New energy automobile charging management method and system for public parking space and medium

Abstract

The invention discloses a new energy vehicle charging management method and system for a public parking space and a medium, and belongs to the technical field of new energy vehicle charging, and the method comprises the steps: obtaining historical charging data based on reservation information if the reservation information of a target vehicle is received; acquiring a vehicle body picture of the target vehicle, performing image recognition on the vehicle body picture, acquiring vehicle information of the target vehicle, and acquiring historical charging data of the target vehicle if it is inquired that the vehicle information is bound with the mobile terminal; the current SOC, the predicted termination SOC and the parking duration of the target vehicle are obtained, the ideal charging power is calculated in combination with the charging limiting power, and if the remaining available power of the charging area is smaller than the ideal charging power, the charging power of the low-priority vehicle is reduced so as to increase the remaining available power; according to the charging power distribution method and device, the charging power can be reasonably distributed, and then the charging efficiency of the new energy automobile is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy vehicle charging, and specifically relates to a new energy vehicle charging management method, system and medium for public parking spaces. Background Art

[0002] With the rapid development of new energy vehicles, the construction of charging infrastructure is becoming increasingly important. However, there are many problems in the current charging management of public parking spaces, such as low utilization of charging piles and non-charging vehicles occupying charging parking spaces, which seriously restricts the convenient use of new energy vehicles. To solve the above problems, the following technical solutions are proposed in the prior art.

[0003] For example, the Chinese patent document with the publication number CN116409188A discloses a charging parking space management method, system and charging parking space based on V2X. The present invention can identify the license plate of the vehicle to be driven into the parking space based on the principle of image recognition, and judge whether the vehicle to be driven into the parking space is a new energy vehicle according to the license plate of the vehicle, and can further judge whether the vehicle is a new energy vehicle that supports charging, and release the new energy vehicle that supports charging, so that it can enter the charging parking space for charging. For another example, the Chinese patent document with the publication number CN116834594A discloses a charging management method, device, electronic device and medium based on charging parking space, which determines the target parking space according to the vacant parking space corresponding to the ordinary parking space when the vehicle is determined to be a fuel type; when the vehicle is a new energy vehicle and does not need to be charged, the target parking space is determined according to the vacant parking space corresponding to the ordinary parking space; when the vehicle is a new energy vehicle and needs to be charged, the target parking space is determined according to the vacant parking space corresponding to the charging parking space, thereby realizing the accurate allocation of parking spaces.

[0004] The above method manages charging parking spaces by distinguishing between fuel vehicles and new energy vehicles. However, there is still the following problem: for new energy vehicles charging in the same charging area, the output power allocated to each charging gun is uneven, so vehicles in a hurry to charge will charge more slowly. Summary of the invention

[0005] In order to solve the above problems, the present invention provides a new energy vehicle charging management method, system and medium for public parking spaces to solve the problems existing in the above background technology.

[0006] In order to achieve the above-mentioned purpose of the invention, the present invention proposes a new energy vehicle charging management method for public parking spaces, comprising: The parking lot is divided into an entry area and a charging area, and if the parking lot receives reservation information of a target vehicle, historical charging data of the target vehicle is obtained based on the reservation information; After the target vehicle passes through the entry area, a body picture of the target vehicle is obtained, image recognition is performed on the body picture, and vehicle information of the target vehicle is obtained. If it is found that the vehicle information is bound to a mobile terminal, the historical charging data of the target vehicle is obtained; After the target vehicle starts charging in the charging area, obtaining the current SOC of the target vehicle, and predicting the termination SOC and parking duration based on the historical charging data; Calculate the ideal charging power by combining the current SOC, the termination SOC, the charging limit power and the parking time. If the remaining available power in the charging zone is less than the ideal charging power, search for a low-priority vehicle that meets a preset condition in the charging zone, and reduce the charging power of the low-priority vehicle to increase the remaining available power. A reminder is sent to charging vehicles in the charging area whose current SOC is greater than a first threshold, where the first threshold fluctuates according to the number of waiting vehicles.

[0007] Further, the first threshold is adjusted based on the following steps: Obtain an environmental photo of the charging area, define vehicles in the environmental photo that are outside the charging area and whose taillights are on as the waiting vehicles, count a first number of the waiting vehicles, count a second number of vehicles that have made reservations to charge in the charging area, add the first number to the second number to obtain a total number of waiting vehicles, and establish a comparison table between the total number and the first threshold value, wherein in the comparison table, a larger the total number, a smaller the first threshold value, and adjust the first threshold value based on the comparison table and the current total number of waiting vehicles.

[0008] Furthermore, after the parking lot receives the reservation information, the following steps are further included: The charging area with vacant parking spaces in the parking lot is defined as an idle area, and historical charging data of the idle area is obtained, wherein the historical charging data includes the number of vehicles charged per minute in the past, and the historical charging data is analyzed to generate multiple charging rules under the idle area, and the time point when the reservation information is received is defined as the current time point, and the charging data of each idle area on the day between the preset time point and the current time point is obtained, and the charging law of each idle area on the day is determined based on the charging data on the day, and defined as the preceding law; Capture the historical charging data between the preset time point and the current time point every day in the past and belonging to the pre-regulation, obtain the estimated arrival time point in the reservation information, and calculate the recommended value of the idle area based on the first formula , the first formula is: , where K is the number of charging vehicles in the idle area at the current time point, , are the number of charging vehicles at the estimated arrival time on the nth day in the preceding rule and the number of charging vehicles at the current time, N is the number of dates belonging to the preceding rule, M is the upper limit of charging vehicles in the idle area, repeat this step to calculate the recommended value for each idle area; The vacant area with the largest recommendation value is used as a recommended area, a driving route from the entry area to the recommended area is generated, and the driving route is pushed to a mobile terminal.

[0009] Further, generating a plurality of charging rules in the idle area includes the following steps: Establishing a coordinate system with time as the horizontal axis and the number of charged vehicles as the vertical axis, and drawing a plurality of first curves in the coordinate system, wherein the first curves are curves showing the number of charged vehicles in the idle area changing with time every day; Extract two first curves, calculate the similarity between the two first curves, if the similarity is greater than a second threshold, classify the two first curves into the same charging law, define the first curve that has been classified into the charging law as the second curve, extract another first curve, and compare it with the second curve, if the similarity is greater than the second threshold, classify the extracted first curve into the same charging law as the second curve, if it is less than or equal to the second threshold, re-extract the first curve until the extraction of the first curve is completed, extract two from the first curves that have not been classified into the charging law and calculate the similarity, repeat this step until all the first curves are classified into the charging law.

[0010] Further, calculating the similarity of the first curve comprises the following steps: An interval in which the two first curves have the same change trend is obtained, which is defined as a comparison interval. A difference in the number of charging vehicles at the same time point of the two first curves within the comparison interval is calculated. A coordinate point in which the difference is less than a third threshold is defined as a comparison point. An interval in which the comparison point appears continuously is defined as a similarity interval. A first length of the horizontal coordinate of each similar interval is obtained, the first lengths are accumulated to obtain a second length, a third length of the horizontal coordinate of the first curve is obtained, and a ratio of the second length to the third length is used as the similarity.

[0011] Further, predicting the termination SOC and parking duration based on the historical charging data includes the following steps: The historical charging data includes the parking duration, starting SOC, ending SOC, charging electricity price and charging date information in the charging area. The charging date information includes the charging date, working day information, starting time point and ending time point of the vehicle. The vehicle information includes the license plate number and vehicle model. A neural network model is trained and established based on the historical charging data. The starting SOC, charging date information and vehicle model of the target vehicle are input into the neural network model as input features. The neural network model outputs the ending SOC and parking duration.

[0012] Furthermore, the preset conditions include that a current SOC of the charging vehicle is greater than a fourth threshold, and a current charging time of the charging vehicle is greater than a fifth threshold.

[0013] Furthermore, image recognition is performed on the vehicle body image based on a CNN model.

[0014] The present invention also provides a new energy vehicle charging management system for public parking spaces, which is used to implement the above-mentioned new energy vehicle charging management method for public parking spaces, and the system includes: The query unit, if the parking lot receives the reservation information of the target vehicle, obtains the historical charging data of the target vehicle based on the reservation information, obtains the body picture of the target vehicle after the target vehicle passes through the entry area, performs image recognition on the body picture, obtains the vehicle information of the target vehicle, and obtains the historical charging data of the target vehicle if it is found that the vehicle information is bound to a mobile terminal; A prediction unit, after the target vehicle starts charging in the charging area, obtains the current SOC of the target vehicle, and predicts the termination SOC and parking duration based on the historical charging data; an adjusting unit, which calculates an ideal charging power in combination with the current SOC, the termination SOC, the charging limit power and the parking duration, and if the remaining available power in the charging zone is less than the ideal charging power, searches for a low-priority vehicle that meets a preset condition in the charging zone, and reduces the charging power of the low-priority vehicle to increase the remaining available power; The reminder unit sends a reminder to a charging vehicle in the charging area whose current SOC is greater than a first threshold, wherein the first threshold fluctuates according to the number of waiting vehicles.

[0015] The present invention also discloses a computer storage medium, wherein the computer storage medium stores program instructions, wherein when the program instructions are executed, the device where the computer storage medium is located is controlled to execute the above-mentioned method.

[0016] Compared with the prior art, the beneficial effects of the present invention are at least as follows: The present invention obtains historical charging data based on the reservation information of the target vehicle, or recognizes the vehicle image after the target vehicle enters the parking lot, and indirectly obtains historical charging data through the acquired vehicle information; on the basis of being able to obtain the vehicle's historical charging data, artificial intelligence technology is combined to predict the vehicle's stay time in the parking lot and the amount of electricity that may need to be charged. When the target vehicle's stay time is short and the required charging amount is large, the charging area will be searched for vehicles with a large current remaining power or that have been charged for a long time, and their charging power will be reduced. Without exceeding the power limit of the charging gun, the charging power of the newly charged vehicle is increased as much as possible, thereby achieving a reasonable distribution of the charging power. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of the steps of the present invention for new energy vehicle charging management in public parking spaces; Figure 2 The figure is a schematic diagram of the system structure of the present invention for new energy vehicle charging management in public parking spaces. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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 intended to limit the present invention.

[0019] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0020] like Figure 1 As shown, a new energy vehicle charging management method for a public parking space includes: S1: Divide the parking lot into an entry area and a charging area. If the parking lot receives reservation information of a target vehicle, historical charging data of the target vehicle is obtained based on the reservation information.

[0021] The entry area is the entry channel set up for the parking lot. The target vehicle is the vehicle that needs to enter the parking lot for charging. If the parking lot management system receives the reservation information of the target vehicle, it indicates that the target vehicle has bound the vehicle information with the mobile terminal in the management system. The mobile terminal is, for example, a mobile phone, and allows the management system to record the vehicle's behavior data. Before this, the system may have recorded multiple charging behavior data of the vehicle. Therefore, the management system retrieves the historical charging behavior data based on the vehicle information, that is, the historical charging data.

[0022] S2: After the target vehicle passes through the entry area, a body picture of the target vehicle is obtained, image recognition is performed on the body picture, and vehicle information of the target vehicle is obtained. If the vehicle information is found to be bound to a mobile terminal, historical charging data of the target vehicle is obtained.

[0023] This implementation uses the CNN deep learning algorithm to identify the vehicle body image to obtain the vehicle information of the target vehicle, including the license plate number and vehicle model. In the absence of reservation information, the only way to obtain historical charging data is through vehicle information. If no historical charging data is obtained, it indicates that the target vehicle may be entering the parking lot for the first time, or the vehicle information is not bound to the mobile terminal. In both cases, the management system does not retain the behavior data of the target vehicle after entering the parking lot to protect user privacy.

[0024] S3: After the target vehicle starts charging in the charging area, the current SOC of the target vehicle is obtained, and the termination SOC and parking duration are predicted based on historical charging data.

[0025] S4: Calculate the ideal charging power based on the current SOC, the termination SOC, the charging limit power and the parking time. If the remaining available power in the charging zone is less than the ideal charging power, find a low-priority vehicle that meets the preset conditions in the charging zone and reduce the charging power of the low-priority vehicle to increase the remaining available power.

[0026] After connecting the charging gun to the vehicle, the current SOC of the target vehicle, that is, the current remaining power, can be obtained. In the field of new energy vehicles, SOC represents the remaining power of the vehicle's power battery. Combined with the historical charging data obtained previously, the possible charging time of the target vehicle in the charging area and the power at which charging may end can be predicted. Artificial intelligence methods can be used for prediction. Afterwards, the ideal charging power, such as 40kw / h, can be obtained by subtracting the current remaining power from the charging power that may end and dividing it by the parking time. When the ideal charging power is less than the charging limit power of the charging gun, the remaining available power in the charging area is less than the ideal charging power, and low-priority vehicles will be found in the charging area. Reduce its charging power to release the remaining available power. Low-priority vehicles include charging vehicles whose current SOC is greater than the second threshold, such as 70%, or whose charging time is too long, such as more than 2 hours.

[0027] S5: Send a reminder to charging vehicles in the charging area whose current SOC is greater than a first threshold, where the first threshold fluctuates according to the number of waiting vehicles.

[0028] The first threshold is continuously adjusted according to actual conditions. For example, if the first threshold is 95%, when there is a vehicle in the charging area with a remaining power greater than 95%, and the charging vehicle is bound to a mobile terminal, a reminder is sent to the corresponding mobile terminal. The reminder may be to suggest that the owner move the vehicle in time to avoid wasting charging resources.

[0029] In addition, during the vehicle charging process, the charging area of ​​this embodiment also obtains the charging current, charging voltage and battery temperature of the charging gun, and cuts off the power supply and generates an alarm when the charging current, charging voltage and battery temperature exceed the preset range.

[0030] The present invention obtains historical charging data based on the reservation information of the target vehicle, or recognizes the vehicle image after the target vehicle enters the parking lot, and indirectly obtains historical charging data through the acquired vehicle information; on the basis of being able to obtain the vehicle's historical charging data, artificial intelligence technology is combined to predict the vehicle's stay time in the parking lot and the amount of electricity that may need to be charged. When the target vehicle's stay time is short and the required charging amount is large, the charging area will be searched for vehicles with a large current remaining power or that have been charged for a long time, and their charging power will be reduced. Without exceeding the power limit of the charging gun, the charging power of the newly charged vehicle is increased as much as possible, thereby achieving a reasonable distribution of the charging power.

[0031] It is particularly noteworthy that the present invention can reasonably distribute the charging power, thereby improving the charging efficiency of new energy vehicles.

[0032] This embodiment adjusts the first threshold based on the following steps: Obtain an environmental photo of the charging area, define vehicles in the environmental photo that are outside the charging area and whose taillights are on as waiting vehicles, count a first number of waiting vehicles, count a second number of vehicles that have made reservations to charge in the charging area, add the first number and the second number to obtain the total number of waiting vehicles, and establish a comparison table between the total number and a first threshold. In the comparison table, the larger the total number, the smaller the first threshold. Adjust the first threshold based on the comparison table and the current total number of waiting vehicles.

[0033] The environmental photos include photos of the charging area and its vicinity, and then image recognition is performed on the photos to obtain vehicles outside the charging area. In addition, the taillights of vehicles in a waiting state are usually lit. Afterwards, the first number of vehicles identified as waiting in the environmental photos and the second number of vehicles that have been reserved in the management system and need to be charged in the charging area are counted to obtain the total number of vehicles that need to be charged in the charging area in the future. The first threshold that needs to be set is determined based on the corresponding relationship between the total number and the first threshold in the comparison table. For example, the comparison table is 2 for the total number and 80% for the first threshold, and 5 for the total number and 70% for the first threshold.

[0034] After the parking lot receives the reservation information, the present embodiment further includes the following steps: The charging area with vacant parking spaces in the parking lot is defined as an idle area, and the historical charging data of the idle area is obtained. The historical charging data includes the number of vehicles charged every minute in the past. The historical charging data is analyzed to generate multiple charging rules for the idle area. The time point when the reservation information is received is defined as the current time point. The daily charging data of each idle area between the preset time point and the current time point of the day is obtained. Based on the daily charging data, the charging rule that occurs in each idle area on that day is determined and defined as the preceding rule.

[0035] For medium and large parking lots, there are often multiple charging areas with scattered locations, and they are generally established by different suppliers. In order to find a charging area with vacant parking spaces, users need to constantly explore in the parking lot, which not only wastes the user's time, but also aggravates the congestion of the parking lot. Therefore, after receiving the reservation information of the target vehicle in the parking lot, the present invention will find the seat vacant areas with vacant parking spaces in each charging area, and then obtain the historical charging data of the vacant areas. The historical charging data includes the number of charging vehicles in the vacant area every minute in the past, such as 14:00, the number of charging vehicles is 3, such as 14:01, the number of charging vehicles is 3. Afterwards, the historical charging data is analyzed to generate the charging rules of each vacant area on a daily basis. Through the charging rules, it can be understood which time periods of the charging area are busier and which time periods are more idle, which is convenient for subsequent analysis.

[0036] The preset time point is a time point set manually, such as 6 o'clock in the morning. After receiving the reservation information at the parking lot, the current time point of receiving the reservation information is determined, such as 10 o'clock, and the charging data of each idle area between 6 o'clock and 10 o'clock on the day is obtained. Then, the current charging data of the day is compared with the historical charging data between 6 o'clock and 10 o'clock every morning in the past, so as to obtain the date with the same charging pattern as the current day, and the corresponding charging pattern is defined as the preceding pattern. Through this step, the charging pattern of each idle area at present is obtained.

[0037] Capture the historical charging data between the preset time point and the current time point every day in the past and under the previous rule, obtain the estimated arrival time point in the reservation information, and calculate the recommended value of the idle area based on the first formula , the first formula is: , where K is the number of charging vehicles in the idle area at the current time point, , are the number of charging vehicles at the estimated arrival time on the nth day in the preceding rule and the number of charging vehicles at the current time, N is the number of dates belonging to the preceding rule, M is the upper limit of charging vehicles in the idle area, repeat this step to calculate the recommended value for each idle area; The vacant area with the largest recommendation value is taken as the recommended area, and a driving route from the entry area to the recommended area is generated and pushed to the mobile terminal.

[0038] The first formula is for the calculation of the recommended value of an idle area. Before using the first formula, first obtain the date that belongs to the previous rule, count its number as the value of N, then obtain the customer's estimated arrival time from the appointment information, obtain the number of charging vehicles at the estimated arrival time and the current time point every day on the date that belongs to the previous rule, and then substitute it into the first formula for calculation. The denominator in the first formula expresses the fluctuation of the number of charging vehicles at two time points, and the larger the upper limit of charging vehicles in the idle area, the larger the calculated recommended value. After calculating the recommended values ​​of all idle areas through the first formula, the idle area with the largest recommended value is used as the recommended area and pushed to the mobile terminal of the target vehicle, and the recommended information is generated at the same time. The recommended information, for example, includes the following content: it is recommended that you go to charging area A, and it is estimated that there will be 3 vacant parking spaces when you arrive.

[0039] Through this step, after the customer makes a reservation for charging, the system can recommend a suitable charging location for the customer based on the reservation time and the charging status of each charging area when arriving, which can further improve the charging management level of public parking spaces.

[0040] In this embodiment, generating multiple charging rules in the idle area includes the following steps: A coordinate system is established with time as the horizontal axis and the number of charging vehicles as the vertical axis, and a plurality of first curves are drawn in the coordinate system, where the first curve is a curve showing the number of charging vehicles in the idle area changing with time every day; Extract two first curves, calculate the similarity between the two first curves, if the similarity is greater than the second threshold, classify the two first curves into the same charging law, define the first curve that has been classified into the charging law as the second curve, extract another first curve, and compare it with the second curve, if the similarity is greater than the second threshold, classify the extracted first curve into the same charging law as the second curve, if it is less than or equal to the second threshold, re-extract the first curve until the extraction of the first curve is completed, extract two from the first curves that have not been classified into the charging law and calculate the similarity, repeat this step until all the first curves are classified into the charging law.

[0041] For the same idle area, draw the first curve of each day in the past in the coordinate system, randomly extract two first curves, and calculate the similarity between the two first curves. The calculation method will be introduced later. If the similarity of the two first curves is greater than the second threshold, that is, the two first curves are very similar, indicating that the charging patterns of these two days are also very similar, so they are stored as a charging pattern. For the convenience of description, these two first curves are defined as second curves; then, extract another first curve and compare it with the two second curves to obtain the similarity. If the newly extracted first curve is very similar to the two second curves, then this first curve is also divided into the corresponding charging pattern, and continue to extract until all the first curves under the idle area are traversed. The first curve that has not been divided into the charging pattern is re-divided using this step.

[0042] In this embodiment, calculating the similarity of the first curve includes the following steps: An interval in which the two first curves have the same change trend is obtained, which is defined as a comparison interval. The difference in the number of charging vehicles at the same time point of the two first curves within the comparison interval is calculated, and the coordinate point in which the difference is less than the third threshold is defined as a comparison point. An interval in which the comparison points appear continuously is defined as a similarity interval. The first length of the horizontal coordinate of each similar interval is obtained, the first length is accumulated to obtain the second length, the third length of the horizontal coordinate of the first curve is obtained, and the ratio of the second length to the third length is used as the similarity.

[0043] The curves with the same changes refer to the time segments in which the number of charged vehicles remains unchanged, increases, and decreases at the same time. After screening out the segment, the difference in the number of charged vehicles at the same time point, if the difference is less than the third threshold, then the number of two points is considered to be close, which is defined as the comparison point here. If the comparison points appear continuously, it indicates that in the rising and falling intervals, the two curves are also rising or falling at the same rate. In the horizontal interval, the number of vehicles charged at the current time is close. Such an interval is set as a similarity interval. It can be seen that the longer the length of the similarity interval, the higher the similarity of the two curves. The second length of the similarity interval is compared with the third length of the first curve, and the ratio is used as the similarity. Then, the larger the ratio, the greater the similarity.

[0044] It should be noted that when comparing which charging pattern the day belongs to, first draw a charging quantity change curve between the current preset time point and the current time point, extract a first curve from each charging pattern divided in the past as a representative curve, and cut off the part between the preset time point and the current time point from the representative curve, compare this part with the charging quantity change curve of the day, and take the first curve with the greatest similarity as the corresponding charging pattern.

[0045] This embodiment predicts the termination SOC and parking duration based on historical charging data, including the following steps: The historical charging data includes the parking time in the charging area, the starting SOC, the ending SOC, the charging electricity price and the charging date information. The charging date information includes the charging date, working day information, the starting time point and the ending time point of the vehicle. The vehicle information includes the license plate number and the vehicle model. A neural network model is trained and established based on the historical charging data. The starting SOC, charging date information and vehicle model of the target vehicle are input into the neural network model as input features. The neural network model outputs the ending SOC and parking time.

[0046] The parking time is, for example, 1 hour or 2 hours. The charging electricity price is the electricity price set by the supplier in the charging area, which generally fluctuates with the time of day. The weekday information indicates whether the charging date is a weekday, and is represented by 0 or 1 as an input feature. This embodiment uses a BP neural network model for training and use. The BP neural network is a type of artificial intelligence algorithm, and has the characteristics of simple structure and strong interpretability. In other embodiments, RBF neural networks or SOM self-organizing networks can also be used as prediction models.

[0047] In this embodiment, the preset conditions include that the current SOC of the charging vehicle is greater than the second threshold, and the current charging time of the charging vehicle is greater than the third threshold.

[0048] like Figure 2As shown, the present invention also provides a new energy vehicle charging management system for public parking spaces, which is used to implement the above-mentioned new energy vehicle charging management method for public parking spaces, and the system includes: The query unit, if the parking lot receives the reservation information of the target vehicle, obtains the historical charging data of the target vehicle based on the reservation information, obtains the body picture of the target vehicle after the target vehicle passes through the entry area, performs image recognition on the body picture, obtains the vehicle information of the target vehicle, and obtains the historical charging data of the target vehicle if the vehicle information is bound to the mobile terminal; A prediction unit, after the target vehicle starts charging in the charging area, obtains the current SOC of the target vehicle and predicts the termination SOC and parking duration based on historical charging data; The adjustment unit calculates the ideal charging power based on the current SOC, the termination SOC, the charging limit power and the parking time. If the remaining available power in the charging area is less than the ideal charging power, a low-priority vehicle that meets the preset conditions is searched in the charging area, and the charging power of the priority vehicle is reduced to increase the remaining available power. The reminder unit sends a reminder to a charging vehicle in a charging area whose current SOC is greater than a first threshold, and the first threshold fluctuates according to the number of waiting vehicles.

[0049] The present invention also discloses a computer storage medium, wherein the computer storage medium stores program instructions, wherein when the program instructions are executed, the device where the computer storage medium is located is controlled to execute the above method.

[0050] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0051] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0052] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0053] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A new energy vehicle charging management method for public parking spaces, characterized in that: include: The parking lot is divided into an entry area and a charging area, and if the parking lot receives reservation information of a target vehicle, historical charging data of the target vehicle is obtained based on the reservation information; After the target vehicle passes through the entry area, a body picture of the target vehicle is obtained, image recognition is performed on the body picture, and vehicle information of the target vehicle is obtained. If it is found that the vehicle information is bound to a mobile terminal, the historical charging data of the target vehicle is obtained; After the target vehicle starts charging in the charging area, obtaining the current SOC of the target vehicle, and predicting the termination SOC and parking duration based on the historical charging data; Calculate the ideal charging power by combining the current SOC, the termination SOC, the charging limit power and the parking time. If the remaining available power in the charging zone is less than the ideal charging power, search for a low-priority vehicle that meets a preset condition in the charging zone, and reduce the charging power of the low-priority vehicle to increase the remaining available power. A reminder is sent to charging vehicles in the charging area whose current SOC is greater than a first threshold, where the first threshold fluctuates according to the number of waiting vehicles.

2. The method according to claim 1, characterized in that The first threshold is adjusted based on the following steps: Obtain an environmental photo of the charging area, define vehicles in the environmental photo that are outside the charging area and whose taillights are on as the waiting vehicles, count a first number of the waiting vehicles, count a second number of vehicles that have made reservations to charge in the charging area, add the first number to the second number to obtain a total number of waiting vehicles, and establish a comparison table between the total number and the first threshold value, wherein in the comparison table, a larger the total number, a smaller the first threshold value, and adjust the first threshold value based on the comparison table and the current total number of waiting vehicles.

3. The method according to claim 1, characterized in that After the parking lot receives the reservation information, the following steps are also included: The charging area with vacant parking spaces in the parking lot is defined as an idle area, and historical charging data of the idle area is obtained, wherein the historical charging data includes the number of vehicles charged per minute in the past, and the historical charging data is analyzed to generate multiple charging rules under the idle area, and the time point when the reservation information is received is defined as the current time point, and the charging data of each idle area on the day between the preset time point and the current time point is obtained, and the charging law of each idle area on the day is determined based on the charging data on the day, and defined as the preceding law; Capture the historical charging data between the preset time point and the current time point every day in the past and belonging to the pre-regulation, obtain the estimated arrival time point in the reservation information, and calculate the recommended value of the idle area based on the first formula , the first formula is: , where K is the number of charging vehicles in the idle area at the current time point, , are the number of charging vehicles at the estimated arrival time on the nth day in the preceding rule and the number of charging vehicles at the current time, N is the number of dates belonging to the preceding rule, M is the upper limit of charging vehicles in the idle area, repeat this step to calculate the recommended value for each idle area; The vacant area with the largest recommendation value is used as a recommended area, a driving route from the entry area to the recommended area is generated, and the driving route is pushed to a mobile terminal.

4. The method according to claim 3, characterized in that: Generating a plurality of charging rules in the idle area comprises the following steps: Establishing a coordinate system with time as the horizontal axis and the number of charged vehicles as the vertical axis, and drawing a plurality of first curves in the coordinate system, wherein the first curves are curves showing the number of charged vehicles in the idle area changing with time every day; Extract two first curves, calculate the similarity between the two first curves, if the similarity is greater than a second threshold, classify the two first curves into the same charging law, define the first curve that has been classified into the charging law as the second curve, extract another first curve, and compare it with the second curve, if the similarity is greater than the second threshold, classify the extracted first curve into the same charging law as the second curve, if it is less than or equal to the second threshold, re-extract the first curve until the extraction of the first curve is completed, extract two from the first curves that have not been classified into the charging law and calculate the similarity, repeat this step until all the first curves are classified into the charging law.

5. The method according to claim 4, characterized in that Calculating the similarity of the first curve comprises the following steps: An interval in which the two first curves have the same change trend is obtained, which is defined as a comparison interval. A difference in the number of charging vehicles at the same time point of the two first curves within the comparison interval is calculated. A coordinate point in which the difference is less than a third threshold is defined as a comparison point. An interval in which the comparison point appears continuously is defined as a similarity interval. A first length of the horizontal coordinate of each similar interval is obtained, the first lengths are accumulated to obtain a second length, a third length of the horizontal coordinate of the first curve is obtained, and a ratio of the second length to the third length is used as the similarity.

6. The method according to claim 1, characterized in that Predicting the termination SOC and parking duration based on the historical charging data includes the following steps: The historical charging data includes the parking duration, starting SOC, ending SOC, charging electricity price and charging date information in the charging area. The charging date information includes the charging date, working day information, starting time point and ending time point of the vehicle. The vehicle information includes the license plate number and vehicle model. A neural network model is trained and established based on the historical charging data. The starting SOC, charging date information and vehicle model of the target vehicle are input into the neural network model as input features. The neural network model outputs the ending SOC and parking duration.

7. The method according to claim 1, characterized in that The preset conditions include that the current SOC of the charging vehicle is greater than a fourth threshold, and the current charging time of the charging vehicle is greater than a fifth threshold.

8. The method according to claim 1, characterized in that Image recognition is performed on the vehicle body image based on a CNN model.

9. A new energy vehicle charging management system for public parking spaces, used to implement the method according to any one of claims 1 to 8, characterized in that: include: The query unit, if the parking lot receives the reservation information of the target vehicle, obtains the historical charging data of the target vehicle based on the reservation information, obtains the body picture of the target vehicle after the target vehicle passes through the entry area, performs image recognition on the body picture, obtains the vehicle information of the target vehicle, and obtains the historical charging data of the target vehicle if it is found that the vehicle information is bound to a mobile terminal; A prediction unit, after the target vehicle starts charging in the charging area, obtains the current SOC of the target vehicle, and predicts the termination SOC and parking duration based on the historical charging data; an adjusting unit, which calculates an ideal charging power in combination with the current SOC, the termination SOC, the charging limit power and the parking duration, and if the remaining available power in the charging zone is less than the ideal charging power, searches for a low-priority vehicle that meets a preset condition in the charging zone, and reduces the charging power of the low-priority vehicle to increase the remaining available power; The reminder unit sends a reminder to a charging vehicle in the charging area whose current SOC is greater than a first threshold, wherein the first threshold fluctuates according to the number of waiting vehicles.

10. A computer storage medium, characterized in that: The computer storage medium stores program instructions, wherein when the program instructions are executed, the device where the computer storage medium is located is controlled to execute the method according to any one of claims 1 to 8.

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