Electric vehicle smart sharing charging system based on smart community and Internet of Things

Abstract

The invention discloses an electric vehicle smart sharing charging system based on a smart community and the Internet of Things, relates to the technical field of smart sharing charging, and solves the problem that related change of charging current is not carried out for related charging states of electric vehicles. In order to meet the charging requirements of the corresponding electric vehicles corresponding to different charging ports, related adjustment is performed according to different charging curves associated with different charging ports, so that the charging requirements of different electric vehicles are regulated and controlled in real time, and the charging efficiency of the electric vehicles is improved. Therefore, it is guaranteed that different charging ports can achieve the best charging mode in the associated charging state of multiple different electric vehicles, the best charging effect can be achieved corresponding to the different electric vehicles, numerical value change is conducted on the specified standard range, the endpoint value of the range is changed, relevant selection of the characteristic curve is conducted again, and the optimal charging effect can be achieved. And based on the numerical range of the processed mean value, determining related abnormal ports and performing associated display.

Description

Technical Field

[0001] The present invention relates to the field of smart shared charging technology, and in particular to a smart shared charging system for electric vehicles based on a smart community and the Internet of Things. Background Art

[0002] Smart charging piles can automatically identify the type of electric vehicle and charging requirements, adjust the output power and voltage, and provide safe and efficient charging services for electric vehicles. At the same time, they can also monitor various parameters during the charging process, such as current, voltage, temperature, etc. in real time. Once an abnormal situation is found, the power supply will be automatically cut off immediately to ensure charging safety;

[0003] The application with publication number CN112009294A discloses a shared charging service system based on a smart city integrated photovoltaic storage and charging parking shed, including a camera, a data analysis module, an audio acquisition module, a ground lock module, a controller, a fault prediction module, a data acquisition module and a display module; the present invention collects video information and audio information of passing vehicles, identifies whether the vehicle has an exhaust pipe and analyzes the audio content to determine whether the vehicle is an electric vehicle or a gasoline vehicle, thereby solving the problem of parking spaces occupied by gasoline vehicles at charging piles, and has the advantages of simple equipment and accurate detection data; when the charging line of the electric vehicle is connected to the charging pile for charging, the battery data of the electric vehicle is collected and analyzed and processed to obtain the battery's danger factor and battery failure factor; timely warning is given to prompt the owner to replace the battery, and at the same time the controller controls the charging pile to cut off the power to avoid the risk caused by the aging of the electric vehicle battery due to long-term use;

[0004] When it comes to smart shared charging management of electric vehicles, power control is generally performed through the corresponding charging station so that the corresponding charging port can supply power normally and perform associated charging for the designated electric vehicle. However, the original charging control method does not make relevant changes to the charging current according to the relevant charging status of the electric vehicle, resulting in low charging efficiency and failure to achieve better charging effects when multiple different electric vehicles are charged. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an intelligent shared charging system for electric vehicles based on a smart community and the Internet of Things, which solves the problem of not making relevant changes to the charging current according to the relevant charging status of the electric vehicle.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an electric vehicle intelligent shared charging system based on a smart community and the Internet of Things, comprising:

[0007] The port power monitoring terminal monitors the charging curves of different charging ports of the smart charging terminal in real time, and transmits the real-time monitored charging curves to the trend change analysis terminal;

[0008] The associated current real-time adjustment terminal performs associated adjustment on the supply current of the specified charging port based on the charging curves monitored by different charging ports, and adjusts the supply current in real time based on its specific trend change process. The specific method is as follows:

[0009] Based on the charging curve generated by its corresponding charging port, the parameter associated with the vertical axis of the charging curve is the charging power, and its horizontal axis is the timeline, identifying the power difference Cz between its initial moment and the adjacent moment i , where i represents the adjacent time period between different adjacent moments, and Cz i = Charging power at the next moment - Charging power at the previous moment, and the power difference Cz generated in real time i Conduct association analysis:

[0010] If Cz i ≥0, then identify Cz i Is it satisfied: (Cz i -Cz i-1 )≥0, indicating that the charging power is increasing and the supply current is sufficient for normal charging, and no associated adjustment is required:

[0011] If (Cz i -Cz i-1 )<0, its Cz i is the power difference determined in the current period, where Cz i-1 The power difference value determined in the previous period is used to gradually increase the supply current for 5 seconds. It is then determined whether the power difference values ​​that appear in succession meet the following condition: Cz i+1 ≥Cz i If satisfied, keep the boosted power supply current unchanged and perform subsequent related monitoring in the same way; if not satisfied, reduce the boosted power supply current to the current value before boost and mark it as DL. Based on the change of charging power between the next moment and the current moment, determine the power supply current at the next moment: [(G i+1 -G i )÷G i ]+1×DL, and perform subsequent related monitoring in the same way;

[0012] If Cz i <0, the power supply current is gradually increased for 5 seconds, and the subsequent power difference is identified to see whether it meets the following conditions: Cz i+1 ≥Cz iIf satisfied, keep the boosted power supply current unchanged and perform subsequent related monitoring in the same way; if not satisfied, reduce the boosted power supply current to the current value before boost and mark it as DL. Based on the change of charging power between the next moment and the current moment, determine the power supply current at the next moment: [(G i+1 -G i )÷G i ]+1×DL, and perform subsequent related monitoring in the same way;

[0013] The port numerical analysis end determines the cycle based on the charging curve generated by each different charging port after charging is completed, performs numerical evaluation and analysis on several groups of charging curves belonging to the corresponding associated cycle, selects characteristic curves from the charging curves, and then transmits the determined several groups of characteristic curves to the abnormal port evaluation end. The specific method is as follows:

[0014] A set of acquisition cycles T is defined, where T is a preset value, and multiple sets of different charging curves completed by different charging ports within this acquisition cycle T are acquired one by one, and the acquired charging curves are evaluated for their trends:

[0015] Based on the set standard power range, which is a preset power range, the relevant curve segment belonging to the standard power range is determined from the charging curve, and the line length ratio of the relevant curve segment is identified: Zb = relevant curve segment line length ÷ total charging curve line length:

[0016] If Zb is less than 80%, the numerical range of the standard power range is kept unchanged, and the end point range is changed. Based on the corresponding change process, the relevant curve segments contained in each different change process are locked. From several change processes, the longest relevant curve segment is calibrated as the characteristic curve of this charging curve. If the characteristic curve has not been confirmed, an error signal is directly generated for display;

[0017] If Zb≥80%, directly mark the relevant curve segment as the characteristic curve of this charging curve;

[0018] The abnormal port assessment end, based on different characteristic curves confirmed by different charging curves, merges several groups of characteristic curves belonging to the same charging port, locks the associated features of its charging port, and then identifies abnormal ports with related abnormalities based on different associated features confirmed by different charging ports; the specific method is:

[0019] Based on several groups of characteristic curves of the same charging port, the charging powers corresponding to the several groups of characteristic curves are averaged to determine a processing average value, and the processing average value is used as the associated feature of the charging port;

[0020] Label several groups of associated features as Tz o, where o represents different charging ports, if Tz o ≥Ys, where Ys is the preset standard parameter, no calibration is performed. If Tz o <Ys, the corresponding port is marked as an abnormal port and displayed.

[0021] The present invention provides an intelligent shared charging system for electric vehicles based on smart communities and the Internet of Things. Compared with the prior art, it has the following beneficial effects:

[0022] In order to ensure that different charging ports can meet the charging needs of corresponding electric vehicles, the present invention performs relevant adjustments according to different charging curves associated with different charging ports, thereby performing real-time regulation and control on the charging needs of different electric vehicles, thereby ensuring that different charging ports can achieve the best charging mode when charging in association with multiple different electric vehicles, so that the corresponding different electric vehicles can achieve the best charging effect;

[0023] According to the set standard range, the characteristic curve contained in the corresponding curve is identified. If the characteristic curve is not up to standard, the numerical value of the specified standard range is changed, and the endpoint value of the range is changed. The relevant characteristic curve is reselected, and then the processing mean of the corresponding port is locked from the selected different characteristic curves. Based on the numerical range of the processing mean, the relevant abnormal port is determined and displayed in association. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0025] Figure 2 It is a schematic diagram of the determination process of the characteristic curve of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] See also Figure 1 , the present application provides an electric vehicle intelligent shared charging system based on a smart community and the Internet of Things, including a port power monitoring terminal, an associated current real-time allocation terminal, a port numerical analysis terminal, and an abnormal port assessment terminal, wherein the port power monitoring terminal is electrically connected to the port numerical analysis terminal or the associated current real-time allocation terminal input node, and the port numerical analysis terminal is electrically connected to the abnormal port assessment terminal input node;

[0028] Among them, the port power monitoring end monitors the charging curves of different charging ports of the smart charging end in real time, and transmits the real-time monitored charging curves to the trend change analysis end. A smart charging sharing end has multiple battery vehicle charging ports, each of which is in a parallel state and can independently complete the charging work of different charging battery vehicles. According to the charging requirements of different battery vehicles, the charging curves of each charging port are inconsistent, and the corresponding charging curves can be directly obtained from the smart charging end. When the corresponding charging port is charging, its charging curve can be confirmed for the specific charging process. Its charging curve can be different associated powers corresponding to different times, and the unit of its associated power is W (watt);

[0029] Its associated current real-time allocation end, based on the charging curves monitored by different charging ports, makes associated adjustments to the supply current of the designated charging port, and based on its specific trend change process, makes real-time adjustments to the supply current to ensure that its charging port can supply power normally (in order to ensure that the corresponding electric vehicle can be charged quickly normally. When the electric vehicle is charging, as the internal battery is gradually filled, the required charging current is also changing all the time. If the electric vehicle needs a large current for charging, but the corresponding port cannot supply such a large current, the charging rate of the electric vehicle will be affected). The specific method of real-time adjustment of the supply current is as follows:

[0030] Based on the charging curve generated by its corresponding charging port, the parameter associated with the vertical axis of the charging curve is the charging power, and its horizontal axis is the timeline, identifying the power difference Cz between its initial moment and the adjacent moment i , where i represents the adjacent time period between different adjacent moments, and Cz i = Charging power at the next moment - Charging power at the previous moment, and the power difference Cz generated in real time i Conduct association analysis:

[0031] If Cz i ≥0, then identify Cz i Is it satisfied: (Cz i -Cz i-1 )≥0, indicating that the charging power is increasing and the supply current is sufficient for normal charging, and no associated adjustment is required:

[0032] If (Cz i -Cz i-1 )<0, its Cz i is the power difference determined in the current period, where Cz i-1The power difference determined in the previous period means that although the charging power is in a climbing state, the trend is slowing down. This may be caused by insufficient power supply current or the storage process of the battery inside the electric vehicle, which gradually increases the power supply current for 5 seconds. Identify whether the subsequent power difference values ​​meet the following conditions: Cz i+1 ≥Cz i If it is satisfied, keep the boosted power supply current unchanged and perform subsequent related monitoring in the same way. If it is not satisfied, it means that it is caused by the battery itself, which means that the battery has entered a slow charging mode or a fast charging state. Its current does not need to change much. Reduce the boosted power supply current to the current value before the boost (that is, the relevant current 5 seconds ago) and mark it as DL. Based on the change of its charging power at the next moment and the current moment, determine the power supply current at the next moment: [(G i+1 -G i )÷G i ]+1×DL, and perform subsequent related monitoring in the same way;

[0033] If Cz i <0, indicating that the charging power is in a decreasing state, which may be caused by insufficient supply current or the storage process of the battery inside the electric vehicle, causing the supply current to increase gradually. The increase time is 5 seconds. Identify whether the subsequent power difference meets the following conditions: Cz i+1 ≥Cz i If it is satisfied, keep the boosted power supply current unchanged and perform subsequent related monitoring in the same way. If it is not satisfied, it means that it is caused by the battery itself, which means that the battery has entered a slow charging mode or a fast charging state. Its current does not need to change much. Reduce the boosted power supply current to the current value before the boost (that is, the relevant current 5 seconds ago) and mark it as DL. Based on the change of its charging power at the next moment and the current moment, determine the power supply current at the next moment: [(G i+1 -G i )÷G i ]+1×DL, and perform subsequent related monitoring in the same way. This stage is the same as (Cz i -Cz i-1 )<0, but the trends of the curves they represent are inconsistent;

[0034] Specifically, in order to ensure that different charging ports can meet the charging needs of corresponding electric vehicles, relevant adjustments are made according to the different charging curves associated with different charging ports, so as to conduct real-time regulation of the charging needs of different electric vehicles, thereby ensuring that different charging ports can achieve the best charging method when charging in association with multiple different electric vehicles, so that the corresponding different electric vehicles can achieve the best charging effect.

[0035] Among them, the port numerical analysis end determines the cycle based on the charging curve generated by each different charging port after charging is completed, performs numerical evaluation and analysis on several groups of charging curves belonging to the corresponding associated cycle, selects the characteristic curve in its charging curve, and then transmits the determined several groups of characteristic curves to the abnormal port evaluation end. Specifically, the characteristic curve here is the curve generated under the normal charging state. The numerical characteristics of this part of the curve do not have large numerical fluctuations, but are relatively stable, that is, the corresponding charging port is for the constant charging stage of the specified electric vehicle. The constant charging stage is the associated stage where the charging power is the most stable and can reach the maximum charging amount. This stage can complete 80% of the charging amount of the corresponding electric vehicle battery;

[0036] Among them, combined Figure 2 , the specific method of selecting the corresponding characteristic curve in its charging curve is:

[0037] A set of acquisition cycles T is defined, where T is a preset value, which is formulated by relevant operators based on experience, and is generally 24h or 72h, etc., and is specifically determined based on the specific charging situation. Multiple sets of different charging curves completed by different charging ports within this acquisition cycle T are acquired one by one, and the acquired charging curves are evaluated for their trends:

[0038] Based on the set standard power range, and the standard power range is a preset power range, which is prepared in advance by the operator, and is the power range when the corresponding charging port is in a normal charging state, that is, the constant charging stage, the relevant curve segment belonging to this standard power range is determined from the charging curve, and the line length ratio of this relevant curve segment is identified: Zb = relevant curve segment line length ÷ charging curve total line length, if Zb ≥ 80%, directly calibrate this relevant curve segment as the characteristic curve of this charging curve, if Zb < 80%, keep the numerical range of this standard power range unchanged, and change its endpoint range, based on the corresponding change process, lock the relevant curve segments contained in each different change process, and from several change processes, calibrate the longest relevant curve segment as the characteristic curve of this charging curve, if the characteristic curve has not been confirmed, then directly generate an error signal for display, which represents the corresponding charging The curve is abnormal, which may be caused by the abnormality of the charging port (the range here remains unchanged, but the endpoint value changes, that is, the original standard power range is [180w, 200w], and its range value is 20. Then after relevant changes, it can change to [170w, 190w] or [190w, 210w] or even other relevant power ranges. In order to lock the corresponding characteristic curve, the characteristic curve determined by the original power range does not show enough relevant characteristics, so the corresponding range is associated with the change, that is, for the case where there is charging fluctuation during charging, then when the range fluctuates, the corresponding characteristic curve can be locked). The characteristic curve can show the charging status and charging power of the corresponding charging port. If there is a charging abnormality in the corresponding charging port, the characteristic curve that can be generated is quite different in numerical state from other characteristic curves.

[0039] Its abnormal port assessment end, based on different characteristic curves confirmed by different charging curves, merges several groups of characteristic curves belonging to the same charging port, locks the associated features of its charging port, and then identifies abnormal ports with related abnormalities based on different associated features confirmed by different charging ports. Specifically, the identified abnormal ports are generally related ports with lower charging power, which generally means that the corresponding ports themselves have related abnormal problems;

[0040] The specific methods for identifying abnormal ports are as follows:

[0041] Based on several groups of characteristic curves of the same charging port, the charging powers corresponding to the several groups of characteristic curves are averaged to determine a processing average value, and the processing average value is used as the associated feature of the charging port;

[0042] Label several groups of associated features as Tz o , where o represents different charging ports, if Tz o≥Ys, where Ys is the preset standard parameter, which is prepared by the relevant operators in advance based on experience, and no calibration is performed. If Tz o <Ys, the corresponding port is marked as an abnormal port and displayed;

[0043] Example: Assume that Ys is set to 500 watts. After calculation, Tz A =550W, Tz B =450W, Tz C = 520 watts. Then port A and port C are not calibrated, while port B is calibrated as an abnormal port and displayed because it is less than the standard parameter Ys, reminding relevant personnel to handle it.

[0044] Some of the data in the above formulas are numerically calculated by removing their dimensions. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0045] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent shared charging system for electric vehicles based on smart communities and the Internet of Things, characterized in that: include: The port power monitoring terminal monitors the charging curves of different charging ports of the smart charging terminal in real time, and transmits the real-time monitored charging curves to the trend change analysis terminal; The associated current real-time adjustment terminal performs associated adjustment on the supply current of the specified charging port based on the charging curves monitored by different charging ports, and adjusts the supply current in real time based on its specific trend change process; The port numerical analysis end determines the cycle based on the charging curve generated by each different charging port after charging is completed, performs numerical evaluation and analysis on several groups of charging curves belonging to the corresponding associated cycle, selects characteristic curves from the charging curves, and then transmits the determined several groups of characteristic curves to the abnormal port evaluation end; The abnormal port assessment end, based on the different characteristic curves confirmed by different charging curves, merges several groups of characteristic curves belonging to the same charging port, locks the associated features of its charging port, and then identifies the abnormal ports with related abnormalities based on the different associated features confirmed by different charging ports.

2. According to claim 1, an intelligent shared charging system for electric vehicles based on a smart community and the Internet of Things is characterized in that: The specific method of the associated current real-time adjustment terminal for real-time adjustment of the power supply current is: Based on the charging curve generated by its corresponding charging port, the parameter associated with the vertical axis of the charging curve is the charging power, and its horizontal axis is the timeline, identifying the power difference Cz between its initial moment and the adjacent moment i , where i represents the adjacent time period between different adjacent moments, and Cz i = Charging power at the next moment - Charging power at the previous moment, and the power difference Cz generated in real time i Conduct association analysis: If Cz i ≥0, then identify Cz i Is it satisfied: (Cz i -Cz i-1 )≥0, indicating that the charging power is increasing and the supply current is sufficient for normal charging, and no associated adjustment is required: If (Cz i -Cz i-1 )<0, its Cz i is the power difference determined in the current period, and its Cz i-1 The power difference value determined in the previous period is used to gradually increase the supply current for 5 seconds. It is then determined whether the power difference values ​​that appear in succession meet the following condition: Cz i+1 ≥Cz i If satisfied, keep the boosted power supply current unchanged and perform subsequent related monitoring in the same way; if not satisfied, reduce the boosted power supply current to the current value before boost and mark it as DL. Based on the change of charging power between the next moment and the current moment, determine the power supply current at the next moment: [(G i+1 -G i )÷G i ]+1×DL, and perform subsequent related monitoring in the same way.

3. According to claim 2, an electric vehicle intelligent shared charging system based on a smart community and the Internet of Things is characterized in that: The specific method of the associated current real-time adjustment terminal for real-time adjustment of the power supply current also includes: If Cz i <0, the power supply current is gradually increased for 5 seconds, and the subsequent power difference is identified to see whether it meets the following conditions: Cz i+1 ≥Cz i If satisfied, keep the boosted power supply current unchanged and perform subsequent related monitoring in the same way; if not satisfied, reduce the boosted power supply current to the current value before boost and mark it as DL. Based on the change of charging power between the next moment and the current moment, determine the power supply current at the next moment: [(G i+1 -G i )÷G i ]+1×DL, and perform subsequent related monitoring in the same way.

4. According to claim 1, the electric vehicle intelligent shared charging system based on smart community and Internet of Things is characterized in that: The specific method of selecting the corresponding characteristic curve in the charging curve at the port numerical analysis end is: A set of acquisition cycles T is defined, where T is a preset value, and multiple sets of different charging curves completed by different charging ports within this acquisition cycle T are acquired one by one, and the acquired charging curves are evaluated for their trends: Based on the set standard power range, which is a preset power range, the relevant curve segment belonging to the standard power range is determined from the charging curve, and the line length ratio of the relevant curve segment is identified: Zb = relevant curve segment line length ÷ total charging curve line length: If Zb is less than 80%, the numerical range of the standard power range is kept unchanged, and its endpoint range is changed. Based on the corresponding change process, the relevant curve segments contained in each different change process are locked. From several change processes, the longest relevant curve segment is calibrated as the characteristic curve of this charging curve. If the characteristic curve has not been confirmed, an error signal is directly generated for display.

5. According to claim 4, the electric vehicle intelligent shared charging system based on smart community and Internet of Things is characterized in that: If Zb≥80%, the relevant curve segment is directly calibrated as the characteristic curve of the charging curve.

6. The electric vehicle intelligent shared charging system based on smart community and Internet of Things according to claim 5 is characterized in that: The abnormal port assessment end identifies abnormal ports in the following specific manner: Based on several groups of characteristic curves of the same charging port, the charging powers corresponding to the several groups of characteristic curves are averaged to determine a processing average value, and the processing average value is used as the associated feature of the charging port; Label several groups of associated features as Tz o , where o represents different charging ports, if Tz o ≥Ys, where Ys is the preset standard parameter, no calibration is performed. If Tz o <Ys, the corresponding port is marked as an abnormal port and displayed.

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