Vehicle parameter updating method, system and vehicle

Abstract

The application discloses a vehicle parameter updating method, a system and a vehicle. The method comprises the following steps: obtaining vehicle data of a vehicle and driving behavior data of a user; determining vehicle control parameter information of the vehicle based on the vehicle data and the driving behavior data; wherein the vehicle control parameter information comprises a target parameter type and a target parameter value of a target parameter; encapsulating the vehicle control parameter information into a structured communication instruction in a preset format; and sending the structured communication instruction to a domain controller of the vehicle, so that the domain controller parses the structured communication instruction to extract the target parameter type and the target parameter value of the vehicle control parameter information, and sends them to a vehicle actuator, so that the vehicle actuator updates the target parameter based on the target parameter value. According to the embodiment of the application, the flexibility of vehicle parameter updating can be improved.

Description

Technical Field

[0001] This application relates to vehicle parameter updating methods, and more particularly to a vehicle parameter updating method, system, and vehicle. Background Technology

[0002] With the rapid development of intelligent connected vehicles, vehicles have transformed from simple means of transportation into mobile intelligent terminals integrating data collection, real-time computing, and intelligent services. In this process, the various control algorithms and parameters integrated in the vehicle's electronic control unit (ECU) directly determine the vehicle's performance, functional characteristics, and user experience.

[0003] Currently, when a vehicle leaves the factory, its control algorithms and key parameters are typically pre-set and embedded in the vehicle's ECU. When these algorithms or parameters need to be updated, optimized, or repaired, the common approach is over-the-air (OTA) technology. This method requires the complete software or firmware package to be downloaded to the vehicle via a wireless network, verified by the vehicle, and then flashed and installed on the vehicle.

[0004] However, the aforementioned existing technical solutions have significant limitations in practical applications. The main problem lies in the fact that the vehicle-side algorithms and parameters are fixed, and updates rely on over-the-air (OTA) updates, resulting in insufficient system flexibility. This makes it impossible to quickly, dynamically, and precisely adjust parameters and adapt functions based on users' personalized driving habits or the vehicle's real-time operational needs. This rigid update model struggles to meet the demands for personalized experiences and agile services in the era of intelligent vehicles. Summary of the Invention

[0005] This application provides a method, system, and vehicle for updating vehicle parameters, which can improve the flexibility of vehicle parameter updates.

[0006] On one hand, this application provides a vehicle parameter update method applied in the cloud. The method includes: acquiring vehicle data and user driving behavior data; determining vehicle control parameter information based on the vehicle data and driving behavior data; wherein the vehicle control parameter information includes the target parameter type and target parameter value of the target parameter; encapsulating the vehicle control parameter information into a structured communication instruction in a preset format; sending the structured communication instruction to the vehicle's domain controller, so that the domain controller parses the structured communication instruction to extract the target parameter type and target parameter value of the vehicle control parameter information, and sends it to the vehicle actuator, thereby enabling the vehicle actuator to update the target parameter based on the target parameter value.

[0007] In some possible implementations, vehicle control parameter information is encapsulated into a structured communication instruction with a preset format, including: determining the vehicle component and operation type to which the target parameter belongs based on its type; encapsulating the vehicle component and operation type into a first data segment of the structured communication instruction; generating a second data segment containing a type field, a length field, and a value field based on the target parameter type and target parameter value; wherein the type field corresponds to the target parameter type, the length field corresponds to the length of the target parameter value, and the value field corresponds to the target parameter value; and encapsulating the first data segment and the second data segment into a structured communication instruction.

[0008] In some possible implementations, structured communication commands are sent to the vehicle's domain controller, including: sending structured communication commands to the vehicle's domain controller via a telematics terminal.

[0009] In some possible implementations, vehicle data includes vehicle driving data within a preset time period, and driving behavior data includes user driving operation behavior data under target driving conditions; based on vehicle data and driving behavior data, vehicle control parameter information is determined, including: based on vehicle driving data and driving operation behavior data, determining the target parameter type of vehicle control parameter information; and when the driving behavior characteristics of the driving operation behavior data meet preset conditions, determining the target parameter value of vehicle control parameter information.

[0010] In some possible implementations, vehicle control parameter information is determined based on vehicle data and driving behavior data, including: real-time acquisition of vehicle operating status data; identification of whether the vehicle has any abnormalities based on the operating status data; and determination of the target parameter type and target parameter value corresponding to the target abnormality when the vehicle is identified as having a target abnormality.

[0011] In some possible implementations, the method also includes: receiving the updated status of the target parameters; and updating the vehicle's parameter update record in the cloud based on the updated status.

[0012] On the other hand, this application provides a vehicle parameter update method applied to a vehicle's domain controller, comprising: receiving a pre-formatted structured communication command sent from the cloud, wherein the structured communication command is encapsulated based on vehicle control parameter information generated from vehicle data and user driving behavior data; wherein the vehicle control parameter information includes a target parameter type and a target parameter value; parsing the structured communication command to extract the encapsulated target parameter type and target parameter value; and sending the target parameter type and target parameter value to a vehicle actuator so that the vehicle actuator updates the target parameter based on the target parameter value.

[0013] In some possible implementations, the structured communication instruction includes a first data segment and a second data segment. Parsing the structured communication instruction to extract the target parameter type and target parameter value encapsulated therein includes: parsing the first data segment of the structured communication instruction to obtain the vehicle component and operation type therein; and parsing the second data segment of the structured communication instruction according to the vehicle component and operation type to extract the target parameter type and target parameter value in the second data segment.

[0014] In some possible implementations, the second data segment of the structured communication instruction is parsed according to the vehicle component and operation type to extract the target parameter type and target parameter value from the second data segment. This includes: parsing the second data segment to obtain the type field, length field, and value field; determining the target parameter type according to the vehicle component, operation type, and type field; and reading the corresponding data from the value field as the target parameter value according to the length field.

[0015] In some possible implementations, receiving a pre-formatted structured communication instruction sent from the cloud includes: receiving a structured communication instruction sent from the cloud to a remote information processing terminal and forwarded by the remote information processing terminal.

[0016] On the other hand, embodiments of this application provide a vehicle parameter update system, the system including a cloud and a domain controller, including: In the cloud, vehicle data and user driving behavior data are acquired; based on the vehicle data and driving behavior data, vehicle control parameter information is determined; the vehicle control parameter information includes the target parameter type and target parameter value; the vehicle control parameter information is encapsulated into a pre-formatted structured communication command; the structured communication command is sent to the vehicle's domain controller, so that the domain controller can parse the structured communication command to extract the target parameter type and target parameter value of the vehicle control parameter information, and send it to the vehicle actuator, thereby enabling the vehicle actuator to update the target parameter based on the target parameter value; The domain controller receives pre-formatted structured communication commands from the cloud. These commands are encapsulated based on vehicle control parameter information generated from vehicle data and user driving behavior data. The vehicle control parameter information includes the target parameter type and target parameter value. The controller parses the structured communication commands to extract the encapsulated target parameter type and target parameter value. It then sends the target parameter type and target parameter value to the vehicle actuators, enabling the actuators to update the target parameters based on the target parameter values.

[0017] On the other hand, embodiments of this application provide a cloud platform, including: The acquisition module is used to acquire vehicle data and user driving behavior data; The determination module is used to determine the vehicle control parameter information of the vehicle based on vehicle data and driving behavior data; wherein, the vehicle control parameter information includes the target parameter type and the target parameter value of the target parameter; The encapsulation module is used to encapsulate vehicle control parameter information into structured communication commands in a preset format; The distribution module is used to distribute structured communication commands to the vehicle's domain controller, so that the domain controller can parse the structured communication commands to extract the target parameter type and target parameter value of the vehicle control parameter information, and send them to the vehicle actuators, thereby enabling the vehicle actuators to update the target parameters based on the target parameter values.

[0018] On the other hand, embodiments of this application provide a domain controller, including: The receiving module is used to receive structured communication commands in a preset format sent from the cloud. The structured communication commands are encapsulated based on vehicle control parameter information generated from vehicle data and user driving behavior data. The vehicle control parameter information includes the target parameter type and target parameter value. The parsing module is used to parse structured communication instructions and extract the target parameter types and values ​​encapsulated within them. The sending module is used to send the target parameter type and target parameter value to the vehicle actuator, so that the vehicle actuator can update the target parameter based on the target parameter value.

[0019] In another aspect, embodiments of this application provide a vehicle, which includes: a processor and a memory storing computer program instructions; the processor executes the computer program instructions to implement a method for updating vehicle parameters.

[0020] The vehicle parameter update method, system, and vehicle of this application embodiment generate adapted vehicle control parameters in the cloud based on actual vehicle operating data and user driving behavior data. This allows parameter adjustments to move beyond factory presets or full software updates, enabling personalized and dynamic parameter adaptation. The vehicle control parameter information is encapsulated into structured communication commands in a preset format and sent to the vehicle domain controller, replacing the traditional OTA full software or firmware package transmission. Parameter updates can be completed without complex flashing procedures, breaking the limitations of fixed parameters and significantly improving system flexibility. The entire process, through the collaboration of cloud analysis and vehicle-side execution, leverages the data processing advantages of the cloud while ensuring the real-time nature of vehicle-side parameter updates. This allows the vehicle to quickly respond to users' personalized driving habits and real-time operating needs, achieving refined parameter adjustments and fully meeting the demands for personalized experiences and agile services in the era of intelligent vehicles. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the structure of a vehicle parameter update system provided in one embodiment of this application; Figure 2 This is a schematic flowchart of a vehicle parameter update method provided in one embodiment of this application; Figure 3 This is a schematic flowchart of a vehicle parameter update method provided in one embodiment of this application; Figure 4 This is a schematic flowchart of a vehicle parameter update method provided in one embodiment of this application; Figure 5 This is a schematic diagram of the cloud structure provided in another embodiment of this application; Figure 6 This is a schematic diagram of the structure of a domain controller provided in another embodiment of this application; Figure 7 This is a structural schematic diagram of a vehicle provided in another embodiment of this application. Detailed Implementation

[0023] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0024] It should be noted that, in this document, relational terms such as "first" and "second" are used merely 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 vehicle 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 vehicle. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or vehicle that includes the element.

[0025] It should be noted that the acquisition, storage, use, and processing of data in this application embodiment all comply with the relevant provisions of national laws and regulations.

[0026] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0027] In existing technologies, vehicle control parameter updates rely on over-the-air (OTA) updates for the entire vehicle, making personalized dynamic adjustments impossible. From a technical architecture perspective, traditional solutions lack a lightweight collaborative mechanism for vehicle-cloud integration. Pure vehicle-side computing is limited by the ECU's computing power, making it unable to deeply analyze massive amounts of user driving behavior data (such as operating habits under different conditions) and vehicle lifecycle operation data, relying solely on factory-preset fixed parameters. While pure cloud computing has computing power advantages, existing technologies lack precise transmission and parsing channels for parameter updates, requiring OTA updates via the distribution of complete software / firmware packages. This necessitates parameter adjustments being tied to overall software remapping, preventing independent and rapid completion. Furthermore, the communication protocol between the vehicle and cloud is rigidly designed, failing to support customized encapsulation and parsing of dynamic parameters. This makes it unsuitable for personalized scenarios where "each vehicle has different parameter requirements," necessitating standardized parameter configurations that fail to match the varying driving habits of different users (e.g., sporty users' demand for peak power versus economy users' demand for energy recovery).

[0028] From the perspective of data utilization and execution mechanisms, on the one hand, the high-frequency driving behavior data and real-time operating status data generated during vehicle operation lack efficient filtering and uploading mechanisms. Full uploading would lead to a surge in communication and storage costs, while partial uploading cannot meet the needs of accurate cloud analysis, resulting in a lack of data support for the generation of personalized parameters. On the other hand, there is a lack of direct linkage mechanism between cloud AI models and vehicle-side actuators (such as BMS and powertrain systems). The cloud cannot generate targeted parameters based on data analysis results and distribute them separately, and the vehicle cannot quickly parse and execute personalized parameter updates. It can only passively receive unified OTA upgrade packages, ultimately resulting in insufficient flexibility and refinement of parameter adjustments, making it difficult to adapt to the needs of personalized experience and agile services in the era of intelligent vehicles.

[0029] The vehicle parameter update method of this application generates adapted vehicle control parameters in the cloud based on actual vehicle operating data and user driving behavior data. This allows parameter adjustments to move beyond factory presets or full software updates, enabling personalized and dynamic parameter adaptation. The vehicle control parameter information is encapsulated into structured communication commands in a preset format and sent to the vehicle domain controller, replacing the traditional OTA full software or firmware package transmission. Parameter updates can be completed without complex flashing procedures, breaking the limitations of fixed parameters and significantly improving system flexibility. The entire process, through the collaboration of cloud analysis and vehicle-side execution, leverages the data processing advantages of the cloud while ensuring the real-time nature of vehicle-side parameter updates. This allows the vehicle to quickly respond to users' personalized driving habits and real-time operating needs, achieving refined parameter adjustments and fully meeting the demands for personalized experiences and agile services in the era of intelligent vehicles.

[0030] To address the problems of the prior art, this application provides a vehicle parameter updating method, system, and vehicle. The vehicle parameter updating method provided in this application will be described first.

[0031] Figure 1 A schematic diagram of the structure of a vehicle parameter update system provided in one embodiment of this application is shown. Figure 1 As shown, the system 100 includes a cloud 101, a domain controller 102, and a vehicle actuator 103.

[0032] As an example, Cloud 101 can refer to the core computing terminal for vehicle-cloud collaboration that has an AI algorithm platform, data storage and analysis capabilities, and integrates functions such as fault diagnosis, early warning algorithms, SOH (State of Health) estimation and parameter configuration, and can process all vehicle lifecycle data.

[0033] As an example, the domain controller 102 can refer to the core control unit on the vehicle side, which is used to receive instructions issued by the cloud 101, parse them and forward the signals to the vehicle actuator 103. It can communicate with the TBOX (Telematics Box) and the vehicle actuator 103 via CAN / FlexRay or Ethernet.

[0034] As an example, vehicle actuator 103 can refer to vehicle components that receive parameter information forwarded by domain controller 102 and perform parameter updates, including BMS (Battery Management System), power system, instrument control, etc., and is the actual application unit of vehicle control parameters.

[0035] Figure 2 A flowchart illustrating a vehicle parameter update method according to an embodiment of this application is shown. Figure 2 As shown, the method includes the following steps.

[0036] S201, acquires vehicle data and user driving behavior data from the cloud.

[0037] As an example, vehicle data can be various operation-related data generated throughout the vehicle's entire lifecycle, including vehicle component status data, driving condition data, energy management data, etc., covering the operating information of components such as BMS (Engine Management System), EMS (Engine Management System), and IBS (Intelligent Battery Sensor).

[0038] As an example, driving behavior data can be data reflecting driving habits generated during the user's operation of the vehicle, including operational behavior data under driving conditions, vehicle speed change data, pedal control data, etc.

[0039] Specifically, as an example, the vehicle-mounted system collects vehicle data and user driving behavior data during vehicle operation according to preset data collection rules, and packages the collected data into binary byte streams. Through the vehicle's TBOX, using a data upload service based on the SOME / IP protocol, the packaged data is uploaded to the cloud. The cloud receives and stores the uploaded data, providing data support for subsequent parameter analysis. During the data upload process, key data can be filtered according to actual needs to reduce the impact of unstable network signals on data transmission and ensure the complete upload of core data.

[0040] S202, the cloud determines the vehicle control parameter information based on vehicle data and driving behavior data; among which, the vehicle control parameter information includes the target parameter type and the target parameter value of the target parameter.

[0041] As an example, vehicle control parameter information can refer to a set of parameters used to regulate the operating state of vehicle actuators, including the specific categories of parameters and their corresponding values, which may cover power parameters, performance parameters, SOC (State of Charge) parameters, balancing parameters, etc.

[0042] As an example, the target parameter type can refer to the specific category identifier of the parameter in the vehicle control parameter information, which is defined by preset coding rules, including maximum continuous discharge power, peak discharge power, maximum charging power, etc., while reserving extended types.

[0043] As an example, the target parameter value can refer to a specific numerical value corresponding to the target parameter type, which is used to clarify the operating standards of the vehicle actuators and is dynamically generated based on the user's driving habits or the vehicle's operating status.

[0044] Specifically, as an example, for predictive maintenance scenarios, the target parameter types and target parameter values ​​that are suitable for vehicle maintenance needs can be determined by combining short-term feature data uploaded from the vehicle and long-term trend analysis results from the cloud.

[0045] As another implementation of S202, vehicle data includes vehicle driving data within a preset time period, driving behavior data includes user driving operation behavior data under target driving conditions, and S202 may also include the following steps.

[0046] As an example, vehicle driving data can refer to relevant data reflecting the driving status generated by a vehicle during its operation within a preset time period, including vehicle speed data, driving condition data, and driving road segment type data, covering vehicle operation information in different scenarios such as highway driving and urban road driving.

[0047] As an example, driving operation behavior data can refer to the relevant data generated when a user operates a vehicle under target driving conditions, including pedal control data, steering operation data, acceleration and deceleration frequency data, etc., which directly reflect the user's driving operation habits.

[0048] Based on vehicle driving data and driving operation behavior data, the target parameter type of the vehicle control parameter information is determined.

[0049] Specifically, as an example, after receiving vehicle driving data and driving behavior data uploaded by the vehicle, the cloud platform uses an AI algorithm platform to perform correlation analysis on the two types of data. First, the vehicle driving data is categorized and filtered to identify the main road types and operating conditions the vehicle is driving on, such as determining whether the vehicle is frequently in high-speed driving conditions or urban congestion conditions. Simultaneously, features are extracted from the driving behavior data to analyze the user's operational preferences under different driving conditions, such as whether they frequently perform deep acceleration or rapid acceleration, or whether they prefer smooth driving and frequent braking to recover energy.

[0050] Specifically, as an example, the target parameter type is matched by combining driving condition characteristics with user operation preferences. If vehicle driving data shows that the vehicle is in a high-speed driving condition for a long time, and driving behavior data reflects that the user frequently accelerates rapidly and presses the accelerator pedal deeply, it indicates that the user has a high demand for vehicle power performance. In this case, the target parameter type is determined to be peak discharge power. If vehicle driving data is mainly in urban congestion conditions, and driving behavior data shows that the user frequently brakes and focuses on energy conservation, then the target parameter type is determined to include maximum charging power and energy recovery-related parameters. Through this data correlation analysis method, it is ensured that the target parameter type is accurately matched with the vehicle usage scenario and user driving needs.

[0051] When the driving behavior data and driving behavior characteristics meet preset conditions, the target parameter values ​​of the vehicle control parameter information are determined.

[0052] As an example, driving behavior characteristics can refer to the regular user driving operation attributes extracted from driving operation behavior data, including acceleration intensity characteristics, high-speed driving operation characteristics, braking frequency characteristics, etc., which are the core basis for judging user driving habits.

[0053] As an example, preset conditions can refer to judgment criteria based on a large amount of vehicle operation data and user driving behavior data, used to measure whether driving behavior characteristics have reached the thresholds that require parameter adjustment, including operation frequency thresholds, operation intensity thresholds, and operating condition duration thresholds.

[0054] As an example, the target parameter value can refer to a specific numerical value corresponding to the target parameter type, which is dynamically generated based on driving behavior characteristics and vehicle performance limitations to ensure that the parameter adjustment conforms to the vehicle's hardware capabilities and meets the user's driving needs.

[0055] Specifically, as an example, pre-defined criteria for judging driving behavior characteristics are set for different target parameter types. For the preset conditions corresponding to peak discharge power, frequency and duration thresholds for deep accelerator pedal operation under high-speed driving conditions are set; for example, if the proportion of high-speed driving conditions reaches a preset percentage and the frequency of deep accelerator pedal operation exceeds a set value. For the preset conditions corresponding to maximum charging power, frequency thresholds for braking operation and thresholds related to energy recovery demand during urban road driving are set.

[0056] Specifically, as an example, a cloud-based AI model quantifies and analyzes driving behavior characteristics in driving operation data to determine whether they meet preset conditions. If the driving behavior characteristics show that the user frequently depresses the accelerator pedal deeply in 90% of high-speed driving conditions, and the maximum vehicle speed consistently exceeds the set value, then the preset conditions for peak discharge power adjustment are met. In this case, the AI ​​model combines battery health status data and powertrain performance data from the vehicle's entire lifecycle data to generate corresponding target parameter values. For example, considering both the vehicle's hardware capabilities and the current battery health status, the target parameter value for peak discharge power is determined to be 300kW.

[0057] Specifically, as an example, if driving behavior characteristics meet the preset conditions for adjusting energy recovery-related parameters—that is, the braking frequency in urban congestion reaches a set threshold—then, based on the battery's current state of charge and the performance of the energy recovery system, the target parameter value for the maximum charging power is determined to be 120kW, and a corresponding energy recovery intensity parameter value is set. The determination of the target parameter value must balance user driving needs with the operational safety of vehicle components, ensuring that while the vehicle's performance is improved after parameter adjustment, the lifespan of the vehicle's core components is not affected.

[0058] The vehicle parameter update method in this application directly links vehicle driving data and driving operation behavior data under target conditions with vehicle usage scenarios and user operating habits, making the determination of target parameter types more in line with actual usage needs and ensuring the targeted nature of parameter adjustments. Preset conditions provide clear judgment criteria for determining target parameter values, avoiding blind adjustment of parameter values ​​and ensuring that parameter values ​​are accurately matched with user driving behavior characteristics, achieving personalized and refined parameter adjustments. Based on the parameter generation logic of specific operating conditions and operation data, vehicle control parameters can dynamically adapt to different driving scenarios (such as highway conditions and urban road conditions), improving the vehicle's operational adaptability and user experience in various scenarios.

[0059] As another implementation of S202, S202 may also include the following steps.

[0060] Real-time acquisition of vehicle operating status data.

[0061] As an example, operational status data can refer to the dynamic status information generated by various core components of a vehicle during real-time operation. It covers the operating parameters of key components such as the battery system, engine system, and intelligent sensors, including battery voltage, current, and temperature data, engine operating parameters, and component operating status signals. It is the basic data for determining whether the vehicle is operating normally.

[0062] Specifically, as an example, the vehicle collects real-time operational status data through sensors and control units distributed across various core components, including the BMS and EMS. The vehicle-side edge computing controller integrates and processes the collected, dispersed operational status data according to preset data acquisition rules, packaging it into binary byte streams. The packaged operational status data is then transmitted to the cloud in real-time via TBOX's data upload service based on the SOME / IP protocol. During transmission, the vehicle-cloud collaborative communication architecture avoids communication pressure caused by uploading full volumes of high-frequency data, prioritizing the real-time performance and integrity of core operational status data. Upon receiving the data, the cloud immediately stores it and incorporates it into an analysis queue, providing data support for subsequent anomaly identification.

[0063] Based on operational status data, identify whether there are any abnormalities in the vehicle.

[0064] As an example, an anomaly can refer to a situation where the vehicle's operating status data deviates from the preset normal range, or the working status of core components does not meet the design standards, including various unexpected operating states such as component performance degradation, exceeding operating parameters, and potential fault hazards.

[0065] Specifically, as an example, the cloud-based AI algorithm platform initiates fault diagnosis and early warning algorithms to continuously analyze the real-time received operational status data. Based on a normal operation parameter threshold system built from full vehicle lifecycle data, it compares the real-time operational status data with preset thresholds and extracts characteristic trends from the data. The cloud-based AI early warning model monitors data dynamics 24 / 7, analyzes battery health status data using SOH estimation algorithms, and combines this with correlation analysis of operational parameters from components such as EMS and IBS to identify whether parameters exceed limits, data abruptly change, or trends are abnormal. If the operational parameters of a core component consistently exceed the preset normal range, or if logical contradictions occur between data from different components, the vehicle is deemed to be malfunctioning.

[0066] When an abnormal state of a vehicle is detected, the target parameter type and target parameter value corresponding to the abnormal state are determined.

[0067] As an example, a target abnormal state can refer to a specific abnormal state that has been identified and confirmed by the cloud and requires adjustment of vehicle control parameters to deal with or mitigate it. It has a clear scope of impact and response requirements, including specific abnormal situations such as abnormal battery temperature and unstable power output.

[0068] As an example, the correspondence can refer to the preset matching rules between the target abnormal state and the vehicle control parameters. That is, a specific abnormal state needs to be mitigated or the fault dealt with by adjusting a specific type of control parameters. This rule is built based on a large number of fault cases and component characteristic data.

[0069] Specifically, as an example, the cloud pre-establishes a dictionary mapping target abnormal states to target parameter types, clearly defining the parameter categories that need to be adjusted for different abnormal states. When a target abnormal state is identified in the vehicle, the cloud-based AI model calls this dictionary to determine the appropriate target parameter type. For example, when a target abnormal state of high battery temperature is identified, the corresponding target parameter type is maximum continuous discharge power; when a target abnormal state of unstable power output is identified, the corresponding target parameter type is peak discharge power.

[0070] Specifically, as an example, target parameter values ​​are generated by combining vehicle lifecycle data, current operating status data, and component hardware limitations. If the abnormality is due to battery overheating, the target parameter value for maximum continuous discharge power is adjusted to a value lower than that under normal operating conditions to avoid component damage. If the abnormal power output is caused by a potential fault, the target parameter value for peak discharge power is adjusted to a reasonable range to ensure safe operation. The encoding of target parameter types follows preset Param Type encoding rules, and existing encodings or reserved extended type encodings can be used to ensure compatibility with the encapsulation requirements of subsequent structured communication commands. The setting of target parameter values ​​must balance the effectiveness of anomaly response with the operational safety of core vehicle components.

[0071] The vehicle parameter update method in this application embodiment acquires real-time operating status data to ensure that the cloud can promptly grasp the current operating status of the vehicle, providing real-time data support for anomaly identification and enabling timely detection of vehicle anomalies. Based on the anomaly identification logic of the operating status data, it can accurately determine whether the vehicle has an unexpected operating state, providing clear triggering conditions for parameter adjustment. For the target anomaly state, it determines the corresponding target parameter type and target parameter value, making parameter adjustment targeted for fault response and risk mitigation, avoiding damage to vehicle components caused by the expansion of anomalies, and ensuring vehicle operating safety. It does not rely on the limited diagnostic computing power of the vehicle end, but achieves anomaly identification and parameter adaptation through the analysis of full operating status data in the cloud, making up for the limitations of the vehicle end's diagnostic capabilities.

[0072] S203, the cloud encapsulates vehicle control parameter information into structured communication commands in a preset format.

[0073] As an example, structured communication commands can encapsulate vehicle control parameter information and serve as a standardized data carrier for data transmission between the vehicle and the cloud. Built on the SOME / IP protocol, it ensures the standardization and compatibility of transmission.

[0074] As an example, a pre-formatted structured communication instruction refers to a binary message body that conforms to the vehicle-to-everything (V2X) communication protocol specification and has clear field division and semantic parsing rules. Its structural design takes into account both scalability and compatibility, and supports adding parameter types without modifying the underlying protocol stack. For example, if it is encapsulated using the SOME / IP protocol, its payload part follows the TLV (Type-Length-Value) encoding format, where the Type field corresponds to the target parameter type, the Length field indicates the byte length of the Value field, and the Value field carries the original binary representation of the target parameter value.

[0075] In one alternative implementation, the encapsulation method is as follows: the target parameter type is encoded as a uint16 type field, the target parameter value is serialized into float32 format according to the IEEE 754 standard and written into the Value field, and then concatenated in TLV order to form the Payload, and then filled with SOME / IP Message Header and Service Header to form a complete instruction.

[0076] In another alternative implementation, the encapsulation method includes: batch packaging multiple target parameter types and their parameter values ​​to generate a composite payload containing multiple TLV units, and setting the Total SegmentCount field in the Header to indicate the number of segments.

[0077] Furthermore, this encapsulation method also employs the following approach: embedding verification fields (such as CRC16) and timeliness fields (such as Timestamp) in the instructions to support vehicle-side integrity verification and timeliness verification.

[0078] S204, the cloud sends structured communication commands to the vehicle's domain controller.

[0079] In one alternative implementation, the delivery method is as follows: the structured communication command is pushed to the cloud platform access point bound to the TBOX via HTTPS or MQTT protocol, the TBOX completes the protocol conversion and transparent transmission, and finally sends it to the domain controller via the vehicle Ethernet.

[0080] In another optional implementation, the delivery method includes: using a breakpoint resume mechanism, temporarily storing the instructions in a persistent queue in the cloud when the TBOX is detected to be offline, and then delivering them in priority order after reconnection.

[0081] Furthermore, this distribution method also employs differentiated QoS (Quality of Service) scheduling based on instruction priority labels (such as "emergency fault response" and "routine performance optimization") to ensure that the end-to-end transmission latency of high-priority instructions is below a set threshold.

[0082] As another implementation of S204, S204 may also include the following steps.

[0083] The cloud sends structured communication commands to the vehicle's domain controller via a telematics terminal. Correspondingly, the domain controller receives the structured communication commands sent from the cloud to the telematics terminal and then forwarded by the telematics terminal.

[0084] As an example, the remote information processing terminal, or TBOX, is the core relay component of vehicle-to-cloud communication. It has data receiving and transparent transmission functions, does not participate in command parsing, and is only responsible for establishing a communication link between the cloud and the domain controller.

[0085] Specifically, as an example, after the cloud completes the encapsulation of structured communication commands, it initiates the command delivery process via a wireless network. Following the SOME / IP protocol's communication specifications, the cloud transmits the commands to the target vehicle's remote information processing terminal (RAD). Upon receiving the commands, the RAD follows a pre-defined communication mechanism, without parsing the command content, acting only as a relay node for signal pass-through. This pass-through process eliminates the need for the complex verification and flashing processes of traditional OTA updates, directly forwarding the complete structured communication commands to the vehicle's domain controller. During transmission, the stability of the SOME / IP protocol ensures that critical data loss due to network signal instability is avoided, while reducing the communication costs associated with uploading high-frequency data in its entirety. This ensures that commands are delivered to the domain controller quickly and in a lightweight manner, laying the foundation for subsequent parameter parsing and updates.

[0086] Specifically, as an example, the domain controller establishes a stable communication connection with the remote information processing terminal via Ethernet or CAN / FlexRay bus, continuously monitoring the signal transmission status of the remote information processing terminal. When the remote information processing terminal forwards a structured communication command, the domain controller receives the command through a preset communication interface. During the reception process, the domain controller performs a preliminary integrity check on the command based on the underlying specifications of the SOME / IP protocol, confirming whether the format of the command's Header field conforms to preset requirements, such as whether key fields like Message ID and Protocol Version are valid, to eliminate potential data corruption or illegal commands during transmission. After successful verification, the domain controller stores the structured communication command, preparing for subsequent parsing and extraction of target parameter types and values. This reception mechanism adapts to the flexible computing architecture of vehicle-cloud collaboration, solving the problems of limited computing power on the pure vehicle side and the difficulty of fixed communication protocols supporting dynamic command transmission, ensuring the reliability and efficiency of command reception.

[0087] The vehicle parameter update method of this application embodiment utilizes the relay and transparent transmission function of the remote information processing terminal to complete the instruction transmission from the cloud to the domain controller without a physical connection, realizing remote operation of parameter updates and improving ease of use. As a dedicated communication component, the remote information processing terminal can ensure the reliability of structured communication instruction transmission, reduce the impact of network signal fluctuations on instruction transmission, and avoid the loss of key parameter instructions. Instructions are directly sent to the domain controller through the terminal, omitting the complex verification and flashing process of traditional OTA, shortening the time consumption of instruction transmission and parameter updates, and improving the timeliness of parameter adjustment.

[0088] S205, the domain controller parses the structured communication instructions to extract the target parameter type and target parameter value of the vehicle control parameter information, and sends it to the vehicle actuator.

[0089] As an example, parsing can refer to the process by which a domain controller extracts the target parameter type and target parameter value encapsulated in a structured communication command according to the SOME / IP protocol specification and preset dictionary rules.

[0090] As an example, a vehicle actuator can refer to a vehicle component that receives parameter information forwarded by the domain controller and performs parameter updates, including BMS, powertrain system, instrument control, etc., and is the actual application unit of vehicle control parameters.

[0091] Specifically, as an example, after receiving the structured communication command passed through the TBOX, the domain controller first parses the Service ID and Method ID in the Header section to determine the vehicle component and operation type corresponding to the command. For example, Service ID 02 identifies it as a powertrain-related parameter, and Method ID 01 identifies it as a discharge power parameter operation. Then, it parses the Payload section, determining the target parameter type based on the encoding and dictionary rules of the Param Type field; combined with the value of the Data Length field, it reads the corresponding length of data from the Value Data field as the target parameter value. After parsing, the domain controller converts the target parameter type and target parameter value into a CAN signal and sends it to the corresponding vehicle actuator via the CAN / FlexRay bus. For example, it sends the peak discharge power parameter to the BMS, and sends the light-up command parameter corresponding to the fault warning to the instrument cluster control.

[0092] S206, The vehicle actuator updates the target parameters based on the target parameter values.

[0093] As an example, parameter updating can refer to the process by which a vehicle actuator receives a target parameter value, replaces the original parameter, and applies the new parameter to actual operation, thereby achieving dynamic adjustment of vehicle performance.

[0094] Specifically, as an example, after receiving the CAN signal from the domain controller, the vehicle actuator identifies the target parameter that needs to be updated through internal communication flags. For instance, after receiving the CAN signal corresponding to the peak discharge power, the BMS recognizes that this parameter needs to be updated and replaces the original peak discharge power parameter with the received target parameter value of 300kW. After the parameter update is completed, the vehicle actuator generates execution status information to indicate whether the parameter update was successful or failed. This execution status information is then transmitted back to the domain controller via Ethernet, and the domain controller then feeds it back to the cloud, forming a complete parameter update closed loop. Users do not need to perform any additional operations during the parameter update process, achieving seamless upgrades and improving the user experience.

[0095] The vehicle parameter update method of this application generates adapted vehicle control parameters in the cloud based on actual vehicle operating data and user driving behavior data. This allows parameter adjustments to move beyond factory presets or full software updates, enabling personalized and dynamic parameter adaptation. The vehicle control parameter information is encapsulated into structured communication commands in a preset format and sent to the vehicle domain controller, replacing the traditional OTA full software or firmware package transmission. Parameter updates can be completed without complex flashing procedures, breaking the limitations of fixed parameters and significantly improving system flexibility. The entire process, through the collaboration of cloud analysis and vehicle-side execution, leverages the data processing advantages of the cloud while ensuring the real-time nature of vehicle-side parameter updates. This allows the vehicle to quickly respond to users' personalized driving habits and real-time operating needs, achieving refined parameter adjustments and fully meeting the demands for personalized experiences and agile services in the era of intelligent vehicles.

[0096] As another implementation of this application, in order to improve the scalability of instruction encapsulation, such as Figure 3 As shown, S203 may also include the following steps.

[0097] S301, based on the target parameter type, determines the vehicle component and operation type to which it belongs.

[0098] As an example, a vehicle component can refer to a core component or system in a vehicle that performs a specific function, including the powertrain system, battery management system, etc., and is the object of vehicle control parameters.

[0099] As an example, operation type can refer to the specific action category performed on vehicle control parameters, including discharge power adjustment, charging power configuration, etc., which are directly related to parameter functions.

[0100] Specifically, as an example, the cloud pre-defines a mapping dictionary between target parameter types and vehicle components and operation types. Target parameter types are identified by Param Type encoding, such as 0x0101 corresponding to maximum continuous discharge power, 0x0102 to peak discharge power, and 0x0103 to maximum charging power. By querying the mapping dictionary based on the encoding, 0x0101 and 0x0102 belong to the powertrain system, with an operation type of discharge power adjustment; 0x0103 belongs to the battery management system, with an operation type of charging power configuration. This mapping relationship quickly clarifies the corresponding vehicle component and operation type for each parameter, providing a foundation for instruction encapsulation.

[0101] S302 encapsulates vehicle components and operation types into the first data segment of a structured communication instruction.

[0102] As an example, the first data segment can refer to the header area of ​​a structured communication instruction, i.e., the Header section, which contains fixed fields that identify vehicle components, operation types, and basic instruction information, in accordance with the SOME / IP protocol specification.

[0103] Specifically, as an example, the Message ID field of the first data segment consists of a 2-byte Service ID and a 2-byte Method ID. The Service ID identifies the vehicle component, with 02 corresponding to the powertrain system and a preset code corresponding to the battery management system. The Method ID identifies the operation type, with 01 corresponding to discharge power adjustment and a preset code corresponding to charging power configuration. This completes the encapsulation of the first data segment, ensuring standardized transmission of vehicle component and operation type information.

[0104] S303, based on the target parameter type and target parameter value, generate a second data segment containing a type field, a length field, and a value field; wherein, the type field corresponds to the target parameter type, the length field corresponds to the length of the target parameter value, and the value field corresponds to the target parameter value.

[0105] As an example, the second data segment can refer to the payload area of ​​a structured communication instruction, i.e., the Payload part, which uses a TLV structure to encapsulate the specific information of the target parameters, ensuring the flexibility and compatibility of parameter transmission.

[0106] As an example, the type field can refer to a uint16 type field that corresponds to the Param Type encoding and identifies the type of the target parameter.

[0107] As an example, the length field can be a uint16 type field that identifies the actual number of bytes in the value field, making it easier to skip unknown type parameters during parsing.

[0108] As an example, a value field can refer to a byte array that stores the specific numerical value of the target parameter, generated based on the parameter's data type.

[0109] Specifically, as an example, the type field is filled with the Param Type encoding of the target parameter type, such as 0x0102 corresponding to peak discharge power. The target parameter value is of type float32, such as 300.0kW. After being converted to a 4-byte stream, the length field is filled with 4. The type field, length field, and value field are concatenated in TLV format order to form a TLV structure for a single parameter. If there are multiple parameter segments, multiple TLV structures are concatenated sequentially according to the number indicated by the Total Segment Count field to form a complete second data segment.

[0110] S304 encapsulates the first and second data segments into structured communication instructions.

[0111] Specifically, as an example, following the SOME / IP protocol requirements, the first data segment (Header) is placed at the beginning, followed immediately by the second data segment (Payload), concatenating them to form a complete structured communication instruction. The Length field of the first data segment is filled with the total number of bytes in the second data segment, ensuring accurate identification of the load range during parsing. After encapsulation, the instruction contains both identification information of vehicle components and operation types, as well as the specific content of the parameters, meeting the parsing requirements of the vehicle-side domain controller and achieving accurate parameter transmission.

[0112] The vehicle parameter update method in this application embodiment encapsulates vehicle components and operation types in the first data segment, enabling the domain controller to quickly locate the target and operation attributes of the parameters, providing clear guidance for subsequent parsing and improving parsing efficiency. The second data segment adopts a type-length-value field structure, which can accurately carry the core information of the target parameter type and target parameter value, and the length field is adapted to the actual length of the value field, ensuring the complete transmission and accurate reading of parameter data. The combination and encapsulation of the two data segments form a standardized structured communication instruction, giving the instruction a unified parsing rule, adapting to the communication needs between the vehicle and the cloud, and ensuring the stability and compatibility of parameter transmission. It can adapt to the encapsulation of different target parameter types without modifying the protocol structure, providing a basis for parameter expansion and improving the scalability of instruction encapsulation.

[0113] As another implementation of this application, the method may further include the following steps.

[0114] Receive the updated status of the target parameters.

[0115] As an example, the update status can refer to the feedback information after the vehicle actuator completes the update of the target parameters, including clear execution results such as successful update or update failure, which is the core basis for verifying whether the parameter adjustment has taken effect.

[0116] Specifically, as an example, after a vehicle actuator such as a BMS updates its target parameters, it generates corresponding update status information. This status information is transmitted to the domain controller via Ethernet. The domain controller processes the status information according to the SOME / IP protocol specification, converting it into a standardized response command. The Message Type of the response command is set to RESPONSE=0x10, and the Return Code field is filled with the response code corresponding to the update status. Subsequently, the domain controller sends the response command to the TBOX via the CAN / FlexRay bus. The TBOX does not parse the command content but only transmits it to the cloud based on the SOME / IP protocol. The cloud AI algorithm platform receives the transmitted response command, verifies the integrity of the command format according to the protocol specification, extracts the update status information, and completes the reception process.

[0117] Based on the updated status, update the vehicle's parameter update records in the cloud.

[0118] As an example, parameter update records can refer to a collection of information related to the entire process of vehicle control parameter adjustment stored in the cloud. This includes key data such as the vehicle's unique identifier, target parameter type, target parameter value, update time, and update status, which is used to trace the history of parameter adjustments and support subsequent data analysis.

[0119] Specifically, as an example, after obtaining the update status from the cloud, the system associates the vehicle's Vehicle Profile ID (a unique vehicle tag generated in the cloud) and extracts key information about this parameter update: the ParamType code corresponding to the target parameter type, the target parameter value, the update status, and the current Timestamp. This information is then linked to the vehicle's full lifecycle data and updated to the parameter update record in the cloud database. If the update status is successful, the parameter's effective time is recorded; if it fails, the response code corresponding to the reason for the failure is noted. The updated record supports subsequent queries and statistical analysis, providing data support for AI model parameter customization strategies and predictive vehicle maintenance, ensuring the entire parameter adjustment process is traceable.

[0120] The vehicle parameter update method of this application embodiment enables the cloud to obtain the execution result (success / failure) of parameter update in real time, forming a closed-loop monitoring of parameter update and timely detection of abnormal situations in the parameter update process; the updating and storage of parameter update records realizes the traceability of the entire process of vehicle control parameter adjustment, providing data support for subsequent parameter optimization, fault diagnosis and vehicle maintenance; based on the historical data in the update records, the cloud parameter generation logic can be further optimized to improve the accuracy and adaptability of subsequent parameter adjustments, forming a continuous optimization mechanism for parameter adjustment.

[0121] As another implementation of S205, structured communication instructions include a first data segment and a second data segment, such as... Figure 4 As shown, S205 may also include the following steps.

[0122] S401, parse the first data segment of the structured communication instruction to obtain the vehicle components and operation type.

[0123] As an example, the first data segment can refer to the header area of ​​a structured communication command, which follows the SOME / IP protocol specification and contains fixed fields such as Message ID and Length. Its core purpose is to identify the vehicle function object and operation attributes associated with the command.

[0124] As an example, a vehicle component can refer to the core functional part or system of the vehicle to which the instruction is directed, and is the object to which the parameter adjustment is applied, such as the power system, battery management system, etc.

[0125] As an example, the operation type can refer to the specific parameter operation category of a vehicle component, such as discharge power adjustment, charging power configuration, etc., which are directly related to the parameter function.

[0126] Specifically, as an example, after receiving a structured communication command, the domain controller first parses the first data segment. It extracts the 4-byte Message ID field and splits it into a 2-byte Service ID and a 2-byte Method ID according to protocol rules. The domain controller has a built-in mapping dictionary between Service IDs and vehicle components; for example, a Service ID of 02 corresponds to the powertrain system. It also uses a preset mapping relationship between Method IDs and operation types; for example, a Method ID of 01 corresponds to discharge power adjustment. Combining these two mapping relationships, the domain controller clarifies the vehicle component and operation type corresponding to the command from the split IDs, providing direction for the accurate parsing of the second data segment.

[0127] S402, based on vehicle components and operation type, parses the second data segment of the structured communication command and extracts the target parameter type and target parameter value from the second data segment.

[0128] As an example, the second data segment can refer to the payload area of ​​a structured communication instruction, which is constructed using a TLV (Type-Length-Value) + structure concatenation method to store the specific type and numerical information of the parameters.

[0129] Specifically, as an example, the domain controller, based on the identified vehicle components and operation types, calls the corresponding parsing rules to parse the second data segment. It extracts the 2-byte Param Type, 2-byte Data Length, and variable-length Value Data sequentially according to the TLV structure. The validity of the Param Type encoding is verified in conjunction with the vehicle component and operation type. For example, in a power system + discharge power adjustment scenario, the 0x0102 encoding corresponds to the target parameter type of peak discharge power. The number of bytes in the Value Data is determined based on the Data Length field, and the Value Data is parsed according to a preset data type (such as float32) to obtain the target parameter value, for example, 300.0kW. If an unknown Param Type encoding is encountered, the parameter segment can be skipped based on the Data Length, ensuring the continuity and compatibility of the parsing process.

[0130] As another implementation of S402, S402 may also include the following steps.

[0131] Parse the second data segment to obtain its type field, length field, and value field.

[0132] Specifically, as an example, the domain controller parses the TLV structure of the second data segment sequentially. First, it reads the first two bytes as the type field to obtain the Param Type encoding; then, it reads the next two bytes as the length field to determine the number of bytes in the value field; finally, based on the number of bytes indicated by the length field, it reads the corresponding length of byte stream from the position following the length field as the value field. If the second data segment contains multiple parameter segments, the above process is repeated to parse each TLV structure sequentially according to the number indicated by the Total Segment Count field, ensuring that all fields are extracted completely.

[0133] The target parameter type is determined based on the vehicle component, operation type, and type field.

[0134] As an example, the mapping relationship can refer to the association rules preset in the domain controller, which clearly define the specific parameter categories corresponding to vehicle components, operation types and type field codes, and ensure the accuracy of parameter identification.

[0135] Specifically, as an example, the domain controller invokes the built-in mapping dictionary to associate and match the parsed vehicle components, operation types, and type field codes. For instance, if the vehicle component is the power system and the operation type is discharge power adjustment, and the type field code is 0x0102, then the target parameter type is determined to be peak discharge power; if the code is 0x0101, it corresponds to maximum continuous discharge power. For reserved extended type codes such as 0xFF00, they are marked as parameter types to be extended according to preset rules to ensure parsing compatibility and adapt to different parameter extension requirements.

[0136] Based on the length field, read the corresponding data from the value field as the target parameter value.

[0137] Specifically, as an example, the domain controller first determines the corresponding data type based on the target parameter type; for example, the parameter data type can be uniformly set to float32. Combining the number of bytes identified by the length field, it verifies whether the length of the value field's byte stream matches, avoiding data loss or redundancy. Then, according to the data parsing rules for float32 type, it converts the value field's byte stream into a specific numerical value. For example, if the length field is 4 bytes and the value field's byte stream corresponds to 300.0 in float32 format, the parsed target parameter value is 300.0kW. After parsing, the value is validated for reasonableness to ensure it is within the vehicle's hardware capabilities, providing reliable data for subsequent parameter distribution.

[0138] The vehicle parameter update method in this application involves step-by-step parsing of the type field, length field, and value field to ensure the complete extraction of parameter information in the second data segment and avoid parameter loss or misreading due to field confusion. It combines vehicle components, operation type, and the type field to determine the target parameter type, and multi-dimensional matching verification improves the accuracy of parameter type identification, avoiding misjudgment of parameter types. Based on the length field, it reads the parameter value of the corresponding length, ensuring the completeness and accuracy of parameter value reading and avoiding parameter errors due to data length mismatch, thus ensuring the accuracy and effectiveness of the parameter values ​​updated by the actuator. It adapts to parameter values ​​of different lengths and parameter types, improving the compatibility and flexibility of the parsing process and supporting the parsing needs of various control parameters.

[0139] The vehicle parameter update method in this application first parses the first data segment to clarify the vehicle components and operation type, providing a clear direction for the parsing of the second data segment, avoiding blind parameter parsing and improving parsing efficiency; based on the targeted parsing of vehicle components and operation type, it ensures that the target parameter type and target parameter value extracted from the second data segment can accurately match the corresponding actuator, avoiding parameter mis-sending or mismatch; the phased parsing logic makes the instruction parsing process more organized, reduces data interference during the parsing process, improves the accuracy of parameter extraction, and ensures the reliability of subsequent actuator parameter updates.

[0140] Based on the vehicle parameter update method provided in the above embodiments, this application also provides specific implementation methods for the cloud and domain controller. Please refer to the following embodiments.

[0141] First see Figure 5 The cloud-based 50 provided in this application embodiment includes the following modules: The acquisition module 501 is used to acquire vehicle data and user driving behavior data; The determination module 502 is used to determine the vehicle control parameter information of the vehicle based on vehicle data and driving behavior data; wherein, the vehicle control parameter information includes the target parameter type and the target parameter value of the target parameter; The encapsulation module 503 is used to encapsulate vehicle control parameter information into structured communication instructions in a preset format; The sending module 504 is used to send structured communication commands to the vehicle's domain controller, so that the domain controller can parse the structured communication commands to extract the target parameter type and target parameter value of the vehicle control parameter information, and send them to the vehicle actuator, thereby enabling the vehicle actuator to update the target parameters based on the target parameter value.

[0142] See Figure 6 The domain controller 60 provided in this application embodiment includes the following modules: The receiving module 601 is used to receive a pre-formatted structured communication command sent from the cloud. The structured communication command is encapsulated based on vehicle control parameter information generated from vehicle data and user driving behavior data. The vehicle control parameter information includes the target parameter type and target parameter value of the target parameter. Parsing module 602 is used to parse structured communication instructions and extract the target parameter types and target parameter values ​​encapsulated therein; The sending module 603 is used to send the target parameter type and target parameter value to the vehicle actuator, so that the vehicle actuator can update the target parameter based on the target parameter value.

[0143] Figure 7 A schematic diagram of the hardware structure of the vehicle provided in an embodiment of this application is shown.

[0144] The vehicle may include a processor 701 and a memory 702 storing computer program instructions.

[0145] Specifically, the processor 701 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0146] Memory 702 may include mass storage for data or instructions. For example, and not limitingly, memory 702 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 702 may include removable or non-removable (or fixed) media. Where appropriate, memory 702 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 702 is non-volatile solid-state memory.

[0147] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.

[0148] The processor 701 implements any of the vehicle parameter update methods in the above embodiments by reading and executing computer program instructions stored in the memory 702.

[0149] In one example, the vehicle may also include a communication interface 703 and a bus 710. Wherein, as... Figure 7 As shown, the processor 701, memory 702, and communication interface 703 are connected through bus 710 and complete communication with each other.

[0150] The communication interface 703 is mainly used to realize communication between various modules, devices, units and / or vehicles in the embodiments of this application.

[0151] Bus 710 includes hardware, software, or both, that couples vehicle components together. For example, and not limitingly, the bus may include Accelerated Graphics Port (AGP) or other graphics buses, Enhanced Industry Standard Architecture (EISA) buses, Front Side Bus (FSB), HyperTransport (HT) interconnects, Industry Standard Architecture (ISA) buses, Infinite Bandwidth Interconnects, Low Pin Count (LPC) buses, memory buses, Microchannel Architecture (MCA) buses, Peripheral Component Interconnect (PCI) buses, PCI-Express (PCI-X) buses, Serial Advanced Technology Attachment (SATA) buses, Video Electronics Standards Association Local (VLB) buses, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 710 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0152] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0153] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0154] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0155] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, systems (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0156] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for updating vehicle parameters, characterized in that, Applied to the cloud, including: Acquire vehicle data and user driving behavior data; Based on the vehicle data and the driving behavior data, the vehicle control parameter information of the vehicle is determined; wherein, the vehicle control parameter information includes the target parameter type and the target parameter value of the target parameter; The vehicle control parameter information is encapsulated into a structured communication command in a preset format; The structured communication command is sent to the vehicle's domain controller, which then parses the command to extract the target parameter type and target parameter value of the vehicle control parameter information and sends it to the vehicle actuator, thereby enabling the vehicle actuator to update the target parameter based on the target parameter value.

2. The method according to claim 1, characterized in that, The step of encapsulating the vehicle control parameter information into a structured communication command with a preset format includes: Based on the target parameter type, determine the vehicle component and operation type to which it belongs; The vehicle components and the operation type are encapsulated into a first data segment of the structured communication instruction; Based on the target parameter type and the target parameter value, a second data segment is generated, which includes a type field, a length field, and a value field; wherein, the type field corresponds to the target parameter type, the length field corresponds to the length of the target parameter value, and the value field corresponds to the target parameter value; The first data segment and the second data segment are encapsulated into the structured communication instruction.

3. The method according to claim 1, characterized in that, The step of sending the structured communication command to the vehicle's domain controller includes: The structured communication commands are sent to the vehicle's domain controller via a remote information processing terminal.

4. The method according to any one of claims 1-3, characterized in that, The vehicle data includes vehicle driving data within a preset time period, and the driving behavior data includes the user's driving operation behavior data under the target driving conditions. The process of determining the vehicle control parameter information based on the vehicle data and the driving behavior data includes: Based on the vehicle driving data and the driving operation behavior data, the target parameter type of the vehicle control parameter information is determined. When the driving behavior characteristics of the driving operation behavior data meet preset conditions, the target parameter value of the vehicle control parameter information is determined.

5. The method according to any one of claims 1-3, characterized in that, The process of determining the vehicle control parameter information based on the vehicle data and the driving behavior data includes: Real-time acquisition of the vehicle's operating status data; Based on the operational status data, identify whether the vehicle is experiencing any abnormalities; If the vehicle is found to have a target abnormal state, the target parameter type and the target parameter value corresponding to the target abnormal state are determined.

6. The method according to claim 1, characterized in that, The method further includes: Receive the updated status of the target parameters; Based on the updated status, update the vehicle's parameter update record in the cloud.

7. A method for updating vehicle parameters, characterized in that, Domain controllers used in vehicles include: The system receives a pre-formatted structured communication command from the cloud. The structured communication command is encapsulated based on vehicle control parameter information generated from the vehicle's data and the user's driving behavior data. The vehicle control parameter information includes the target parameter type and target parameter value of the target parameter. Parse the structured communication instructions and extract the target parameter type and target parameter value encapsulated therein; The target parameter type and the target parameter value are sent to the vehicle actuator so that the vehicle actuator updates the target parameter based on the target parameter value.

8. The method according to claim 7, characterized in that, The structured communication instruction includes a first data segment and a second data segment. Parsing the structured communication instruction and extracting the encapsulated target parameter type and target parameter value includes: Parse the first data segment of the structured communication instruction to obtain the vehicle components and operation type therein; Based on the vehicle component and the operation type, the second data segment of the structured communication instruction is parsed to extract the target parameter type and the target parameter value from the second data segment.

9. The method according to claim 8, characterized in that, The step of parsing the second data segment of the structured communication instruction according to the vehicle component and the operation type, and extracting the target parameter type and the target parameter value from the second data segment, includes: Parse the second data segment to obtain its type field, length field, and value field; The target parameter type is determined based on the vehicle component, the operation type, and the type field; Based on the length field, the corresponding data is read from the value field as the target parameter value.

10. The method according to any one of claims 7-9, characterized in that, The receiving of structured communication instructions in a preset format sent from the cloud includes: Receive structured communication instructions sent from the cloud to the remote information processing terminal and forwarded by the remote information processing terminal.

11. A vehicle parameter update system, characterized in that, The system includes a cloud and a domain controller, including: The cloud platform is used to acquire vehicle data and user driving behavior data; based on the vehicle data and driving behavior data, it determines the vehicle control parameter information; wherein the vehicle control parameter information includes the target parameter type and target parameter value of the target parameter; the vehicle control parameter information is encapsulated into a structured communication instruction in a preset format; the structured communication instruction is sent to the vehicle's domain controller, so that the domain controller parses the structured communication instruction to extract the target parameter type and target parameter value of the vehicle control parameter information, and sends it to the vehicle actuator, thereby enabling the vehicle actuator to update the target parameter based on the target parameter value; The domain controller is configured to receive structured communication instructions in a preset format sent from the cloud. These instructions are encapsulated based on vehicle control parameter information generated from vehicle data and user driving behavior data. The vehicle control parameter information includes the target parameter type and target parameter value. The controller parses the structured communication instructions, extracts the encapsulated target parameter type and target parameter value, and sends the target parameter type and target parameter value to the vehicle actuator, enabling the vehicle actuator to update the target parameter based on the target parameter value.

12. A cloud computing platform, characterized in that, include: The acquisition module is used to acquire vehicle data and user driving behavior data; The determination module is used to determine the vehicle control parameter information of the vehicle based on the vehicle data and the driving behavior data; wherein, the vehicle control parameter information includes the target parameter type and the target parameter value of the target parameter; An encapsulation module is used to encapsulate the vehicle control parameter information into a structured communication instruction in a preset format; The sending module is used to send the structured communication command to the domain controller of the vehicle, so that the domain controller can parse the structured communication command to extract the target parameter type and target parameter value of the vehicle control parameter information, and send it to the vehicle actuator, thereby enabling the vehicle actuator to update the target parameter based on the target parameter value.

13. A domain controller, characterized in that, include: The receiving module is used to receive a pre-formatted structured communication command sent from the cloud. The structured communication command is encapsulated based on vehicle control parameter information generated from vehicle data and user driving behavior data. The vehicle control parameter information includes the target parameter type and target parameter value of the target parameter. The parsing module is used to parse the structured communication instructions and extract the target parameter type and target parameter value encapsulated therein; The sending module is used to send the target parameter type and the target parameter value to the vehicle actuator, so that the vehicle actuator updates the target parameter based on the target parameter value.

14. A vehicle, characterized in that, The vehicle includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the vehicle parameter update method as described in any one of claims 1-10.

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