Parameter updating method, device, processing equipment and storage medium

Abstract

The present application discloses a parameter update method, device, processing equipment and storage medium, the method comprising: parsing and processing the acquired vehicle data; inputting the parsed vehicle data into a preset algorithm to obtain a calculation result; generating a parameter update message based on the calculation result; and sending the parameter update message to the vehicle terminal. The embodiment of the present application arranges a cloud platform, so that during the parameter update process in the vehicle, there is no need to update the entire vehicle system or software, eliminating the risk of downtime due to update failure, thereby greatly saving time and energy, reducing software change costs, improving efficiency and ensuring accuracy. At the same time, due to the unified variable parameter structure on the cloud, more accurate and personalized parameter tuning is achieved, the response to safety requirements is more timely, and the user experience can be improved.

Description

Technical Field

[0001] The present application generally relates to the field of vehicle technology, and more particularly to a parameter updating method, apparatus, processing device and storage medium. Background Art

[0002] For new energy vehicles, as internal and external data change, and the continuous use of various components, aging may occur, causing changes in the performance of various parameters. In order to ensure the normal operation of the vehicle, it is necessary to remotely manage, update, and repair program modules such as the battery management system, power system, human-computer interaction, and internal parameters.

[0003] At present, the process of updating program modules and parameters in vehicles is mainly carried out through Over-the-Air Technology (OTA), which uses the air interface of communication on the on-board terminal to remotely manage, update, and repair various data, software applications, and certain firmware during vehicle operation, so as to improve various performance such as cruising range, maximum speed, or ride comfort.

[0004] The above-mentioned update technology generally requires a comprehensive upgrade of the entire system or software of the vehicle computer, which is time-consuming and cannot update and adjust parameters in real time while driving. In addition, due to poor network signals or vehicle-mounted communication modules, OTA upgrades may easily fail or even cause downtime. The vehicle needs to be upgraded to a 4S store, where professional maintenance personnel or professionals will conduct a series of tests on the vehicle to upgrade the vehicle system, modules or parameters. This ultimately results in high software upgrade costs in the vehicle, complex operations, and poor user experience. Summary of the invention

[0005] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a parameter updating method, apparatus, processing device and storage medium.

[0006] In a first aspect, an embodiment of the present application provides a parameter updating method, which is used for a server, and the parameter updating method includes:

[0007] Analyze and process the acquired vehicle data;

[0008] Inputting the analyzed vehicle data into a preset algorithm to obtain a calculation result, wherein the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated;

[0009] generating a parameter update message based on the calculation result, the parameter update message including an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated;

[0010] Send the parameter update message to the vehicle terminal.

[0011] Optionally, in the parameter updating method of an embodiment of the present application, the vehicle is a new energy vehicle, and the vehicle parameters include performance parameters of a power battery pack.

[0012] Optionally, in the parameter updating method of the embodiment of the present application, generating a parameter updating message based on the calculation result includes:

[0013] Analyze the calculation result to obtain the flag field of each vehicle parameter;

[0014] When the flag field indicates that the vehicle parameter needs to be updated, a parameter update message is generated based on the identifier of the vehicle parameter that needs to be updated and the target value of the vehicle parameter that needs to be updated.

[0015] Optionally, in the parameter updating method of the embodiment of the present application, sending the parameter updating message to the vehicle terminal includes:

[0016] Based on the vehicle frame number, the parameter update message is sent to the vehicle terminal, and the vehicle data of each vehicle corresponds to the vehicle frame number one by one.

[0017] Optionally, the parameter updating method of the embodiment of the present application, parsing the acquired vehicle data includes:

[0018] Splitting the vehicle data;

[0019] The split vehicle data is stored in a preset data table.

[0020] Optionally, the parameter updating method of the embodiment of the present application, before parsing the acquired vehicle data, the method further includes:

[0021] Removing abnormal data from the vehicle data;

[0022] The valid data in the vehicle data after removing the abnormal data is filtered according to the preset conditions.

[0023] In a second aspect, an embodiment of the present application provides a parameter updating method, the method comprising:

[0024] Reporting vehicle data to a server so that the server processes the vehicle data through a preset algorithm to obtain a calculation result, the calculation result including a flag field of each vehicle parameter, the flag field indicating whether the corresponding vehicle parameter needs to be updated;

[0025] A parameter update message sent by a server is received, wherein the parameter update message includes an identifier of a vehicle parameter to be updated and a target value of the vehicle parameter to be updated.

[0026] Based on the identifier of the vehicle parameter to be updated, the current vehicle parameter is updated to the target value.

[0027] In a third aspect, an embodiment of the present application provides a parameter updating device, the device comprising:

[0028] A reporting module, used to report vehicle data to a server, so that the server processes the vehicle data through a preset algorithm to obtain a calculation result, the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated;

[0029] The receiving module is used to receive a parameter update message sent by the server, wherein the parameter update message includes an identifier of a vehicle parameter to be updated and a target value of the vehicle parameter to be updated.

[0030] The updating module is used to update the current vehicle parameter to the target value based on the identifier of the vehicle parameter to be updated.

[0031] In a fourth aspect, an embodiment of the present application provides a computer processing device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is used to implement the parameter updating method as described in the first aspect or the second aspect of claim 1 when executing the program.

[0032] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is used to implement the parameter updating method as described in the first aspect or the second aspect.

[0033] The parameter updating method, apparatus, processing equipment and storage medium provided in the embodiments of the present application parse and process the acquired vehicle data, and then input the parsed data into a preset algorithm to output calculation results including various vehicle parameters, and finally independently update the corresponding parameters according to the calculation results, so as to ensure the independent, rapid and real-time update of various vehicle parameters during operation. In this way, during the parameter updating process in the vehicle, there is no need to update the entire vehicle system or software, eliminating the risk of downtime due to update failure, thereby greatly saving time and energy, reducing software change costs, improving efficiency and ensuring accuracy. At the same time, due to the unified structure of variable parameters in the cloud, more accurate and personalized parameter tuning is achieved, the response to safety requirements is more timely, and the user experience can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0035] Figure 1Shown is a schematic diagram of the architecture of parameter updating in an embodiment of the present application;

[0036] Figure 2 A flow chart of a parameter updating method according to an embodiment of the present application;

[0037] Figure 3 A flow chart of a parameter updating method according to another embodiment of the present application;

[0038] Figure 4 A flow chart of a parameter updating method according to another embodiment of the present application;

[0039] Figure 5 A schematic diagram of the structure of a parameter updating device according to an embodiment of the present application;

[0040] Figure 6 This is a structural diagram of a parameter updating device according to another embodiment of the present application;

[0041] Figure 7 A schematic diagram of the structure of a computer of a processing device according to an embodiment of the present application. DETAILED DESCRIPTION

[0042] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant disclosure, rather than to limit the disclosure. It should also be noted that, for ease of description, only the parts related to the disclosure are shown in the accompanying drawings.

[0043] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0044] It is understandable that in order to ensure the normal operation of the vehicle, remote management, updating and repair of internal operating programs and various parameters are required.

[0045] For example, due to changes in internal and external data and the environment, it is necessary to update the program modules running on the vehicle terminal from time to time, such as the battery management system, power system, human-computer interaction and other modules; or, as new energy vehicles are used, some firmware structures will gradually age with the increase in years of use, causing changes in the performance of various parameters of components in the vehicle, and it is also necessary to promptly correct the corresponding parameters of various components in the vehicle, such as the need to recalibrate and repair parameters such as the charge and status of the power battery pack.

[0046] It is understandable that when managing the update of running programs, the Over-the-Air Technology (OTA) update technology is currently used. Due to network signals, vehicle communication modules, or other unknown failures, the upgrade may fail or even cause downtime. In this case, the vehicle needs to be returned to the 4S store for professional maintenance personnel or professionals to perform a series of tests on the vehicle to upgrade the vehicle system or module.

[0047] Moreover, the above-mentioned updating technology usually involves an all-round upgrade of the entire system or software of the vehicle computer, and does not support independent updating of a module or parameter, which takes a long time. The recalibration of the parameters also requires going to a 4S shop and having professionals complete it. Moreover, it is impossible to update and adjust the parameters in real time while driving, which takes a long time, ultimately making the software upgrade cost in the vehicle high, the operation complicated, and the user experience poor.

[0048] In the embodiment of the present application, in order to solve a series of problems caused by the existing vehicle terminal in the process of upgrading the software in the new energy vehicle through the OTA technology, by building Figure 1 The network architecture shown, with the help of the cloud service architecture, enables all vehicle-mounted terminals to report their own data to the cloud in real time, and then the cloud uses pre-loaded program algorithms to process the real-time data reported by all vehicle-mounted terminals, so as to efficiently and accurately run out the parameters to be updated in all vehicles, and transmit them to the vehicle-mounted terminals of the vehicles in real time through the network, so as to update the parameters to be updated in real time, realize independent upgrade and update of individual modules or parameters in the vehicle, and real-time update and adjustment of parameters during driving, avoiding the need for a comprehensive upgrade of the entire system or software of the vehicle computer, thereby avoiding the time-consuming problems and downtime risks caused by the comprehensive upgrade process, and ultimately improving the user experience.

[0049] like Figure 1 FIG. 1 is a schematic diagram of the architecture of parameter updating of an embodiment of the present application. Figure 1 As shown, the architecture may include multiple vehicles and a backend server, such as a cloud server.

[0050] Figure 1 Each vehicle in the system is equipped with a vehicle-mounted terminal, and each vehicle-mounted terminal has a communication module, so as to realize cloud interaction with the back-end cloud server through the communication module.

[0051] In addition, each vehicle terminal runs various application modules that control the normal operation of the vehicle, such as the battery management system (BMS), power system, human-computer interaction and other program modules.

[0052] It is understandable that during the operation of the above-mentioned application, the parameters related to the vehicle application are tested and calibrated by engineers when the vehicle leaves the factory.

[0053] As the vehicle ages, the performance of various components of the vehicle gradually ages, causing corresponding parameters to change. Accordingly, it is necessary to recalibrate the relevant parameters on the vehicle terminal to ensure the normal operation of each program module.

[0054] For example, as the power battery pack in new energy vehicles increases in service life, the battery pack capacity and life will be affected, causing the corresponding parameters to change, and ultimately causing the vehicle's cruising range to be inaccurate. At this time, it is necessary to recalibrate and update the power battery pack related parameters, such as the capacity of the power battery pack and the battery state of charge (SOC) and other battery pack performance parameters, so that during the operation of the vehicle, the battery manager system (BAM) can use the recalibrated parameters to accurately calculate the cruising range and other operating data related to the power battery pack parameters.

[0055] The cloud server is a server or server cluster running in the background, on which a database architecture, such as a distributed architecture, is built. The algorithm module or model for data processing is deployed in the distributed architecture.

[0056] It can be understood that in practice, the historical data of all vehicles collected by the data collector is stored in the cloud server, and then the data is parsed and cleaned, and then saved to the established cloud platform data warehouse or other database; some data processing technologies can also be used to consume real-time data in the message queue.

[0057] Different algorithm modules or models are deployed in the distributed architecture of the cloud platform according to the computing cycles and data requirements of different algorithms.

[0058] In practice, periodic historical data can be imported into the corresponding algorithm modules on a large scale through technologies such as Spark and MapReduce for batch processing; real-time data can be imported into the corresponding algorithm modules in a streaming manner through technologies such as Flume, Flink, and Storm for real-time processing.

[0059] It can be understood that due to the different historical data of different vehicles, the results calculated by the algorithm are also different. In addition, each algorithm module detects and calculates multiple different parameters, and judges whether the parameter needs to be tuned through the parameter flag field of the algorithm output result. For example, when the output result of the "Flag_Upjump_SJ" field is 1, it means that the parameter needs to be tuned. Therefore, personalized tuning of individual parameters of different vehicles can be achieved.

[0060] Furthermore, on the big data cloud platform, the parameter structures and data types of the algorithm output are unified. This ensures that even in the case of different car models and different battery cell models, only the specific parameters that need to be adjusted need to be transmitted through messages to achieve information exchange and rapid parameter updates between the cloud platform and the vehicle computer. There is no need to re-match and upgrade software or programs due to factors such as different car models and vehicle computer systems.

[0061] It can be understood that the embodiment of the present application not only utilizes big data to realize the analysis of massive data, but also utilizes the cloud platform to realize the cloud storage and cloud computing of massive data. It can realize the interaction between cloud and car, and quickly and in real time adjust personalized parameters during operation. It is not necessary to update the entire vehicle system or software, but only to adjust and correct individual parameters, so as to achieve the purpose of updating.

[0062] That is, through Figure 1 The architecture shown in the figure, as well as the algorithm modules deployed in the distributed architecture of the cloud server, greatly saves time and energy and reduces the cost of software changes. At the same time, due to the unified structure of variable parameters in the cloud, parameters can be quickly updated without program changes, eliminating the risk of downtime due to update failure, responding to security needs more promptly, and improving user experience. It also closely links the Internet of Things, cloud computing, and big data together, complementing each other, achieving wider coverage and more comprehensive application scenarios, which improves efficiency and ensures accuracy.

[0063] All vehicle-mounted terminals use the tuning parameters of the vehicle computers derived from the cloud platform's big data, enabling more accurate and personalized parameter tuning.

[0064] In order to better explain the parameter update process of the embodiment of the present application, Figures 2 to 4 Elaborate in detail.

[0065] Figure 2 The following is a flow chart of a parameter updating method according to an embodiment of the present application. The method specifically includes:

[0066] S110, analyzing and processing the acquired vehicle data.

[0067] S120, inputting the analyzed vehicle data into a preset algorithm to obtain a calculation result, wherein the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated.

[0068] S130, generating a parameter update message based on the calculation result, wherein the parameter update message includes an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated.

[0069] S140, sending a parameter update message to the vehicle terminal.

[0070] Specifically, a remote server, such as a cloud server, can extract multiple vehicles within a period of time from a database, and can also obtain real-time vehicle data, such as historical data and real-time data of new energy vehicles.

[0071] For example, the operating data of the power battery packs of 10,000 new energy vehicles within three months is extracted from the database.

[0072] It is understandable that before this, the cloud server can receive the vehicle data uploaded by the on-board terminals of all vehicles and store it in the database as the historical data of all vehicles for analysis and processing by the cloud server.

[0073] The vehicle data may include various types of data collected by sensors arranged on the vehicle, or may include vehicle data generated during the operation of an application on the vehicle terminal.

[0074] For example, the SOC of the power battery pack collected by the sensor, the vehicle speed collected by the speed sensor, or the power conversion rate and power consumption generated during operation.

[0075] Furthermore, after the cloud server extracts the historical data of multiple vehicles, it can pre-process the extracted historical data. For example, it can process abnormal data, filter valid data, and convert the format of the extracted historical data to obtain a unified processable format, and store it again in a preset format.

[0076] After the preprocessing is completed, the cloud server can import the preprocessed historical data into the preset algorithm to perform calculations on the extracted batch of vehicle historical data to output the calculation results. The calculation results are then parsed to determine the vehicle parameters that need to be updated, and finally the identifiers of the vehicle parameters that need to be updated and the target values ​​of the vehicle parameters that need to be updated are packaged together to generate parameter update messages, which are sent to the vehicle terminals of the corresponding vehicles to instruct the corresponding vehicle terminals to independently update the individual parameters in the vehicle according to the received messages.

[0077] It can be understood that the server pre-stores the target values ​​corresponding to each vehicle parameter, that is, the server can regularly obtain the standard parameters of each component in each type of vehicle under different wear conditions, so as to provide them to the vehicle terminal as target values ​​for recalibration, i.e., updating, of the vehicle parameters.

[0078] It can be understood that the calculation result may include a flag field for each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated.

[0079] For example, when the flag field of a vehicle parameter is 1, it indicates that the vehicle parameter needs to be updated and optimized. When the flag field is not 1, it indicates that the parameter does not need to be corrected, that is, it does not need to be updated.

[0080] It can be understood that the definition of the above-mentioned flag field can be determined according to actual conditions, and this application does not impose any restrictions on this.

[0081] The parameter updating method of the embodiment of the present application closely links the Internet of Things, cloud computing and big data together through the deployed cloud platform, realizes cloud storage and cloud computing of massive data, outputs the calculation results including various vehicle parameters, and finally independently updates the corresponding parameters according to the calculation results to realize cloud-vehicle interaction. The personalized parameters are quickly and in real time during operation, so that during the parameter update process in the vehicle, there is no need to update the entire vehicle system or software, and each parameter can be updated independently to achieve the purpose of updating, thereby greatly saving time and energy, reducing software change costs, improving efficiency and ensuring accuracy. At the same time, due to the unified structure of variable parameters on the cloud, parameters can be quickly updated without program changes, eliminating the risk of downtime due to update failure, achieving more accurate and personalized parameter tuning, responding to safety needs more promptly, and improving user experience.

[0082] On the other hand, in other embodiments, Figure 3 As shown, the method is used for a vehicle-mounted terminal, and the parameter updating method specifically includes:

[0083] S210, reporting vehicle data to the server, so that the server processes the vehicle data through a preset algorithm to obtain a calculation result, which includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated.

[0084] S220, receiving a parameter update message sent by the server, where the parameter update message includes an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated.

[0085] S230: Based on the identifier of the vehicle parameter to be updated, update the current vehicle parameter to the target value.

[0086] Specifically, during the operation of a vehicle, such as a new energy vehicle, the communication module in the installed vehicle terminal can report various types of vehicle data generated during the use of the vehicle to the remote server at a preset frequency, so that the vehicle data of all new energy vehicles is stored in the database of the cloud server as historical data. In this way, the cloud server can parse and process the stored batch historical data, perform calculations using a pre-stored algorithm, obtain calculation results, and generate parameter update messages based on the calculation results, which are then sent to the corresponding vehicle terminal.

[0087] Furthermore, after receiving the parameter update message sent by the cloud server, the vehicle terminal parses the parameter update message to obtain the identifier of the parameter to be updated and the target value corresponding to the vehicle parameter. Finally, according to the target value and parameter identifier, the parameter corresponding to the parameter identifier is updated to the target value to complete the recalibration of the parameter.

[0088] For example, in new energy vehicles, after reporting vehicle data related to the power battery pack to the cloud server at a preset frequency, the cloud server can determine the vehicles that need to update the power battery pack related parameters, as well as the specific parameter identifiers, after calculating and processing the collected batch power battery pack related data. For example, it is determined that the life parameters of the power battery pack of a new energy vehicle need to be recalibrated.

[0089] Furthermore, after receiving the parameter update message sent by the cloud server, the vehicle terminal can parse the parameter update message and update the life of the power battery pack to the target value in the parameter update message according to the identifier of the life of the power battery pack.

[0090] It can be understood that in order for the cloud server to accurately identify the source of data, and then to parse the calculation results, accurately identify the target vehicle that needs to update the parameters, and accurately send the corresponding parameter update message for instructing the vehicle to update the parameter mark to the corresponding vehicle's on-board terminal, when each on-board terminal uploads vehicle data to the cloud server, it is also necessary to upload the identifier for vehicle identity identification at the same time.

[0091] For example, the identifier used for vehicle identification may be the frame number of a new energy vehicle.

[0092] The parameter updating method in the embodiment of the present application reports the generated vehicle data to the cloud server in real time during the operation of the vehicle through the deployed cloud platform, so that the cloud server processes the uploaded batch data, and then receives the parameter identifiers that need to be updated and the corresponding target values ​​issued by the server to complete the independent update of the parameters. In the process of updating the vehicle parameters, there is no need to update the entire vehicle system or software. Each parameter can be updated independently to achieve the purpose of updating, thereby greatly saving time and energy, reducing the cost of software changes, improving efficiency and ensuring accuracy. At the same time, due to the unified structure of variable parameters on the cloud, parameters can be quickly updated without program changes, eliminating the risk of downtime due to update failure, achieving more accurate and personalized parameter tuning, and responding to safety requirements more promptly, which can improve user experience.

[0093] In order to better understand the parameter updating method of the embodiment of the present application, the following takes the relevant parameters of the power battery pack in the new energy vehicle as an example. Figure 4 The updating process of vehicle parameters in new energy vehicles is elaborated in detail.

[0094] like Figure 4 As shown, the method specifically includes:

[0095] S411, the vehicle terminal uploads vehicle data to the cloud server.

[0096] S412, the cloud server receives and stores the vehicle data uploaded by the vehicle terminal.

[0097] Specifically, Figure 1 During operation, all the vehicle terminals shown in the figure upload all the collected vehicle data to the cloud server at a preset frequency.

[0098] For example, the on-board terminal collects relevant data of the power battery pack in the new energy vehicle, such as the current remaining charge, charging time, usage time, etc., generates a vehicle data packet, and uploads it to the cloud server.

[0099] It can be understood that the vehicle data packet may include the frame number of the new energy vehicle so as to identify the identity of the new energy vehicle.

[0100] Furthermore, after receiving the vehicle data packet uploaded by the vehicle terminal, the cloud server parses the vehicle data packet to obtain all vehicle data and the frame number therein, and then stores them in a database arranged in the cloud server in a preset format as historical data of the vehicle.

[0101] For example, after parsing the vehicle data packet, the remaining charge, charging time, usage time, etc. of the power battery pack of each new energy vehicle are stored in a table according to the frame number of each new energy vehicle.

[0102] S413, the cloud server extracts the stored vehicle data.

[0103] Specifically, the cloud server can execute a data processing program at a preset cycle to analyze and process batch historical data of vehicles stored in the database to calculate the vehicles that need parameter updates among all vehicles and the specific parameters that need to be recalibrated.

[0104] For example, in an embodiment of the present application, historical data of 10,000 electric vehicle batteries within three months can be extracted from the database of the cloud platform through scripts or Hive SQL statements, such as extracting batch historical data of the remaining charge, charging time, voltage, current, usage time, etc. of the power battery packs of 10,000 vehicles within three months.

[0105] Furthermore, after extracting the stored vehicle data, in order to improve the calculation accuracy, the extracted data can be pre-processed according to pre-set conditions. That is, the following steps are performed:

[0106] S414, removing abnormal data in the vehicle data.

[0107] S415, filtering valid data in the vehicle data after removing abnormal data according to preset conditions.

[0108] Specifically, in some embodiments, after the cloud server extracts the historical data of the vehicle from the database, it can perform preliminary preprocessing on the extracted initial historical data to prepare for subsequent processing using an algorithm.

[0109] For example, firstly, abnormal data such as duplicate data, data with missing fields, and / or erroneous data in the extracted vehicle data may be removed.

[0110] If the value 200 appears in the range of 1-100, then this value is abnormal data that exceeds the range and needs to be removed.

[0111] Furthermore, the vehicle data with abnormal data removed can be screened according to preset conditions to obtain valid data to be processed.

[0112] It can be understood that the preset condition may be related to the actual meaning of the vehicle parameters.

[0113] For example, for the parameter of the charging time of the power battery pack, considering that the charging of the power battery pack has a certain continuity, that is, it takes a period of time to complete the charging. Therefore, the duration of the SOC change process can be used as a basis to filter out historical data that meets the general charging duration as valid data for subsequent calculation and processing. That is, the preset condition is the charging duration.

[0114] In practice, Hive SQL can be used to filter out only the SOC value of each vehicle, starting from charging less than or equal to 50 to the end, that is, the data of the full charging time period when the SOC is equal to 100, that is, to filter out valid data that meets the charging time.

[0115] In addition, the Hive SQL window function lag() can be used to ensure that the charging data of full charging across days can also be filtered out as valid data to be processed.

[0116] It is understandable that, during preprocessing, the above steps may be selectively performed according to actual conditions, and the embodiments of the present application do not impose any limitation on this.

[0117] Furthermore, after completing the above-mentioned initial stage preprocessing, the preprocessed historical data can also be subjected to preliminary analysis processing to complete the preparation for the actual operation processing.

[0118] That is, in some embodiments, after the above preprocessing operation, the method performs the following parsing processing steps:

[0119] S416, splitting the vehicle data.

[0120] S417, storing the split vehicle data in a preset data table.

[0121] Specifically, in order to be able to import the extracted vehicle data into the algorithm module for computational processing, the preprocessed vehicle data needs to be split according to field attributes so that the data of each component is separated and stored one by one in a preset manner.

[0122] For example, the filtered full charge data is split according to the battery cells in the power battery pack to separate the slow charge data of each battery cell. Finally, the split vehicle data is stored in a preset data table.

[0123] That is, for the charging parameters of the power battery pack mentioned above, in practice, the 120 cell voltage fields (such as Json data type) in the vehicle data can be split into 120 single cell voltage fields (such as Double data type). Finally, the split historical data is stored in the preset "dws_syc1_gb_log_charge" table for subsequent calculation and processing.

[0124] Furthermore, after the above-mentioned preprocessing and analysis processing is performed on the extracted vehicle data, the processed vehicle data can be imported into a preset algorithm for processing.

[0125] That is, the method performs the following steps:

[0126] S418, importing the vehicle data in the data table into the preset algorithm to obtain the calculation result.

[0127] S419, analyzing the calculation result to obtain the flag field of each vehicle parameter.

[0128] Specifically, through the above steps, the extracted original batch historical data is pre-processed and analyzed, and then the pre-deployed algorithm is started to perform operation processing on the analyzed vehicle historical data and output the operation result. The operation result is then analyzed, that is, by identifying the update identification field, all parameters that need to be updated for all vehicles are obtained.

[0129] For example, in Python program, PySpark API is used to extract vehicle data from preset tables in cloud platform database, such as the "dws_syc1_gb_log_charge" table, which has been preprocessed and parsed. Then, the extracted vehicle data of each vehicle is imported into the preset algorithm in the program, and then the program is run on the cloud platform through the Spark-submit command in the script, and batch operations are performed on 10,000 vehicles using Hadoop's distributed architecture mechanism.

[0130] Furthermore, the fields in the calculation results are analyzed. First, whether the parameters need to be recalibrated is determined based on the values ​​of the vehicle parameter flag fields in the calculation results. For example, when the output result of the "Flag_Upjump_SJ" field is 1, it means that the vehicle parameters need to be optimized. At the same time, the value in the "SOC_Upjump_SJ" field represents the value of the recalibrated parameters, that is, the target value.

[0131] When the value output by the flag field is not 1, it means that the vehicle parameters do not need to be corrected, that is, they do not need to be updated.

[0132] It can be understood that the above-mentioned specific method of performing operations on historical data is merely an exemplary description. As long as the data analysis and processing can be achieved, the implementation of this application does not impose any restrictions on this.

[0133] S420: When the flag field indicates that the vehicle parameter needs to be updated, a parameter update message is generated based on the identifier of the vehicle parameter that needs to be updated and the target value of the vehicle parameter that needs to be updated.

[0134] S421, sending the parameter update message to the vehicle terminal, the vehicle data of each vehicle corresponds to the vehicle frame number one by one.

[0135] S422, receiving a parameter update message sent by the server, where the parameter update message includes an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated.

[0136] S423, based on the identifier of the vehicle parameter to be updated, updating the current vehicle parameter to the target value

[0137] Specifically, after the cloud server analyzes the calculation results, it can determine all the parameters that need to be updated in all the vehicle terminals, and then generate a parameter update message corresponding to each parameter to be updated based on the analysis result.

[0138] It can be understood that the parameter update message may include the identifier of the parameter to be updated and the target value, and may also include the identifier of the object to which the parameter update message is sent, such as the frame number of a new energy vehicle.

[0139] Furthermore, after generating the parameter update message, the cloud server can send the updated specific parameter values ​​in batches to the on-board terminal of the corresponding vehicle in the form of messages based on the vehicle frame number, thereby realizing cloud-vehicle interaction.

[0140] Finally, after receiving the parameter update message, the vehicle terminal can parse the received parameter update message to obtain the identifier of the parameter to be updated and the target value, and then update the parameter corresponding to the identifier to the target value according to the parameter identifier.

[0141] For example, after parsing the parameter update message, the vehicle terminal determines that parameters such as the charge amount and service life of the power battery pack in the battery management system need to be updated to the target values ​​included in the parameter update message.

[0142] In the embodiment of the present application, the relevant parameters of the power battery pack of the new energy vehicle are updated through the deployed cloud platform, which closely links the Internet of Things, cloud computing and big data, realizes cloud storage and cloud computing of massive data, realizes cloud-vehicle interaction, and quickly and in real time personalizes parameters during operation. In the process of updating parameters in the vehicle, there is no need to update the entire vehicle system or software, and each parameter can be updated independently to achieve the purpose of updating, thereby greatly saving time and energy, reducing software change costs, improving efficiency and ensuring accuracy. At the same time, due to the unified structure of variable parameters on the cloud, parameters can be quickly updated without program changes, eliminating the risk of downtime due to update failure, achieving more accurate and personalized parameter tuning, and responding to safety needs more promptly, which can improve user experience.

[0143] On the other hand, the embodiment of the present application also provides a parameter updating device, such as Figure 5 As shown, the device 500 includes:

[0144] The parsing module 510 is used to parse and process the acquired vehicle data;

[0145] A calculation module 520, used for inputting the vehicle data after the analysis into a preset algorithm to obtain a calculation result, wherein the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated;

[0146] A generating module 530, configured to generate a parameter update message based on the calculation result, wherein the parameter update message includes an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated;

[0147] The sending module 540 is used to send the parameter update message to the vehicle terminal.

[0148] Optionally, in the parameter updating device of the embodiment of the present application, the vehicle is a new energy vehicle, and the vehicle parameters include performance parameters of the power battery pack.

[0149] Optionally, in the parameter updating device of the embodiment of the present application, the generating module 540 includes:

[0150] The parsing unit 531 is used to parse the calculation result and obtain the flag field of each vehicle parameter;

[0151] The generating unit 532 is configured to generate a parameter updating message based on an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated when the flag field indicates that the vehicle parameter needs to be updated.

[0152] Optionally, in the parameter updating device of the embodiment of the present application, the sending module 540 is specifically used for:

[0153] Based on the vehicle frame number, the parameter update message is sent to the vehicle terminal, and the vehicle data of each vehicle corresponds to the vehicle frame number one by one.

[0154] Optionally, in the parameter updating device of the embodiment of the present application, the parsing module 510 includes:

[0155] A splitting unit 511 is used to split the vehicle data;

[0156] The storage unit 512 is used to store the split vehicle data in a preset data table.

[0157] Optionally, the parameter updating device of the embodiment of the present application further includes:

[0158] The preprocessing module 550 is used to perform preprocessing on the vehicle data.

[0159] Optionally, in the parameter updating device of the embodiment of the present application, the preprocessing module 560 includes:

[0160] A removal unit 551, used to remove abnormal data in the vehicle data;

[0161] The screening unit 552 is used to screen the valid data in the vehicle data after removing the abnormal data.

[0162] On the other hand, the embodiment of the present application also provides a parameter updating device, such as Figure 6 As shown, the device 600 includes:

[0163] The reporting module 610 is used to report the vehicle data to the server, so that the server processes the vehicle data through a preset algorithm to obtain a calculation result, which includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated;

[0164] The receiving module 620 is used to receive a parameter update message sent by the server, wherein the parameter update message includes an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated.

[0165] The updating module 630 is used to update the current vehicle parameter to the target value based on the identifier of the vehicle parameter to be updated.

[0166] On the other hand, the embodiment of the present application also provides a parameter updating system, such as Figure 1 As shown, the system may include multiple vehicle-mounted terminals installed in new energy vehicles and a cloud server arranged at a remote end.

[0167] On the other hand, an embodiment of the present application also provides a processing device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the parameter updating method described in the above embodiment when executing the program.

[0168] Reference below Figure 7 , Figure 7 A schematic diagram of the structure of a computer electronic device which is a processing device of an embodiment of the present application.

[0169] like Figure 7 As shown, the computer electronic device includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 702 or the program loaded from the storage part 702 to the random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the electronic device are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0170] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, a modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed, so that a computer program read therefrom is installed into the storage section 708 as needed.

[0171] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a machine-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 709, and / or installed from a removable medium 711. When the computer program is executed by a central processing unit (CPU) 701, the above-mentioned functions defined in the electronic device of the present application are executed.

[0172] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electronic device, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction-executing electronic device, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction-executing electronic device, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0173] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the processing equipment, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the aforementioned module, program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based electronic device that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0174] The units or modules involved in the embodiments described in the present application may be implemented by software or by hardware. The units or modules described may also be arranged in a processor, for example, they may be described as: a processor comprising: an acquisition module, a sending module, a parsing module, a calculation module, a generation module and a sending module. Among them, the names of these units or modules do not constitute a limitation on the units or modules themselves under certain circumstances. For example, the calculation module may also be described as "used to input the vehicle data after the analysis process into a preset algorithm to obtain a calculation result, wherein the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated".

[0175] As another aspect, the present application further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently and not be assembled into the electronic device. The above computer-readable storage medium stores one or more programs, and when the above programs are used by one or more processors to execute the parameter updating method described in the present application:

[0176] Analyze and process the acquired vehicle data;

[0177] Inputting the analyzed vehicle data into a preset algorithm to obtain a calculation result, wherein the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated;

[0178] generating a parameter update message based on the calculation result, wherein the parameter update message includes an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated;

[0179] Send the parameter update message to the vehicle terminal.

[0180] In summary, the parameter updating method, apparatus, processing equipment and storage medium provided in the embodiments of the present application closely link the Internet of Things, cloud computing and big data together through the deployed cloud platform, perform cloud storage and cloud computing of massive data, and ensure the independent, rapid and real-time updating of each vehicle parameter during operation, so that during the parameter updating process in the vehicle, there is no need to update the entire vehicle system or software, eliminating the risk of downtime due to update failure, thereby greatly saving time and energy, reducing software change costs, improving efficiency and ensuring accuracy. At the same time, due to the unified structure of variable parameters in the cloud, more accurate and personalized parameter tuning is achieved, the response to safety requirements is more timely, and the user experience can be improved.

[0181] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A parameter updating method, characterized in that: The updating method comprises: Analyze and process the acquired vehicle data; Inputting the analyzed vehicle data into a preset algorithm to obtain a calculation result, wherein the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated; generating a parameter update message based on the calculation result, wherein the parameter update message includes an identifier of the vehicle parameter to be updated and a target value of the vehicle parameter to be updated; Sending the parameter update message to the vehicle terminal; The parsing process of the acquired vehicle data includes: The vehicle data is split according to field attributes, where one field attribute corresponds to one vehicle component; The split vehicle data is stored in a preset data table; Before parsing the acquired vehicle data, the method further includes: Removing abnormal data from the vehicle data, wherein the abnormal data includes at least one of the following: duplicate data, data with missing fields, and erroneous data; Filter valid data in the vehicle data after removing abnormal data according to preset conditions, wherein the preset conditions are related to the actual meaning of vehicle parameters; The generating of the parameter update message based on the calculation result comprises: Analyze the calculation results to obtain the flag fields of each vehicle parameter; When the flag field indicates that the vehicle parameter needs to be updated, a parameter update message is generated based on the identifier of the vehicle parameter that needs to be updated and the target value of the vehicle parameter that needs to be updated.

2. The parameter updating method according to claim 1, characterized in that: The vehicle is a new energy vehicle, and the vehicle parameters include performance parameters of a power battery pack.

3. The parameter updating method according to claim 1, characterized in that: The sending the parameter update message to the vehicle-mounted terminal comprises: The parameter update message is sent to the vehicle terminal based on the vehicle frame number, and the vehicle data of each vehicle corresponds to the vehicle frame number one by one.

4. A parameter updating method, characterized in that: The parameter updating method comprises: Reporting vehicle data to a server, so that the server processes the vehicle data through a preset algorithm to obtain a calculation result, wherein the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated; Receiving a parameter update message sent by a server, wherein the parameter update message includes an identifier of a vehicle parameter to be updated and a target value of the vehicle parameter to be updated; Based on the identifier of the vehicle parameter to be updated, updating the current vehicle parameter to the target value; The operation result is that the server splits the vehicle data according to field attributes, and stores the split vehicle data in a preset data table, where one field attribute corresponds to one vehicle component; The vehicle data is valid data in the vehicle data after the server removes abnormal data in the vehicle data, and the abnormal data is filtered out according to a preset condition, wherein the abnormal data includes at least one of the following: duplicate data, data with missing fields, and erroneous data; The parameter update message is: the server parses the calculation result to obtain the flag field of each vehicle parameter; when the flag field indicates that the vehicle parameter needs to be updated, it is generated based on the identification of the vehicle parameter that needs to be updated and the target value of the vehicle parameter that needs to be updated.

5. A parameter updating device, characterized in that: The device comprises: A reporting module, used to report vehicle data to a server, so that the server processes the vehicle data through a preset algorithm to obtain a calculation result, wherein the calculation result includes a flag field of each vehicle parameter, and the flag field indicates whether the corresponding vehicle parameter needs to be updated; A receiving module, used for receiving a parameter update message sent by a server, wherein the parameter update message includes an identifier of a vehicle parameter to be updated and a target value of the vehicle parameter to be updated; An updating module, configured to update the current vehicle parameter to the target value based on the identifier of the vehicle parameter to be updated; The operation result is that the server splits the vehicle data according to field attributes, and stores the split vehicle data in a preset data table, where one field attribute corresponds to one vehicle component; The vehicle data is valid data in the vehicle data after the server removes abnormal data in the vehicle data, and the abnormal data is filtered out according to a preset condition, wherein the abnormal data includes at least one of the following: duplicate data, data with missing fields, and erroneous data; The parameter update message is: the server parses the calculation result to obtain the flag field of each vehicle parameter; when the flag field indicates that the vehicle parameter needs to be updated, it is generated based on the identification of the vehicle parameter that needs to be updated and the target value of the vehicle parameter that needs to be updated.

6. A computer processing device, characterized in that The processing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the parameter updating method according to any one of claims 1 to 3 when executing the program.

7. A computer-readable storage medium having a computer program stored thereon, wherein the computer program is used to implement the parameter updating method according to any one of claims 1 to 3.

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