time range; Perform a difference processing on the time range overlap value and the time range overlap threshold to generate a time range overlap difference; Perform a ratio processing on the time range overlap difference and the time range overlap threshold to generate a vehicle charging duration score; Among them, the generation method of the time range overlap value is specifically as follows: Compare each time point in the charging time range required for the vehicle connected to the charging pile with all time points in the electricity price preferential time range; If the time point in the charging time range required for the vehicle connected to the charging pile is the same as the time point in the electricity price preferential time range, mark this time point as an overlapping time point; Obtain the total number of all overlapping time points, and process the ratio of the total number of all overlapping time points to the total number of time points in the charging time range required for the vehicle connected to the charging pile to generate a time range overlap value.

[0033] As a preferred embodiment of the present invention, the generation method of the charging strategy feature vector is specifically as follows: Through the formula ;

[0034] Generate the charging strategy feature vector f; In the formula, C start represents the start charging time score, C duration represents the vehicle charging duration score, a1 and a2 are weight coefficients, and a1 + a2 = 1.

[0035] As a preferred embodiment of the present invention, the S2 specifically includes: Compare the charging strategy feature vector with the charging strategy feature vector threshold; If the charging strategy feature vector is less than or equal to the charging strategy feature vector threshold, it means that the smaller the charging strategy feature vector, the higher the tendency to set the current charging as the slow charging mode, then set the charging mode of the current charging pile as the slow charging mode; If the charging strategy feature vector is greater than the charging strategy feature vector threshold, it means that the larger the charging strategy feature vector, the lower the tendency to set the current charging as the slow charging mode, then set the charging mode of the current charging pile as the user - set mode.

[0036] As Figure 3 shown, as a preferred embodiment of the present invention, the S3 specifically includes the following steps: S30. Obtain the vehicle usage time, and generate a usage frequency distribution map of the vehicle usage time; S31. Obtain the driving mileage corresponding to the vehicle usage time, and generate a driving mileage distribution map corresponding to the vehicle usage time; S32. Combine the usage frequency distribution map of the vehicle usage time and the driving mileage distribution map corresponding to the vehicle usage time to generate a vehicle travel event cycle map.

[0037] As a preferred embodiment of the present invention, the generation method of the usage frequency distribution map of the vehicle usage time is specifically as follows: Set the analysis period, evenly divide the analysis period into several analysis sub-periods according to a single timing cycle period, obtain the vehicle usage time within the analysis sub-period, and perform data processing on the vehicle usage time to obtain the vehicle usage moment; It should be explained that data processing refers to performing data simplification processing on the vehicle usage time within the analysis sub-period, taking the timing cycle as a single cycle, and removing the number of cycles in the vehicle usage time; for example, if the analysis period is set to one month, divide one month into thirty days, and the vehicle usage time is 9 o'clock on the first day, 14 o'clock on the second day, 20 o'clock on the third day, 6 o'clock on the fourth day, etc. After removing the number of cycles in the vehicle usage time, the vehicle usage moments are 9 o'clock, 4 o'clock, 20 o'clock, 6 o'clock, etc.; Obtain the number of vehicle usage moments corresponding to each moment in a single timing cycle period; Perform a ratio processing on the number of vehicle usage moments corresponding to each moment in the timing cycle period and the total number of vehicle usage moments to generate the vehicle usage frequency of a single moment in the timing cycle period; Generate a usage frequency distribution map of vehicle usage moments based on the vehicle usage frequencies of single moments in all timing cycle periods in the analysis period.

[0038] As a preferred embodiment of the present invention, the generation method of the driving mileage distribution map corresponding to the vehicle usage moment is as follows: Obtain the driving mileage corresponding to each moment in a single timing cycle period and mark it as the driving mileage corresponding to the moment; Perform an average value processing on all the driving mileages corresponding to the moments in the sub-period to generate the average driving mileage corresponding to the moment; Generate a driving mileage distribution map corresponding to the vehicle usage moment based on all the average driving mileages corresponding to the moments.

[0039] As a preferred embodiment of the present invention, the generation method of the predicted vehicle usage time point is specifically as follows: Compare the vehicle usage frequency of a single moment in the timing cycle period in the vehicle travel event cycle map with the frequency threshold; If the vehicle usage frequency of a single moment in the timing cycle period in the vehicle travel event cycle map is less than the frequency threshold, it means that the smaller the vehicle usage frequency of a single moment in the timing cycle period in the vehicle travel event cycle map, the lower the possibility of vehicle usage at this moment, then mark this moment as a moment with a lower possibility of vehicle travel; If the vehicle usage frequency at a single moment in the time sequence cycle of the vehicle travel event cycle map is greater than or equal to the frequency threshold, it means that the greater the vehicle usage frequency at a single moment in the time sequence cycle of the vehicle travel event cycle map, the greater the likelihood of vehicle usage at that moment. Then, mark that moment as a moment with a higher likelihood of vehicle travel; Sort all the moments with a higher likelihood of vehicle travel in chronological order to generate a set of moments with a higher likelihood of vehicle travel; In the chronological direction, starting from the start charging time, obtain the first moment with a higher likelihood of vehicle travel in the set of moments with a higher likelihood of vehicle travel, which is the vehicle predicted usage time point.

[0040] As a preferred embodiment of the present invention, the acquisition method of the weather temperature factor is specifically as follows: Obtain the current weather temperature and compare the current weather temperature with the minimum value of the battery standard operating temperature range; If the current weather temperature is less than the minimum value of the battery standard operating temperature range, mark the current weather temperature as an abnormal weather temperature; Perform a difference process on the abnormal weather temperature and the minimum value of the battery standard operating temperature range to generate a temperature difference; Perform a ratio process on the temperature difference and the minimum value of the battery standard operating temperature range to generate a weather temperature factor; It should be explained that during the low-temperature use of the vehicle battery, it will cause the upper limit of the battery charge amount to decrease; in addition, in a low-temperature environment, some of the battery charge of the vehicle is heated (to enhance its chemical reaction activity) to ensure its normal operation.

[0041] As a preferred embodiment of the present invention, the S6 specifically includes: Through the formula ;

[0042] Generate the charging power setting value P of the charging pile sct ; In the formula, represents the expected charge amount to be charged into the vehicle, t use represents the vehicle predicted usage time point, t start represents the start charging time point.

[0043] As Figure 4 shown, the present invention also provides a charging control system for a charging pile. The system includes: A charging strategy feature analysis unit, which is used to obtain the charging data of the vehicle connected to the charging pile and the electricity price preferential time range in the area where the charging pile is located, and generate a charging strategy feature vector; among them, the charging data includes the start charging time point and the expected charging duration; A charging mode determination module, configured to determine the charging mode of the current charging pile according to the charging strategy feature vector; A vehicle travel time period spectrum construction unit. If the charging mode is determined to be the slow charging mode, the vehicle travel time period spectrum construction unit is configured to obtain the driving data of the vehicle connected to the charging pile and generate a vehicle travel event period spectrum; the driving data includes the vehicle usage time and the driving mileage corresponding to the vehicle usage time; A vehicle usage prediction module, configured to generate a vehicle predicted usage time point according to the vehicle travel event period spectrum and the start charging time point; A vehicle charging analysis module, configured to obtain the current remaining charge amount of the vehicle battery and the predicted power consumption rate corresponding to the vehicle predicted usage time point, establish a vehicle charging analysis model, and generate the predicted charge amount to be charged into the vehicle; A charging pile charging power analysis module, configured to generate a charging power setting value of the charging pile according to the predicted charge amount to be charged into the vehicle and the vehicle predicted usage time point; A charging pile charging power control module, configured to control the charging power of the charging pile according to the charging power setting value of the charging pile.

[0044] As Figure 5 shown, as a preferred embodiment of the present invention, the charging strategy feature analysis unit specifically includes: A data acquisition module, configured to acquire the start charging time point of the vehicle connected to the charging pile, the electricity price preferential time range, and the predicted charging duration of the vehicle connected to the charging pile; the predicted charging duration refers to the duration required for the charge amount of the vehicle battery to be fully charged; A start charging time analysis module, configured to generate a start charging time score according to the start charging time point of the vehicle connected to the charging pile and the electricity price preferential time range; A vehicle charging duration analysis module, configured to generate a vehicle charging duration score according to the predicted charging duration of the vehicle connected to the charging pile; A charging strategy feature vector generation module, configured to generate a charging strategy feature vector according to the start charging time score and the vehicle charging duration score.

[0045] As Figure 6 shown, as a preferred embodiment of the present invention, the vehicle travel time period spectrum construction unit specifically includes: A vehicle usage frequency analysis module, configured to acquire the vehicle usage time and generate a usage frequency distribution map of the vehicle usage time; A vehicle driving mileage analysis module, configured to acquire the driving mileage corresponding to the vehicle usage time and generate a driving mileage distribution map corresponding to the vehicle usage time; A vehicle travel event cycle spectrum generation module is used to merge the usage frequency distribution diagram at the vehicle usage time and the driving mileage distribution diagram corresponding to the vehicle usage time to generate a vehicle travel event cycle spectrum.

[0046] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A charging control method for a charging pile, characterized in that: The following steps are involved: Obtain the charging data of the vehicle connected to the charging pile and the preferential electricity price time range in the area where the charging pile is located, and generate a charging strategy feature vector; wherein the charging data includes the starting time of charging and the estimated charging time; According to the charging strategy feature vector, the charging mode of the current charging pile is formulated; the charging mode includes the user setting mode and the slow charging mode; If the charging mode is set to slow charging mode, the driving data of the vehicle connected to the charging pile is obtained to generate a vehicle travel event cycle map; the driving data includes the time of vehicle use and the mileage corresponding to the time of vehicle use; Generate the predicted vehicle usage time point based on the vehicle travel event cycle map and the charging start time point; Obtain the current remaining charge of the vehicle battery and the estimated power consumption rate corresponding to the predicted usage time of the vehicle, establish a vehicle charging analysis model, and generate the estimated charge amount of the vehicle; Wherein, the expression of the vehicle charging analysis model is: ; In the expression, It indicates the estimated charge amount of the vehicle, L time It represents the average mileage corresponding to the time in the vehicle travel event cycle map, P avg It represents the estimated power consumption rate corresponding to the predicted usage time of the vehicle, T represents the weather temperature factor, Q0 represents the current remaining charge of the vehicle; the estimated power consumption rate P corresponding to the predicted usage time of the vehicle avg Refers to the average of the power consumption rates of all vehicles at the corresponding time points in the predicted use of the analysis period; the power consumption rate refers to the speed at which the vehicle's charge is consumed; Generate a charging power setting value for the charging pile based on the estimated charge amount of the vehicle and the predicted time point of vehicle use; Control the charging power of the charging pile according to the charging power setting value of the charging pile.

2. The charging control method of the charging pile according to claim 1, characterized in that: The step of acquiring charging data of vehicles connected to the charging pile and a preferential electricity price time range in the area where the charging pile is located, and generating a charging strategy feature vector specifically includes the following steps: Obtain the start time of charging for the vehicle connected to the charging pile, the preferential electricity price time range, and the estimated charging time for the vehicle connected to the charging pile; the estimated charging time refers to the time required for the vehicle battery to be fully charged; Generate a charging start time score based on the charging start time of the vehicle connected to the charging pile and the electricity price preferential time range; Generate a vehicle charging time score based on the estimated charging time of the vehicle connected to the charging pile; A charging strategy feature vector is generated based on the charging start time score and the vehicle charging time score.

3. The charging control method of the charging pile according to claim 2, characterized in that: The method for generating the charging start time score is specifically as follows: Compare the charging start time of the vehicle connected to the charging pile with the electricity price preferential time range. If the charging start time of the vehicle connected to the charging pile is not within the electricity price preferential time range, mark the charging start time as an out-of-valley time point. When the charging start time of the vehicle connected to the charging pile is outside the valley time point, the charging strategy needs to be adjusted; Perform difference processing between the out-of-valley time point and the proximal end point of the electricity price preferential time range in the time series to generate the out-of-valley time escape amount; The out-of-valley time escape amount is compared with the total number of time points in a single cycle sequence to generate a charging start time score; The specific method for generating the vehicle charging time score is as follows: Generate a time range required for charging the vehicle connected to the charging pile based on the estimated charging time of the vehicle connected to the charging pile; Generate a time range overlap value based on the time range required for charging the vehicle connected to the charging pile and the time range of electricity price discount; Performing difference processing on the time range overlap value and the time range overlap threshold value to generate a time range overlap difference value; The time range overlap difference is compared with the time range overlap threshold to generate a vehicle charging time score; The time range overlap value is generated as follows: Compare each time point in the time range required for charging the vehicle connected to the charging pile with all time points in the time range of the electricity price discount; If a time point in the time range required for charging the vehicle connected to the charging pile is the same as a time point in the electricity price preferential time range, the time point is marked as an overlapping time point; Obtain the total number of all overlapping time points, perform ratio processing on the total number of all overlapping time points and the total number of time points in the time range required for charging of the vehicle connected to the charging pile, and generate a time range overlap value; The charging strategy feature vector is generated in the following manner: By formula ; Generate a charging strategy feature vector f; In the formula, C start It indicates the start charging time score, C duration It represents the vehicle charging time score, a1 and a2 are weight coefficients, and a1+a2=1.

4. The charging control method of the charging pile according to claim 2, characterized in that: The charging mode of the current charging pile is formulated according to the charging strategy feature vector, specifically: comparing the charging strategy feature vector to a charging strategy feature vector threshold; If the charging strategy feature vector is less than or equal to the charging strategy feature vector threshold, it means that the smaller the charging strategy feature vector is, the higher the tendency that the current charging can be set to the slow charging mode is, and the charging mode of the current charging pile is proposed to be the slow charging mode; If the charging strategy feature vector is greater than the charging strategy feature vector threshold, it means that the larger the charging strategy feature vector is, the lower the tendency that the current charging can be set to the slow charging mode is, and the charging mode of the current charging pile is set to the user-set mode.

5. The charging control method of the charging pile according to claim 1, characterized in that: If the charging mode is set to be a slow charging mode, the driving data of the vehicle connected to the charging pile is obtained to generate a vehicle travel event cycle map, which specifically includes the following steps: If the charging mode is planned to be a slow charging mode, obtain the start charging time of the vehicle connected to the charging pile, the preferential electricity price time range, and the estimated charging time of the vehicle connected to the charging pile; Generate a usage frequency distribution diagram of the vehicle usage time according to the vehicle usage time; Generate a mileage distribution map corresponding to the vehicle usage time according to the mileage corresponding to the vehicle usage time; The frequency distribution diagram of vehicle usage time and the mileage distribution diagram corresponding to the vehicle usage time are combined to generate a vehicle travel event cycle map.

6. The charging control method of the charging pile according to claim 5, characterized in that: The method for generating the usage frequency distribution diagram of the vehicle usage time is specifically as follows: Setting an analysis period, dividing the analysis period into several analysis sub-periods evenly according to a single time series cycle, obtaining the vehicle use time within the analysis sub-period, and performing data processing on the vehicle use time to obtain the vehicle use time; Obtain the number of vehicle usage moments corresponding to each moment in a single timing cycle; The number of vehicle use moments corresponding to each moment in the time sequence cycle is processed by ratio with the total number of vehicle use moments to generate the vehicle use frequency at a single moment in the time sequence cycle; Generate a frequency distribution diagram of vehicle usage moments according to the vehicle usage frequencies at single moments in all sequential cycles during the analysis period; The mileage distribution map corresponding to the vehicle usage time is generated in the following manner: Obtain the mileage of the vehicle at each moment in a single time series cycle, and mark it as the mileage corresponding to the moment; The mileage corresponding to all moments in the molecular cycle is averaged to generate the average mileage corresponding to the moment; According to the average mileage corresponding to all times, a mileage distribution map corresponding to the vehicle usage time is generated.

7. The charging control method of the charging pile according to claim 1, characterized in that: The method for generating the predicted vehicle usage time point is specifically as follows: Compare the vehicle usage frequency at a single moment in a time series cycle in the vehicle travel event cycle graph with a frequency threshold; If the vehicle use frequency at a single moment in the time series cycle in the vehicle travel event cycle map is less than the frequency threshold, it means that the lower the vehicle use frequency at a single moment in the time series cycle in the vehicle travel event cycle map, the lower the possibility of the vehicle being used at that moment, and the moment is marked as a moment with low vehicle travel possibility; If the vehicle use frequency at a single moment in the time series cycle in the vehicle travel event cycle map is greater than or equal to the frequency threshold, it means that the greater the vehicle use frequency at a single moment in the time series cycle in the vehicle travel event cycle map, the greater the possibility that the vehicle is used at this moment, and the moment is marked as a moment with a high possibility of vehicle travel; Sort all moments with high vehicle travel probability in chronological order to generate a collection of moments with high vehicle travel probability; Taking time series as the direction and the start time of charging as the starting point, the first moment of high vehicle travel possibility in the collection of moments of high vehicle travel possibility is obtained, which is the predicted use time point of the vehicle.

8. The charging control method of the charging pile according to claim 1, characterized in that: The weather temperature factor is obtained in the following manner: Get the current weather temperature, and compare the current weather temperature with the minimum value of the battery standard operating temperature range; If the current weather temperature is lower than the minimum value of the battery standard operating temperature range, the current weather temperature is marked as abnormal weather temperature; Perform difference processing on the abnormal weather temperature and the minimum value of the battery standard operating temperature range to generate a temperature difference value; The temperature difference is compared with the minimum value of the battery's standard operating temperature range to generate a weather temperature factor.

9. The charging control method of the charging pile according to claim 1, characterized in that: The charging power setting value of the charging pile is generated according to the estimated charge amount of the vehicle and the predicted use time of the vehicle, specifically: By formula ; Generate charging pile charging power setting value P sct ; In the formula, It represents the estimated charge amount of the vehicle, t use It represents the predicted time point of vehicle use, t start Indicates the time point when charging starts.

10. The charging control system of the charging pile is characterized in that: The system is used to execute the method described in any one of claims 1 to 9, and the system comprises: A charging strategy feature analysis unit is used to obtain the charging data of the vehicle connected to the charging pile and the preferential electricity price time range in the area where the charging pile is located, and generate a charging strategy feature vector; wherein the charging data includes the start time of charging and the estimated charging time; The charging mode formulation module is used to formulate the charging mode of the current charging pile according to the charging strategy feature vector; A vehicle travel time cycle map construction unit, if the charging mode is set to be a slow charging mode, the vehicle travel time cycle map construction unit is used to obtain the driving data of the vehicle connected to the charging pile and generate a vehicle travel event cycle map; the driving data includes the vehicle use time and the mileage corresponding to the vehicle use time; A vehicle usage prediction module is used to generate a vehicle predicted usage time point based on a vehicle travel event cycle map and a charging start time point; The vehicle charging analysis module is used to obtain the current remaining charge of the vehicle battery and the estimated power consumption rate corresponding to the predicted usage time of the vehicle, establish a vehicle charging analysis model, and generate the estimated charge amount of the vehicle; The charging pile charging power analysis module is used to generate a charging pile charging power setting value according to the estimated charge amount of the vehicle and the predicted vehicle usage time point; The charging pile charging power control module is used to control the charging power of the charging pile according to the charging power setting value of the charging pile; Wherein, the charging strategy characteristic analysis unit specifically includes: The data acquisition module is used to obtain the start time of charging of the vehicle connected to the charging pile, the preferential electricity price time range and the estimated charging time of the vehicle connected to the charging pile; the estimated charging time refers to the time required for the vehicle battery to be fully charged; The charging start time analysis module is used to generate a charging start time score based on the charging start time of the vehicle connected to the charging pile and the electricity price preferential time range; The vehicle charging time analysis module is used to generate a vehicle charging time score based on the estimated charging time of the vehicle connected to the charging pile; A charging strategy feature vector generation module, used to generate a charging strategy feature vector according to a charging start time score and a vehicle charging time score; The vehicle travel time cycle graph construction unit specifically includes: A vehicle usage frequency analysis module is used to obtain the vehicle usage time and generate a usage frequency distribution diagram of the vehicle usage time; The vehicle mileage analysis module is used to obtain the mileage corresponding to the time when the vehicle is used and generate a mileage distribution map corresponding to the time when the vehicle is used; The vehicle travel event cycle map generation module is used to merge the usage frequency distribution map of the vehicle usage time and the mileage distribution map corresponding to the vehicle usage time to generate a vehicle travel event cycle map.

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