CN114954127A - Conduction type direct current quick charging online diagnosis method and system thereof - Google Patents
Conduction type direct current quick charging online diagnosis method and system thereof Download PDFInfo
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- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
- B60L3/12—Recording operating variables ; Monitoring of operating variables
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
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- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
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Abstract
A conduction type direct current quick charging online diagnosis method comprises the following steps: establishing a vehicle-end battery diagnosis fault list, and performing self-defined diagnosis on the vehicle-end charging fault based on the vehicle-end battery diagnosis fault list; the vehicle-end battery diagnosis fault list defines fault codes of charging termination reasons according to a communication protocol and summarizes the fault codes to form a charging termination reason fault summary table; establishing a charging fault remote diagnosis service system, and identifying a vehicle end charging fault based on the charging fault remote diagnosis service system; the charging fault remote diagnosis service system comprises: the system comprises a battery management system, a vehicle-mounted terminal and a big data cloud platform. The establishment of the vehicle-end battery diagnosis fault list provides a basis for the implementation of an online diagnosis method, can assist a user in quickly locking the problem of charging stop faults, and is favorable for adding historical fault codes and charging stop fault reasons caused by corresponding historical faults into the diagnosis fault list by establishing a charging fault remote diagnosis service system so as to perfect diagnosis fault reasons and further search and analyze the diagnosis fault reasons.
Description
Technical Field
The invention belongs to the technical field of automobile direct-current quick charging, and particularly relates to a conductive direct-current quick charging online diagnosis method and a conductive direct-current quick charging online diagnosis system.
Background
Along with the rapid increase of the number of electric automobiles, matched manufacturers of public charging facilities and parts and products thereof are increasingly common, and the fault proportion that the vehicles cannot be charged is higher than that of the whole vehicles due to the problem that the charging piles are operated frequently.
The proportion of the three reasons which lead to the failure of charging of the electric automobile due to the fact that the electric automobile is not in accordance with the standard, the improper operation and maintenance and the irregular construction is 67.5%, and particularly, the proportion is high due to the fact that the direct-current charging pile, the communication protocol consistency and the insulation test are not in accordance with the standard requirements, the mechanical locking buckle of the gun head of the charging pile is broken or damaged to cause the failure of the mechanical lock and the like. Meanwhile, the problems of poor reliability and insufficient safety of functions exist in vehicle pile matching, and the problems include unstable network connection, unstable charging facility functions, failure of key protection functions and the like, so that a new energy electric vehicle owner is subjected to great charging trouble. Because the troubleshooting of the charging fault has certain speciality, the user can only ask for help from car enterprises and matching factories of public charging facilities,
the existing quick-charging troubleshooting scheme is mainly field diagnosis; analyzing real-time message data by using a CAN analysis tool on the site of an engineer; performing fault identification and execution of a maintenance scheme according to the experience of engineering personnel; the cost of analyzing and processing the problem is too high; in order to assist the user to quickly lock the problem of incapability of charging, it is still necessary and urgent to develop and design a conductive dc quick-charging online diagnosis method and system thereof to solve the problem of incapability of charging.
Disclosure of Invention
The invention aims to provide a conductive direct-current quick-charging online diagnosis method and a conductive direct-current quick-charging online diagnosis system, and aims to solve the technical problem of how to assist a user to quickly lock an electric vehicle and prevent the electric vehicle from being charged.
The purpose of the invention and the technical problem to be solved are realized by adopting the following technical scheme.
The invention provides an online diagnosis method for conduction type direct current quick charging, which comprises the following steps: establishing a vehicle-end battery diagnosis fault list, and performing self-defined diagnosis on vehicle-end charging faults on the basis of the vehicle-end battery diagnosis fault list; the vehicle-end battery diagnosis fault list defines fault codes of charging termination reasons according to a communication protocol and summarizes the fault codes to form a charging termination reason fault summary table; establishing a charging fault remote diagnosis service system, and identifying a vehicle end charging fault based on the charging fault remote diagnosis service system; wherein, the charging fault remote diagnosis service system includes: battery management system, vehicle terminal and big data cloud platform, based on charge trouble remote diagnosis service system discernment car end charging fault includes: after a vehicle-end charging fault is identified, actively latching fault message data in a first time period before the charging fault occurs based on the battery management system and sending the fault message data to the vehicle-mounted terminal; analyzing a charging fault diagnosis instruction issued by the big data cloud platform based on a diagnosis module of the vehicle-mounted terminal; determining whether an access environment of a diagnostic function is met and configuring a diagnostic model based on a remote diagnostic service port of the big data cloud platform, wherein the diagnostic function is implemented based on the diagnostic model; and issuing a charging fault diagnosis instruction based on the big data platform, executing remote diagnosis of the charging fault and downloading message data related to the charging fault.
Preferably, before establishing the vehicle-end battery diagnosis fault list, the method further comprises: defining scene diagnosis content of the battery management system, judging charging conditions in real time in a handshake stage, a parameter configuration stage, a charging stage and a charging finishing stage, and judging charging faults.
Preferably, after the vehicle-end battery diagnosis fault list is established, the method further comprises the following steps: and the battery management system pushes the charging fault reason to a user through a display screen of the vehicle terminal and charging application software.
Preferably, the method further includes, after the diagnosis module based on the vehicle-mounted terminal analyzes the charging fault diagnosis instruction issued by the big data cloud platform and before the charging fault diagnosis instruction is sent to the vehicle-mounted terminal: the fault message data is a CAN communication message, and the CAN communication message of the first time period before the latched charging fault occurs is packed, compressed and stored in a memory; and recording the fault code of the vehicle end charging fault in a diagnosis snapshot.
Preferably, the transmitting to the in-vehicle terminal includes: the battery management system supports the diagnosis access session forwarded by the vehicle-mounted terminal and/or sends the fault message data of the first time period before the latching charging fault occurs to the vehicle-mounted terminal in a compressed file form.
Preferably, before the determining whether the access environment of the diagnosis function is met and configuring the diagnosis model based on the remote diagnosis service port of the big data cloud platform, the method further comprises: and sending a charging fault diagnosis instruction which is issued by the big data cloud platform and analyzed by a diagnosis module based on the vehicle-mounted terminal to the battery management system through a diagnosis CAN bus.
Preferably, the analyzing, by the diagnosis module based on the vehicle-mounted terminal, the charging fault diagnosis instruction issued by the big data cloud platform further includes: the vehicle-mounted terminal supports synchronous downloading and uploading of diagnosis data from the big data cloud platform to the big data cloud platform.
In a second aspect of the present invention, a conductive dc fast charging online diagnostic system for implementing the above diagnostic method includes: the system comprises a battery management system, a vehicle-mounted terminal and a big data cloud platform; the battery management system is used for identifying a charging fault at a vehicle end, actively latching fault message data in a first time period before the charging fault occurs and sending the fault message data to the vehicle-mounted terminal; the vehicle-mounted terminal is used for analyzing a charging fault diagnosis instruction issued by the big data cloud platform; the big data cloud platform comprises a remote diagnosis service port and a diagnosis module, wherein the remote diagnosis service port is used for judging whether an access environment of a diagnosis function is met or not and configuring the diagnosis model, and the diagnosis function is implemented based on the diagnosis model; the big data cloud platform is further used for issuing a charging fault diagnosis instruction, executing remote diagnosis of the charging fault and downloading message data related to the charging fault.
Preferably, the battery management system is further configured to: packaging and compressing the latched CAN communication message in the first time period before the charging fault occurs, and storing the packaged CAN communication message in a memory; recording a fault code of the vehicle end charging fault in a diagnosis snapshot; and supporting the diagnosis access session forwarded by the vehicle-mounted terminal and/or sending the fault message data of the first time period before the latch charging fault occurs to the vehicle-mounted terminal in a compressed file form.
Preferably, the vehicle-mounted terminal is further configured to: a charging fault diagnosis instruction sent by the big data cloud platform analyzed by a diagnosis module based on the vehicle-mounted terminal is sent to the battery management system through a diagnosis CAN bus; and downloading and uploading the synchronization of the diagnostic data from the big data cloud platform to the big data cloud platform.
A third aspect of the present invention provides an electronic device, including: a memory to store processor non-transitory readable instructions; and the processor is used for reading the readable instructions from the memory, so that the readable instructions are executed by the processor to realize the conductive direct current quick charging online diagnosis method.
A fourth aspect of the present invention provides a readable storage medium, which includes executable instructions, when the executable instructions are executed on a device, the device is caused to perform the online diagnosis method for conductive direct current fast charging as described above.
Compared with the prior art, the invention has obvious advantages and beneficial effects. By the technical scheme, the invention at least has one of the following advantages and beneficial effects:
the invention provides an on-line diagnosis method for conduction type direct current quick charging, which is characterized in that a vehicle-end battery diagnosis fault list is established, and self-defined diagnosis of vehicle-end charging faults is carried out on the basis of the vehicle-end battery diagnosis fault list; the vehicle-end battery diagnosis fault list defines fault codes of charging termination reasons according to a communication protocol and summarizes the fault codes to form a charging stop reason fault summary table so as to define and summarize charging stop fault reasons in the conductive direct-current quick-charging online diagnosis, provide basis for the implementation of an online diagnosis method and assist a user in quickly locking charging stop faults.
Secondly, the invention provides an on-line diagnosis method of conduction type direct current quick charging, which is characterized in that a charging fault remote diagnosis service system is established, and a vehicle end charging fault is identified based on the charging fault remote diagnosis service system; wherein, the charging fault remote diagnosis service system includes: battery management system, vehicle terminal and big data cloud platform, based on charge trouble remote diagnosis service system discernment car end charging fault includes: after a vehicle-end charging fault is identified, actively latching fault message data in a first time period before the charging fault occurs based on the battery management system and sending the fault message data to the vehicle-mounted terminal; analyzing a charging fault diagnosis instruction issued by the big data cloud platform based on a diagnosis module of the vehicle-mounted terminal; determining whether an access environment of a diagnostic function is met and configuring a diagnostic model based on a remote diagnostic service port of the big data cloud platform, wherein the diagnostic function is implemented based on the diagnostic model; and issuing a charging fault diagnosis instruction based on the big data platform, executing remote diagnosis of the charging fault and downloading message data related to the charging fault. By adopting the conductive international direct current quick-charging online diagnosis method, the vehicle-mounted terminal can inquire and analyze the historical fault codes which do not determine the fault occurrence time and need to support the fault code freeze frame, and the historical fault codes and the charging stopping fault reasons caused by the corresponding historical faults are added into a diagnosis fault list, so that the diagnosis fault reasons are perfected, and the diagnosis fault reasons are further retrieved and analyzed.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
FIG. 1 is a schematic flow chart of a conductive DC quick-charging online diagnosis method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a conductive dc quick-charging online diagnosis system according to an embodiment of the present invention;
FIG. 3 is a flow chart of a remote diagnosis method for conductive national standard DC fast charging according to an embodiment of the present invention;
fig. 4 is a flowchart of a method for downloading conductive dc fast-charging remote online diagnostic data according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of the embodiments, structures, features and effects thereof according to the present invention will be made with reference to the accompanying drawings and preferred embodiments.
In an embodiment of the present invention, as shown in fig. 1, the present invention provides an online diagnosis method for conductive dc fast charging, including: and establishing a vehicle-end battery diagnosis fault list, and performing self-defined diagnosis on the vehicle-end charging fault based on the vehicle-end battery diagnosis fault list. The present embodiment will be described by taking a Battery Management System (BMS) as an example of the battery management system data stream (BMS-Fr 12-518). Establishing a vehicle-end battery diagnosis fault list according to a Battery Management System (BMS) charging termination reason and a charging pile charging termination reason defined in a national standard communication protocol flow, and performing self-defined diagnosis of vehicle-end charging faults based on the vehicle-end battery diagnosis fault list, wherein part of charging termination reason fault definition examples and corresponding signal meanings comprise:
the signal meaning corresponding to the battery charging overcurrent information is power storage battery charging overcurrent, and the signal code is 0xC 14;
the signal meaning corresponding to the battery over-temperature information is that the temperature of the power storage battery is too high, and the signal code is 0xC 15;
the signal meaning corresponding to the charger active stop information is that the charger actively stops, and the signal code is 0xDB7(BMS stop charging reason);
the signal meaning corresponding to the SOC target value information is that the required SOC target value is reached, and the signal code is 0xDB7(BMS reason for stopping charging);
the signal meaning corresponding to the cell voltage set value information is that the cell voltage set value is reached, and the signal code is 0xDB7(BMS reason for stopping charging);
the signal meaning corresponding to the total voltage set value information is that the total voltage set value is reached, and the signal code is 0xDB7(BMS reason for stopping charging);
the signal meaning corresponding to the BMS current over-current information is that the current is over-current, and the signal code is 0xDB9 (the reason for the BMS charging interruption error);
the signal meaning corresponding to the voltage difference information is voltage abnormality, and the signal code is 0xDB9(BMS interruption charging error reason);
the signal meaning corresponding to the insulation fault information is insulation fault, and the signal code is 0xDB8 (fast charging insulation fault).
And the vehicle-end battery diagnosis fault list carries out user-defined diagnosis on the vehicle-end charging fault to obtain a fault code corresponding to the reason for stopping charging. The vehicle-end battery diagnosis fault list defines fault codes for terminating charging reasons according to a communication protocol and summarizes the fault codes to form a charging-stopping reason fault summary table, as shown in table 1, when a power storage battery is in charging overcurrent and overcurrent, a signal corresponding to battery charging overcurrent information in a message name is called BV _ Charge _ Over _ Current for short, a signal meaning (power storage battery charging overcurrent, the battery charging overcurrent signal code is 0xC14), a start bit is 15(MSB), a bit length is 2, a byte sequence adopts a high-significant bit (Motorola sequence) located in a low byte, a value type is Unsigned shaping (unnigned), a weighted factor is 1, and a gain value is 0. The table values are respectively: three fault codes, namely, normal 0x0, overcurrent 0x1 and untrusted 0x2, it is obvious that the above fault code 0x0 is normal, and the above fault code 0x1 is an authentic fault code.
Table 1: failure definition example table for charging stop reason
As shown in fig. 1, when a fast charging insulation Fault occurs, a signal corresponding to insulation Fault information in the message name is abbreviated as (Isolation _ Fault), a signal meaning (power battery charging overcurrent, the battery charging overcurrent signal code is 0xC14), a start bit is 31(MSB), a bit length is 2, a high significant bit (Motorola order) in a low byte is adopted in a byte order, a value type is Unsigned, a weighted factor is 1, and a gain value is 0. The table values corresponding to the insulation fault information are respectively: three types of fault codes, normal 0x0, fault 0x1 and untrusted 0x2, also indicate that normal 0x0 and fault 0x1 are also trusted fault codes.
The vehicle-end custom parking and charging reason fault definition diagnosis information comprises: message name, signal abbreviation, signal meaning, start bit (MSB), bit length, byte order, value type, factor, gain, value table, etc. A partial outage cause failure definition is obtained as shown in table 1. In addition, the scene diagnosis content of the battery management system is defined, the charging condition is judged in real time at different stages, and the charging fault is judged. For example, the battery management system needs to determine the charging condition and determine the charging fault in real time in the handshaking phase, the parameter configuration phase, the charging phase and the charging ending phase.
Establishing a charging fault remote diagnosis service system, and identifying a vehicle end charging fault based on the charging fault remote diagnosis service system; wherein, the charging fault remote diagnosis service system includes: as shown in fig. 2, the gateway and the charging pile are in communication connection through the Battery Management System (BMS), the Gateway (GW) and the big data cloud platform (TPS) are in communication connection through the vehicle-mounted Terminal (TBOX), and the server terminal and the big data cloud platform (TPS) are in communication connection.
The step of identifying the vehicle-end charging fault based on the charging fault remote diagnosis service system comprises the following steps: after the Battery Management System (BMS) identifies the charging fault of the vehicle end, the fault message data of a first time period before the charging fault occurs is actively latched based on the Battery Management System (BMS) and is sent to the vehicle-mounted Terminal (TBOX). And in the first time period, the charging fault generates a communication message, and the fault message data is transmitted to the vehicle-mounted Terminal (TBOX) through the communication message. In this embodiment, the first period of time is preferably within 3 min. Of course, those skilled in the art can select the charging fault remote diagnosis service within a reasonable time range according to the instantaneity requirement of the charging fault remote diagnosis service, and the charging fault remote diagnosis service is within the protection scope of the invention. Analyzing a charging fault diagnosis instruction issued by the big data cloud platform based on a diagnosis module of the vehicle-mounted terminal; a diagnosis module is integrated in a vehicle-mounted Terminal (TBOX), the diagnosis module has a diagnosis access function, and the diagnosis module can analyze a charging fault diagnosis instruction issued by a big data cloud platform (TPS). The big data cloud platform is provided with a remote diagnosis service port, the remote diagnosis service port receives data of an access environment of a diagnosis function, whether the access environment of the diagnosis function is met or not is judged based on the remote diagnosis service port of the big data cloud platform, and if the access environment symbol of the diagnosis function is met, the remote diagnosis service port judges the access environment of the diagnosis function; and configuring relevant data of a diagnosis model based on an access environment of a diagnosis function which is met by a remote diagnosis service port of the big data cloud platform, wherein the diagnosis function is implemented based on the diagnosis model. And issuing a charging fault diagnosis instruction based on the big data platform (TPS), wherein the charging fault diagnosis instruction is a charging fault diagnosis instruction containing fault information of at least one charging stop reason in the table 1, so that the vehicle-mounted Terminal (TBOX) executes remote diagnosis of the charging fault through the Gateway (GW) and the Battery Management System (BMS) and downloads message data related to the charging fault.
The series of remote diagnosis access and services such as establishing a Battery Management System (BMS), a vehicle-mounted Terminal (TBOX), a big data cloud platform (TSP) and a service port thereof comprise intelligent diagnosis, data management, model development, diagnosis execution, man-machine interaction and software upgrading of a vehicle end and a cloud end. The remote diagnosis method comprises but is not limited to file issuing, diagnosis result uploading, diagnosis model design and release, buried point signal and trigger rule setting, diagnosis instruction sequence editing, vehicle historical problem editing, vehicle-side diagnosis model execution, cloud-side diagnosis model execution, vehicle-side diagnosis instruction sequence execution, cloud-side historical problem retrieval and analysis, diagnosis result output, fault and diagnosis information prompting, vehicle-side software upgrading and cloud-side software upgrading, and the remote diagnosis access and service of the vehicle side and the cloud side are shown in table 2.
Table 2: remote diagnosis access and service example table
| Service code | Service scope | Type of service | Service information | Service name |
| S-XX-06 | Vehicle end/cloud end | Intelligent diagnostics | Data management | Document distribution |
| S-XX-07 | Vehicle end/cloud end | Intelligent diagnostics | Data management | Uploading diagnostic results |
| S-XX-08 | Cloud terminal | Intelligent diagnostics | Model development | Diagnostic model design publishing |
| S-XX-09 | Cloud | Intelligent diagnostics | Model development | Buried point signal and trigger rule set |
| S-XX-10 | Cloud | Intelligent diagnostics | Model development | Diagnostic instruction sequence editing |
| S-XX-11 | Cloud | Intelligent diagnostics | Model development | Vehicle history question editing |
| S-XX-12 | Vehicle end | Intelligent diagnostics | Diagnostic execution | Vehicle end diagnostic model execution |
| S-XX-13 | Cloud terminal | Intelligent diagnostics | Diagnostic execution | Cloud diagnostic model execution |
| S-XX-14 | Vehicle end | Intelligent diagnostics | Diagnostic execution | Vehicle end execution diagnosis command sequence |
| S-XX-15 | Vehicle end/cloud end | Intelligent diagnostics | Diagnostic execution | Cloud execution of diagnostic instruction sequences |
| S-XX-16 | Cloud | Intelligent diagnostics | Diagnostic execution | Cloud historical problem retrieval analysis |
| S-XX-17 | Cloud | Intelligent diagnostics | Diagnostic execution | Diagnostic result output |
| S-XX-18 | Vehicle end/cloud end | Intelligent diagnostics | Human-computer interaction | Fault and diagnostic information prompting |
| S-XX-19 | Vehicle end/cloud end | Intelligent diagnostics | Software upgrade | Vehicle end software upgrade |
| S-XX-20 | Cloud | Intelligent diagnostics | Software upgrade | Cloud software upgrade |
In addition, the remote diagnostic access and service category includes, but is not limited to, a diagnostic service list for a diagnostic service, a service classification, an identification service ID, a diagnostic service name, a parameter contract, ECU support, mode restriction, security access restriction, default mode, extended mode, programming mode, addressing restriction, and support subfunctions, etc., the diagnostic service list is established based on the ISO-14229-1 standard, and in the parameter contract, the execution of the service is defined as: m: forcing; u: and (4) selecting by a user. Meanwhile, the ECU supports the indication of whether the ECU supports the service, and if the fault code fed back by the ECU is analyzed to obtain "if the ECU supports the service" or "if the ECU does not support the service", the ECU must support the service specified as "M" to further analyze the fault code of the ECU. The details are shown in table 3.
Table 3: diagnostic service class example table
In an embodiment of the present invention, in the conductive dc fast charging online diagnosis method provided by the present invention, before the establishing a vehicle-end battery diagnosis fault list, the method further includes: defining scene diagnosis content of the battery management system, judging charging conditions in real time in a handshake stage, a parameter configuration stage, a charging stage and a charging finishing stage, and judging charging faults. The defining of the battery management system scene diagnosis content comprises the following steps: physical connection confirmation, handshake phase confirmation, parameter configuration phase confirmation, charging phase confirmation and charging end phase confirmation.
And confirming the physical connection before the confirmation in the handshake phase so as to ensure that the physical communication of all the connections is smooth. The physical connection confirmation includes: the physical communication connection state between the charging post, the Battery Management System (BMS), the Gateway (GW), the vehicle Terminal (TBOX), the cloud platform (TSP), and the server terminal connected to the cloud platform (TSP) is confirmed by confirming whether the data stream BMS _ NM _604 (abbreviated as 0X604) and BMS _ Fr09_3E9 (abbreviated as 0X3E9) are connected in the physical connection confirmation. Specifically, a server terminal or a vehicle-mounted Terminal (TBOX) connected to the cloud platform (TSP) sends a fast charge wake-up command (BMS _ WakeUp _ fast charge) through a Battery Management System (BMS) to perform a fast charge a + wake-up function, and when the Battery Management System (BMS) receives communication information (such as 01) returned by a charging pile, the wake-up is successful; otherwise, the wake-up failure indicates the physical connection failure.
The handshake phase acknowledgement includes: the Battery Management System (BMS) is detected and confirmed in a handshaking phase through GBT 27930-. If the ' Rec _0X00_ Overtime & Rec _0xAA _ Overtime ' returned by the vehicle-side Battery Management System (BMS) is received and is 0 ', the fact that the CRM message is received by the Battery Management System (BMS) normally is indicated, when the detection meets the physical connection communication standard, the fact that the handshake stage of the Battery Management System (BMS) in the quick charging process is successful is indicated, and VIN information (0X01cec56f4: byte24-40) in the Battery Management System (BMS) identification message is displayed; otherwise, the handshake overtime is prompted, and the handshake phase is failed.
The parameter configuration phase confirmation comprises the following steps: after detection, configuration parameters of a charging pile, a Battery Management System (BMS), a Gateway (GW) and a vehicle-mounted Terminal (TBOX) are confirmed through GBT 27930-2015 communication protocol between an off-board conductive charger of an electric vehicle and a battery management system, BMS _ Fr12_518 (abbreviated as 0X518) and BMS _ Fr07_277 (abbreviated as 0X 277). The detection and confirmation comprises the steps of detecting the BMS readiness state, wherein if data information of '0X 100956F4, byte0 being AA' returned by a vehicle end is received, the vehicle is ready; and detecting the charging pile readiness state, and if receiving data information of 0X100A56F4 byte0 which is returned by the charging pile and AA, indicating that the charging pile is ready. When the vehicle end and the charging pile are ready, and the detection meets the physical connection communication standard, the parameter configuration stage is judged to be successful; and if the vehicle end and the charging pile are not ready, judging that the fault is confirmed in the parameter configuration stage.
In an embodiment of the present invention, in the conductive dc fast charging online diagnosis method provided by the present invention, after the establishing of the vehicle-end battery diagnosis fault list, the method further includes: and the battery management system pushes the charging fault reason to a user through a display screen of the vehicle terminal and charging application software. Based on the above-mentioned vehicle-end battery diagnosis fault list, generating a corresponding fault code for the charging fault reason through the Battery Management System (BMS), receiving the returned fault code through the vehicle-mounted Terminal (TBOX), analyzing the fault code by a diagnosis module of the vehicle-mounted Terminal (TBOX), and determining the position and the reason of the charging fault, and displaying and pushing the charging fault reason to a user of the vehicle-mounted terminal by an Infotainment Host (IHU) on the vehicle-end terminal through a display screen provided with modern application software (CDCS) in a CDCS digital movie server. For example, the diagnosis module of the vehicle-mounted Terminal (TBOX) determines the reason of the overhigh temperature of the power storage battery according to the fault definition of the charge stop reason by receiving '0 xC150x 2', causes the charge stop fault, immediately displays the reason of the charge stop fault caused by the overhigh temperature of the power storage battery on the display screen of the vehicle-mounted Terminal (TBOX) through the Battery Management System (BMS), and the display screen of the vehicle-mounted Terminal (TBOX) can respectively display two categories of 'power storage battery' and 'overhigh temperature'. Or, the vehicle-mounted Terminal (TBOX) sends the position cause data of the charging fault to a big data cloud platform (TPS), and a user connects the big data cloud platform (TPS) through charging application APP software installed in a server terminal, such as a mobile phone, and directly obtains the charging fault cause by accessing and receiving charging fault cause data information stored on the big data cloud platform (TPS) through the charging application APP software.
In another embodiment of the present invention, the conductive dc fast charging online diagnosis method further includes, after the diagnosis module based on the vehicle-mounted terminal analyzes the charging fault diagnosis instruction issued by the big data cloud platform and before the diagnosis module is sent to the vehicle-mounted terminal: the fault message data is a CAN communication message, and the CAN communication message of the first time period before the latched charging fault occurs is packed, compressed and stored in a memory; and recording the fault code of the vehicle end charging fault in a diagnosis snapshot. For example, the fault message data is a CAN communication message, if "Rec _0X00_ OverTime & Rec _0xAA _ OverTime" returned by a vehicle-side Battery Management System (BMS) is received, it indicates that the CRM message received by the Battery Management System (BMS) is normal, and when all the detections meet the physical connection communication standard, it indicates that the handshake stage of the Battery Management System (BMS) in the quick charging process is successful, and displays VIN information (0X01cec56f4: byte24-40) in the Battery Management System (BMS) identification message; otherwise, the handshake overtime is prompted, and the handshake phase is failed. The CRM message and the VIN message are processed by items including bit filling, data block coding, cyclic redundancy check, priority discrimination and the like, and meanwhile, 8 bytes can not occupy too long bus time, so that the real-time requirement of fault message data communication is ensured, and the general requirements of control commands, working states and test data in the common industrial field are met. The CAN bus communication data only encodes the communication data block by abolishing the traditional station address coding, so that the number of nodes in the network is theoretically unlimited, and the identification code of the data block CAN be composed of multi-bit binary numbers, so that a plurality of different data blocks CAN be defined. Particularly, the CAN protocol adopts CRC check and CAN provide a corresponding error processing function, the reliability of data communication is ensured when the VIN information (0X01cec56f4: byte24-40) is coded, and the method is suitable for interconnection and intercommunication of physical communication connection of the Battery Management System (BMS), a Gateway (GW), a vehicle-mounted Terminal (TBOX), a big data cloud platform (TPS) and a server terminal connected with the big data cloud platform (TPS). Packaging and compressing CAN communication messages of a first time period before the charging fault latched by a Battery Management System (BMS) occurs, and storing the CAN communication messages into a memory; based on the characteristic that the communication speed of the CAN bus communication data is high, the first time period CAN be set within a time period not greater than 3min optionally. Of course, those skilled in the art can select the charging fault remote diagnosis service within a reasonable time range according to the instantaneity requirement of the charging fault remote diagnosis service, and the charging fault remote diagnosis service is within the protection scope of the invention. The memory may alternatively be an EEPROM memory. As an optional scheme, the fault code of the vehicle-end charging fault may be recorded in a diagnostic snapshot, and may also be summarized and merged into the charging-off-reason fault definition list.
In an embodiment of the present invention, the conductive dc fast charging online diagnosis method provided by the present invention, the sending to the vehicle-mounted terminal includes: the battery management system supports the diagnosis access session forwarded by the vehicle-mounted terminal and/or sends the fault message data of the first time period before the latching charging fault occurs to the vehicle-mounted terminal in a compressed file form. The Battery Management System (BMS) receives a diagnosis access request sent by a server terminal and received by a big data cloud platform (TPS) and forwarded by the vehicle-mounted terminal, latches fault message data of a charging fault occurring in a current first time period (for example, within 3 min), and supports the vehicle-mounted terminal to forward the fault message data of the first time period before the latching charging fault occurs to the vehicle-mounted Terminal (TBOX) in a compressed file form. For example, the Battery Management System (BMS) latches the fault message data of the battery over-temperature information "0 xC15-0x 1" occurring in the current first time period (e.g., within 3 min), and supports the vehicle-mounted terminal to forward the fault message data of the first time period before the occurrence of the latched charging fault to the vehicle-mounted Terminal (TBOX) in the form of a compressed file. And then, as for the Battery Management System (BMS), taking a charging fault occurring in a current first time period (e.g. within 3 min) as a diagnosis access session, and performing a "fast message exchange" between the Battery Management System (BMS) and a connected charging pile, wherein the battery management system can support the diagnosis access session forwarded by the vehicle-mounted terminal, such as the "fast message exchange" to be sent to the vehicle-mounted Terminal (TBOX) in a compressed file. Or the battery management system can also support the diagnosis access session forwarded by the vehicle-mounted Terminal (TBOX), such as 'terminating charging reason' and sending fault message data of the quick-charging A-awakening failure in the first time period before the latching charging fault occurs to the vehicle-mounted Terminal (TBOX) in the form of compressed files. The diagnosis access session includes, but is not limited to, data management, model development, diagnosis execution, human-computer interaction and software upgrade on the vehicle side and the cloud side.
In an embodiment of the present invention, before the determining, by the remote diagnosis service port based on the big data cloud platform, whether to conform to an access environment of a diagnosis function and configuring a diagnosis model, an online diagnosis method for conductive direct current fast charging further includes:
and a charging fault diagnosis instruction issued by the big data cloud platform is analyzed by a diagnosis module based on the vehicle-mounted terminal and is sent to the battery management system through a diagnosis CAN bus. A diagnosis module is arranged in the vehicle-mounted Terminal (TBOX), the diagnosis module can analyze a charging fault diagnosis instruction issued by the big data cloud platform, for example, a diagnosis service list based on ISO-14229-1, the diagnosis service can make an appointment on a parameter of the service, and the parameter appointment defines that the execution of the service is as follows: "M: force "," U: user selection "; in addition, the diagnostic service may also indicate whether the ECU supports the service, such as if "ECU supports the service" and "ECU does not support the service", but the ECU must support the service specified as "M". And the diagnosis module of the vehicle-mounted terminal analyzes the charging fault diagnosis instruction issued by the big data cloud platform based on the diagnosis service list of ISO-14229-1 and sends the charging fault diagnosis instruction to the Battery Management System (BMS) through a diagnosis CAN bus of the vehicle end.
In an embodiment of the present invention, the method for conducting online diagnosis of dc fast charging provided by the present invention, the analyzing, by the diagnosis module based on the vehicle-mounted terminal, the charging fault diagnosis instruction issued by the big data cloud platform further includes: the vehicle Terminal (TBOX) supports the synchronous downloading and uploading of diagnostic data from and to the big data cloud platform. For example, the vehicle-mounted Terminal (TBOX) further supports synchronization of diagnostic data of the diagnostic module, such as a charging fault diagnosis instruction issued by the big data cloud platform is analyzed by the diagnostic module each time; and determining whether an access environment of a diagnosis function is met or not based on a remote diagnosis service port of the big data cloud platform and configuring a diagnosis model, wherein the diagnosis function is implemented based on the diagnosis model. The message data related to the charging fault and the reason of the charging fault generated when the diagnosis model is implemented are respectively stored in the vehicle-mounted Terminal (TBOX) and a memory of the big data cloud platform. When the diagnosis module of the vehicle-mounted Terminal (TBOX) analyzes a charging fault diagnosis instruction issued by the big data cloud platform, diagnosis service is carried out on a vehicle end and a cloud end, and a charging stopping reason corresponding to a corresponding fault code is downloaded on the big data cloud platform based on a vehicle end charging stopping reason fault code. In addition, when the diagnosis module of the vehicle-mounted Terminal (TBOX) analyzes a charging fault diagnosis instruction issued by the big data cloud platform, diagnosis service is performed on a vehicle end and a cloud end, and based on a vehicle end charging stop reason fault code, when a charging stop reason corresponding to the corresponding fault code is not found on the big data cloud platform, the diagnosis module analyzes the charging stop reason fault code, and uploads the fault code of the charging stop reason and the charging stop reason to the big data cloud platform. The vehicle-mounted Terminal (TBOX) downloads and uploads the diagnosis data from the big data cloud platform to the big data cloud platform through synchronization supporting the diagnosis data, so that the diagnosis speed of the vehicle-mounted Terminal (TBOX) is higher, and the diagnosis data is more perfect through downloading and uploading the diagnosis data from the big data cloud platform to the big data cloud platform through synchronization supporting the diagnosis data, so that the fault problem is more favorably retrieved and analyzed.
In an embodiment of the present invention, as shown in fig. 3, the method for remotely diagnosing a conductive international dc fast charge provided by the present invention includes:
defining a remote diagnosis model on a big data cloud platform (TPS), and configuring and sending instructions of the remote diagnosis model on the cloud platform; when the working state of the Battery Management System (BMS) is a non-starting state, the vehicle-mounted Terminal (TBOX) forwards the diagnosis message data to the Battery Management System (BMS) through the Gateway (GW); a Battery Management System (BMS) confirms the current working mode, enters a diagnosis mode and responds to a diagnosis message sent by a Gateway (GW) in real time; and reporting relevant access request information to a Gateway (GW); analyzing the diagnosis information returned by Gateway (GW) diagnosis by a vehicle-mounted Terminal (TBOX); and returning the returned diagnosis information to the cloud platform for terminating the analysis and retrieval of the charging problem.
In the above embodiment of the present invention, as an optional implementation manner, the conductive direct-current quick-charging remote diagnosis method further includes: a vehicle-mounted Terminal (TBOX) supports the inquiry of a fault code freeze frame of a historical fault code of which the fault time is not recorded; meanwhile, the vehicle-mounted Terminal (TBOX) also supports the analysis of fault code freeze frames of historical fault codes of which the fault time is not recorded.
In an embodiment of the present invention, as shown in fig. 4, a method for downloading conductive dc fast-charging remote online diagnostic data provided by the present invention includes: a Battery Management System (BMS) compresses and latches CAN message data of the quick charge fault in real time; after charging is stopped, a Battery Management System (BMS) latches fault heat preservation data in real time, and uploads the fault heat preservation data to a vehicle-mounted Terminal (TBOX) through a Gateway (GW) for storage, so that the problem of stopping charging is analyzed and eliminated. A big data cloud platform Terminal (TPS) retrieves a vehicle-mounted Terminal (TBOX) of a fault vehicle through a vehicle identification code and a part number, and accesses and/or downloads message data of the vehicle-mounted Terminal (TBOX); and the user downloads the message data of the vehicle-mounted Terminal (TBOX) locally through a big data cloud platform (TBOX), and analyzes the message data.
In a second aspect of the present invention, the present invention provides a conductive dc fast charging online diagnostic system for implementing the diagnostic method described above, the diagnostic system comprising: the system comprises a battery management system, a vehicle-mounted terminal and a big data cloud platform; the battery management system is used for identifying a charging fault at a vehicle end, actively latching fault message data in a first time period before the charging fault occurs and sending the fault message data to the vehicle-mounted terminal; the vehicle-mounted terminal is used for analyzing a charging fault diagnosis instruction issued by the big data cloud platform; the big data cloud platform comprises a remote diagnosis service port and a diagnosis module, wherein the remote diagnosis service port is used for judging whether an access environment of a diagnosis function is met or not and configuring the diagnosis model, and the diagnosis function is implemented based on the diagnosis model; the big data cloud platform is further used for issuing a charging fault diagnosis instruction, executing remote diagnosis of the charging fault and downloading message data related to the charging fault.
As shown in fig. 2, the conductive direct current quick charging online diagnosis system of the diagnosis method further includes a Gateway (GW), the gateway is in communication connection with the charging pile through a Battery Management System (BMS), the Gateway (GW) is in communication connection with the big data cloud platform (TPS) through the vehicle-mounted Terminal (TBOX), and the server terminal is in communication connection with the big data cloud platform (TPS). The Gateway (GW) can analyze and display the fault code of abnormal quit charging on an Infotainment Host (IHU) on the vehicle terminal provided with modern application software (CDCS). The Gateway (GW) may also perform diagnostic access, diagnostic response, charging status, latched message data transfer, charging fault code upload, etc. with the Battery Management System (BMS). And the Battery Management System (BMS) and the charging pile perform interaction such as reason for stopping charging, S +, S-, CC2, awakening A +, fast charging port positive electrode temperature detection, fast charging port negative electrode temperature detection and the like.
In an embodiment of the present invention, the present invention provides a conductive dc fast charging online diagnostic system for implementing the diagnostic method, and the battery management system is further configured to: packaging and compressing the latched CAN communication message in the first time period before the charging fault occurs, and storing the packaged CAN communication message in a memory; recording a fault code of the vehicle end charging fault in a diagnosis snapshot; and supporting the diagnosis access session forwarded by the vehicle-mounted terminal and/or sending the fault message data of the first time period before the latching charging fault occurs to the vehicle-mounted terminal in a compressed file form.
In an embodiment of the present invention, in the conduction type dc fast charging online diagnosis system for implementing the diagnosis method, the vehicle-mounted terminal is further configured to: a charging fault diagnosis instruction sent by the big data cloud platform analyzed by a diagnosis module based on the vehicle-mounted terminal is sent to the battery management system through a diagnosis CAN bus; and downloading and uploading the synchronization of the diagnostic data from the big data cloud platform to the big data cloud platform.
The conductive direct-current quick-charging online diagnosis system of the diagnosis method can provide diagnosis services, which further comprise: intelligent diagnosis, data management, model development, diagnosis execution, human-computer interaction and software upgrading of the vehicle end and the cloud end. The method comprises but is not limited to file issuing, diagnosis result uploading, diagnosis model design and release, buried point signal and trigger rule setting, diagnosis instruction sequence editing, vehicle historical problem editing, vehicle-side diagnosis model execution, cloud-side diagnosis model execution, vehicle-side diagnosis instruction sequence execution, cloud-side historical problem retrieval and analysis, diagnosis result output, fault and diagnosis information prompting, vehicle-side software upgrading and cloud-side software upgrading. Specifically, as shown in table 2, the remote diagnosis access and service example table issues files at the vehicle end and the cloud end through data management of intelligent diagnosis, and transmits a diagnosis model, a trigger rule, a database file and the like from the cloud end to the vehicle end. And uploading the diagnosis result at the vehicle end and the cloud end through intelligent diagnosis data management, and uploading the intelligent diagnosis result information of the vehicle end to the cloud end. And designing and issuing a diagnosis model through intelligent diagnosis model development at the cloud end, and designing and issuing the diagnosis model by using a graphical diagnosis development tool deployed at the cloud end. And (4) carrying out buried point signal and trigger rule setting on bus signals needing to be monitored by a vehicle end and bus signal change rules triggering the intelligent diagnosis function through model development of intelligent diagnosis at the cloud end. And editing a diagnosis instruction sequence, such as reading a diagnosis instruction of a DTC (digital time control) through intelligent diagnosis model development at the cloud. And editing vehicle history problems through intelligent diagnosis model development at the cloud end, and editing vehicle history faults at the cloud end. And executing the vehicle end diagnosis model at the vehicle end through intelligent diagnosis execution, and executing the diagnosis model at the vehicle end. And carrying out cloud diagnosis model execution through diagnosis execution of intelligent diagnosis at the cloud end, and executing the diagnosis model at the cloud end. And executing a diagnosis instruction sequence at the vehicle end through diagnosis execution of intelligent diagnosis at the vehicle end, and sending a diagnosis instruction as required during the execution of the diagnosis model, such as reading a DTC. And executing the diagnosis instruction sequence at the vehicle end and the cloud end through the diagnosis execution cloud end of intelligent diagnosis, and remotely sending the diagnosis instruction sequence at the cloud end, such as reading a DTC. And performing cloud historical problem retrieval and analysis through intelligent diagnosis execution at the cloud, and retrieving and analyzing fault reasons at the cloud based on the vehicle historical problems and uploaded information such as vehicle bus data and DTCs. And outputting a diagnosis result through diagnosis execution of intelligent diagnosis at the cloud end, and displaying the diagnosis result in a graphical interface at a system terminal. Fault and diagnosis information prompt is carried out at the vehicle end and the cloud end through intelligent diagnosis human-computer interaction, and human-computer interaction aiming at the fault information and the diagnosis information is carried out on a large screen at the vehicle end. And vehicle-end software upgrading is carried out at the vehicle end and the cloud end through intelligent diagnosis software upgrading, and software modules of data acquisition, diagnosis engine science and the like of the vehicle end can be upgraded through OTA. And carrying out cloud software upgrading through intelligent diagnosis software upgrading at the cloud, and upgrading a cloud diagnosis platform (comprising a development tool and a diagnosis system).
In a third aspect of the invention, the invention provides an electronic device, as shown in fig. 5, the electronic device 500 comprising: a memory 501 for storing processor non-transitory readable instructions; and a processor 502 for reading the readable instructions from the memory, so that the readable instructions are executed by the processor to implement the conductive direct current fast charging online diagnosis method.
In a fourth aspect of the present invention, the present invention provides a readable storage medium, on which executable instructions are stored, and when the executable instructions are executed on a device, the electronic device is caused to execute the conductive direct current fast charging online diagnosis method.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (12)
1. A conduction type direct current quick charging online diagnosis method is characterized by comprising the following steps:
establishing a vehicle-end battery diagnosis fault list, and performing self-defined diagnosis on vehicle-end charging faults on the basis of the vehicle-end battery diagnosis fault list; the vehicle-end battery diagnosis fault list defines fault codes of charging termination reasons according to a communication protocol and summarizes the fault codes to form a charging termination reason fault summary table;
establishing a charging fault remote diagnosis service system, and identifying a vehicle end charging fault based on the charging fault remote diagnosis service system; wherein, the charging fault remote diagnosis service system includes: battery management system, vehicle terminal and big data cloud platform, based on charge trouble remote diagnosis service system discernment car end charging fault includes:
after a vehicle-end charging fault is identified, actively latching fault message data in a first time period before the charging fault occurs based on the battery management system and sending the fault message data to the vehicle-mounted terminal;
analyzing a charging fault diagnosis instruction issued by the big data cloud platform based on a diagnosis module of the vehicle-mounted terminal;
determining whether an access environment of a diagnostic function is met and configuring a diagnostic model based on a remote diagnostic service port of the big data cloud platform, wherein the diagnostic function is implemented based on the diagnostic model;
and issuing a charging fault diagnosis instruction based on the big data platform, executing remote diagnosis of the charging fault and downloading message data related to the charging fault.
2. The conductive direct-current quick-charging online diagnosis method according to claim 1, wherein before establishing the vehicle-end battery diagnosis fault list, the method further comprises:
defining scene diagnosis content of the battery management system, judging charging conditions in real time in a handshake stage, a parameter configuration stage, a charging stage and a charging finishing stage, and judging charging faults.
3. The conductive direct-current quick-charging online diagnosis method according to claim 1, wherein after the establishing of the vehicle-end battery diagnosis fault list, the method further comprises the following steps: and the battery management system pushes the charging fault reason to a user through a display screen of the vehicle terminal and charging application software.
4. The conductive direct-current rapid charging online diagnosis method according to claim 1, wherein after the diagnosis module based on the vehicle-mounted terminal analyzes the charging fault diagnosis instruction issued by the big data cloud platform and before the charging fault diagnosis instruction is sent to the vehicle-mounted terminal, the method further comprises:
the fault message data is a CAN communication message, and the CAN communication message of the first time period before the latched charging fault occurs is packed, compressed and stored in a memory;
and recording the fault code of the vehicle end charging fault in a diagnosis snapshot.
5. The conductive direct-current quick-charging online diagnosis method according to claim 1, wherein the sending to the vehicle-mounted terminal comprises:
the battery management system supports the diagnosis access session forwarded by the vehicle-mounted terminal and/or sends the fault message data of the first time period before the latching charging fault occurs to the vehicle-mounted terminal in a compressed file form.
6. The conductive direct-current quick-charging online diagnosis method according to claim 1, wherein before the step of determining whether the access environment of the diagnosis function is met and configuring the diagnosis model based on the remote diagnosis service port of the big data cloud platform, the method further comprises:
and a charging fault diagnosis instruction issued by the big data cloud platform is analyzed by a diagnosis module based on the vehicle-mounted terminal and is sent to the battery management system through a diagnosis CAN bus.
7. The conductive direct-current rapid charging online diagnosis method according to claim 1, wherein the analyzing of the charging fault diagnosis instruction issued by the big data cloud platform by the diagnosis module based on the vehicle-mounted terminal further comprises:
the vehicle-mounted terminal supports synchronous downloading and uploading of diagnosis data from the big data cloud platform to the big data cloud platform.
8. A conductive dc rapid charging on-line diagnostic system for implementing the diagnostic method of any one of claims 1 to 7, comprising: the system comprises a battery management system, a vehicle-mounted terminal and a big data cloud platform;
the battery management system is used for identifying a charging fault at a vehicle end, actively latching fault message data in a first time period before the charging fault occurs and sending the fault message data to the vehicle-mounted terminal;
the vehicle-mounted terminal is used for analyzing a charging fault diagnosis instruction issued by the big data cloud platform;
the big data cloud platform comprises a remote diagnosis service port, a diagnosis module and a diagnosis module, wherein the remote diagnosis service port is used for judging whether an access environment of a diagnosis function is met or not and configuring the diagnosis module, and the diagnosis function is implemented based on the diagnosis module; the big data cloud platform is further used for issuing a charging fault diagnosis instruction, executing remote diagnosis of the charging fault and downloading message data related to the charging fault.
9. The conductive direct current rapid charging online diagnostic system of claim 8, wherein the battery management system is further configured to:
packaging and compressing the latched CAN communication message in the first time period before the charging fault occurs, and storing the packaged CAN communication message in a memory;
recording a fault code of the vehicle end charging fault in a diagnosis snapshot; and
and the diagnosis access session forwarded by the vehicle-mounted terminal is supported and/or the fault message data of the first time period before the latching charging fault occurs is sent to the vehicle-mounted terminal in a compressed file form.
10. The conductive direct current rapid charging online diagnostic system of claim 8, wherein the vehicle-mounted terminal is further configured to:
a charging fault diagnosis instruction sent by the big data cloud platform analyzed by a diagnosis module based on the vehicle-mounted terminal is sent to the battery management system through a diagnosis CAN bus; and
and downloading and uploading the synchronization of the diagnostic data from the big data cloud platform to the big data cloud platform.
11. An electronic device, comprising:
a memory to store processor non-transitory readable instructions; and
a processor for reading the readable instructions from the memory, so that the readable instructions are executed by the processor to implement the conductive direct current fast charging online diagnosis method of any one of claims 1 to 7.
12. A readable storage medium comprising executable instructions that, when run on a device, cause the device to perform the method of online diagnosis of conductive dc boost according to any one of claims 1 to 7.
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Address after: 314500 988 Tong Tong Road, Wu Tong Street, Tongxiang, Jiaxing, Zhejiang Applicant after: United New Energy Automobile Co.,Ltd. Address before: 314500 988 Tong Tong Road, Wu Tong Street, Tongxiang, Jiaxing, Zhejiang Applicant before: Hezhong New Energy Vehicle Co.,Ltd. |
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Denomination of invention: A conductive DC fast charging online diagnostic method and its system Granted publication date: 20231205 Pledgee: Tongxiang Science and Technology Entrepreneurship Service Center Co.,Ltd. Pledgor: United New Energy Automobile Co.,Ltd. Registration number: Y2024330000709 |