Electric vehicle remote charging online monitoring system and method

Abstract

The invention discloses an electric vehicle remote charging on-line monitoring system and method, and relates to the field of electric vehicle charging, and the system comprises an acquisition module which is used for collecting electric vehicle charging state information in real time, and adjusting and controlling the period of the electric vehicle charging state information collected by the acquisition module in real time based on the electric vehicle charging state information; the visualization unit is used for receiving the electric vehicle charging state information acquired by the acquisition module and displaying the electric vehicle charging state information; the monitoring module is used for acquiring the electric vehicle charging state information accumulatively acquired by the acquisition module and monitoring the electric vehicle charging comprehensive risk based on the electric vehicle charging state information; according to the method, key parameters such as voltage, current and battery temperature are collected in real time, the collection frequency is intelligently adjusted based on parameter fluctuation characteristics, data redundancy can be reduced when the charging state is stable, the monitoring frequency can be encrypted when the parameters fluctuate abnormally, and the efficiency and pertinence of data collection are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging, and in particular to an electric vehicle remote charging online monitoring system and method. Background Art

[0002] Charging monitoring is a technology that uses smart devices or systems to track and manage the charging process in real time. It monitors parameters such as charging voltage, current, charge level, and temperature, displays charging progress in real time, and warns of abnormalities such as overcharging, overheating, and short circuits, ensuring charging safety. It is widely used in electric vehicle charging.

[0003] The invention patent application with application number 202111296915.8 discloses an online monitoring system for remote charging of electric vehicles, including a cloud server set at a remote end, a user terminal and a control terminal remotely connected to the cloud server, the cloud server is connected to a smart meter through a gateway, and the smart meter is connected to a number of electric housekeepers, and the electric housekeepers are used to charge electric vehicles; wherein the electric housekeepers include a mounting plate for mounting on the wall, a shell fixedly set on the mounting plate, a metal pin with one end located inside the shell and the other end extending out of the shell, and a movable plate slidably set in the shell, and the movable plate is provided with A metal clip corresponding to the metal pin is used to clamp the metal pin for conductivity after the movable plate moves up; an iron core is provided at the bottom of the movable plate, and an electric demagnetization electromagnet is provided at a position corresponding to the iron core at the bottom of the outer shell. A limit plate is provided in the outer shell, and a guide rod is provided between the limit plate and the bottom of the outer shell. A guide hole is provided on the movable plate, and the guide hole on the movable plate slides with the guide rod. This application aims to solve the problem that "the charging data of electric vehicles for charging facilities is not comprehensive enough, and it is impossible to accurately analyze whether the charging status is normal. After the electric vehicle is charged, the power supply is still in a connected state, which increases the probability of danger."

[0004] However, for the electric vehicle itself in the electric vehicle charging scenario, the existing technology does not have a comprehensive charging monitoring technology to fully ensure the safety of electric vehicle charging;

[0005] Therefore, an electric vehicle remote charging online monitoring system and method are proposed. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides an electric vehicle remote charging online monitoring system and method, which can effectively solve the problems of the prior art.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] The present invention discloses an online monitoring system for remote charging of electric vehicles, comprising:

[0009] The acquisition module is used to collect the electric vehicle charging status information in real time, and to adjust the cycle of the acquisition module to collect the electric vehicle charging status information in real time based on the electric vehicle charging status information; the visualization unit is used to receive the electric vehicle charging status information collected by the acquisition module and display the electric vehicle charging status information; the monitoring module is used to obtain the electric vehicle charging status information accumulated by the acquisition module, and to monitor the comprehensive risk of electric vehicle charging based on the electric vehicle charging status information; the judgment module is used to set the electric vehicle charging risk judgment threshold, obtain the electric vehicle charging comprehensive risk monitoring result in the monitoring module, and compare the monitoring result with the judgment threshold. When the monitoring result is greater than the judgment threshold, it is judged that there is a risk in the electric vehicle charging; the early warning module is used to trigger the operation and issue an early warning when the judgment result of the judgment module is that there is a risk in the electric vehicle charging; the emergency maintenance unit is used to receive the judgment result in the judgment module, and disconnect the electric vehicle charging power supply from the electric vehicle when the judgment result is that there is a risk in the electric vehicle charging.

[0010] Furthermore, the collection module is provided with a marking unit and a storage unit at a lower level. The marking unit is used to receive the electric vehicle charging status information collected by the collection module and mark the electric vehicle charging status information with a collection timestamp. The storage unit is used to obtain the electric vehicle charging status information marked with a collection timestamp in the marking unit, and sort and store the electric vehicle charging status information based on the collection timestamp marked with the electric vehicle charging status information.

[0011] Among them, an initial operation cycle is set in the acquisition module. Based on the initial operation cycle, the acquisition module runs continuously for three times when the electric vehicle is connected to the power supply, and then performs the regulation of the acquisition cycle.

[0012] Furthermore, the electric vehicle charging status information collected by the acquisition module includes: voltage, current, battery temperature, remaining power, and battery health status (SOH). When the voltage, current, battery temperature, remaining power, and battery health status (SOH) in the electric vehicle charging status information are stored in the storage unit, they are all stored in a line graph representing a change trend.

[0013] The control of the cycle of the acquisition module collecting the electric vehicle charging status information is subject to:

[0014]

[0015] Where: d is the next cycle of the acquisition module to collect electric vehicle charging status information; d0 is the initial operation cycle; n is the total number of historical acquisitions of electric vehicle charging status information; v i 、v i+1 is the voltage value collected at the i-th and i+1-th times; min(v i ,v i+1 ) means taking the minimum value in brackets; I i , Ii+1 is the current value collected at the i-th and i+1-th times; C i 、C i+1 is the stable value collected at the i-th and i+1-th times; SOH i 、SOH i+1 is the SOH value collected at the i-th and i+1-th times; ω(v), ω(I), ω(C), and ω(SOH) are the weights of the corresponding voltage, current, battery temperature, and battery health SOH;

[0016] Among them, when d is applied to the collection of electric vehicle charging status information, the electric vehicle charging status information is collected at the beginning of d, and the next cycle of collecting electric vehicle charging status information is requested again based on the above formula.

[0017] Furthermore, the ω(v), ω(I), ω(C), and ω(SOH) are all positive numbers whose sum is 1, and obey:

[0018]

[0019] Furthermore, the visualization unit is integrated with a mobile computer device having a display function, and the visualization unit is interactively connected with the storage unit to retrieve the electric vehicle charging status information stored in the form of a line graph in the storage unit, and refresh the line graph representing the electric vehicle charging status information in real time;

[0020] Among them, when the visualization unit displays a line graph representing the charging status information of an electric vehicle, it synchronously identifies the risk index of each line graph corresponding to the charging status information of the electric vehicle based on the line graph, takes the line graph with the highest risk index as the display target, executes the display instruction, and refreshes the identification operation of the risk index of each line graph corresponding to the charging status information of the electric vehicle each time the line graph updates the data, and completes the replacement of the displayed line graph based on the identification result.

[0021] Furthermore, the logical representation of the risk index of the electric vehicle charging status information corresponding to the line graph is as follows:

[0022] Sample the nodes in the line graph and record them as the sampling point set;

[0023] When the identification target is voltage or current:

[0024]

[0025] When the identification target is battery temperature or battery health status (SOH):

[0026]

[0027] Where: RI is the risk index; S is the standard deviation of fluctuation determined based on the corresponding value of each sampling point in the sampling point set; k is the trend slope determined based on the line segment between each sampling point in the sampling point set; R is the trend change rate determined based on the line segment between each sampling point in the sampling point set; max(S), max(|k|), and max(R) are the maximum values ​​of the standard deviation of fluctuation, the absolute value of the trend slope, and the trend change rate in the historical information; It means taking the maximum value of each summation term in the numerator of the fractional part of the above formula;

[0028] in, Express The averaging operation.

[0029] Furthermore, during the operation phase of the monitoring module, the charging status information of the electric vehicle accumulated by the acquisition module is acquired, and the operation of monitoring the comprehensive charging risk of the electric vehicle based on the charging status information of the electric vehicle is performed, namely:

[0030] The corresponding risk index of each electric vehicle charging status information obtained during the operation of the visualization unit is obtained, and the corresponding risk index of each electric vehicle charging status information is used to monitor the comprehensive risk of electric vehicle charging. The monitoring logic is expressed as follows:

[0031] Each time corresponding to voltage, current, battery temperature, battery health SOH, the risk index is calculated and recorded as RI v , RI I , RI C , RI SOH ;

[0032]

[0033] In the formula: RI syn is the comprehensive risk of electric vehicle charging; u is the cumulative number of times the risk index corresponding to the current charging status information of each electric vehicle is obtained; max s (RI v , RI I , RI C , RI SOH ) represents the maximum value of the risk index corresponding to the charging status information of each electric vehicle obtained for the sth time;

[0034] Based on the update of the risk index corresponding to the charging status information of each electric vehicle, the RI is repeatedly calculated. syn Then there is RI syn (1) RI syn (2), ..., RI syn (x-1), RI syn (x), RI is always applied syn (1) RI syn (2), ..., RI syn (x-1), RIsyn The latest four calculation results in (x) determine whether there is a risk in charging electric vehicles;

[0035] RI syn (x-2)-RI syn (x-3)<RI syn (x-1)-RI syn (x-2)<RI syn (x)-RI syn (x-1);

[0036] If the above formula is established, it is determined that there is a risk in charging the electric vehicle. The above determination logic and the logic of determining whether there is a risk in charging the electric vehicle in the determination module are synchronously applied in the system.

[0037] Furthermore, when the determination result is that there is no risk in charging the electric vehicle, the determination module refreshes the system operation;

[0038] The warning module is connected to the electric device owned by the user of the electric vehicle through the network. When the operation is triggered, the preset warning information is sent to the electric device owned by the user of the electric vehicle through the network, and the operation of issuing the warning is completed;

[0039] Among them, the emergency maintenance unit has a higher operating priority than the early warning module in the system.

[0040] Furthermore, the acquisition module is interactively connected to a marking unit and a storage unit at the lower level through a wireless network, the acquisition module is interactively connected to a visualization unit through a wireless network, the visualization unit is interactively connected to a storage unit through a wireless network, the visualization unit is interactively connected to a monitoring module and a determination module through a wireless network, the determination module is interactively connected to an early warning module through a wireless network, and the early warning module and the determination module are interactively connected to an emergency maintenance unit through a wireless network.

[0041] In another aspect, a method for online monitoring of remote charging of an electric vehicle includes:

[0042] Configure the collection cycle, collect the electric vehicle charging status information in real time based on the collection cycle, and record the collected electric vehicle charging status information in a line graph representing trend changes; identify the electric vehicle charging risk index based on the recorded charging status information of each type of electric vehicle; monitor the comprehensive risk of electric vehicle charging in combination with the risk index identification results corresponding to the historical charging status information of each type of electric vehicle; set the electric vehicle charging risk determination logic, obtain the comprehensive risk monitoring results of electric vehicle charging, and determine whether there is a risk in electric vehicle charging based on the monitoring results and the electric vehicle charging risk determination logic; issue a warning when it is determined that there is a risk in electric vehicle charging, and simultaneously disconnect the electric vehicle charging power supply from the electric vehicle.

[0043] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0044] The present invention provides a system and method for online monitoring of electric vehicle remote charging. During implementation, the system and method collect key parameters such as voltage, current, and battery temperature in real time, and intelligently adjust the collection frequency based on parameter fluctuation characteristics. This system and method can reduce data redundancy when the charging state is stable and increase the monitoring frequency when parameters fluctuate abnormally, significantly improving the efficiency and pertinence of data collection.

[0045] At the visualization level, the system presents multi-dimensional data in real-time in the form of dynamic line graphs. Through intelligent risk index recognition technology, it automatically prioritizes the parameter dimensions with the highest current risk, helping users quickly identify charging hazards.

[0046] At the same time, multi-parameter risk indexes are integrated into the risk monitoring link, and a comprehensive risk model is constructed through historical data comparison and dynamic weighting algorithm. It can not only provide real-time warning of abnormal conditions, but also complete a complete maintenance strategy from monitoring to warning to disposal through the emergency power-off mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0048] Figure 1 This is a structural diagram of an online monitoring system for remote charging of electric vehicles;

[0049] Figure 2 The figure is a flow chart of an online monitoring method for remote charging of electric vehicles. DETAILED DESCRIPTION

[0050] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings 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 making creative efforts are within the scope of protection of the present invention.

[0051] The present invention will be further described below with reference to the embodiments.

[0052] Example 1:

[0053] This embodiment of an electric vehicle remote charging online monitoring system, such as Figure 1 Shown, including:

[0054] A collection module is used to collect the charging status information of the electric vehicle in real time, and to adjust the period of the collection module collecting the charging status information of the electric vehicle in real time based on the charging status information of the electric vehicle;

[0055] The collection module is provided with a marking unit and a storage unit at the lower level. The marking unit is used to receive the electric vehicle charging status information collected by the collection module and mark the collection time stamp of the electric vehicle charging status information. The storage unit is used to obtain the electric vehicle charging status information marked with the collection time stamp in the marking unit, and sort and store the electric vehicle charging status information based on the collection time stamp marked with the electric vehicle charging status information.

[0056] Among them, the acquisition module is provided with an initial operation cycle, and the acquisition module runs three times continuously based on the initial operation cycle when the electric vehicle is connected to the power supply, and then performs the control of the acquisition cycle;

[0057] The electric vehicle charging status information collected by the acquisition module includes: voltage, current, battery temperature, remaining power, and battery health status (SOH). When the voltage, current, battery temperature, remaining power, and battery health status (SOH) in the electric vehicle charging status information are stored in the storage unit, they are all stored in a line graph indicating the change trend;

[0058] The control of the cycle of the acquisition module to collect the charging status information of electric vehicles is subject to:

[0059]

[0060] Where: d is the next cycle of the acquisition module to collect electric vehicle charging status information; d0 is the initial operation cycle; n is the total number of historical acquisitions of electric vehicle charging status information; v i 、v i+1 is the voltage value collected at the i-th and i+1-th times; min(v i ,v i+1 ) means taking the minimum value in brackets; I i , I i+1 is the current value collected at the i-th and i+1-th times; C i 、C i+1 is the stable value collected at the i-th and i+1-th times; SOH i 、SOH i+1 is the SOH value collected at the i-th and i+1-th times; ω(v), ω(I), ω(C), and ω(SOH) are the weights of the corresponding voltage, current, battery temperature, and battery health SOH;

[0061] Wherein, when d is applied to the collection of electric vehicle charging status information, the electric vehicle charging status information is collected at the beginning of d, and the next cycle of collecting electric vehicle charging status information is requested again based on the above formula;

[0062] ω(v), ω(I), ω(C), and ω(SOH) are all positive numbers whose sum is 1 and obey:

[0063]

[0064] By using the logic formula in the above embodiment, the period of the system acquisition module collecting the electric vehicle charging status information is adaptively regulated, so that the collected content of the electric vehicle charging status information is more referenceable, thereby improving the accuracy of the operation of subsequent modules of the system in this embodiment;

[0065] A visualization unit is used to receive the electric vehicle charging status information collected by the collection module and display the electric vehicle charging status information;

[0066] The visualization unit is integrated with a mobile computer device having a display function. The visualization unit is interactively connected with the storage unit, retrieves the electric vehicle charging status information stored in the form of a line graph in the storage unit, and refreshes and displays the line graph representing the electric vehicle charging status information in real time;

[0067] Wherein, when displaying the line graphs representing the charging status information of the electric vehicle, the visualization unit synchronously identifies the risk index of the charging status information of the electric vehicle corresponding to each line graph based on the line graph, takes the line graph with the highest risk index as the display target, executes the display instruction, and refreshes the identification operation of the risk index of the charging status information of the electric vehicle corresponding to each line graph each time the line graph updates data, and completes the replacement of the displayed line graph based on the identification result;

[0068] The logical expression of the risk index of the electric vehicle charging status information corresponding to the line graph is as follows:

[0069] Sample the nodes in the line graph and record them as the sampling point set;

[0070] When the identification target is voltage or current:

[0071]

[0072] When the identification target is battery temperature or battery health status (SOH):

[0073]

[0074] Where: RI is the risk index; S is the standard deviation of fluctuation determined based on the corresponding value of each sampling point in the sampling point set; k is the trend slope determined based on the line segment between each sampling point in the sampling point set; R is the trend change rate determined based on the line segment between each sampling point in the sampling point set; max(S), max(|k|), and max(R) are the maximum values ​​of the standard deviation of fluctuation, the absolute value of the trend slope, and the trend change rate in the historical information; It means taking the maximum value of each summation term in the numerator of the fractional part of the above formula;

[0075] in, Express The mean operation of ;

[0076] Through the above logic formula, the calculation method of the risk index corresponding to the charging status information of each type of electric vehicle is limited;

[0077] The monitoring module is used to obtain the electric vehicle charging status information accumulated by the collection module, and monitor the comprehensive charging risk of the electric vehicle based on the electric vehicle charging status information;

[0078] During the operation phase of the monitoring module, the charging status information of electric vehicles accumulated by the acquisition module is obtained, and the operation of monitoring the comprehensive risk of electric vehicle charging is performed based on the charging status information of electric vehicles, namely:

[0079] The corresponding risk index of each electric vehicle charging status information obtained during the operation of the visualization unit is obtained, and the corresponding risk index of each electric vehicle charging status information is used to monitor the comprehensive risk of electric vehicle charging. The monitoring logic is expressed as follows:

[0080] Each time corresponding to voltage, current, battery temperature, battery health SOH, the risk index is calculated and recorded as RI v , RI I , RI C , RI SOH ;

[0081]

[0082] In the formula: RI syn is the comprehensive risk of electric vehicle charging; u is the cumulative number of times the risk index corresponding to the current charging status information of each electric vehicle is obtained; max s (RI v , RI I , RI C , RI SOH ) represents the maximum value of the risk index corresponding to the charging status information of each electric vehicle obtained for the sth time;

[0083] Based on the update of the risk index corresponding to the charging status information of each electric vehicle, the RI is repeatedly calculated. syn Then there is RI syn(1) RI syn (2), ..., RI syn (x-1), RI syn (x), RI is always applied syn (1) RI syn (2), ..., RI syn (x-1), RI syn The latest four calculation results in (x) determine whether there is a risk in charging electric vehicles;

[0084] RI syn (x-2)-RI syn (x-3)<RI syn (x-1)-RI syn (x-2)<RI syn (x)-RI syn (x-1);

[0085] If the above equation is true, it is determined that there is a risk in charging electric vehicles. The above judgment logic and the logic of determining whether there is a risk in charging electric vehicles in the judgment module are synchronously applied in the system.

[0086] Through the above formula, the electric vehicle charging status information is output in a digital form, and another electric vehicle charging risk determination logic is provided, so that this logic is combined with the determination module to provide more effective risk monitoring of the electric vehicle charging process;

[0087] A determination module is used to set a threshold for determining the risk of electric vehicle charging, obtain the comprehensive risk monitoring results of electric vehicle charging in the monitoring module, compare the monitoring results with the determination threshold, and determine that there is a risk in electric vehicle charging when the monitoring result is greater than the determination threshold;

[0088] An early warning module is used to trigger operation and issue an early warning when the judgment module determines that there is a risk in charging the electric vehicle;

[0089] An emergency maintenance unit is configured to receive a determination result from the determination module and, when the determination result indicates that there is a risk in charging the electric vehicle, disconnect the electric vehicle charging power supply from the electric vehicle;

[0090] When the determination result of the determination module is that there is no risk in charging the electric vehicle, the system operation is refreshed;

[0091] The early warning module is connected to the electric device owned by the user of the electric vehicle through the network. When the operation is triggered, the preset early warning information is sent to the electric device owned by the user of the electric vehicle through the network, and the operation of issuing the early warning has been completed;

[0092] Among them, the emergency maintenance unit has a higher operating priority than the early warning module in the system;

[0093] The acquisition module is interactively connected to the marking unit and the storage unit through a wireless network. The acquisition module is interactively connected to the visualization unit through a wireless network. The visualization unit is interactively connected to the storage unit through a wireless network. The visualization unit is interactively connected to the monitoring module and the judgment module through a wireless network. The judgment module is interactively connected to the early warning module through a wireless network. The early warning module and the judgment module are interactively connected to the emergency maintenance unit through a wireless network.

[0094] In this embodiment, the collection module collects the electric vehicle charging status information in real time, and adjusts the collection cycle of the electric vehicle charging status information in real time based on the electric vehicle charging status information. The marking unit synchronously receives the electric vehicle charging status information collected by the collection module and marks the collection time stamp of the electric vehicle charging status information. The storage unit obtains the electric vehicle charging status information marked with the collection time stamp in the marking unit in real time, and sorts and stores the electric vehicle charging status information based on the collection time stamp marked by the electric vehicle charging status information. The visualization unit is post-operated to receive the electric vehicle charging status information collected by the collection module and display the electric vehicle charging status information. The monitoring module then obtains the electric vehicle charging status information accumulated by the collection module and monitors the comprehensive charging risk of the electric vehicle based on the electric vehicle charging status information.

[0095] The judgment module sets the electric vehicle charging risk judgment threshold, obtains the comprehensive risk monitoring result of the electric vehicle charging in the monitoring module, compares the monitoring result with the judgment threshold, and judges that there is a risk in the electric vehicle charging when the monitoring result is greater than the judgment threshold. Finally, the early warning module is triggered to run when the judgment module determines that there is a risk in the electric vehicle charging, and issues an early warning. The emergency maintenance unit receives the judgment result in the judgment module in real time, and disconnects the electric vehicle charging power supply from the electric vehicle when the judgment result is that there is a risk in the electric vehicle charging.

[0096] Through the system in the above embodiment, a comprehensive charging monitoring service is provided for the electric vehicle body in the charging scenario, ensuring the stability of the electric vehicle charging process and being able to respond in time to avoid aggravation of risk problems when abnormal risks occur.

[0097] Example 2:

[0098] In terms of specific implementation, based on Example 1, this example refers to Figure 2 The electric vehicle remote charging online monitoring system in Example 1 is further described in detail:

[0099] A method for online monitoring of remote charging of an electric vehicle, comprising:

[0100] Step 1: Configure a collection cycle, collect electric vehicle charging status information in real time based on the collection cycle, and record the collected electric vehicle charging status information in a line graph representing trend changes;

[0101] Step 2: Identify the charging risk index of each type of electric vehicle based on the recorded charging status information of each type of electric vehicle;

[0102] Step 3: Combine the historical charging status information of various types of electric vehicles with the corresponding risk index identification results to monitor the comprehensive risk of electric vehicle charging;

[0103] Step 4: Set up the electric vehicle charging risk determination logic, obtain the electric vehicle charging comprehensive risk monitoring results, and determine whether there is a risk in electric vehicle charging based on the monitoring results and the electric vehicle charging risk determination logic;

[0104] Step 5: When it is determined that there is a risk in charging the electric vehicle, an early warning is issued, and the connection between the electric vehicle charging power supply and the electric vehicle is simultaneously disconnected.

[0105] In summary, during the execution of the systems and methods in the above embodiments, by real-time collection of key parameters such as voltage, current, and battery temperature, and intelligently adjusting the collection frequency based on the parameter fluctuation characteristics, it can not only reduce data redundancy when the charging state is stable, but also increase the monitoring frequency when the parameters fluctuate abnormally, thereby significantly improving the efficiency and pertinence of data collection. At the visualization level, the system has made a breakthrough in presenting multi-dimensional data in real time in the form of a dynamic line graph, and through the intelligent recognition technology of risk index, it automatically captures the parameter dimensions with the highest current risk and displays them first, helping users to quickly identify charging hazards. At the same time, it integrates multi-parameter risk indexes in the risk monitoring link, and constructs a comprehensive risk model through historical data comparison and dynamic weighting algorithm. It can not only provide real-time warning of abnormal conditions, but also complete a complete maintenance strategy from monitoring to warning to disposal through the emergency power-off mechanism.

[0106] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An electric vehicle remote charging online monitoring system, characterized in that: include: A collection module is used to collect the charging status information of the electric vehicle in real time, and to adjust the period of the collection module collecting the charging status information of the electric vehicle in real time based on the charging status information of the electric vehicle; A visualization unit is used to receive the electric vehicle charging status information collected by the collection module and display the electric vehicle charging status information; The monitoring module is used to obtain the electric vehicle charging status information accumulated by the collection module, and monitor the comprehensive charging risk of the electric vehicle based on the electric vehicle charging status information; A determination module is used to set a threshold for determining the risk of electric vehicle charging, obtain the comprehensive risk monitoring results of electric vehicle charging in the monitoring module, compare the monitoring results with the determination threshold, and determine that there is a risk in electric vehicle charging when the monitoring result is greater than the determination threshold; An early warning module is used to trigger operation and issue an early warning when the judgment module determines that there is a risk in charging the electric vehicle; The emergency maintenance unit is used to receive the determination result from the determination module, and when the determination result is that there is a risk in charging the electric vehicle, disconnect the connection between the electric vehicle charging power supply and the electric vehicle.

2. The electric vehicle remote charging online monitoring system according to claim 1, characterized in that: The collection module is provided with a marking unit and a storage unit at the lower level. The marking unit is used to receive the electric vehicle charging status information collected by the collection module and mark the electric vehicle charging status information with a collection timestamp. The storage unit is used to obtain the electric vehicle charging status information marked with a collection timestamp in the marking unit, and sort and store the electric vehicle charging status information based on the collection timestamp marked with the electric vehicle charging status information. Among them, an initial operation cycle is set in the acquisition module. Based on the initial operation cycle, the acquisition module runs continuously for three times when the electric vehicle is connected to the power supply, and then performs the regulation of the acquisition cycle.

3. The electric vehicle remote charging online monitoring system according to claim 2, characterized in that: The electric vehicle charging status information collected by the acquisition module includes: voltage, current, battery temperature, remaining power, and battery health status (SOH). When the voltage, current, battery temperature, remaining power, and battery health status (SOH) in the electric vehicle charging status information are stored in the storage unit, they are all stored in a line graph representing the change trend; The control of the cycle of the acquisition module collecting the electric vehicle charging status information is subject to: Where: d is the next cycle of the acquisition module to collect electric vehicle charging status information; d0 is the initial operation cycle; n is the total number of historical acquisitions of electric vehicle charging status information; v i 、v i+1 is the voltage value collected at the i-th and i+1-th times; min(v i ,v i+1 ) means taking the minimum value in brackets; I i , I i+1 is the current value collected at the i-th and i+1-th times; C i 、C i+1 is the stable value collected at the i-th and i+1-th times; SOH i 、SOH i+1 is the SOH value collected at the i-th and i+1-th times; ω(v), ω(I), ω(C), and ω(SOH) are the weights of the corresponding voltage, current, battery temperature, and battery health SOH; Among them, when d is applied to the collection of electric vehicle charging status information, the electric vehicle charging status information is collected at the beginning of d, and the next cycle of collecting electric vehicle charging status information is requested again based on the above formula.

4. The electric vehicle remote charging online monitoring system according to claim 3, characterized in that: The ω(v), ω(I), ω(C), and ω(SOH) are all positive numbers whose sum is 1 and obey:

5. The electric vehicle remote charging online monitoring system according to claim 1, characterized in that: The visualization unit is integrated with a mobile computer device having a display function, and the visualization unit is interactively connected with the storage unit to retrieve the electric vehicle charging status information stored in the form of a line graph in the storage unit, and refresh the line graph representing the electric vehicle charging status information in real time; Among them, when the visualization unit displays a line graph representing the charging status information of an electric vehicle, it synchronously identifies the risk index of each line graph corresponding to the charging status information of the electric vehicle based on the line graph, takes the line graph with the highest risk index as the display target, executes the display instruction, and refreshes the identification operation of the risk index of each line graph corresponding to the charging status information of the electric vehicle each time the line graph updates the data, and completes the replacement of the displayed line graph based on the identification result.

6. The electric vehicle remote charging online monitoring system according to claim 5, characterized in that: The logical expression of the risk index of the electric vehicle charging status information corresponding to the line graph is as follows: Sample the nodes in the line graph and record them as the sampling point set; When the identification target is voltage or current: When the identification target is battery temperature or battery health status (SOH): Where: RI is the risk index; S is the standard deviation of fluctuation determined based on the corresponding values ​​of each sampling point in the sampling point set; k is the trend slope determined based on the line segments between each sampling point in the sampling point set; R is the trend change rate determined based on the line segments between each sampling point in the sampling point set; max(S), max(|k|), and max(R) are the maximum values ​​of the standard deviation of fluctuation, the absolute value of the trend slope, and the trend change rate in the historical information; It means taking the maximum value of each summation term in the numerator of the fractional part of the above formula; in, Express The averaging operation.

7. The electric vehicle remote charging online monitoring system according to claim 1, characterized in that: During the operation phase of the monitoring module, the charging status information of the electric vehicle accumulated by the acquisition module is acquired, and the operation of monitoring the comprehensive charging risk of the electric vehicle is performed based on the charging status information of the electric vehicle, namely: The corresponding risk index of each electric vehicle charging status information obtained during the operation of the visualization unit is obtained, and the corresponding risk index of each electric vehicle charging status information is used to monitor the comprehensive risk of electric vehicle charging. The monitoring logic is expressed as follows: Each time corresponding to voltage, current, battery temperature, battery health SOH, the risk index is calculated and recorded as RI v , RI I , RI C , RI SOH ; In the formula: RI syn is the comprehensive risk of electric vehicle charging; u is the cumulative number of times the risk index corresponding to the current charging status information of each electric vehicle is obtained; max s (RI v , RI I , RI C , RI SOH ) represents the maximum value of the risk index corresponding to the charging status information of each electric vehicle obtained for the sth time; Based on the update of the risk index corresponding to the charging status information of each electric vehicle, the RI is repeatedly calculated. syn Then there is RI syn (1) RI syn (2), ..., RI syn (x-1), RI syn (x), RI is always applied syn (1) RI syn (2), ..., RI syn (x-1), RI syn The latest four calculation results in (x) determine whether there is a risk in charging electric vehicles; RI syn (x-2)-RI syn (x-3)<RI syn (x-1)-RI syn (x-2)<RI syn (x)-RI syn (x-1); If the above formula is established, it is determined that there is a risk in charging the electric vehicle. The above determination logic and the logic of determining whether there is a risk in charging the electric vehicle in the determination module are synchronously applied in the system.

8. The electric vehicle remote charging online monitoring system according to claim 1, characterized in that: When the determination result is that there is no risk in charging the electric vehicle, the determination module refreshes the system operation; The warning module is connected to the electric device owned by the user of the electric vehicle through the network. When the operation is triggered, the preset warning information is sent to the electric device owned by the user of the electric vehicle through the network, and the operation of issuing the warning has been completed; Among them, the emergency maintenance unit has a higher operating priority than the early warning module in the system.

9. The electric vehicle remote charging online monitoring system according to claim 1, characterized in that: The acquisition module is interactively connected to a marking unit and a storage unit at the lower level through a wireless network. The acquisition module is interactively connected to a visualization unit through a wireless network. The visualization unit is interactively connected to a storage unit through a wireless network. The visualization unit is interactively connected to a monitoring module and a determination module through a wireless network. The determination module is interactively connected to an early warning module through a wireless network. The early warning module and the determination module are interactively connected to an emergency maintenance unit through a wireless network.

10. A method for online monitoring of remote charging of electric vehicles, the method being an implementation method of an online monitoring system for remote charging of electric vehicles as claimed in any one of claims 1 to 9, characterized in that: include: Step 1: Configure a collection cycle, collect electric vehicle charging status information in real time based on the collection cycle, and record the collected electric vehicle charging status information in a line graph representing trend changes; Step 2: Identify the charging risk index of each type of electric vehicle based on the recorded charging status information of each type of electric vehicle; Step 3: Combine the historical charging status information of various types of electric vehicles with the corresponding risk index identification results to monitor the comprehensive risk of electric vehicle charging; Step 4: Set up the electric vehicle charging risk determination logic, obtain the electric vehicle charging comprehensive risk monitoring results, and determine whether there is a risk in electric vehicle charging based on the monitoring results and the electric vehicle charging risk determination logic; Step 5: When it is determined that there is a risk in charging the electric vehicle, an early warning is issued, and the connection between the electric vehicle charging power supply and the electric vehicle is simultaneously disconnected.

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