New energy vehicle electric detection optimization and automatic diagnosis method and system

Abstract

The invention discloses a new energy vehicle electric detection optimization and automatic diagnosis method and system, and relates to the technical field of new energy vehicle electric detection diagnos.The method comprises the steps that a communication link is established, an ECU list is obtained, a topological graph is generated, full-time-period message data is collected, a UDS diagnosis command is sent, fault codes are collected, and operation parameters are synchronized; and the parallel detection unit has a multi-loop function, distinguishes fault types, uploads data to a background database to analyze and match maintenance guidance, and finally safely downloads and writes an ECU parameter optimization packet, generates an electric detection report and outputs a power battery health assessment result. Thus, by integrating core designs such as multi-protocol adaptation and parallel detection and connecting all key links, electric detection gets rid of dependence of a PC end, fault diagnosis is more comprehensive, parameter optimization is safer, operation is more convenient, electric detection efficiency and accuracy are improved, cost and hidden dangers are reduced, multi-scene use requirements are met, and standardized operation and maintenance of a new energy vehicle power system in the whole life cycle are achieved.

Description

Technical Field

[0001] This application relates to the field of electrical inspection and diagnostic technology for new energy vehicles, and in particular to an optimized and automatic method and system for electrical inspection and diagnostic of new energy vehicles. Background Technology

[0002] With the rapid development of the new energy vehicle industry, the complexity of vehicle electronic control systems continues to increase, placing higher demands on the electrical testing, parameter optimization, and fault diagnosis of new energy vehicles. Currently, in the field of new energy vehicle testing, traditional electrical testing systems mostly rely on PC-based equipment, which suffers from limited operational scenarios and insufficient portability. Furthermore, their functions are relatively limited, often focusing only on fault code reading or basic parameter detection, making it difficult to achieve integrated operation of the entire process of electrical testing, measurement, and parameter optimization. In the fault diagnosis stage, traditional systems only collect the fault codes themselves, lacking the support of synchronous vehicle operating parameters at the time of fault triggering, resulting in one-sided fault analysis and making it difficult for repair personnel to accurately locate the root cause of the fault. Component testing is mostly limited to mechanical function verification, neglecting communication link and electrical circuit status detection, which can easily lead to misjudgment of fault types and increase repair costs. During ECU parameter optimization, there are issues with insufficient security protection for parameter package transmission and inaccurate version matching, which can easily lead to unauthorized flashing or parameter misuse, causing the risk of vehicle loss of control. At the same time, existing systems lack the ability to quantitatively assess the health of power batteries, failing to provide users with preventative maintenance guidance, affecting battery life and vehicle operational safety.

[0003] Furthermore, traditional electrical inspection systems suffer from weak data management autonomy, high cross-platform development costs, and difficulty in simultaneously meeting the needs of multiple scenarios such as R&D testing, production line inspection, and after-sales maintenance, thus hindering the improvement of operational efficiency for new energy vehicles. Therefore, there is an urgent need for an integrated, safe, and intelligent solution for optimizing and automatically diagnosing electrical inspections of new energy vehicles to address the shortcomings of existing technologies. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method and system for optimizing and automatically diagnosing electrical inspections of new energy vehicles, including the following:

[0005] Firstly, this application provides a method for optimizing and automatically diagnosing electrical testing of new energy vehicles, the method comprising:

[0006] Establish a communication link with the vehicle, obtain the list of vehicle ECUs and generate an ECU topology diagram, and collect vehicle message data at all times through the vehicle's OBD port;

[0007] Based on the ECU topology diagram, UDS diagnostic commands are sent to each ECU to collect fault codes and key vehicle operating parameters synchronized with the fault code trigger time.

[0008] Perform parallel testing of network communication, low-voltage circuit, and high-voltage circuit on vehicle units to determine whether the communication function, electrical circuit function, and mechanical function of the unit are normal, and distinguish between communication faults and mechanical faults.

[0009] The fault codes, key vehicle operating parameters, and unit component test results are uploaded to the background database, which performs semantic parsing on the fault codes and matches them with maintenance guidance information.

[0010] Download the digitally signed and encrypted ECU parameter optimization package, and write it to the corresponding ECU after completing version number verification and security authentication.

[0011] After the data is written, an electrical test report is generated and pushed to the display interface. At the same time, the power battery health assessment model is called to output a health score and maintenance prompts.

[0012] Optionally, establishing a communication link with the vehicle, obtaining a list of vehicle ECUs, and generating an ECU topology diagram includes:

[0013] The VCI box connects to the vehicle's OBD interface via Bluetooth, WIFI, or USB. After completing two-way authentication, an encrypted channel is established. Then, based on the CAN / CANFD / PWM / KL protocol, all ECU nodes are scanned one by one. The hardware version, software version, supplier code, and logical address of each node are summarized to form an ECU list. An ECU topology map is automatically generated with logical addresses as vertices and CAN routing relationships as edges.

[0014] Optionally, the collection of fault codes and key vehicle operating parameters synchronized with the fault code triggering time includes:

[0015] Read the DTC status mask of each ECU, extract fault code snapshot data in batches. The snapshot data includes at least the vehicle speed, ECU temperature, ambient temperature, slope data, vehicle voltage, vehicle current, gear, fault trigger time, and the name of the ECU that first reported the fault. After adding a unified timestamp to the fault codes and snapshot data, encapsulate them into a data package and sort the fault codes according to the fault trigger time.

[0016] Optionally, the background database performs semantic parsing of the fault code and matches it with maintenance guidance information, including:

[0017] The fault codes are read in the order of their trigger time. Then, the first two bytes of the fault code are used as an index to match the fault description, failure type, and list of suspicious parameters in the DTC knowledge base. The list of suspicious parameters is used as the key to retrieve the corresponding signal value in the snapshot data. When the signal value exceeds the preset threshold, the matching of maintenance guidance information is triggered. The maintenance guidance information includes at least the fault location steps, wiring harness pin diagram, standard resistor voltage range, tightening torque value, and recommended special tool number. At the same time, a vehicle fault electrical inspection report is generated.

[0018] Optionally, before downloading the digitally signed and encrypted ECU parameter optimization package, the method further includes:

[0019] First, send the vehicle model VIN, ECU hardware number, ECU software number, and current parameter version number to the TSP cloud platform; the TSP cloud platform stores ECU parameter optimization packages with digital signatures and encryption that have been pre-approved by the background database, and returns ECU parameter optimization packages corresponding to the vehicle model and ECU version based on the received information;

[0020] The ECU parameter optimization package uses symmetric encryption, with the key derived from the ECU's unique serial number. The digital signature uses an elliptic curve signature algorithm. After downloading, the digital signature verification, decryption, and local public key and private key verification are performed locally in sequence. After all verifications are successful, the version description file in the upgrade package is extracted. The version description file is compared with the current version of the local ECU field by field. When the hardware number, software number, dependent version number, and checksum are all consistent, the writing process begins.

[0021] Optionally, the step of downloading the digitally signed and encrypted ECU parameter optimization package, and writing it to the corresponding ECU after version number verification and security authentication includes:

[0022] First, the UDS download service is used to request transmission, and then the data is transmitted block by block according to the block transmission protocol. Each block of data is appended with a block sequence number and a CRC32 check value. After the ECU receives the data, it sends back the CRC32 result in real time. If the check fails, the block is immediately retransmitted.

[0023] After the transmission is complete, the parameter optimization routine is started. The routine sequentially executes the following steps: fuel self-learning adjustment value reset, idle speed self-learning value reset, forced throttle self-learning, 58-tooth gear signal learning, SK code anti-theft activation by scanning and writing code, after-sales general reset, steering wheel zeroing, caliper action parameter optimization, window reset parameter optimization, slope parking parameter optimization, ABS parameter optimization, and ESC parameter optimization. After all the steps are completed, the extended session is exited and the ECU is automatically reset.

[0024] Optionally, the step of calling the power battery health assessment model to output a health score and maintenance prompts includes:

[0025] The system reads historical operating parameters of the power battery and vehicle operating parameters uploaded by the battery management system, uses a preset algorithm to extrapolate and calculate the parameters, and performs self-evaluation and scoring through a self-built health model to obtain a health score out of 100. When the health score is lower than a preset threshold, a maintenance prompt is automatically generated, which includes a description of the power battery status and corresponding maintenance suggestions.

[0026] Secondly, this application provides a new energy vehicle electrical inspection optimization and automatic diagnostic system, which includes:

[0027] The communication link establishment module is used to establish a communication link with the vehicle, obtain the list of vehicle ECUs and generate an ECU topology diagram, and collect vehicle message data at all times through the vehicle's OBD port.

[0028] The UDS diagnostic acquisition module is connected to the communication link establishment module. It is used to send UDS diagnostic commands to each ECU according to the ECU topology diagram, and to collect fault codes and key vehicle operating parameters that are synchronized with the fault code trigger time.

[0029] The unit component testing module, connected to the communication link establishment module, is used to perform parallel testing of network communication, low-voltage circuit, and high-voltage circuit of vehicle unit components, to determine whether the communication function, electrical circuit function, and mechanical function of the unit components are normal, and to distinguish between communication faults and mechanical faults.

[0030] The background parsing module is connected to the UDS diagnostic acquisition module and the unit component testing module respectively. It is used to receive fault codes, key vehicle operating parameters and unit component test results, perform semantic parsing on the fault codes and match maintenance guidance information.

[0031] The network transmission digital signature verification and decryption module is used to perform digital signature verification, decryption, and local public key and private key verification on the downloaded ECU parameter optimization package;

[0032] The secure flashing module is connected to the backend parsing module and the network transmission digital signature verification and decryption module, respectively. It is used to download the ECU parameter optimization package that has been digitally signed and encrypted, and write it to the corresponding ECU after completing version number verification and security authentication.

[0033] The report generation and health assessment module is connected to the safe flashing module. It is used to generate an electrical test report after the writing is completed and push it to the display interface. At the same time, it calls the power battery health assessment model to output a health score and maintenance prompts.

[0034] Optionally, the communication link establishment module is specifically used to connect to the VCI box of the vehicle's OBD interface via Bluetooth, WIFI, or USB interface, establish an encrypted channel after completing two-way identity authentication, and then scan all ECU nodes one by one based on CAN / CANFD / PWM / KL protocol, summarize the node hardware version, software version, supplier code, and logical address to form an ECU list, and automatically generate an ECU topology map with logical address as vertex and CAN routing relationship as edge.

[0035] Optionally, the UDS diagnostic acquisition module is specifically used to read the DTC status mask of each ECU, extract fault code snapshot data in batches, and the snapshot data includes at least the vehicle speed, ECU temperature, ambient temperature, slope data, vehicle voltage, vehicle current, gear, fault trigger time, and the name of the ECU that first reported the fault. The fault codes and snapshot data are then encapsulated into a data package after being stamped with a unified timestamp, and the fault codes are sorted according to the fault trigger time.

[0036] Optionally, the background parsing module is specifically used to read the sorted fault codes in the order of fault triggering time, then use the first two bytes of the fault code as an index to match the fault description, failure type and list of suspicious parameters in the DTC knowledge base, use the list of suspicious parameters as a key to retrieve the corresponding signal value in the snapshot data, and trigger the matching of maintenance guidance information when the signal value exceeds a preset threshold. The maintenance guidance information includes at least the fault location steps, wiring harness pin diagram, standard resistor voltage range, tightening torque value and recommended special tool number, and generates a vehicle fault electrical inspection report at the same time.

[0037] Optionally, the device further includes an ECU parameter optimization package acquisition module, used to send the vehicle model VIN, ECU hardware number, ECU software number and current parameter version number to the TSP cloud platform; the TSP cloud platform stores ECU parameter optimization packages with digital signatures and encryption that have been pre-approved by the background database, and returns ECU parameter optimization packages corresponding to the vehicle model and ECU version according to the received information;

[0038] The ECU parameter optimization package uses symmetric encryption, with the key derived from the ECU's unique serial number. The digital signature uses an elliptic curve signature algorithm. After downloading, the digital signature verification, decryption, and local public key and private key verification are performed locally in sequence. After all verifications are successful, the version description file in the upgrade package is extracted. The version description file is compared with the current version of the local ECU field by field. When the hardware number, software number, dependent version number, and checksum are all consistent, the writing process begins.

[0039] Optionally, the secure flashing module is specifically used to first request transmission using the UDS download service, and then transmit data block by block according to the block transmission protocol. Each block of data is appended with a block sequence number and a CRC32 check value. After receiving the data, the ECU sends back the CRC32 result in real time. If the check fails, the block is immediately retransmitted.

[0040] After the transmission is complete, the parameter optimization routine is started. The routine sequentially executes the following steps: fuel self-learning adjustment value reset, idle speed self-learning value reset, forced throttle self-learning, 58-tooth gear signal learning, SK code anti-theft activation by scanning and writing code, after-sales general reset, steering wheel zeroing, caliper action parameter optimization, window reset parameter optimization, slope parking parameter optimization, ABS parameter optimization, and ESC parameter optimization. After all the steps are completed, the extended session is exited and the ECU is automatically reset.

[0041] Optionally, the report generation and health assessment module is specifically used to read the historical operating parameters of the power battery and the vehicle operating parameters uploaded by the battery management system, perform calculations on the parameters using a preset algorithm, and conduct self-evaluation and scoring through a self-built health model to obtain a health score out of 100. When the health score is lower than a preset threshold, a maintenance prompt is automatically generated, which includes a description of the power battery status and corresponding maintenance suggestions.

[0042] Thirdly, this application provides an apparatus comprising a memory and a processor, the memory for storing instructions or code, and the processor for executing the instructions or code to cause the apparatus to perform the method described in any of the implementations of the first aspect.

[0043] Fourthly, this application provides a computer-readable storage medium storing code, wherein when the code is executed, a device executing the code implements the method described in any of the implementations of the first aspect.

[0044] This application provides a method for optimizing and automatically diagnosing electrical faults in new energy vehicles. When executing the method, a communication link with the vehicle is first established, a list of all vehicle ECUs is obtained, and an ECU topology diagram is generated. Simultaneously, full-time vehicle message data is collected through the vehicle's OBD port. Then, based on the ECU topology diagram, UDS diagnostic commands are sent to each ECU, fault codes and key vehicle operating parameters synchronized with the fault code trigger time are collected. Next, parallel testing of network communication, low-voltage circuits, and high-voltage circuits is performed on vehicle components to determine whether the communication, electrical circuit, and mechanical functions of the components are normal, distinguishing between communication faults and mechanical faults. The fault codes, key vehicle operating parameters, and component test results are uploaded to a background database. The background database performs semantic parsing of the fault codes and matches them with maintenance guidance information. Finally, an ECU parameter optimization package, digitally signed and encrypted, is downloaded, and after version number verification and security authentication, it is written to the corresponding ECU. After writing, an electrical fault test report is generated and pushed to the display interface. Simultaneously, a power battery health assessment model is invoked to output a health score and maintenance prompts. By integrating core designs such as multi-protocol adaptation, parallel testing, digital signature encryption, and precise version matching, this system seamlessly connects communication connections, data acquisition, fault analysis, security optimization, and result feedback. This allows new energy vehicle electrical testing to break free from PC dependence, resulting in more comprehensive fault diagnosis, safer parameter optimization, and more convenient operation. It effectively solves the problems of traditional electrical testing systems, such as limited functionality, incomplete fault analysis, insufficient data transmission security, and high risk of misoperation. This achieves the effects of improving electrical testing efficiency, ensuring the accuracy of testing and parameter optimization, and reducing labor costs and safety hazards. Consequently, it can meet the needs of multiple scenarios, including R&D testing, production line testing, and after-sales maintenance, realizing standardized and efficient operation and maintenance management of the entire lifecycle of new energy vehicle electrical systems. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings used in the description of the embodiment or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 An architecture diagram of a multi-functional operation and maintenance platform for new energy vehicles provided in this application embodiment;

[0047] Figure 2 A simplified system diagram of a multi-functional operation and maintenance platform for new energy vehicles provided in this application embodiment;

[0048] Figure 3 A flowchart of an optimized and automatic diagnostic method for electrical testing of new energy vehicles provided in this application embodiment;

[0049] Figure 4 This is a schematic diagram of the structure of a new energy vehicle electrical inspection optimization and automatic diagnosis system provided in an embodiment of this application. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0051] This application discloses a method for optimizing and automatically diagnosing electrical inspections of new energy vehicles. Relying on a multi-functional operation and maintenance platform for new energy vehicles, it achieves full-scenario electrical inspection, testing, parameter optimization, and safety diagnosis, aiming to solve the problems of traditional electrical inspection systems, such as reliance on PCs, limited functionality, insufficient security, and poor data management autonomy and controllability. This operation and maintenance platform is developed based on C / C++ and can run on Android / iOS mobile phones / tablets, meeting the needs of multiple scenarios such as R&D testing, production line inspection, and after-sales maintenance, reducing cross-platform development costs and improving enterprise economic efficiency. The following details the platform architecture and specific embodiments:

[0052] Figure 1 This is an architecture diagram of a multi-functional operation and maintenance platform for new energy vehicles provided in an embodiment of this application. Figure 1 As shown, the platform is centered on a "multi-functional operation and maintenance platform for new energy vehicles." It achieves data management interaction with the backend database through an intermediate interface. It integrates five major interactive programs through the platform's API interface: parameter optimization program, detection program, electrical inspection program, digital encryption / decryption program, and communication / connection program. It includes a parameter optimization module, a detection module, an electrical inspection module, a network transmission digital verification and decryption module, and a VCI adaptation module. The platform establishes a communication connection with the vehicle interface (OBD port) through a VCI communication system (including multiple communication physical interfaces, USB interface, Bluetooth / WIFI interface) to realize data transmission and command interaction.

[0053] Figure 2 This is a simplified system diagram of a multi-functional operation and maintenance platform for new energy vehicles provided in an embodiment of this application. Figure 2 As shown, the core of the platform consists of three main modules: the app application (user operation entry point), the communication device (connection carrier between the platform and the vehicle), and the backend database (data storage and support module).

[0054] Figure 3 A flowchart of an optimized and automatic diagnostic method for electrical testing of new energy vehicles is provided as an embodiment of this application. The flowchart is based on... Figure 1 Based on the overall architecture of the new energy vehicle multi-functional operation and maintenance platform shown, and relying on Figure 2 The system comprises three core modules: a clearly defined APP application, a communication device (VCI box), and a backend database. These modules work collaboratively, leveraging the platform architecture's functional support and inter-module coordination to systematically optimize and automatically diagnose electrical defects across all scenarios. Figure 3 As shown, the specific steps are as follows:

[0055] S301. Establish a communication link with the vehicle, obtain the list of vehicle ECUs and generate an ECU topology diagram, and collect vehicle message data at all times through the vehicle's OBD port.

[0056] The communication link is the connection channel between the platform and the vehicle for data transmission and command interaction, and it is the foundation for all subsequent electronic diagnostic and testing functions. The ECU list is a list that records the core information of all electronic control units (ECUs) in the vehicle, including the ECU's hardware version, software version, supplier code, and logical address, which is used to clarify the composition of the vehicle's electronic control system and support subsequent accurate diagnosis. The ECU topology diagram is a graphical model built with ECU logical addresses as vertices and CAN routing relationships as edges, which can intuitively present the communication relationships between each ECU and facilitate the location of fault nodes. The VCI box, or Bluetooth connection box, connects to the vehicle's OBD diagnostic interface to realize data interaction between the platform and the vehicle controller, and can receive all data from the vehicle controller. In practice, the communication device connects to the VCI box of the vehicle's OBD interface via Bluetooth, WIFI, or USB. After completing two-way authentication, an encrypted channel is established to prevent tampering or theft during data transmission. Based on CAN / CANFD / PWM / KL protocols, all ECU nodes are scanned one by one, and the hardware version, software version, supplier code, and logical address of each node are summarized to form a complete list of vehicle ECUs. An ECU topology map is automatically generated using ECU logical addresses as vertices and CAN routing relationships as edges. Simultaneously, vehicle message data is collected at all times through the vehicle's OBD port, providing data support for remote technical support and fault diagnosis for back-end service personnel. The benefits of this step are that the multi-interface adaptation design ensures compatibility with different vehicle models, the encrypted channel improves data transmission security, the all-time message collection provides a complete data foundation for remote diagnostics, and the ECU topology map makes the electronic control system structure clear at a glance, reducing the difficulty of fault location.

[0057] S302. Based on the ECU topology diagram, send UDS diagnostic commands to each ECU to collect fault codes and key vehicle operating parameters synchronized with the fault code trigger time.

[0058] UDS diagnostic commands are standardized instructions based on the Unified Diagnostic Services (UDS) protocol, used to send data acquisition and fault detection requests to ECUs, ensuring the universality and accuracy of diagnostic operations. Fault codes (DTCs) are identifiers stored by the ECU when a fault is detected, reflecting the fault type and location, and are the core basis for fault diagnosis. Snapshot data is vehicle operating data synchronously recorded at the time the fault code is triggered, restoring the vehicle state at the time of the fault and providing crucial support for root cause analysis. In specific implementation, UDS diagnostic commands are sent to each ECU according to the ECU topology diagram. First, the DTC status mask of each ECU is read (used to confirm the current state of the fault code), and then fault code snapshot data is extracted in batches. The snapshot data includes at least the vehicle speed, ECU temperature, ambient temperature, slope data, vehicle voltage, vehicle current, gear position, fault trigger time, and the name of the ECU that first reported the fault. Then, the fault codes and snapshot data are timestamped and encapsulated into a data packet, and the fault codes are sorted according to the fault trigger time to facilitate tracing the logical sequence of fault occurrence. The beneficial effect of this step is that the standardized UDS diagnostic commands ensure the accuracy and universality of fault information collection. The combination of fault codes and synchronous snapshot data, along with time sorting, enables a complete reconstruction of the fault scenario, helping maintenance personnel to quickly pinpoint the cause of the fault and avoid blind troubleshooting.

[0059] S303. Perform parallel testing of network communication, low-voltage circuit, and high-voltage circuit of vehicle unit components to determine whether the communication function, electrical circuit function, and mechanical function of the unit components are normal, and distinguish between communication faults and mechanical faults.

[0060] Parallel testing refers to simultaneously testing network communication, low-voltage circuits, and high-voltage circuits to avoid misdiagnosis caused by single-dimensional testing and improve testing efficiency. Communication failures are caused by abnormal signal transmission between the unit and the ECU, not by unit failure itself. Mechanical failures are caused by failure of the mechanical structure or function of the unit itself, and are unrelated to signal transmission. In practice, the test module establishes network communication, low-voltage circuit, and high-voltage circuit connections with the vehicle under test through a communication device to conduct comprehensive and targeted testing, including high-speed / low-speed function checks of the radiator fan, front oxygen heating function tests, rear oxygen heating function tests, DC-DC wake-up tests, GCU wake-up tests, VCU motor and water pump function tests, and engine electronic water pump function tests. A menu of test functions is also reserved for future expansion of testing functions as needed. During the testing process, the vehicle's network communication signals are first collected and analyzed to determine whether the signal transmission between the unit and the ECU is normal, and to rule out false fault codes caused by network communication problems. Next, the low-voltage circuit test verifies the continuity of the unit's power supply and control circuits, while the high-voltage circuit test (for high-voltage system units) confirms whether the high-voltage power supply and insulation performance meet standards. Subsequently, the test module's interactive program sends a test command to the faulty ECU, using electrical signal drive to determine whether the mechanical function of the moving unit is normal. By combining the results of these three types of tests, the communication function, electrical circuit function, and mechanical function status of the unit are clearly defined, accurately distinguishing between communication faults and mechanical faults. Upon completion of the test, a "Unit Function Test Report PDF" is automatically generated, providing a basis for repair personnel to quickly pinpoint the fault mode and develop a repair plan. This step breaks through the limitations of traditional single mechanical function testing, covering the core causes of unit faults. The accurate differentiation of fault types avoids incorrect part replacements by repair personnel, significantly improving repair efficiency and accuracy, and reducing repair costs.

[0061] S304. Upload the fault code, the key vehicle operating parameters, and the unit component test results to the background database. The background database performs semantic parsing on the fault code and matches it with maintenance guidance information.

[0062] Semantic parsing transforms abstract fault codes into easily understandable fault descriptions, failure types, and other information, facilitating comprehension by maintenance personnel. The DTC knowledge base is a database storing information corresponding to various fault codes, including fault descriptions, suspected parameters, and repair solutions, serving as the core support for fault parsing. Repair guidance information provides standardized repair references for specific faults, including operating procedures, technical parameters, and specialized tools, lowering the repair threshold. In practice, the fault codes collected in step S302, key vehicle operating parameters, and unit component test results from step S303 are uploaded to the backend database. When performing semantic parsing on the fault codes, the backend database first reads the sorted fault codes in chronological order of fault triggering time. Then, using the first two bytes of the fault code as an index, it matches the fault description, failure type, and list of suspected parameters in the DTC knowledge base. Using the list of suspected parameters as the key, it retrieves the corresponding signal value from the snapshot data. When the signal value exceeds a preset threshold, it triggers the matching of repair guidance information. The repair guidance information includes at least fault location steps, wiring harness pin diagrams, standard resistance voltage ranges, tightening torque values, and recommended specialized tool numbers, while simultaneously generating a vehicle fault electrical inspection report. In this way, through knowledge base matching and data association analysis, abstract fault codes are transformed into specific and operable repair solutions, which lowers the skill threshold for repair personnel. Standardized fault electrical inspection reports enable traceability of the testing process and ensure repair quality.

[0063] S305. Download the ECU parameter optimization package that has been digitally signed and encrypted, and write it to the corresponding ECU after completing version number verification and security authentication.

[0064] The ECU parameter optimization package is a data package developed by R&D personnel and pre-approved by the background database. It is used to optimize ECU control parameters, improve vehicle performance, or fix control logic problems. The digital signature is an identity identifier generated using the elliptic curve signature algorithm, used to verify the authenticity of the optimization package and prevent unauthorized package flashing. Symmetric encryption is used to encrypt with a key derived from the ECU's unique serial number to ensure the security of the optimization package during transmission and prevent data tampering. In practice, before downloading the digitally signed and encrypted ECU parameter optimization package, the vehicle model VIN, ECU hardware number, ECU software number, and current parameter version number are sent to the TSP cloud platform. The TSP cloud platform stores ECU parameter optimization packages with digital signatures and encryption that have been pre-approved by the background database, and returns ECU parameter optimization packages corresponding to the vehicle model and ECU version based on the received information. The ECU parameter optimization package uses symmetric encryption, with the key derived from the ECU's unique serial number, and the digital signature uses an elliptic curve signature algorithm. After downloading, the local system sequentially performs digital signature verification (verifying the authenticity of the optimization package), decryption (unlocking the optimization package data), and local public and private key verification (further confirming data integrity). After all verifications are successful, the version description file within the upgrade package is extracted, and the version description file is compared field by field with the current version of the local ECU. When the hardware number, software number, dependent version number, and checksum are all consistent, the writing process begins. During the writing process, the ECU parameter optimization package is first requested and transmitted via the UDS download service. Then, data is transmitted block by block according to the block transmission protocol, with each block appended with a block number and a CRC32 checksum. After receiving the data, the ECU sends back the CRC32 result in real time. If the checksum fails, the block is immediately retransmitted to ensure data transmission integrity. After the transmission is complete, the parameter optimization routine is started. The routine sequentially executes the following steps: fuel self-learning adjustment value reset, idle speed self-learning value reset, forced throttle self-learning, 58-tooth gear signal learning, SK code anti-theft activation via QR code scanning, after-sales general reset, steering wheel zeroing, caliper action parameter optimization, window reset parameter optimization, slope parking parameter optimization, ABS parameter optimization, and ESC parameter optimization. After all steps are completed, the extended session is exited and the ECU is automatically reset to make the optimized parameters take effect. This step employs a comprehensive security mechanism encompassing review, encryption, signature verification, and comparison to prevent unauthorized or tampered optimization package flashing. This effectively avoids vehicle loss of control and data tampering caused by parameter optimization errors, ensuring vehicle operational safety. The block transmission and verification mechanism enhances the reliability of data writing, while the standardized parameter optimization process reduces operational difficulty and increases the flashing success rate.

[0065] S306. After writing is complete, an electrical test report is generated and pushed to the display interface. At the same time, the power battery health assessment model is called to output a health score and maintenance prompts.

[0066] The power battery health assessment model is a self-evaluation model built based on historical operating parameters of the power battery and vehicle operating data. It is used to quantitatively assess the health status of the power battery, providing a basis for preventative maintenance. The health score uses a 100-point scale to quantitatively score the power battery's health status, intuitively reflecting the battery's performance degradation. Maintenance tips are personalized suggestions generated based on the battery's health status, used to extend battery life and reduce usage risks. In specific implementation, after the ECU parameter optimization package is written, the system automatically generates an electrical inspection report. This report includes core information such as communication link establishment status, fault detection results, unit component test conclusions, and parameter optimization execution status, and is pushed to the display interface on the mobile phone / tablet for real-time viewing and retention. Simultaneously, the power battery health assessment model outputs a health score and maintenance tips: it reads historical operating parameters of the power battery and vehicle operating parameters uploaded by the battery management system, uses a preset algorithm to extrapolate and calculate the parameters, and performs a self-evaluation and scoring through the self-built health model to obtain a 100-point health score. When the health score is lower than a preset threshold, a maintenance tip is automatically generated, including a description of the power battery status and corresponding maintenance suggestions (such as equalization charging, capacity calibration, etc.). This step enables full traceability of the testing and optimization process through comprehensive electrical testing reports, meeting the data management needs of multiple scenarios such as R&D, production, and after-sales service. The quantitative assessment of the power battery's health and maintenance tips provide users with preventative maintenance guidance, which helps extend battery life and reduce vehicle operating costs and safety risks.

[0067] The steps described above in this invention are accomplished using a "Multi-functional Platform for Automatic Diagnosis of New Energy Vehicle Electrical Inspection Parameters with Digital Verification and Decryption." This platform, developed in C / C++, consists of three main modules: an APP application, a communication device, and a backend database. It can run on Android / Apple phones or tablets. The platform collects messages from the vehicle's OBD port around the clock via a VCI box, enabling network communication checks, low / high voltage circuit checks, electrical signal checks, and mechanical function testing. Through fault code semantic analysis and matching with maintenance guidance information, it helps maintenance personnel quickly locate faults. Full-process digital verification and decryption ensures the reliability and completeness of the ECU flashing package source. A hierarchical parameter optimization package generation and review mechanism allows R&D personnel to focus on data development, while maintenance personnel only perform version verification and flashing, avoiding secondary human modifications. Through power battery health self-assessment, it displays battery status and maintenance suggestions in real time. Therefore, the platform simultaneously meets the needs of production line off-line inspection, inventory vehicle re-inspection, after-sales fault diagnosis, and remote technical support, reducing cross-platform learning and repetitive development costs, shortening the electrical inspection software development cycle, and improving enterprise economic efficiency.

[0068] The above are some specific implementations of a new energy vehicle electrical inspection optimization and automatic diagnosis method provided in the embodiments of this application. Based on this, this application also provides a corresponding system. The system provided in the embodiments of this application will be described below from the perspective of functional modularization.

[0069] Figure 4 This is a schematic diagram of a new energy vehicle electrical inspection optimization and automatic diagnostic system provided in an embodiment of this application. (Combined with...) Figure 4 As shown in the embodiment of this application, the new energy vehicle electrical inspection optimization and automatic diagnosis system 400 includes:

[0070] The communication link establishment module 410 is used to establish a communication link with the vehicle, obtain the list of vehicle ECUs and generate an ECU topology diagram, and collect vehicle message data at all times through the vehicle's OBD port.

[0071] UDS diagnostic acquisition module 420 is connected to the communication link establishment module and is used to send UDS diagnostic commands to each ECU according to the ECU topology diagram, and to collect fault codes and key vehicle operating parameters synchronized with the fault code trigger time.

[0072] The unit component testing module 430 is connected to the communication link establishment module and is used to perform parallel testing of network communication, low-voltage circuit and high-voltage circuit of vehicle unit components to determine whether the communication function, electrical circuit function and mechanical function of the unit components are normal and to distinguish between communication faults and mechanical faults.

[0073] The background parsing module 440 is connected to the UDS diagnostic acquisition module and the unit component testing module respectively. It is used to receive fault codes, key vehicle operating parameters and unit component test results, perform semantic parsing on the fault codes and match maintenance guidance information.

[0074] The network transmission digital signature verification and decryption module 450 is used to perform digital signature verification, decryption, and local public key and private key verification on the downloaded ECU parameter optimization package;

[0075] The secure flashing module 460 is connected to the background parsing module and the network transmission digital signature verification and decryption module, respectively. It is used to download the ECU parameter optimization package that has been digitally signed and encrypted, and write it to the corresponding ECU after completing version number verification and security authentication.

[0076] The report generation and health assessment module 470 is connected to the safety flashing module. It is used to generate an electrical test report after the writing is completed and push it to the display interface. At the same time, it calls the power battery health assessment model to output a health score and maintenance prompts.

[0077] In one implementation of this application, the communication link establishment module is specifically used to connect to the VCI box of the vehicle's OBD interface via Bluetooth, WIFI, or USB interface, establish an encrypted channel after completing two-way identity authentication, and then scan all ECU nodes one by one based on CAN / CANFD / PWM / KL protocol, summarize the node hardware version, software version, supplier code, and logical address to form an ECU list, and automatically generate an ECU topology map with logical address as vertex and CAN routing relationship as edge.

[0078] In one implementation of this application, the UDS diagnostic acquisition module is specifically used to read the DTC status mask of each ECU, extract fault code snapshot data in batches, and the snapshot data includes at least the vehicle speed, ECU temperature, ambient temperature, slope data, vehicle voltage, vehicle current, gear, fault trigger time, and the name of the ECU that first reported the fault. The fault codes and snapshot data are then encapsulated into a data packet after being stamped with a unified timestamp, and the fault codes are sorted according to the fault trigger time.

[0079] In one implementation of this application, the background parsing module is specifically used to read the sorted fault codes in the order of fault triggering time, then use the first two bytes of the fault code as an index to match the fault description, failure type and list of suspicious parameters in the DTC knowledge base, use the list of suspicious parameters as a key to retrieve the corresponding signal value in the snapshot data, and trigger the matching of maintenance guidance information when the signal value exceeds a preset threshold. The maintenance guidance information includes at least the fault location steps, wiring harness pin diagram, standard resistor voltage range, tightening torque value and recommended special tool number, and generates a vehicle fault electrical inspection report at the same time.

[0080] In one implementation of this application, the device further includes an ECU parameter optimization package acquisition module, used to send the vehicle model VIN, ECU hardware number, ECU software number and current parameter version number to the TSP cloud platform; the TSP cloud platform stores ECU parameter optimization packages with digital signatures and encryption that have been pre-approved by the background database, and returns ECU parameter optimization packages corresponding to the vehicle model and ECU version according to the received information;

[0081] The ECU parameter optimization package uses symmetric encryption, with the key derived from the ECU's unique serial number. The digital signature uses an elliptic curve signature algorithm. After downloading, the digital signature verification, decryption, and local public key and private key verification are performed locally in sequence. After all verifications are successful, the version description file in the upgrade package is extracted. The version description file is compared with the current version of the local ECU field by field. When the hardware number, software number, dependent version number, and checksum are all consistent, the writing process begins.

[0082] In one implementation of this application, the secure flashing module is specifically used to first request transmission using the UDS download service, then transmit data block by block according to the block transmission protocol, with each block of data having an appended block number and a CRC32 check value. After receiving the data, the ECU sends back the CRC32 result in real time, and if the check fails, it immediately retransmits the block.

[0083] After the transmission is complete, the parameter optimization routine is started. The routine sequentially executes the following steps: fuel self-learning adjustment value reset, idle speed self-learning value reset, forced throttle self-learning, 58-tooth gear signal learning, SK code anti-theft activation by scanning and writing code, after-sales general reset, steering wheel zeroing, caliper action parameter optimization, window reset parameter optimization, slope parking parameter optimization, ABS parameter optimization, and ESC parameter optimization. After all the steps are completed, the extended session is exited and the ECU is automatically reset.

[0084] In one implementation of this application, the report generation and health assessment module is specifically used to read the historical operating parameters of the power battery and the vehicle operating parameters uploaded by the battery management system, perform calculations on the parameters using a preset algorithm, and perform self-evaluation and scoring through a self-built health model to obtain a health score out of 100. When the health score is lower than a preset threshold, a maintenance prompt is automatically generated, which includes a description of the power battery status and corresponding maintenance suggestions.

[0085] This application also provides corresponding devices and computer storage media for implementing the solutions provided in this application.

[0086] The device includes a memory and a processor. The memory stores instructions or code, and the processor executes the instructions or code to cause the device to perform the method described in any embodiment of this application.

[0087] The computer storage medium stores code, and when the code is run, the device running the code implements the method described in any embodiment of this application.

[0088] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that all or part of the steps in the methods of the above embodiments can be implemented by means of software plus a general-purpose hardware platform. Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as a read-only memory (ROM) / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network communication device such as a router) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0089] It is understood that in the specific embodiments of this application, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved need to obtain user permission or consent when the above embodiments of this application are applied to specific products or technologies, and the collection, use and processing of related data need to comply with the relevant laws, regulations and standards of relevant countries and regions.

[0090] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0091] It should also be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components indicated as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the solution in this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0092] The above description is merely one specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A new energy vehicle electrical inspection optimization and automatic diagnosis method, characterized in that, The method includes: Establish a communication link with the vehicle, obtain the list of vehicle ECUs and generate an ECU topology diagram, and collect vehicle message data at all times through the vehicle's OBD port; Based on the ECU topology diagram, UDS diagnostic commands are sent to each ECU to collect fault codes and key vehicle operating parameters synchronized with the fault code trigger time. Perform parallel testing of network communication, low-voltage circuit, and high-voltage circuit on vehicle unit components to determine whether the communication function, electrical circuit function, and mechanical function of the unit components are normal, and distinguish between communication faults and mechanical faults. The fault codes, key vehicle operating parameters, and unit component test results are uploaded to the background database, which performs semantic parsing on the fault codes and matches them with maintenance guidance information. Download the digitally signed and encrypted ECU parameter optimization package, and write it to the corresponding ECU after completing version number verification and security authentication. After the data is written, an electrical test report is generated and pushed to the display interface. At the same time, the power battery health assessment model is called to output a health score and maintenance prompts.

2. The method according to claim 1, characterized in that, The establishment of a communication link with the vehicle, obtaining a list of vehicle ECUs and generating an ECU topology diagram includes: The VCI box connects to the vehicle's OBD interface via Bluetooth, WIFI, or USB. After completing two-way authentication, an encrypted channel is established. Then, based on the CAN / CANFD / PWM / KL protocol, all ECU nodes are scanned one by one. The hardware version, software version, supplier code, and logical address of each node are summarized to form an ECU list. An ECU topology map is automatically generated with logical addresses as vertices and CAN routing relationships as edges.

3. The method according to claim 1, characterized in that, The collected fault codes and key vehicle operating parameters synchronized with the fault code trigger time include: Read the DTC status mask of each ECU, extract fault code snapshot data in batches. The snapshot data includes at least the vehicle speed, ECU temperature, ambient temperature, slope data, vehicle voltage, vehicle current, gear, fault trigger time, and the name of the ECU that first reported the fault. After adding a unified timestamp to the fault codes and snapshot data, encapsulate them into a data package and sort the fault codes according to the fault trigger time.

4. The method according to claim 1, characterized in that, The background database performs semantic parsing on the fault codes and matches them with maintenance guidance information, including: The fault codes are read in the order of their trigger time. Then, the first two bytes of the fault code are used as an index to match the fault description, failure type, and list of suspicious parameters in the DTC knowledge base. The list of suspicious parameters is used as the key to retrieve the corresponding signal value in the snapshot data. When the signal value exceeds the preset threshold, the matching of maintenance guidance information is triggered. The maintenance guidance information includes at least the fault location steps, wiring harness pin diagram, standard resistor voltage range, tightening torque value, and recommended special tool number. At the same time, a vehicle fault electrical inspection report is generated.

5. The method according to claim 1, characterized in that, Before downloading the digitally signed and encrypted ECU parameter optimization package, the method further includes: Send the vehicle model VIN, ECU hardware number, ECU software number, and current parameter version number to the TSP cloud platform; the TSP cloud platform stores ECU parameter optimization packages with digital signatures and encryption that have been pre-approved by the background database, and returns ECU parameter optimization packages corresponding to the vehicle model and ECU version based on the received information; The ECU parameter optimization package uses symmetric encryption, with the key derived from the ECU's unique serial number. The digital signature uses an elliptic curve signature algorithm. After downloading, the digital signature verification, decryption, and local public key and private key verification are performed locally in sequence. After all verifications are successful, the version description file in the upgrade package is extracted. The version description file is compared with the current version of the local ECU field by field. When the hardware number, software number, dependent version number, and checksum are all consistent, the writing process begins.

6. The method according to claim 1, characterized in that, The process of downloading the digitally signed and encrypted ECU parameter optimization package, and writing it to the corresponding ECU after version number verification and security authentication includes: First, the UDS download service is used to request transmission, and then the data is transmitted block by block according to the block transmission protocol. Each block of data is appended with a block sequence number and a CRC32 check value. After the ECU receives the data, it sends back the CRC32 result in real time. If the check fails, the block is immediately retransmitted. After the transmission is complete, the parameter optimization routine is started. The routine sequentially executes the following steps: fuel self-learning adjustment value reset, idle speed self-learning value reset, forced throttle self-learning, 58-tooth gear signal learning, SK code anti-theft activation by scanning and writing code, after-sales general reset, steering wheel zeroing, caliper action parameter optimization, window reset parameter optimization, slope parking parameter optimization, ABS parameter optimization, and ESC parameter optimization. After all the steps are completed, the extended session is exited and the ECU is automatically reset.

7. The method according to claim 1, characterized in that, The process of calling the power battery health assessment model to output a health score and maintenance tips includes: The system reads historical operating parameters of the power battery and vehicle operating parameters uploaded by the battery management system, uses a preset algorithm to extrapolate and calculate the parameters, and performs self-evaluation and scoring through a self-built health model to obtain a health score out of 100. When the health score is lower than a preset threshold, a maintenance prompt is automatically generated, which includes a description of the power battery status and corresponding maintenance suggestions.

8. A new energy vehicle electrical inspection optimization and automatic diagnostic system, characterized in that, include: The communication link establishment module is used to establish a communication link with the vehicle, obtain the list of vehicle ECUs and generate an ECU topology diagram, and collect vehicle message data at all times through the vehicle's OBD port. The UDS diagnostic acquisition module is connected to the communication link establishment module. It is used to send UDS diagnostic commands to each ECU according to the ECU topology diagram, and to collect fault codes and key vehicle operating parameters that are synchronized with the fault code trigger time. The unit component testing module, connected to the communication link establishment module, is used to perform parallel testing of network communication, low-voltage circuit, and high-voltage circuit of vehicle unit components, to determine whether the communication function, electrical circuit function, and mechanical function of the unit components are normal, and to distinguish between communication faults and mechanical faults. The background parsing module is connected to the UDS diagnostic acquisition module and the unit component testing module respectively. It is used to receive fault codes, key vehicle operating parameters and unit component test results, perform semantic parsing on the fault codes and match maintenance guidance information. The network transmission digital signature verification and decryption module is used to perform digital signature verification, decryption, and local public key and private key verification on the downloaded ECU parameter optimization package; The secure flashing module is connected to the backend parsing module and the network transmission digital signature verification and decryption module, respectively. It is used to download the ECU parameter optimization package that has been digitally signed and encrypted, and write it to the corresponding ECU after completing version number verification and security authentication. The report generation and health assessment module is connected to the safe flashing module. It is used to generate an electrical test report after the writing is completed and push it to the display interface. At the same time, it calls the power battery health assessment model to output a health score and maintenance prompts.

9. A computing device, characterized in that, The computing device includes: a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the steps of the method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 7.

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