Electric vehicle charging pile fault diagnosis method

Abstract

The invention discloses an electric vehicle charging pile fault diagnosis method, and particularly relates to the technical field of fault diagnosis, and the method comprises the steps: obtaining the current data of a charging pile after the charging is completed, obtaining a current abnormal fluctuation coefficient according to the current data, and obtaining a fault coefficient according to a connection reliability coefficient, an information interaction coefficient and the current abnormal fluctuation coefficient; and comparing the fault coefficient with a preset fault coefficient threshold value, and judging whether the charging pile breaks down or not according to a comparison result, so that the fault of the charging pile after charging is completed can be evaluated, damage to the charging pile cannot be further aggravated when the charging pile is used for charging an electric vehicle next time, and the charging efficiency of the electric vehicle is improved. And the user safety is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis, and in particular to a method for diagnosing faults of an electric vehicle charging pile. Background Art

[0002] With the continuous advancement of new energy vehicle technology and the enhancement of environmental awareness, the popularity of electric vehicles has increased rapidly. More and more people choose electric vehicles as their main means of transportation. This trend has also promoted the demand and construction of electric vehicle charging piles. Charging piles, as an important supporting facility for electric vehicles, have become more and more common.

[0003] To ensure the reliability and safety of charging piles, fault diagnosis of electric vehicle charging piles has also become key. Generally, charging piles are usually equipped with a self-test function, which can perform a self-test at each startup to check the status of hardware and software, identify and report any abnormalities. Once a fault in the charging pile is identified, an alarm will be issued immediately, and charging will be cut off in time to ensure the safety of electric vehicles and charging piles.

[0004] However, in the above technology, the self-check function of the charging pile generally starts the self-check at the beginning of the charging pile, and lacks a fault assessment of the charging pile after the charging is completed. For example, if the charging pile of the electric car may have failed after the last charging, but because the charging process has been completed, the fault of the charging pile is not discovered in time. When the charging pile is used to charge the electric car next time, the damage to the charging pile may be further aggravated, and may even threaten the safety of the user. Summary of the invention

[0005] The purpose of the present invention is to solve the problem of lack of fault assessment of the charging pile after charging is completed. When the charging pile is used to charge the electric vehicle next time, the damage to the charging pile may be further aggravated, and may even threaten the safety of the user. A fault diagnosis method for an electric vehicle charging pile is proposed.

[0006] The present invention provides a method for diagnosing faults of an electric vehicle charging pile, the method comprising:

[0007] Acquire connection data between the charging gun of the charging pile and the electric vehicle, and obtain a connection unreliability coefficient based on the connection data between the charging gun and the electric vehicle;

[0008] Obtain the last communication status data between the charging pile and the electric vehicle, and obtain the information interaction coefficient according to the last communication status data;

[0009] Obtain the current data of the charging pile after charging is completed, and obtain the current abnormal fluctuation coefficient based on the current data;

[0010] The fault coefficient is obtained according to the connection reliability coefficient, the information interaction coefficient and the current abnormal fluctuation coefficient, and the fault coefficient is compared with the preset fault coefficient threshold value, and whether the charging pile has a fault is determined according to the comparison result.

[0011] Optionally, the connection unreliability coefficient obtained according to the connection data between the charging gun and the electric vehicle includes:

[0012] The connection unreliability coefficient includes a connection times coefficient and a connection instability coefficient. The connection times coefficient is obtained by:

[0013] Obtain the total number of actual connections between the charging gun of the charging pile and the electric vehicle at different times during charging, and mark the total number of actual connections and the preset total number of connections as D respectively. 实 l and D 预 l , l represents the number of moments, l = 1, 2, 3, 4, ..., h, h is a positive integer;

[0014] According to D 实 l and D 预 l The connection times coefficient Fj is obtained, and the calculation formula is:

[0015] Optionally, the method for obtaining the connection instability coefficient is:

[0016] Obtain the time period that the charging gun of the charging pile and the electric vehicle are connected each time during charging, and collect the time periods that each connection lasts to obtain a duration collection;

[0017] Compare each time data in the duration set with a preset minimum threshold, and mark the data corresponding to the time data less than the preset minimum threshold as invalid connection time;

[0018] The connection stability coefficient is calculated based on the total number of data in the duration set and the number of data corresponding to the invalid connection time. The calculation formula is: Wn=ln(m / c+1), where Wn is the connection stability coefficient, m is the number of data corresponding to the invalid connection time, and c is the total number of data in the duration set.

[0019] The connection reliability coefficient is calculated using the following formula: Azs=a1×Fj+a2×Wn; wherein Azs is the connection reliability coefficient, and a1 and a2 represent the preset weight coefficients of the connection number coefficient and the connection instability coefficient.

[0020] Optionally, obtaining the information interaction coefficient according to the last communication state data includes:

[0021] The information interaction coefficient includes a data transmission deviation coefficient and a data transmission success rate coefficient. The method for obtaining the data transmission deviation coefficient is:

[0022] Get the number of data actually transmitted from the electric vehicle to the charging pile background system at different times during the last communication between the charging pile and the electric vehicle, and mark the number of data actually transmitted from the electric vehicle to the charging pile background system as G 实 p , p represents the number of moments, p = 1, 2, 3, 4, ..., n, n is a positive integer;

[0023] G 实 p Within the preset transmission number range [U 少 , U 多 ] are re-marked as E a , a represents the number of data actually transmitted to the charging pile background system G 实 p Within the preset transmission number range [U 少 , U 多 ] is numbered as the number of times outside the range, a=1, 2, 3, 4, ..., v, where v is a positive integer; the data transmission deviation coefficient SD is calculated, and the calculation formula is: SD=ln(v / n+1).

[0024] Optionally, the method for obtaining the data transmission success rate coefficient is:

[0025] Get the number of data stripe packets successfully transmitted by the electric vehicle to the charging pile background system and the number of data stripe packets attempted to be uploaded to the charging pile background system at different times during the last communication between the charging pile and the electric vehicle, and mark them as B respectively. 成 f and B 尝 f , f represents the number of moments, f = 1, 2, 3, 4, ..., g, g is a positive integer;

[0026] According to B 成 f and B 尝 f The data transmission success rate coefficient is obtained, and the calculation formula is:

[0027]

[0028] Where RF is the data transmission success rate coefficient;

[0029] Calculate the information interaction coefficient, the calculation formula is: Wherein, Dax is the information interaction coefficient, and b1 and b2 represent the preset weight coefficients of the data transmission deviation coefficient and the data transmission success rate coefficient.

[0030] Optionally, obtaining the current abnormal fluctuation coefficient according to the current data includes:

[0031] Get the actual current value of the charging pile at different times within a fixed time interval after the charging pile is completed, and calibrate the actual current value as I 实 x , x represents the number of the actual current value of the charging pile at different times within a fixed time interval, x = 1, 2, 3, 4, ..., t, t is the actual current value I obtained 实 x , and t is a positive integer;

[0032] Calculate the actual current value I of the charging pile at different times within a fixed time interval 实 x The standard deviation of is calibrated as Q. The calculation formula of standard deviation Q is:

[0033]

[0034] in, The average value of the actual current value of the STM32 microcontroller at different times within a fixed time interval is obtained as follows:

[0035] By measuring the actual current value I of the charging pile at different times within a fixed time interval 实 x The standard deviation Q of the current is used to obtain the abnormal current fluctuation coefficient Hjg, and the expression obtained is: Hjg=Q.

[0036] Optionally, the fault coefficient obtained according to the connection reliability coefficient, the information interaction coefficient and the current abnormal fluctuation coefficient includes:

[0037] Substituting the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient into the constructed abnormal model, the fault coefficient is obtained, which can be achieved by the following formula:

[0038]

[0039] Where Lgt is the fault coefficient, Azs, Dax and Hjg represent the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient respectively, α, β and γ are the proportional coefficients of the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient respectively, and α, β and γ are all greater than 0.

[0040] Optionally, comparing the fault coefficient with a preset fault coefficient threshold, and judging whether the charging pile fails according to the comparison result includes:

[0041] The fault coefficient is compared with the fault coefficient threshold. When the fault coefficient is not less than the fault coefficient threshold, it indicates that the charging pile has a fault. The charging pile immediately issues an alarm and stops the charging function.

[0042] When the fault coefficient is less than the fault coefficient threshold, it indicates that the charging pile has not failed, the charging function is still in normal use, and the charging pile does not issue an alarm.

[0043] Beneficial effects of the present invention:

[0044] The present invention proposes a fault diagnosis method for an electric vehicle charging pile, which obtains current data of the charging pile after charging is completed, obtains a current abnormal fluctuation coefficient based on the current data, obtains a fault coefficient based on a connection reliability coefficient, an information interaction coefficient and a current abnormal fluctuation coefficient, and compares the fault coefficient with a preset fault coefficient threshold value, and determines whether the charging pile has a fault based on the comparison result. In this way, the fault of the charging pile after charging is completed can be evaluated, so that the next time the charging pile is used to charge the electric vehicle, the damage to the charging pile will not be further aggravated, thereby ensuring the safety of the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] Figure 1 This is a flow chart of the electric vehicle charging pile fault diagnosis method provided by the present invention. DETAILED DESCRIPTION

[0047] 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.

[0048] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0049] The embodiment of the present invention provides a method for diagnosing faults in an electric vehicle charging pile. Figure 1 , Figure 1 A flow chart of a method for diagnosing a fault in an electric vehicle charging pile provided by an embodiment of the present invention. The method comprises the following steps:

[0050] Acquire connection data between the charging gun of the charging pile and the electric vehicle, and obtain a connection unreliability coefficient based on the connection data between the charging gun and the electric vehicle;

[0051] Obtain the last communication status data between the charging pile and the electric vehicle, and obtain the information interaction coefficient according to the last communication status data;

[0052] Obtain the current data of the charging pile after charging is completed, and obtain the current abnormal fluctuation coefficient based on the current data;

[0053] The fault coefficient is obtained according to the connection reliability coefficient, the information interaction coefficient and the current abnormal fluctuation coefficient, and the fault coefficient is compared with the preset fault coefficient threshold value, and whether the charging pile has a fault is determined according to the comparison result.

[0054] Based on the electric vehicle charging pile fault diagnosis method provided by the embodiment of the present invention, the current data of the charging pile after charging is completed is obtained, and the current abnormal fluctuation coefficient is obtained according to the current data, and the fault coefficient is obtained according to the connection reliability coefficient, the information interaction coefficient and the current abnormal fluctuation coefficient. The fault coefficient is compared with a preset fault coefficient threshold, and whether the charging pile has a fault is determined according to the comparison result. In this way, the fault of the charging pile after charging is completed can be evaluated, so that the next time the charging pile is used to charge the electric vehicle, the damage to the charging pile will not be further aggravated, thereby ensuring the safety of the user.

[0055] In one embodiment, obtaining a connection unreliability coefficient according to connection data between the charging gun and the electric vehicle includes:

[0056] The connection unreliability coefficient includes a connection times coefficient and a connection instability coefficient. The connection times coefficient is obtained by:

[0057] Obtain the total number of actual connections between the charging gun of the charging pile and the electric vehicle at different times during charging, and mark the total number of actual connections and the preset total number of connections as D respectively. 实 l and D 预 l , l represents the number of moments, l = 1, 2, 3, 4, ..., h, h is a positive integer;

[0058] According to D 实 l and D 预 l The connection times coefficient Fj is obtained, and the calculation formula is:

[0059] The method for obtaining the connection instability coefficient is:

[0060] Obtain the time period that the charging gun of the charging pile and the electric vehicle are connected each time during charging, and collect the time periods that each connection lasts to obtain a duration collection;

[0061] Compare each time data in the duration set with a preset minimum threshold, and mark the data corresponding to the time data less than the preset minimum threshold as invalid connection time;

[0062] The connection stability coefficient is calculated based on the total number of data in the duration set and the number of data corresponding to the invalid connection time. The calculation formula is: Wn=ln(m / c+1), where Wn is the connection stability coefficient, m is the number of data corresponding to the invalid connection time, and c is the total number of data in the duration set.

[0063] The connection reliability coefficient is calculated using the following formula: Azs=a1×Fj+a2×Wn; wherein Azs is the connection reliability coefficient, and a1 and a2 represent the preset weight coefficients of the connection number coefficient and the connection instability coefficient.

[0064] It should be noted that the actual total number of connections between the charging gun of the charging pile and the electric vehicle can be obtained based on the monitoring system inside the charging pile. In addition, the preset total connection number threshold and the preset minimum threshold are set by professionals based on actual conditions and are not specifically limited.

[0065] It should be noted that the connection unreliability coefficient refers to the total number of successful connections between the charging gun of the charging pile and the electric vehicle and the duration of each successful connection when the charging pile is charging; if the total number of successful connections between the charging gun and the electric vehicle is greater and the duration of each successful connection is shorter, it means that the charging pile has failed. Although the current charging may not be affected, the next time the charging pile is used to charge the electric vehicle, the damage to the charging pile may be further aggravated, and may even threaten the safety of the user. The reasons are:

[0066] Mechanical wear: Frequent connection and disconnection can cause mechanical wear on the charging gun and the electric vehicle interface. The contact points in the interface may become loose or lose elasticity, resulting in poor contact.

[0067] Increased contact resistance: Unstable connections increase the resistance of electrical contacts, causing heating at the connection point, which affects the stability of the connection. Unstable contact resistance may also cause contact arcing, increasing the risk of failure.

[0068] Unstable current and voltage: Frequent connection and disconnection may cause instantaneous changes in current and voltage. This instability will have an impact on the electrical system of the charging pile and even damage the internal components.

[0069] Overheating problem: Unstable electrical contact caused by poor connection will cause overheating, further aggravating the loss of internal components and shortening the service life of the charging pile.

[0070] Communication interruption: Unstable connection during charging will affect the communication between the charging pile and the electric vehicle, which may lead to problems such as charging protocol execution errors and charging data loss.

[0071] Control system abnormality: Unstable connection may cause abnormal operation of the charging pile control system, affecting the normal control and protection functions of the charging process.

[0072] Gradual damage: When the connection is unstable, the internal components of the charging pile will be subjected to continuous mechanical and electrical shocks. This gradual damage may become more obvious during future charging processes, leading to more frequent failures.

[0073] Safety hazards: Unstable connections increase safety hazards such as overheating, short circuits, and arcing, which may lead to serious safety problems such as electrical fires or electric shocks in future use.

[0074] Increased risk: Even if there are no obvious problems during the current charging process, due to the continued loss of the charging pile and the instability of the electrical system, serious failures may occur during the next use, directly threatening the safety of users.

[0075] Charging interruptions: Unstable connections may lead to frequent interruptions in the charging process, affecting the charging status of the electric vehicle and potentially causing safety issues during use.

[0076] Therefore, the high unreliability coefficient of the connection between the charging gun and the electric vehicle means that the charging pile has been connected and disconnected multiple times during the connection process, and the duration after each connection is short, indicating that the charging pile has failed. Although the charging may not be significantly affected, this unstable connection will gradually increase the damage to the charging pile, increase the risk of failure in future use, and pose a threat to user safety.

[0077] In one embodiment, obtaining the information interaction coefficient according to the last communication state data includes:

[0078] The information interaction coefficient includes a data transmission deviation coefficient and a data transmission success rate coefficient. The method for obtaining the data transmission deviation coefficient is:

[0079] Get the number of data actually transmitted from the electric vehicle to the charging pile background system at different times during the last communication between the charging pile and the electric vehicle, and mark the number of data actually transmitted from the electric vehicle to the charging pile background system as G 实 p, p represents the number of moments, p = 1, 2, 3, 4, ..., n, n is a positive integer;

[0080] G 实 p Within the preset transmission number range [U 少 , U 多 ] are re-marked as E a , a represents the number of data actually transmitted to the charging pile background system G 实 p Within the preset transmission number range [U 少 , U 多 ] is a number of the number of times outside the range, a = 1, 2, 3, 4, ..., v, v is a positive integer; calculate the data transmission deviation coefficient SD, the calculation formula is: SD = ln (v / n + 1);

[0081] The method for obtaining the data transmission success rate coefficient is:

[0082] Get the number of data stripe packets successfully transmitted by the electric vehicle to the charging pile background system and the number of data stripe packets attempted to be uploaded to the charging pile background system at different times during the last communication between the charging pile and the electric vehicle, and mark them as B respectively. 成 f and B 尝 f , f represents the number of moments, f = 1, 2, 3, 4, ..., g, g is a positive integer;

[0083] According to B 成 f and B 尝 f The data transmission success rate coefficient is obtained, and the calculation formula is:

[0084]

[0085] Where RF is the data transmission success rate coefficient;

[0086] Calculate the information interaction coefficient, the calculation formula is: Wherein, Dax is the information interaction coefficient, and b1 and b2 represent the preset weight coefficients of the data transmission deviation coefficient and the data transmission success rate coefficient.

[0087] It should be noted that the number of data actually transmitted by the electric vehicle to the charging pile background system and the number of data packets successfully transmitted by the electric vehicle to the charging pile background system can be obtained according to the monitoring system in the charging pile background system, and the number of data packets that the electric vehicle attempts to transmit to the charging pile background system can be obtained through the monitoring system inside the electric vehicle. In addition, the preset transmission number range can be set by professionals according to actual circumstances, and there is no specific limitation.

[0088] It should be noted that the information interaction coefficient refers to the error degree of data transmission and the degree of data transmission success when the electric vehicle data is transmitted to the charging pile background system during the last communication between the charging pile and the electric vehicle. If the error degree of data transmission is greater and the degree of data transmission success is smaller, it means that the charging pile has failed. Although the current charging may not be affected, the next time the charging pile is used to charge the electric vehicle, it may further aggravate the damage to the charging pile and may even threaten the safety of the user. The reasons are:

[0089] Communication module problem: Data transmission errors and low success rate indicate that the communication module of the charging pile may have hardware failure or interference problems, which may cause unstable communication and affect the control and monitoring of the charging process.

[0090] Electrical failure risk: Data transmission errors and low success rates may also be manifestations of electrical system problems, such as unstable power supply, poor contact, etc. These problems may further affect the normal operation of the charging pile.

[0091] Further damage to the charging pile: If data transmission problems already exist during the current charging process, these problems may gradually worsen, leading to accelerated aging or damage to the internal components of the charging pile.

[0092] Potential failures: Frequent data transmission errors may increase the risk of failure within the charging station, leading to more serious problems during future charging processes.

[0093] Unstable charging: Data transmission errors and low success rate may cause the control instructions during the charging process to fail to execute correctly, affecting the stability and safety of charging.

[0094] Electrical safety hazards: Unstable communications may cause overheating, short circuits or other electrical problems during charging, increasing user safety risks.

[0095] Therefore, a high degree of data transmission errors and a low degree of data transmission success are important signs of problems in the charging pile communication system, indicating that the charging pile has failed. Although the charging process may not be significantly affected, these problems will gradually worsen, further exacerbating the damage to the charging pile and increasing the risk of failures and safety hazards during future charging processes.

[0096] In one embodiment, obtaining the current abnormal fluctuation coefficient according to the current data includes:

[0097] Get the actual current value of the charging pile at different times within a fixed time interval after the charging pile is completed, and calibrate the actual current value as I 实 x , x represents the number of the actual current value of the charging pile at different times within a fixed time interval, x = 1, 2, 3, 4, ..., t, t is the actual current value I obtained 实 x , and t is a positive integer;

[0098] Calculate the actual current value I of the charging pile at different times within a fixed time interval 实 x The standard deviation of is calibrated as Q. The calculation formula of standard deviation Q is:

[0099]

[0100] in, The average value of the actual current value of the STM32 microcontroller at different times within a fixed time interval is obtained as follows:

[0101] By measuring the actual current value I of the charging pile at different times within a fixed time interval 实 x The standard deviation Q of the current is used to obtain the abnormal current fluctuation coefficient Hjg, and the expression obtained is: Hjg=Q.

[0102] It should be noted that the actual current value of the charging pile at different times can be obtained according to the monitoring system inside the charging pile;

[0103] It should be noted that the current abnormal fluctuation coefficient refers to the degree of current fluctuation of the charging pile within a fixed time interval after the charging of the charging pile is completed. If the current fluctuation is greater, it means that the charging pile has failed. Although the current charging may not be affected, the next time the charging pile is used to charge the electric vehicle, it may further aggravate the damage to the charging pile and may even threaten the safety of the user. The reasons are:

[0104] Aging or damage to circuit components: Large current fluctuations may be a sign of aging or damage to circuit components, such as capacitors, transformers, or inductors, which have degraded performance and are unable to stabilize the current.

[0105] Unstable power supply: Large current fluctuations may also be caused by unstable power supply, such as voltage fluctuations or insufficient power supply. These problems will have a negative impact on the normal operation of the charging pile.

[0106] Accelerated wear of internal components: Current fluctuations will cause the internal components of the charging pile to operate in an unstable electrical environment, accelerating their wear and aging.

[0107] Potential failures increase: Current fluctuations may cause components to gradually damage, forming potential failure hazards. Although the current charging process may not be significantly affected, these hazards will become more obvious in future use.

[0108] Overheating and arcing: Current fluctuations can cause overheating of internal components of the charging pile and even arcing. These phenomena can not only damage the charging pile, but may also cause safety accidents such as electrical fires.

[0109] Short circuit and electric shock: Unstable current increases the risk of short circuit and electric shock, posing a threat to user safety.

[0110] Therefore, large current fluctuations indicate that there are problems such as poor electrical contact, aging components or unstable power supply inside the charging pile, which means that the charging pile has failed. Although the charging process may not be significantly affected this time, these problems will gradually intensify, leading to accelerated wear of the internal components of the charging pile and potential hidden dangers of failure, increasing the risk of failure in future use and user safety threats.

[0111] In one embodiment, the fault coefficient obtained according to the connection reliability coefficient, the information interaction coefficient and the current abnormal fluctuation coefficient includes:

[0112] Substituting the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient into the constructed abnormal model, the fault coefficient is obtained, which can be achieved by the following formula:

[0113]

[0114] Where Lgt is the fault coefficient, Azs, Dax and Hjg represent the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient respectively, α, β and γ are the proportional coefficients of the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient respectively, and α, β and γ are all greater than 0.

[0115] In one embodiment, comparing the fault coefficient with a preset fault coefficient threshold, and judging whether the charging pile fails according to the comparison result includes:

[0116] The fault coefficient is compared with the fault coefficient threshold. When the fault coefficient is not less than the fault coefficient threshold, it indicates that the charging pile has a fault. The charging pile immediately issues an alarm and stops the charging function.

[0117] When the fault coefficient is less than the fault coefficient threshold, it indicates that the charging pile has not failed, the charging function is still in normal use, and the charging pile does not issue an alarm.

[0118] It should be noted that when the fault coefficient is not less than the fault coefficient threshold, it means that the charging pile has a fault. Although the charging process may not be significantly affected, these problems will gradually worsen, further aggravating the damage to the charging pile and increasing the risk of failures and safety hazards in future charging processes. It is very likely that the next time the charging pile is used to charge the electric vehicle, the damage to the charging pile will be further aggravated, and it may even threaten the safety of the user. Therefore, the charging pile can be determined to have a fault, and an alarm will be issued and the charging function will be stopped.

[0119] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for diagnosing faults in an electric vehicle charging pile, characterized in that: The following steps are involved: Acquire connection data between the charging gun of the charging pile and the electric vehicle, and obtain a connection unreliability coefficient based on the connection data between the charging gun and the electric vehicle; Obtain the last communication status data between the charging pile and the electric vehicle, and obtain the information interaction coefficient according to the last communication status data; Obtain the current data of the charging pile after charging is completed, and obtain the current abnormal fluctuation coefficient based on the current data; The fault coefficient is obtained according to the connection reliability coefficient, the information interaction coefficient and the current abnormal fluctuation coefficient, and the fault coefficient is compared with the preset fault coefficient threshold value, and whether the charging pile has a fault is determined according to the comparison result.

2. The electric vehicle charging pile fault diagnosis method according to claim 1, characterized in that: The connection unreliability coefficients obtained based on the connection data of the charging gun and the electric vehicle include: The connection unreliability coefficient includes a connection times coefficient and a connection instability coefficient. The connection times coefficient is obtained by: Obtain the total number of actual connections between the charging gun of the charging pile and the electric vehicle at different times during charging, and mark the total number of actual connections and the preset total number of connections as D respectively. 实 l and D 预 l , l represents the number of moments, l = 1, 2, 3, 4, ..., h, h is a positive integer; According to D 实 l and D 预 l The connection times coefficient Fj is obtained, and the calculation formula is:

3. The electric vehicle charging pile fault diagnosis method according to claim 2, characterized in that: The method for obtaining the connection instability coefficient is: Obtain the time period that the charging gun of the charging pile and the electric vehicle are connected each time during charging, and collect the time periods that each connection lasts to obtain a duration collection; Compare each time data in the duration set with a preset minimum threshold, and mark the data corresponding to the time data less than the preset minimum threshold as invalid connection time; The connection stability coefficient is calculated based on the total number of data in the duration set and the number of data corresponding to the invalid connection time. The calculation formula is: Wn=ln(m / c+1), where Wn is the connection stability coefficient, m is the number of data corresponding to the invalid connection time, and c is the total number of data in the duration set. The connection reliability coefficient is calculated using the following formula: Azs=a1×Fj+a2×Wn; wherein Azs is the connection reliability coefficient, and a1 and a2 represent the preset weight coefficients of the connection number coefficient and the connection instability coefficient.

4. The electric vehicle charging pile fault diagnosis method according to claim 1, characterized in that: The information interaction coefficients obtained based on the last communication status data include: The information interaction coefficient includes a data transmission deviation coefficient and a data transmission success rate coefficient. The method for obtaining the data transmission deviation coefficient is: Get the number of data actually transmitted from the electric vehicle to the charging pile background system at different times during the last communication between the charging pile and the electric vehicle, and mark the number of data actually transmitted from the electric vehicle to the charging pile background system as G 实 p , p represents the number of moments, p = 1, 2, 3, 4, ..., n, n is a positive integer; G 实 p Within the preset transmission number range [U 少 , U 多 ] are re-marked as E a , a represents the number of data actually transmitted to the charging pile background system G 实 p Within the preset transmission number range [U 少 , U 多 ] is numbered as the number of times outside the range, a=1, 2, 3, 4, ..., v, where v is a positive integer; the data transmission deviation coefficient SD is calculated, and the calculation formula is: SD=ln(v / n+1).

5. The electric vehicle charging pile fault diagnosis method according to claim 4, characterized in that: The method for obtaining the data transmission success rate coefficient is: Get the number of data stripe packets successfully transmitted by the electric vehicle to the charging pile background system and the number of data stripe packets attempted to be uploaded to the charging pile background system at different times during the last communication between the charging pile and the electric vehicle, and mark them as B respectively. 成 f and B 尝 f , f represents the number of moments, f = 1, 2, 3, 4, ..., g, g is a positive integer; According to B 成 f and B 尝 f The data transmission success rate coefficient is obtained, and the calculation formula is: Where RF is the data transmission success rate coefficient; Calculate the information interaction coefficient, the calculation formula is: Wherein, Dax is the information interaction coefficient, and b1 and b2 represent the preset weight coefficients of the data transmission deviation coefficient and the data transmission success rate coefficient.

6. The electric vehicle charging pile fault diagnosis method according to claim 1, characterized in that: The current abnormal fluctuation coefficient obtained according to the current data includes: Get the actual current value of the charging pile at different times within a fixed time interval after the charging pile is completed, and calibrate the actual current value as I 实 x , x represents the number of the actual current value of the charging pile at different times within a fixed time interval, x = 1, 2, 3, 4, ..., t, t is the actual current value I obtained 实 x , and t is a positive integer; Calculate the actual current value I of the charging pile at different times within a fixed time interval 实 x The standard deviation of is calibrated as Q. The calculation formula of standard deviation Q is: in, The average value of the actual current value of the STM32 microcontroller at different times within a fixed time interval is obtained as follows: By measuring the actual current value I of the charging pile at different times within a fixed time interval 实 x The standard deviation Q of the current is obtained, and the abnormal fluctuation coefficient Hjg of the current is obtained. The expression obtained is: Hjg=Q.

7. The electric vehicle charging pile fault diagnosis method according to claim 1, characterized in that: The fault coefficients obtained based on the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient include: Substituting the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient into the constructed abnormal model, the fault coefficient is obtained, which can be achieved by the following formula: Where Lgt is the fault coefficient, Azs, Dax and Hjg represent the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient respectively, α, β and γ are the proportional coefficients of the connection reliability coefficient, information interaction coefficient and current abnormal fluctuation coefficient respectively, and α, β and γ are all greater than 0.

8. The electric vehicle charging pile fault diagnosis method according to claim 1, characterized in that: Comparing the fault coefficient with the preset fault coefficient threshold, and judging whether the charging pile has a fault according to the comparison result includes: The fault coefficient is compared with the fault coefficient threshold. When the fault coefficient is not less than the fault coefficient threshold, it indicates that the charging pile has a fault. The charging pile immediately issues an alarm and stops the charging function. When the fault coefficient is less than the fault coefficient threshold, it indicates that the charging pile has not failed, the charging function is still in normal use, and the charging pile does not issue an alarm.

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