Abnormality diagnosis method for electric vehicle, vehicle, and storage medium

Abstract

The application discloses a charging abnormality diagnosis method of an electric vehicle, a vehicle and a computer readable storage medium. The charging abnormality diagnosis method of the electric vehicle comprises the following steps: according to a preset current table, a table lookup current at a current temperature of a target vehicle is inquired; according to a body restraint condition of the target vehicle, data processing is performed on the table lookup current, and a charging request current is obtained; an input current of a charging pile of the target vehicle is acquired; and according to the table lookup current, the charging request current and the input current of the charging pile, charging abnormality diagnosis information is generated, so that the abnormal conditions of a charging process of the target vehicle are diagnosed according to the charging abnormality information. The method effectively automatically divides the charging abnormality conditions of the vehicle through the table lookup current, the charging request current and the input current of the charging pile.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of electric vehicles, and particularly relates to a charging abnormality diagnosis method for an electric vehicle, a vehicle, and a storage medium. BACKGROUND

[0002] In related technologies, the charging abnormality detection of the charging process of an electric vehicle is usually performed by manually detecting the vehicle with charging abnormality. However, this is time-consuming and laborious, and affects the user experience. Therefore, how to automatically diagnose the abnormal reasons of the charging process of an electric vehicle has become a problem to be solved. SUMMARY

[0003] The application provides a charging abnormality diagnosis method for an electric vehicle, a vehicle, and a computer readable storage medium.

[0004] The application provides a charging abnormality diagnosis method for an electric vehicle, which comprises the following steps.

[0005] According to a preset current table, a table lookup current at a current temperature of a target vehicle is queried;

[0006] According to a body constraint condition of the target vehicle, data processing is performed on the table lookup current to obtain a charging request current;

[0007] An input current of a charging pile of the target vehicle is obtained;

[0008] According to the table lookup current, the charging request current, and the input current of the charging pile, charging abnormality diagnosis information is generated to diagnose an abnormal condition of the charging process of the target vehicle according to the charging abnormality information.

[0009] The application can judge specific abnormal conditions in the charging process of a target vehicle according to various current values in the target vehicle. Specifically, the method can query a table lookup current at a current temperature according to a preset current table. The preset current table includes a standard charging current of a vehicle corresponding to each temperature. Limited by a body constraint condition of the target vehicle, when the table lookup current is connected to the target vehicle as a charging current, the current obtained by the target vehicle is a charging request current. The charging request current can represent the current actually required by the current vehicle during charging. The method further obtains an input current of a charging pile of the target vehicle used for actual charging, and diagnoses an abnormal condition in the charging process of the current target vehicle according to the numerical relationship among the table lookup current, the charging request current, and the input current of the charging pile, thereby outputting charging abnormality information representing the diagnosis result. Through this method, the application provides the table lookup current, the charging request current, and the input current of the charging pile as a measurement standard value for measuring the abnormal condition of the charging process of the vehicle, thereby effectively realizing automatic diagnosis of the charging abnormality of the vehicle.

[0010] In some embodiments, the generating the charging abnormality diagnosis information according to the table lookup current, the charging request current and the charging pile input current comprises:

[0011] In the case that the charging pile input current is less than the charging request current, generating charging pile abnormality information.

[0012] The application can diagnose that the charging pile input current obtained by the vehicle cannot meet the requirement of the charging request current required by the vehicle charging in the case that the charging pile input current is less than the charging request current, and thus the charging abnormality condition is generated. Therefore, the current charging abnormality condition of the vehicle is accurately classified according to the charging pile input current and the charging request current.

[0013] In some embodiments, the generating the charging pile abnormality information in the case that the charging pile input current is less than the charging request current comprises:

[0014] calculating a first integral value of a difference between the charging request current and the charging pile input current within a preset charging time;

[0015] calculating a second integral value of the charging request current within the preset charging time;

[0016] In the case that a ratio of the first integral value to the second integral value is greater than a first threshold value, generating the charging pile abnormality information.

[0017] The application calculates the charging loss caused by the insufficient charging pile input current of the vehicle in the charging process by calculating the first integral value, calculates the charging capacity that should be obtained by the vehicle charging at the charging request current by the second integral value, and determines the proportion of the loss amount to the charging capacity that should be obtained by the ratio of the first integral value to the second integral value, so as to measure whether the charging with the charging pile input current is sufficient to affect the charging state of the vehicle according to the first threshold value, and thus the charging abnormality condition of the vehicle is effectively diagnosed.

[0018] In some embodiments, the generating the charging abnormality diagnosis information according to the table lookup current, the charging request current and the charging pile input current comprises:

[0019] In the case that the charging request current is less than the table lookup current, generating vehicle abnormality information.

[0020] The application can diagnose that the charging request current obtained by the vehicle cannot meet the requirement of the table lookup current required by the vehicle theoretically charging in the case that the charging request current is less than the table lookup current, and thus the charging abnormality condition is generated. Therefore, the current charging abnormality condition of the vehicle is accurately classified according to the table lookup current and the charging request current.

[0021] In some embodiments, the generating the vehicle abnormality information in the case that the charging request current is less than the table current includes:

[0022] calculating a third integral value of a difference between the table current and the charging request current within a preset charging time;

[0023] calculating a fourth integral value of the charging request current within the preset charging time;

[0024] generating the vehicle abnormality information in the case that a ratio of the third integral value to the fourth integral value is greater than a second threshold.

[0025] The application calculates the charging loss amount of the vehicle caused by the body constraint condition of the vehicle itself in the charging process by calculating the third integral value, calculates the charging amount that the vehicle should obtain in the table charging by the fourth integral value, and determines the proportion of the loss amount to the charging amount that should be obtained by the ratio of the third integral value to the fourth integral value, so as to measure whether the body constraint condition is sufficient to affect the charging state of the vehicle according to the second threshold, and further effectively diagnose the abnormal charging condition of the vehicle.

[0026] In some embodiments, the method further includes:

[0027] obtaining an ideal current of a target vehicle at an ideal temperature according to the preset current table;

[0028] generating environment abnormality information in the case that the ideal current is greater than the table current.

[0029] The application can diagnose that there is a gap between the table current that the vehicle can obtain at the current temperature and the ideal current that the vehicle obtains at the ideal temperature in the case that the ideal current is greater than the table current. The charging abnormality condition is caused because the charging safety requirement corresponding to the current temperature causes the table current to be lower than the ideal current. Further, accurate classification of the current charging abnormality condition of the vehicle according to the table current and the charging request current is realized.

[0030] In some embodiments, the generating the environment abnormality information in the case that the ideal current is greater than the table current includes:

[0031] calculating a fifth integral value of a difference between the ideal current and the table current within a preset charging time;

[0032] calculating a sixth integral value of the ideal current within the preset charging time;

[0033] generating the environment abnormality information in the case that a ratio of the fifth integral value to the sixth integral value is greater than a third threshold.

[0034] The application calculates the missing amount of charging capacity of the vehicle charging with the table current during the charging process and charging with the ideal current by calculating the fifth integral value, calculates the charging capacity that should be obtained by the vehicle charging with the ideal current at the ideal temperature by the sixth integral value, and determines the proportion of the missing amount in the obtained charging capacity by the ratio of the fifth integral value and the sixth integral value, so as to measure whether the current temperature is sufficient to affect the charging state of the vehicle according to the third threshold, and further effectively diagnose the abnormal charging condition of the vehicle.

[0035] In some embodiments, before the table current at the current temperature of the target vehicle is queried according to the preset current table, the method further comprises:

[0036] obtaining the actual charging time of the vehicle to be detected;

[0037] obtaining the expected value of the charging time of the vehicle to be detected according to a preset database;

[0038] In the case where the actual charging time does not meet the constraint of the expected value of the charging time, the vehicle to be detected is marked as the target vehicle.

[0039] By obtaining the expected value of the charging time of other vehicles of the similar type of the vehicle to be detected and the actual charging time of the vehicle to be detected, whether the charging condition of the vehicle to be detected is abnormal can be judged, and the vehicle to be detected with abnormal charging condition is divided into the target vehicle, so as to further diagnose the abnormal condition of the vehicle.

[0040] In some embodiments, the expected value of the charging progress is obtained according to a preset database, comprising:

[0041] performing clustering analysis on the data in the preset database according to a preset clustering algorithm to obtain a target charging time set;

[0042] performing average value calculation on the target charging time set to obtain the expected value of the charging time.

[0043] By the preset clustering algorithm, the charging time of other vehicles of the similar type of the vehicle to be detected can be clustered and analyzed to obtain a target charging time set corresponding to the vehicle to be detected, and the expected value of the charging time required for the charging of the vehicle to be detected is calculated according to the average value of the target charging time set, so as to divide the charging condition of each vehicle to be detected by the expected value of the charging time, and screen out the target vehicle with abnormal charging from the vehicle to be detected.

[0044] The application also provides a vehicle, comprising:

[0045] a memory, and

[0046] a processor in communication connection with the memory, wherein

[0047] The memory has stored therein instructions, and the processor is capable of executing the instructions stored in the memory to implement the charging abnormality diagnosis method of the electric vehicle according to any one of the preceding embodiments.

[0048] The application further provides a computer readable storage medium, wherein the computer readable storage medium has stored therein computer executable instructions, and the computer is capable of implementing the charging abnormality diagnosis method of the electric vehicle according to any one of the preceding embodiments by executing the computer executable instructions.

[0049] Additional aspects and advantages of embodiments of the present application will be described in the following description and will be apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0050] The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:

[0051] Figure 1 A flowchart of the charging abnormality diagnosis method provided by the embodiments of the present application.

[0052] Figure 2 A certain specific flowchart of the charging abnormality diagnosis method provided by the embodiments of the present application.

[0053] Figure 3 A structural schematic diagram of the vehicle provided by the embodiments of the present application.

[0054] Main element symbol explanation: vehicle 10, processor 11, memory 12. DETAILED DESCRIPTION

[0055] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the embodiments of the present application, and cannot be understood as limiting the embodiments of the present application.

[0056] Please refer to Figure 1 The embodiments of the present application provide a charging abnormality diagnosis method of an electric vehicle, comprising:

[0057] S1, according to a preset current table, querying a table current at a current temperature of a target vehicle.

[0058] S2, data processing is performed on the table current according to a body restraint condition of the target vehicle to obtain a charging request current.

[0059] S3, an input current of a charging pile of the target vehicle is obtained.

[0060] S4, charging abnormality diagnosis information is generated according to the table current, the charging request current and the input current of the charging pile, so as to diagnose abnormal conditions of a charging process of the target vehicle according to the charging abnormality information.

[0061] Referring to Figure 3 The application further provides a vehicle 10 comprising a memory 11 and a processor 12. The charging abnormality diagnosis of the electric vehicle according to the application can be implemented by the vehicle 10 according to the application. Specifically, the memory 11 stores a program, and the processor 12 is configured to execute the program, so as to query a table current at a current temperature of the target vehicle 10 according to a preset current table. The table current can be data processed according to a body restraint condition of the target vehicle 10 to obtain a charging request current. The input current of the charging pile of the target vehicle 10 can also be obtained. The charging abnormality diagnosis information can be generated according to the table current, the charging request current and the input current of the charging pile, so as to diagnose abnormal conditions of a charging process of the target vehicle 10 according to the charging abnormality information. The table current at the current temperature of the target vehicle 10 is queried according to the preset current table. In the application scenario of the user, when the electric vehicle has a charging abnormality during the charging process, the specific abnormality information is often difficult to directly obtain, and the user cannot obtain the relevant test conclusion in the first time, and then the vehicle 10 is adjusted according to the test conclusion. Therefore, according to the method, whether the fault corresponding to the charging abnormality condition exists in the charging pile can be judged according to the input current of the charging pile and the charging request current, or whether the fault corresponding to the charging abnormality exists in the vehicle 10 itself can be judged according to the table current and the charging request current, so that the user can roughly judge the fault reason in the first time, so as to facilitate the user to quickly troubleshoot the charging fault of the vehicle 10 according to the fault reason, and to improve the user experience.

[0062] The application can determine specific abnormal conditions occurring in the charging process of the target vehicle 10 according to various current values in the target vehicle 10. Specifically, the method can query a table current at the current temperature according to a preset current table. The preset current table includes the standard charging current of the vehicle 10 corresponding to each temperature. Limited by the body constraint condition of the target vehicle 10, when the table current is accessed as the charging current to the target vehicle 10, the current obtained by the target vehicle 10 is the charging request current. The charging request current can represent the actual current required to be received by the vehicle 10 during charging. The method further obtains the charging pile input current actually obtained by the target vehicle 10 for actual charging, and diagnoses the abnormal condition in the current charging process of the target vehicle 10 according to the numerical relationship among the table current, the charging request current and the charging pile input current, thereby outputting charging abnormal information representing the diagnosis result.

[0063] In summary, the charging abnormality diagnosis method provided by the application effectively diagnoses the specific charging abnormality reason of the vehicle 10 in the charging abnormality condition by obtaining the charging pile input current in the charging process of the vehicle 10, the table current that should be obtained by the vehicle 10 in the current state, and the charging request current that should be actually obtained according to the influence of the body constraint condition on the table current, and taking this as a standard value for measuring the abnormal condition of the vehicle 10 in the charging process, thereby providing better user experience.

[0064] In some embodiments, S4 comprises:

[0065] In the case that the charging pile input current is less than the charging request current, charging pile abnormal information is generated.

[0066] The processor is configured to generate charging pile abnormal information in the case that the charging pile input current is less than the charging request current.

[0067] Specifically, the method can further refine the abnormal diagnosis result in the charging process of the vehicle by specifically dividing the charging abnormal information. Specifically, in the case that the charging pile input current is less than the charging request current, the method can determine that the power transmission capacity of the current charging pile is insufficient, which causes the charging pile input current to be unable to meet the basic limit of the charging request current required by the vehicle charging, and further causes the charging abnormality of slow charging speed, thereby outputting the charging pile abnormal information to represent the charging pile failure.

[0068] In this way, the application can diagnose that the charging pile input current obtained by the vehicle cannot meet the requirement of the charging request current required by the vehicle charging when the charging pile input current is less than the charging request current, and thus the charging abnormality condition occurs. Therefore, the current charging abnormality condition of the vehicle can be accurately classified according to the charging pile input current and the charging request current.

[0069] In some embodiments, the generating the charging pile abnormal information comprises:

[0070] calculating a first integral value of a difference between the charging request current and the charging pile input current within a preset charging time.

[0071] calculating a second integral value of the charging request current within the preset charging time.

[0072] generating the charging pile abnormal information when a ratio of the first integral value and the second integral value is greater than a first threshold value.

[0073] The processor can calculate a first integral value of a difference between the charging request current and the charging pile input current within a preset charging time. The processor can also calculate a second integral value of the charging request current within the preset charging time. The processor can also generate the charging pile abnormal information when a ratio of the first integral value and the second integral value is greater than a first threshold value.

[0074] Specifically, the method can reduce the misjudgment probability of vehicle charging abnormal diagnosis during vehicle charging according to a preset first threshold value. Specifically, the method first calculates a first integral value of a difference between the charging request current and the charging pile input current within a preset charging time, to represent the actual charging amount lost within the preset charging time. Further, the method calculates a second integral value of the charging request current within the preset charging time, to represent the charging amount that the target vehicle should obtain within the preset charging time. By calculating the ratio of the first integral value and the second integral value, the method can obtain the proportion of the lost charging amount in the charging amount that should be obtained. When the proportion is greater than the first threshold value, the method can determine that the charging pile input amount is insufficient within the preset charging time due to insufficient charging performance of the charging pile, and further generate charging pile abnormal information representing slow charging speed. Further, when the proportion is less than or equal to the first threshold value, the method determines that the lost charging amount is insufficient to cause the charging speed to decrease, and performs other detection to further diagnose the charging process abnormality.

[0075] In some specific embodiments, the method can calculate a first integral value of a difference between the charging request current I BMS请求 and the charging pile input current I 桩输出 within a time period of t0-t1, and calculate a second integral value of I BMS请求 within the time period of t0-t1, and compare a ratio of the first integral value and the second integral value with a first threshold value, when the ratio is greater than the first threshold value, the method can output the charging pile abnormal information. Specifically, the first threshold value can be 25%, or other values, and the value is obtained from engineering experience or confirmed according to user application scenarios.

[0076] Thus, the application calculates the charging loss caused by the insufficient charging pile input current of the vehicle during charging by calculating the first integral value, calculates the charging amount that the vehicle should obtain by charging at the charging request current by the second integral value, and determines the proportion of the loss amount in the charging amount that should be obtained by the ratio of the first integral value to the second integral value, so as to measure whether the charging at the charging pile input current is sufficient to affect the charging state of the vehicle according to the first threshold, and then effectively diagnose the abnormal charging condition of the vehicle.

[0077] In some embodiments, S4 comprises:

[0078] In the case that the charging request current is less than the table current, vehicle abnormal information is generated.

[0079] The processor is configured to generate vehicle abnormal information in the case that the charging request current is less than the table current.

[0080] The method can also refine the abnormal diagnosis result of the vehicle charging process by specifically dividing the charging abnormal information. Specifically, in the case that the charging request current is less than the table current, the method can determine that, at the current temperature, due to the constraint condition of the vehicle itself, the current that the vehicle can obtain cannot meet the charging current marked by the table current, thereby causing the charging abnormality of slow charging, and outputting the vehicle abnormal information to represent that the vehicle itself has a fault.

[0081] Specifically, the vehicle has different vehicle conditions under different driving states, use conditions, etc. According to different vehicle conditions, the body constraint condition of the vehicle changes accordingly, so the charging request current is a variable that changes according to the vehicle condition. The method can further detect whether the vehicle has a fault again after generating the vehicle abnormal information, after a preset detection duration, to improve the fault diagnosis accuracy of the vehicle.

[0082] Thus, the application can diagnose that, in the case that the charging request current is less than the table current, the charging request current obtained by the vehicle cannot meet the requirement of the table current required by the vehicle in theory, and thus the charging abnormality occurs. Thus, the current charging abnormality of the vehicle is accurately classified according to the table current and the charging request current.

[0083] In some embodiments, in the case that the charging request current is less than the table current, generating vehicle abnormal information comprises:

[0084] A third integral value of the difference between the table current and the charging request current within a preset charging time is calculated.

[0085] A fourth integral value of the charging request current within a preset charging time is calculated.

[0086] generate the vehicle abnormality information in a case where the ratio of the third integral value to the fourth integral value is greater than the second threshold value.

[0087] The processor is configured to calculate a third integral value of a difference between the lookup table current and the charging request current within a preset charging time. The processor is also configured to calculate a fourth integral value of the charging request current within the preset charging time. The processor is also configured to generate the vehicle abnormality information in a case where the ratio of the third integral value to the fourth integral value is greater than the second threshold value.

[0088] Specifically, the method can reduce the misjudgment probability of vehicle charging abnormality diagnosis during vehicle charging according to the preset second threshold value. Specifically, the method can calculate a fourth integral value of a difference between the lookup table current and the charging request current within a preset charging time, to represent a charging loss value caused by the body constraint condition of the target vehicle within the preset charging time. Further, the method can calculate a fourth integral value obtained by integrating the lookup table current within the preset charging time, to obtain a charging amount that the target vehicle should obtain according to the lookup table current. By comparing the ratio of the third integral value to the fourth integral value with the second threshold value, it can be detected whether the charging loss value caused by the body constraint condition of the target vehicle is within the acceptable range of the second threshold value. If the ratio of the third integral value to the fourth integral value is greater than the second threshold value, the charging loss caused by the body constraint condition causes the vehicle charging abnormality, and the vehicle abnormality information is output to represent that the target vehicle itself is abnormal.

[0089] Specifically, the method can calculate a third integral value of a difference between the lookup table current I BMS查表 and the charging request current I BMS请求 within a time range from t0 to t1, and calculate a fourth integral value of the charging request current I BMS请求 within the time range from t0 to t1. When the ratio of the third integral value to the fourth integral value is greater than a second threshold value, the method can generate vehicle abnormality information to represent that the target vehicle itself is abnormal. The second threshold value can be 25%, and the specific value can be obtained from engineering experience or set according to user demand.

[0090] In this way, the third integral value is calculated to calculate the charging loss caused by the body constraint condition of the vehicle during the charging process, the fourth integral value is calculated to obtain the charging amount that the vehicle should obtain according to the lookup table charging, and the ratio of the third integral value to the fourth integral value is used to determine the proportion of the loss amount in the charging amount that should be obtained, so as to measure whether the body constraint condition is sufficient to affect the charging state of the vehicle according to the second threshold value, and then effectively diagnose the vehicle charging abnormality condition.

[0091] ​In some embodiments, the charging abnormality information comprises environment abnormality information, the charging abnormality diagnosis information further comprises the environment abnormality information, and the charging abnormality diagnosis method further comprises:

[0092] According to the preset current table, an ideal current of the target vehicle at an ideal temperature is obtained.

[0093] In a case where the ideal current is greater than the table current, environment abnormality information is generated.

[0094] The processor is configured to obtain, according to the preset current table, an ideal current of the target vehicle at an ideal temperature, and to generate, in a case where the ideal current is greater than the table current, environment abnormality information.

[0095] Specifically, the method can further refine the abnormality diagnosis result in the charging process of the vehicle by specifically dividing the charging abnormality information. Specifically, the charging abnormality information can further comprise environment abnormality information. The method can obtain an ideal current corresponding to the charging of the vehicle in the preset current table at an ideal temperature, and in a case where the ideal current is greater than the table current, the method can determine that, due to the current environmental temperature factor, there is a gap between the table current at which the target vehicle can be safely charged and the ideal current at which the vehicle is charged in an ideal state, and determine that the current environment is not suitable for the charging of the target vehicle, and output environment abnormality information to represent the environmental abnormality.

[0096] In this way, in a case where the ideal current is greater than the table current, the method can diagnose that there is a gap between the table current that can be obtained by the vehicle at the current temperature and the ideal current obtained by the vehicle at the ideal temperature. Due to the charging safety requirement corresponding to the current temperature, the table current is lower than the ideal current, so that the charging abnormality condition is generated. Then, accurate classification of the current charging abnormality condition of the vehicle according to the table current and the charging request current is realized.

[0097] In some embodiments, in a case where the ideal current is greater than the table current, generating the environment abnormality information comprises:

[0098] A fifth integral value of a difference between the ideal current and the table current within a preset charging time is calculated.

[0099] A sixth integral value of the ideal current within the preset charging time is calculated.

[0100] In a case where a ratio of the fifth integral value to the sixth integral value is greater than a third threshold value, the environment abnormality information is generated.

[0101] The processor is configured to calculate a fifth integral value of a difference between the ideal current and the table current within a preset charging time, to calculate a sixth integral value of the ideal current within the preset charging time, and to generate, in a case where a ratio of the fifth integral value to the sixth integral value is greater than a third threshold value, the environment abnormality information.

[0102] Specifically, the method can reduce the misjudgment probability of vehicle charging abnormality diagnosis during vehicle charging according to a preset third threshold. Specifically, the method can calculate a fifth integral value of the difference between the ideal current and the table current within a preset charging time, to represent the charging quantity loss value caused by environmental factors when charging the target vehicle with the table current within the preset charging time. At the same time, a sixth integral value of the ideal current within the preset charging time is calculated to represent the charging quantity that should be obtained when charging the target vehicle with the ideal current within the preset charging time. By calculating the ratio of the fifth integral value to the sixth integral value, the method can obtain the proportion of the charging quantity loss value in the charging quantity that should be obtained when charging the target vehicle with the ideal current, and further verify whether the proportion meets the limitation of the third threshold. When the ratio of the fifth integral value to the sixth integral value is greater than the third threshold, the method can determine that environmental factors cause the charging process to be abnormal, and output environmental abnormality information to represent that environmental abnormalities cause charging abnormalities.

[0103] Specifically, the method further obtains the current environmental temperature of the vehicle in order to reduce the misjudgment probability of vehicle charging abnormality, and calculates the absolute value of the difference between the environmental temperature and the ideal temperature. When the ratio of the fifth integral value to the sixth integral value is greater than the third threshold, and the absolute value is greater than a temperature threshold, the method outputs environmental abnormality information to improve the judgment accuracy of vehicle charging abnormality. The temperature threshold can be 10°C, determined by engineering experience value, or changed according to user demand.

[0104] Specifically, the method can calculate a fifth integral value of the difference between the ideal current and the table current I BMS查表 within a time range from t0 to t1, and calculate a sixth integral value of the ideal current within the time range from t0 to t1, and compare the ratio of the fifth integral value to the sixth integral value with the third threshold. When is greater than the third threshold, the method can determine that environmental factors cause the vehicle charging abnormality, and output an environmental abnormality signal.

[0105] In this way, the application calculates the charging quantity loss of the vehicle charging with the table current and the ideal current in the charging process by calculating the fifth integral value, and calculates the charging quantity that should be obtained when charging with the ideal current at the ideal temperature by calculating the sixth integral value, and determines the proportion of the loss in the obtained charging quantity by calculating the ratio of the fifth integral value to the sixth integral value, so as to measure whether the current temperature is sufficient to affect the charging state of the vehicle according to the third threshold, and further effectively diagnose the vehicle charging abnormality.

[0106] In some embodiments, before S1, the charging anomaly diagnosis method further comprises:

[0107] An actual charging time of the vehicle to be detected is obtained.

[0108] An expected charging time value of the vehicle to be detected is obtained according to a preset database.

[0109] In a case where the actual charging time does not satisfy a constraint of the expected charging time value, the vehicle to be detected is marked as a target vehicle.

[0110] The processor is configured to obtain the actual charging time of the vehicle to be detected, obtain the expected charging time value of the vehicle to be detected according to the preset database, and mark the vehicle to be detected as the target vehicle in a case where the actual charging time does not satisfy the constraint of the expected charging time value.

[0111] Specifically, the method can also monitor the charging state of all vehicles to be detected that are currently charging through the charging pile in real time, so as to divide the target vehicles in which charging anomalies occur. Specifically, the method can obtain the actual charging time of each vehicle to be detected, and compare the actual charging time with the expected charging time value obtained according to the preset database. In a case where the actual charging time does not satisfy the expected charging time value, the method can mark the part of the vehicles to be detected as the target vehicles, so as to diagnose the charging anomaly state of the target vehicles marked.

[0112] In this way, by obtaining the expected charging time value of other vehicles of a similar type as the vehicle to be detected and the actual charging time of the vehicle to be detected, the method can determine whether the charging state of the vehicle to be detected is abnormal, and then divide the vehicle to be detected in which the charging state is abnormal into the target vehicle, so as to further diagnose the abnormal state of the vehicle.

[0113] In some embodiments, obtaining the expected charging progress value according to the preset database comprises:

[0114] The data in the preset database is analyzed by clustering according to a preset clustering algorithm, to obtain a target charging duration set.

[0115] The target charging duration set is calculated by averaging to obtain the expected charging time value.

[0116] The processor is configured to analyze the data in the preset database by clustering according to a preset clustering algorithm, to obtain a target charging duration set, and calculate the target charging duration set by averaging to obtain the expected charging time value.

[0117] Specifically, the method can further cluster the charging data of vehicles similar to the vehicle to be detected according to a clustering algorithm in advance to identify outlier charging abnormal data, and exclude the charging abnormal data from the preset database to obtain a target charging duration set. Further, the method calculates the charging data of each similar vehicle in the target charging duration set to obtain a charging time expectation value that can limit the actual charging time. The clustering algorithm can be a DBScan (Density-Based Spatial Clustering of Applications with Noise) clustering method, a k-means clustering method, and a hierarchial clustering method, but is not limited thereto.

[0118] In this way, the application can cluster the charging durations of other vehicles similar to the vehicle to be detected by a preset clustering algorithm to obtain a target charging duration set corresponding to the vehicle to be detected, and calculate the average value of the target charging duration set to obtain a charging time expectation value for calibrating the charging time required by the vehicle to be detected, and then divide the charging condition of each vehicle to be detected by the charging time expectation value to screen out target vehicles with charging abnormalities in the vehicle to be detected.

[0119] Please refer to Figure 2 In some specific embodiments, the application provides a specific judgment process according to the actual application scene of vehicle charging abnormal condition diagnosis. Specifically, since the main reason for the charging abnormal phenomenon of the vehicle during charging is the insufficient power transmission capacity of the charging pile, followed by the charging abnormality caused by the vehicle condition change during use of the electric vehicle, and finally the charging abnormality caused by extreme environmental factors. Therefore, the method first compares the ratio of the first integral value to the second integral value with the first threshold value to verify whether the charging abnormal condition is caused by the charging pile. After the first comparison, the ratio of the third integral value to the fourth integral value is compared with the second threshold value to verify whether the charging abnormal condition is caused by the vehicle body constraint condition of the vehicle itself. After the second comparison, the ratio of the fifth integral value to the sixth integral value is compared with the third threshold value to verify whether the charging abnormal condition is caused by the environment. It can be envisaged that the comparison results of the three comparisons do not contradict each other, i.e. the diagnosis result of the charging abnormal condition of the vehicle can be any combination of the charging pile, the electric vehicle, and the environment, but the above comparison order is adopted to improve the efficiency of obtaining the diagnosis result of the charging abnormality of the vehicle by the user.

[0120] Specifically, when the method performs three comparisons, and it is detected that the charging abnormal condition of the vehicle does not belong to any one of the charging pile reason, the electric vehicle reason and the environmental reason, a vehicle configuration abnormal report is output. The vehicle configuration abnormal report can be that the vehicle SOC estimation is insufficient, the vehicle battery cell voltage is insufficient, the vehicle copper bar is abnormal, etc.

[0121] The application provides a computer readable storage medium, and computer executable instructions are stored in the computer readable storage medium. The computer can implement the charging abnormality diagnosis method of the electric vehicle according to any one of the above by executing the computer executable instructions.

[0122] The computer executable instructions stored in the computer readable storage medium provided by the application can be executed by a computer, so as to implement the charging abnormality diagnosis method provided by the application. By executing the charging abnormality diagnosis method, the application can achieve the beneficial effects of the charging abnormality diagnosis method. The specific beneficial effects have been described above, and will not be repeated here.

[0123] In the description of the present specification, the description of the terms "certain embodiments", "in one example", "exemplarily", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0124] Any process or method descriptions in flow charts or otherwise described herein represent embodiments that can be implemented as executable instructions. The computer executable instructions can be in many forms, including, but not limited to, a specially designed machine, a piece of a machine, a program of instructions in source code format, a program of instructions in object code format, or a program of instructions in executable format. When the computer executable instructions are implemented in source code format, an interpreter can be used to execute the instructions. When the computer executable instructions are implemented in object code format, an object code execution machine can be used to execute the instructions. When the computer executable instructions are implemented in executable format, a computer can be used to execute the instructions. The software program can be stored in a computer readable storage medium, such as a hard disk, a compact disk, a random access memory (RAM), a read only memory (ROM), an erasable programmable read only memory (EPROM) or a flash memory, etc.

[0125] Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A method of diagnosing a charging abnormality of an electric vehicle, characterized by, The method comprises the following steps: acquiring an actual charging time of a vehicle to be detected; acquiring a charging time expectation value of the vehicle to be detected according to a preset database; in a case where the actual charging time does not meet a constraint of the charging time expectation value, marking the vehicle to be detected as a target vehicle; inquiring a table lookup current at a current temperature of the target vehicle according to a preset current table; performing data processing on the table lookup current according to a body constraint condition of the target vehicle to obtain a charging request current; acquiring a charging pile input current of the target vehicle; generating charging abnormal information according to the table lookup current, the charging request current and the charging pile input current, so as to diagnose an abnormal condition of a charging process of the target vehicle according to the charging abnormal information.

2. The charge abnormality diagnosing method according to claim 1, characterized by, The step of generating the charging abnormal information according to the table lookup current, the charging request current and the charging pile input current comprises the following steps: in a case where the charging pile input current is less than the charging request current, generating charging pile abnormal information.

3. The charge abnormality diagnosing method according to claim 2, characterized by, The step of generating the charging pile abnormal information in the case where the charging pile input current is less than the charging request current comprises the following steps: calculating a first integral value of a difference between the charging request current and the charging pile input current within a preset charging time; calculating a second integral value of the charging request current within the preset charging time; in a case where a ratio of the first integral value to the second integral value is greater than a first threshold value, generating the charging pile abnormal information.

4. The charge abnormality diagnosing method according to claim 1, characterized by, The step of generating the charging abnormal information according to the table lookup current, the charging request current and the charging pile input current comprises the following steps: in a case where the charging request current is less than the table lookup current, generating vehicle abnormal information.

5. The charge abnormality diagnosing method according to claim 4, characterized by, The step of generating the vehicle abnormal information in the case where the charging request current is less than the table lookup current comprises the following steps: calculating a third integral value of a difference between the table lookup current and the charging request current within a preset charging time; calculating a fourth integral value of the charging request current within the preset charging time; in a case where a ratio of the third integral value to the fourth integral value is greater than a second threshold value, generating the vehicle abnormal information.

6. The charge abnormality diagnosing method according to claim 1, characterized by The method further comprises the following steps: acquiring an ideal current of a target vehicle at an ideal temperature according to the preset current table; in a case where the ideal current is greater than the table lookup current, generating environment abnormal information.

7. The charge abnormality diagnosing method according to claim 6, characterized by, The step of generating the environment abnormal information in the case where the ideal current is greater than the table lookup current comprises the following steps: calculating a fifth integral value of a difference between the ideal current and the table lookup current within a preset charging time; calculating a sixth integral value of the ideal current within the preset charging time; in a case where a ratio of the fifth integral value to the sixth integral value is greater than a third threshold value, generating the environment abnormal information.

8. The charge abnormality diagnosing method according to claim 1, characterized by, The step of acquiring the charging time expectation value of the vehicle to be detected according to the preset database comprises the following steps: performing clustering analysis on data in the preset database according to a preset clustering algorithm to obtain a target charging time length set; performing average value calculation on the target charging time length set to obtain the charging time expectation value.

9. A vehicle characterized by comprising: The method comprises the following steps: a memory, and A processor in communication connection with the memory, wherein The memory has stored instructions, and the processor can execute the instructions stored in the memory to implement the method for diagnosing charging abnormalities of an electric vehicle according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium has stored computer executable instructions, and the computer can implement the method for diagnosing charging abnormalities of an electric vehicle according to any one of claims 1 to 8 by executing the computer executable instructions.

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