CN-121973667-A - Method, system, equipment, medium and product for detecting faults of charging pile group

Abstract

The invention relates to the technical field of automobile charging piles and discloses a method, a system, equipment, a medium and a product for detecting faults of a charging pile group, wherein the method comprises the steps of acquiring charging behavior data of a target charging pile group and a preset normal charging behavior habit model, and judging whether the target charging pile group has abnormal charging; after the charging abnormality of the target charging pile group is judged, each charging pile of the electric vehicle is connected into the target charging pile group, a plurality of random numbers are generated through the random number disturbance request in response to the random number disturbance request, the charging output parameters of the charging piles are adjusted according to the random numbers, the charging state data of the electric vehicle in the charging stage corresponding to the charging output parameters after each adjustment is obtained, and the fault condition of each charging pile is determined according to the charging output parameters after each adjustment and the charging state data, so that the timeliness of fault detection can be ensured, and meanwhile, the fault detection cost and the efficiency are balanced.

Inventors

• LIN DAIWEI
• BAI HAO
• LI WEI
• PENG JIANRONG
• LU ZHIXIN
• LIANG ZHIJIANG
• ZHONG WENZHENG
• LIANG ZIWEI
• LIU XIAN
• FENG ZHANHAO
• CHEN CONG
• LIANG JIANXIANG
• Li kangquan
• LI HAOCHENG
• YANG ZHICHENG
• GUO GUOWEI
• ZHENG CHUTAO
• CHEN FAWEN
• Xi Zeli
• Wei ben
• HE SHAN

Assignees

• 广东电网有限责任公司佛山供电局

Dates

Publication Date

20260505

Application Date

20260407

Claims (10)

1. 1. The method for detecting the fault of the charging pile group is characterized by comprising the following steps of: Acquiring charging behavior data of a plurality of electric vehicles accessed by a target charging pile group in a current detection period, and judging whether the target charging pile group has abnormal charging according to the charging behavior data and a preset normal charging behavior habit model; After judging that the target charging pile group has abnormal charging, responding to a random number disturbance request for each charging pile connected with an electric automobile in the target charging pile group, generating a plurality of random numbers through the random number disturbance request, and adjusting charging output parameters of the charging piles according to each random number; and acquiring charging state data of the electric vehicle in a charging stage corresponding to the charging output parameters after each adjustment, and determining the fault condition of each charging pile according to the charging output parameters after each adjustment and the charging state data.
2. 2. The method for detecting the faults of the charging pile group according to claim 1, wherein the normal charging behavior habit model comprises a first charging behavior habit model and a second charging behavior habit model, the first charging behavior habit model is a two-dimensional normal distribution model constructed based on a probability density function of charging time and the battery residual quantity SOC, and the second charging behavior habit model is a two-dimensional normal distribution model constructed based on a probability density function of charging power and a charging time period.
3. 3. The method for detecting a fault in a charging pile group according to claim 2, wherein the charging behavior data includes a charging time, a charging power, a charging time period, and a remaining battery power SOC at the start of charging, which are required for a single full charge of the electric vehicle; judging whether the target charging pile group has abnormal charging according to the charging behavior data and a preset normal charging behavior habit model, including: Inputting the charging time required by the single full charge and the battery residual quantity SOC at the beginning of charging into the first charging behavior habit model to obtain a first probability density value; Judging whether the target charging pile group has abnormal charging or not according to the first probability density value and the second probability density value: And if the first probability density value is lower than a preset first threshold value and/or the second probability density value is lower than a preset second threshold value, judging that the target charging pile group has abnormal charging.
4. 4. The method for detecting a fault in a charging pile group according to claim 1, wherein the charging output parameters include an output supply voltage and an output supply current; the generating a plurality of random numbers through the random number disturbance request, and adjusting the charging output parameters of the charging pile according to each random number, includes: Generating a plurality of random numbers according to a preset time interval through a random number generation module arranged in the charging pile; And according to each random number, searching a preset voltage gear and a preset current gear corresponding to the random number in a preset random number mapping table, and adjusting the output power supply voltage and the output power supply current of the charging pile according to the preset voltage gear and the preset current gear, wherein the preset random number mapping table comprises a plurality of random numbers and the mapping relation between the preset voltage gear and the preset current gear corresponding to the random numbers, the voltage difference value between the preset voltage gears corresponding to any two random numbers is not smaller than a preset voltage threshold, and the current difference value between the preset current gears corresponding to any two random numbers is not smaller than a preset current threshold.
5. 5. The method of claim 4, wherein the charging state data includes a remaining time required for a current expected full charge and a current temperature of the battery, and wherein determining the fault condition of each charging pile based on each adjusted charging output parameter and the charging state data comprises: According to the charging output parameters after each adjustment, determining the charging voltage change trend and the charging current change trend of the charging pile; respectively determining a charging efficiency change trend of the charging pile and a current temperature change trend of the battery according to the current expected full charge required residual time and the current temperature of the battery corresponding to the charging output parameters after each adjustment; Comparing the consistency of the charging efficiency change trend with the charging voltage change trend, and if the charging efficiency change trend is not consistent with the charging voltage change trend, judging that the charging pile has faults; and comparing the consistency of the current temperature change trend of the battery with the charging current change trend, and judging that the charging pile has faults if judging that the current temperature change trend of the battery is inconsistent with the charging current change trend.
6. 6. The charging pile group fault detection method according to claim 1, further comprising: acquiring charging power of each electric automobile accessed by the target charging pile group in the current detection period and battery residual quantity SOC when charging is started; determining a plurality of target electric vehicles according to the charging power of each electric vehicle and the battery residual capacity SOC when charging is started, wherein the difference between the charging powers of any two target electric vehicles is smaller than a preset power difference threshold value, and the difference between the battery residual capacities SOC when charging is started is smaller than a preset SOC difference threshold value; acquiring charging state data of each target electric automobile, wherein the charging state data comprises time required by single full charge and current temperature of a battery; Normalizing the time required by the single full charge and the current temperature of the battery, and carrying out weighted fusion on the normalized time required by the single full charge and the normalized current temperature of the battery to generate a comprehensive state score; Taking every two target electric vehicles in all the target electric vehicles as a group of comparison groups, and calculating the difference value between the comprehensive state scores of the two target electric vehicles in each comparison group to be used as the comprehensive state score difference value of the comparison groups; Sorting the comparison groups in a descending order according to the magnitude relation of the comprehensive state grading difference values, and taking charging piles corresponding to the comparison groups with preset groups before sorting as suspected fault charging piles; And acquiring the comprehensive state scoring difference value of each suspected fault charging pile and other charging piles, and judging that the suspected fault charging pile is the suspected fault charging pile if the comprehensive state scoring difference values of the suspected fault charging pile and at least two other charging piles exceed a preset scoring difference threshold.
7. 7. A charging pile group fault detection system, characterized by comprising: The charging abnormality judging module is used for acquiring charging behavior data of a plurality of electric vehicles accessed by a target charging pile group in a current detection period and judging whether the target charging pile group has charging abnormality or not according to the charging behavior data and a preset normal charging behavior habit model; The charging parameter adjustment module is used for responding to a random number disturbance request to generate a plurality of random numbers according to each charging pile of the electric automobile connected into the target charging pile group after judging that the target charging pile group has the abnormal charging, and adjusting the charging output parameters of the charging piles according to each random number; the fault detection module is used for acquiring the charging state data of the electric vehicle in the charging stage corresponding to the charging output parameters after each adjustment, and determining the fault condition of each charging pile according to the charging output parameters after each adjustment and the charging state data.
8. 8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the method for detecting a fault in a charging pile group according to any one of claims 1-6.
9. 9. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed implements the steps of the charging pile group fault detection method according to any one of claims 1-6.
10. 10. A computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, wherein the program instructions, when executed by a computer, cause the computer to perform the steps of the charging pile group fault detection method according to any one of claims 1-6.

Description

Method, system, equipment, medium and product for detecting faults of charging pile group Technical Field The invention relates to the technical field of automobile charging piles, in particular to a method, a system, equipment, a medium and a product for detecting faults of a charging pile group. Background The number of charging pile groups managed by a market body (such as an enterprise) is often huge, and at present, the manual inspection mode is adopted for the fault inspection of the charging pile groups, but the manual inspection efficiency is low, and the existing fault detection of the charging piles is often carried out on single charging piles, and although some fault detection is carried out on the charging pile groups, the fault detection is often carried out at high frequency and independently, so that the cost of the fault detection is high. For example, chinese patent application CN121142201a requires visual data acquisition of the charging posts with respect to each other to monitor the cable docking operation of each charging post prior to charging the vehicle. According to the fault detection method, in order to ensure that faults can be detected in real time, whether the current vehicle is charged or not, high-frequency visual data acquisition is needed, so that the fault detection cost is high. In addition, the existing fault detection of the charging pile group usually only actively carries out fault detection, the active detection means that detection instructions and active data acquisition are required to be actively sent out, the maintenance cost of a detection platform is higher, and the charging pile fault is difficult to discover timely. Disclosure of Invention In view of the above, the present invention provides a method, a system, a device, a medium and a product for detecting a fault of a charging pile group. The first aspect of the invention provides a method for detecting faults of a charging pile group, which comprises the following steps: Acquiring charging behavior data of a plurality of electric vehicles accessed by a target charging pile group in a current detection period, and judging whether the target charging pile group has abnormal charging according to the charging behavior data and a preset normal charging behavior habit model; After judging that the target charging pile group has abnormal charging, responding to a random number disturbance request for each charging pile connected with an electric automobile in the target charging pile group, generating a plurality of random numbers through the random number disturbance request, and adjusting charging output parameters of the charging piles according to each random number; and acquiring charging state data of the electric vehicle in a charging stage corresponding to the charging output parameters after each adjustment, and determining the fault condition of each charging pile according to the charging output parameters after each adjustment and the charging state data. In one embodiment, the normal charging behavior habit model comprises a first charging behavior habit model and a second charging behavior habit model, wherein the first charging behavior habit model is a two-dimensional normal distribution model constructed based on a probability density function of charging time and battery residual quantity SOC, and the second charging behavior habit model is a two-dimensional normal distribution model constructed based on a probability density function of charging power and a period in which charging is performed. In one embodiment, the charging behavior data includes a charging time, a charging power, a charging time period, and a battery remaining capacity SOC when charging is started, which are required for a single full charge of the electric vehicle; judging whether the target charging pile group has abnormal charging according to the charging behavior data and a preset normal charging behavior habit model, including: Inputting the charging time required by the single full charge and the battery residual quantity SOC at the beginning of charging into the first charging behavior habit model to obtain a first probability density value; Judging whether the target charging pile group has abnormal charging or not according to the first probability density value and the second probability density value: And if the first probability density value is lower than a preset first threshold value and/or the second probability density value is lower than a preset second threshold value, judging that the target charging pile group has abnormal charging. In one embodiment, the charging output parameters include an output supply voltage and an output supply current; the generating a plurality of random numbers through the random number disturbance request, and adjusting the charging output parameters of the charging pile according to each random number, includes: Generating a plurality of random numbers according to a pre