Hybrid electric vehicle emission data batch statistics and analysis method, device and equipment and storage medium

Abstract

The invention discloses a batch statistics and analysis method, device and equipment for emission data of a hybrid electric vehicle and a storage medium, and relates to the technical field of vehicle emission, and the method comprises the steps: obtaining vehicle model information, an emission type, a test site, a test report file and a data statistics template inputted by a user; determining a target test template according to the vehicle type information, the test site and the emission type; based on the target test template, reading the test report file to obtain test data; and obtaining a data statistics file based on the data statistics template and the test data. A preset test template is matched through a test site input by a user and an emission type, and automatic analysis of reports in different formats is achieved; and the analyzed test data is automatically written into a statistical file according to a standardized format in combination with a data statistical template selected by a user, so that the efficiency and accuracy of data extraction and summarization are remarkably improved.

Description

Technical Field

[0001] This application relates to the field of automotive emission technology, and in particular to methods, apparatus, equipment and storage media for batch statistical analysis of emission data of hybrid electric vehicles. Background Technology

[0002] In the research and certification process of hybrid vehicles, dozens of emission parameters (such as carbon dioxide, nitrogen oxides, particulate matter mass, etc.) need to be extracted in batches and accurately from a large number of emission test reports generated by multiple test sites around the world, and then standardized, summarized and statistically analyzed to support regulatory compliance assessment and engineering decisions.

[0003] Currently, emission test reports are processed manually, which involves opening each file one by one, visually identifying, and manually copying and pasting the required parameters into a summary table. This method has the following technical drawbacks: first, it has low processing efficiency and cannot meet the needs of processing large batches of reports; second, it is prone to human error, leading to inaccurate or missing data extraction; and third, it is difficult to adapt to the differences in data structure, parameter naming, units, and layout of reports from different test sites, resulting in insufficient scalability and adaptability.

[0004] Currently, the urgent technical problem to be solved is how to automatically, accurately, and in batches extract and standardize key emission parameters from multi-source heterogeneous hybrid vehicle emission test reports, in order to overcome the technical shortcomings of manual processing methods, such as low efficiency, high error rate, and inability to flexibly adapt to different report formats.

[0005] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main objective of this application is to provide a method, apparatus, device, and storage medium for batch statistical analysis of hybrid vehicle emission data, aiming to solve the technical problem of how to improve the analysis efficiency of hybrid vehicle emission test reports in multi-source heterogeneous formats.

[0007] To achieve the above objectives, this application proposes a method for batch statistical analysis of emissions data from hybrid electric vehicles, the method comprising: Obtain user-inputted vehicle model information, emission type, test site, test report documents, and data statistics templates; Based on the vehicle model information, the test site, and the emission type, determine the target test template; Based on the target test template, the test report file is read to obtain test data; Based on the data statistics template and the experimental data, a data statistics file is obtained.

[0008] In one embodiment, the step of reading the test report file based on the target test template to obtain test data includes: Based on the target test template, determine the data source location information, parameter mapping relationship and data cleaning rules; Based on the data source location information, the parameter mapping relationship, and the data cleaning rules, the test report file is read to obtain the test data.

[0009] In one embodiment, the step of reading the test report file and obtaining test data based on the data source location information, the parameter mapping relationship, and the data cleaning rules includes: Based on the data source location information and the file type of the test report file, the test report file is read to determine the target parameters; Based on the target parameters and the parameter mapping relationship, parameter mapping is performed to obtain standardized data; Based on the data cleaning rules, the standardized data is cleaned to obtain experimental data.

[0010] In one embodiment, obtaining a data statistics file based on the data statistics template and the experimental data includes: Based on the data statistics template, determine the header style, parameter order, derived fields, and chart to be generated; Based on the experimental data, the header style, the parameter arrangement order, the derived fields, and the chart to be generated, a data statistics file is generated.

[0011] In one embodiment, generating a data statistics file based on the experimental data, the header style, the parameter arrangement order, the derived fields, and the chart to be generated includes: Based on the derived fields and the experimental data, the derived field data is obtained; Based on the chart to be generated and the experimental data, the chart data is obtained; A data statistics file is generated based on the parameter arrangement order, the table header style, the derived field data, the chart data, and the chart data.

[0012] In one embodiment, after reading the test report file based on the target test template to obtain the test data, the method further includes: Based on user needs, determine the location information of the new data source, the mapping relationship of the new parameter, and the new data cleaning rules; Based on the newly added data source location information, the newly added parameter mapping relationship, and the newly added data cleaning rules, a new test template is determined; Based on the newly added test templates, the test report template library will be updated.

[0013] In one embodiment, after obtaining the data statistics file based on the data statistics template and the experimental data, the process includes: Based on user needs, determine the new header style, the new parameter arrangement order, the new derived fields, and the new charts to be generated; Based on the newly added header style, the newly added parameter arrangement order, the newly added derived fields, and the newly added chart to be generated, a new data statistics template is determined; The data statistics template library will be updated based on the newly added data statistics template.

[0014] Furthermore, to achieve the above objectives, this application also proposes a device for batch statistical analysis of hybrid vehicle emission data, the device comprising: The input module is used to obtain user-input vehicle model information, emission type, test site, test report file, and data statistics template; The selection module is used to determine the target test template based on the vehicle model information, the test site, and the emission type. The reading module is used to read the test report file based on the target test template to obtain test data; The output module is used to obtain a data statistics file based on the data statistics template and the test data.

[0015] In addition, to achieve the above objectives, this application also proposes a device for batch statistical analysis of hybrid vehicle emission data, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the method for batch statistical analysis of hybrid vehicle emission data as described above.

[0016] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the method for batch statistical analysis of hybrid vehicle emission data as described above.

[0017] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the hybrid vehicle emission data batch statistics and analysis method described above.

[0018] This application obtains user-inputted vehicle model information, emission type, test site, test report file, and data statistics template; determines a target test template based on the vehicle model information, test site, and emission type; reads the test report file based on the target test template to obtain test data; and obtains a data statistics file based on the data statistics template and the test data. By matching the user-input test site and emission type with a pre-set test template, it achieves automatic parsing of reports in different formats; furthermore, combined with the user-selected data statistics template, it automatically writes the parsed test data into a statistical file in a standardized format, significantly improving the efficiency and accuracy of data extraction and summarization. Simultaneously, the template-based architecture enhances adaptability and scalability to different report formats and statistical requirements. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating an embodiment of the method for batch statistical analysis of emission data of hybrid electric vehicles in this application. Figure 2 A schematic diagram of the emission data statistical input interface provided in Embodiment 1 of the method for batch statistical analysis of emission data of hybrid electric vehicles in this application; Figure 3 This is a schematic diagram of the module structure of the hybrid vehicle emission data batch statistics and analysis device according to an embodiment of this application; Figure 4 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the batch statistical analysis method for hybrid vehicle emission data in this application embodiment.

[0022] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0024] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0025] The main solution of this application embodiment is as follows: obtaining vehicle model information, emission type, test site, test report file and data statistics template input by the user; determining the target test template based on the vehicle model information, the test site and the emission type; reading the test report file based on the target test template to obtain test data; and obtaining a data statistics file based on the data statistics template and the test data.

[0026] In this embodiment, for ease of description, the following description uses a computer as the execution subject.

[0027] Current technology processes emission test reports manually, opening each file one by one and manually copying and pasting the required parameters into a summary table. This method has the following drawbacks: first, it is inefficient and cannot meet the needs of processing large volumes of reports; second, it is prone to human error, leading to inaccurate or missing data extraction; and third, it is difficult to adapt to the differences in data structure, parameter naming, units, and layout of reports from different test sites, resulting in insufficient scalability and adaptability.

[0028] This application provides a solution that automatically parses reports of different formats by matching user-inputted test sites and emission types with pre-set test templates. Then, combined with user-selected data statistics templates, the parsed test data is automatically written into statistical files in a standardized format, which significantly improves the efficiency and accuracy of data extraction and summarization. At the same time, the templated architecture enhances the adaptability and scalability to different report formats and statistical needs.

[0029] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or computer capable of performing the above functions. The following description uses a computer as an example to illustrate this embodiment and the subsequent embodiments.

[0030] Based on this, embodiments of this application provide a method for batch statistical analysis of emission data from hybrid electric vehicles, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the method for batch statistical analysis of emission data of hybrid electric vehicles in this application.

[0031] In this embodiment, the method for batch statistical analysis of hybrid vehicle emission data includes steps S10 to S40: Step S10: Obtain the vehicle model information, emission type, test site, test report file, and data statistics template input by the user; It should be noted that vehicle model information includes, but is not limited to, vehicle model, engine management system (EMS), vehicle control unit (HCU), or transmission control unit (TCU) software version information. For example, if the vehicle is a gasoline vehicle, enter the software version numbers of the EMS and TCU; if the vehicle is a hybrid vehicle, enter the software version numbers of the EMS and HCU. Emission type refers to the regulations or test type to which the test belongs, such as Type I test, Type II test, etc. Test site refers to the location or test cycle where the emission test is conducted. Test report file refers to the document containing the raw test data, which can be in Excel, CSV, TXT, or PDF format. Data statistics template refers to the template file that the user has pre-selected or customized to specify the structure and style of the output results.

[0032] For example, refer to Figure 2 , Figure 2 For the emissions data input interface, the required information includes vehicle model information (EMS version number, vehicle model, TCU version number), emissions type (Type I test), test site ((1) test center)) and other information (catalyst, break-in mileage, etc.). Test reports can be imported via the "Import Test Report" button.

[0033] Understandably, since hybrid vehicle emissions testing involves multiple vehicle models, multiple test standards, multiple test sites, and multiple report formats, manual processing requires repeated confirmation and matching of the above information, which can easily lead to data correspondence errors or inconsistent formats. Therefore, step S10 can obtain and associate these key input parameters in a structured manner, avoiding data parsing failures or statistical biases caused by information mismatch or omissions, thereby improving the accuracy, repeatability, and system adaptability of the data processing flow.

[0034] Step S20: Determine the target test template based on the vehicle model information, the test site, and the emission type; It should be noted that the target test template is a set of predefined or configurable parsing rules for a specific test site, emission type, and vehicle model characteristics. It exists in the form of a configuration file (such as a JSON file) and is used to guide the system on how to extract and transform data from test reports in a specific format.

[0035] It is understandable that, since reports from different test sites have significant differences in data structure, parameter naming and layout, and the report structure for the same site may also be different for different emission types (such as Type I and Type II), step S20 can accurately match and call the corresponding parsing rules through the three key dimensions of vehicle model, test site and emission type, avoiding data reading errors or parsing failures due to rule mismatch, thereby improving the accuracy of data extraction and the reliability of the system.

[0036] Step S30: Based on the target test template, read the test report file to obtain test data; It should be noted that the experimental data is a structured dataset obtained after parsing, mapping, and preliminary cleaning.

[0037] Understandably, since test report files are usually multi-source, heterogeneous, and non-standardized, direct manual reading or parsing using fixed rules can easily lead to extraction errors or data loss due to format differences, inconsistent parameter naming, or inconsistent units. Therefore, step S30 enables automatic and structured data extraction and conversion based on the parsing rules defined in the target test template that matches the test site, emission type, and vehicle model. This avoids data errors and format confusion caused by manual intervention or rule mismatch, thereby improving the accuracy, completeness, and processing efficiency of data acquisition.

[0038] In one feasible implementation, step S30 may include: determining data source location information, parameter mapping relationship, and data cleaning rules based on the target test template; and reading the test report file to obtain test data based on the data source location information, the parameter mapping relationship, and the data cleaning rules.

[0039] It should be noted that the data source location information is a definition used to accurately locate the target parameter in the test report file. For example, for Excel / CSV files, it is the worksheet name and cell range, and for PDF / TXT files, it is the text matching rule or regular expression. The parameter mapping relationship is the correspondence between the original parameter names in the test report and the unified parameter names in the system. The data cleaning rules are a set of operations used to handle unit conversion, invalid character removal, missing value imputation, and format standardization.

[0040] Specifically, the step of reading the test report file and obtaining test data based on the data source location information, the parameter mapping relationship, and the data cleaning rules includes: reading the test report file based on the data source location information and the file type of the test report file, and determining the target parameters; performing parameter mapping based on the target parameters and the parameter mapping relationship to obtain standardized data; and performing data cleaning on the standardized data based on the data cleaning rules to obtain test data.

[0041] It should be noted that the file types of the test report include Excel (.xlsx / .xls), CSV, TXT, or PDF, etc.; the target parameters are the raw data items extracted from the test report based on the data source location information (which may have original names, units, and specific formats); and the standardized data is the data after the target parameters have been converted into data with unified naming and structure within the system according to the parameter mapping relationship.

[0042] For example, for a PDF report from a test site, the data source location information might be defined as "finding the text line containing 'CO2 Emission' and extracting the numerical part thereafter"; the extracted target parameter is "CO2 Emission: 125.6 g / km"; through parameter mapping, "CO2 Emission" is mapped to the internal parameter name "CO2_gkm", resulting in the standardized data "CO2_gkm: 125.6"; then, according to the data cleaning rules, the unit "g / km" is uniformly converted to "g / km" and the validity of the value is verified, finally obtaining the cleaned test data "CO2_gkm: 125.6".

[0043] In this embodiment, by decomposing the template parsing process into three standardized steps—location, mapping, and cleaning—the technical challenge of accurately and repeatedly extracting key emission parameters from multi-source heterogeneous reports is solved, and the modularity, configurability, and high reliability of the data parsing process are achieved.

[0044] In one feasible implementation, step S30 may include: determining new data source location information, new parameter mapping relationships, and new data cleaning rules based on user needs; determining new test templates based on the new data source location information, the new parameter mapping relationships, and the new data cleaning rules; and updating the test report template library based on the new test templates.

[0045] It should be noted that user requirements refer to the system's need to support parsing previously uncovered test site report formats or new emission test types; new data source location information refers to new rules defined for this new report format to locate target parameter positions; new parameter mapping relationships refer to new correspondences mapping the native parameter names in this new report to unified parameter names within the system; new data cleaning rules refer to new cleaning rules such as unit conversion and invalid character handling formulated for the characteristics of this new report data; new test templates refer to complete template configuration files composed of the above-mentioned new location information, mapping relationships, and cleaning rules, used to parse this new report format; and the test report template library refers to the collection of all available test templates stored within the system, usually existing in the form of files or databases, and is the core knowledge base for the system to achieve multi-format support.

[0046] For example, when the system needs to support Excel-format emission reports for a new test site "Test_Cycle_X", the user inputs new requirements through the interface. The system guides the user to define the following in sequence: data source location information (e.g., the parameter "NOx [mg / km]" is located in "Sheet1!D10"), new parameter mapping relationships (e.g., mapping "NOx [mg / km]" to the internal parameter name "NOx_mgkm"), and new data cleaning rules (e.g., deleting the unit string "[mg / km]", keeping only the numerical value). After completion, the system generates a new test template "Template_Test_Cycle_X.mat" and adds it to the test report template library. Afterward, the new report format can be parsed by the system normally.

[0047] In this embodiment, by providing a user-configurable template extension mechanism, the system can flexibly adapt to new test report formats, solving the technical rigidity problem of traditional fixed parsing programs needing to be redeveloped or have their source code modified because they cannot adapt to new formats, and realizing the sustainable expansion and long-term applicability of the system's parsing capabilities.

[0048] The above are merely feasible implementations of step S30 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S30.

[0049] Step S40: Based on the data statistics template and the experimental data, a data statistics file is obtained.

[0050] It should be noted that the data statistics file is an output file generated according to the selected template specifications, containing structured emission data and its analysis results (such as derived calculation values), usually in Excel format, for subsequent review, analysis and archiving.

[0051] It is understandable that different users or application scenarios (such as regulatory submissions, internal R&D analysis, and management reports) have different requirements for the format, content depth, and visualization of data presentation. If a fixed output format is used, it will be impossible to flexibly meet diverse needs. Therefore, step S40 is performed to dynamically organize and render experimental data based on the data statistics template selected by the user, avoiding the need for manual adjustment or report re-production due to rigid output format, thereby improving the applicability, standardization, and efficiency of the output results.

[0052] In one feasible implementation, step S40 may include: determining the header style, parameter arrangement order, derived fields, and chart to be generated based on the data statistics template; and generating a data statistics file based on the experimental data, the header style, the parameter arrangement order, the derived fields, and the chart to be generated.

[0053] It should be noted that the header style refers to the formatting definition of each column's title name, font, color, and merged cells in the output file; the parameter arrangement order refers to the column order of each emission parameter in the output table; the derived fields refer to additional indicators calculated based on the original experimental data, such as the difference from the limit, percentage change, and cumulative value; the charts to be generated refer to the graphs that need to be automatically generated in the output file according to the template preset, such as line charts and bar charts.

[0054] Specifically, generating a data statistics file based on the experimental data, the header style, the parameter arrangement order, the derived fields, and the chart to be generated includes: obtaining derived field data based on the derived fields and the experimental data; obtaining chart data based on the chart to be generated and the experimental data; and generating a data statistics file based on the parameter arrangement order, the header style, the derived field data, the chart data, and the chart data.

[0055] It should be noted that derived field data refers to additional data results obtained by calculating, transforming, or combining experimental data according to the definition of derived fields. Chart data is a graph automatically generated in the output file based on the structured information required to construct the chart, including chart type, axis labels, data point values, and series names, as well as the experimental data.

[0056] For example, the user selects the "Internal R&D Analysis Template," which defines a green background for the table header, parameters arranged in the order of "CO2, NOx, PM, electricity consumption...", requires calculation of the derived field "Difference between Actual NOx Value and Limit Value", and generates a "Line Chart of Emission Trends for Each Pollutant" at the end of the file. The system uses this template to fill in the experimental data into the corresponding positions, performs calculations, inserts charts, and finally generates a statistical file that meets the needs of R&D analysis.

[0057] In this implementation, by decoupling the data content from the presentation style and dynamically generating the final file based on the template, the problem of being unable to adapt to the needs of multiple users and scenarios due to the single output format is solved, and the flexible report generation capability of "one-time processing, multiple outputs" is realized.

[0058] In one feasible implementation, step S40 may include: determining the new header style, the new parameter arrangement order, the new derived fields, and the new chart to be generated based on user needs; determining the new data statistics template based on the new header style, the new parameter arrangement order, the new derived fields, and the new chart to be generated; and updating the data statistics template library based on the new data statistics template.

[0059] It should be noted that user requirements refer to output format or content requirements that are not covered by existing templates, proposed to meet specific reporting targets or analytical purposes; new header styles, new parameter ordering, new derived fields, and new charts to be generated are output format specifications defined for these new requirements; new data statistics templates are complete template configurations for generating new statistical documents, consisting of the above-mentioned new specifications.

[0060] For example, to meet the requirements for submitting data to European certification bodies, users need to create a new template: the header should use European standard terminology and a bilingual (Chinese and English) format, parameters should be arranged in the order required by regulations, a new "WLTP Integrated Emissions" derived field should be added, and an "Emission Pollutant Distribution Pie Chart" should be generated. After users configure these specifications through the interface, the system saves it as a new template "EU_Submission_Template" and updates it to the data statistics template library. Thereafter, users can directly select this template to generate statistical files that conform to the European standard format.

[0061] In this embodiment, by allowing users to customize and expand statistical output templates, the problem that the system output format cannot adapt to changes in external standards or updates in internal analysis needs in a timely manner is solved, thus realizing the sustainable evolution and personalized customization of output capabilities.

[0062] The above are merely feasible implementations of step S40 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S40.

[0063] This embodiment provides a method for batch statistical analysis of hybrid vehicle emission data. It acquires user-input vehicle model information, emission type, test site, test report file, and data statistics template. Based on the vehicle model information, test site, and emission type, a target test template is determined. Based on the target test template, the test report file is read to obtain test data. Based on the data statistics template and the test data, a data statistics file is obtained. By matching the user-input test site and emission type with a pre-set test template, automatic parsing of reports in different formats is achieved. Furthermore, combined with the user-selected data statistics template, the parsed test data is automatically written into a statistical file in a standardized format, significantly improving the efficiency and accuracy of data extraction and summarization. Simultaneously, the template-based architecture enhances adaptability and scalability to different report formats and statistical requirements.

[0064] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the method for batch statistical analysis of hybrid vehicle emission data in this application. Any simple modifications based on this technical concept are within the scope of protection of this application.

[0065] This application also provides a device for batch statistical analysis of emissions data from hybrid electric vehicles. Please refer to [link / reference]. Figure 3 The hybrid vehicle emission data batch statistics and analysis device includes: Input module 10 is used to obtain user-input vehicle model information, emission type, test site, test report file, and data statistics template; Selection module 20 is used to determine the target test template based on the vehicle model information, the test site and the emission type; The reading module 30 is used to read the test report file based on the target test template to obtain test data; Output module 40 is used to obtain a data statistics file based on the data statistics template and the test data.

[0066] The hybrid vehicle emission data batch statistical analysis device provided in this application, employing the hybrid vehicle emission data batch statistical analysis method in the above embodiments, can solve the technical problem of how to improve the analysis efficiency of multi-source heterogeneous format hybrid vehicle emission test reports. Compared with the prior art, the beneficial effects of the hybrid vehicle emission data batch statistical analysis device provided in this application are the same as those of the hybrid vehicle emission data batch statistical analysis method provided in the above embodiments, and other technical features in the hybrid vehicle emission data batch statistical analysis device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0067] The selection module 20 is further configured to determine the data source location information, parameter mapping relationship, and data cleaning rules based on the target test template; and to read the test report file to obtain test data based on the data source location information, the parameter mapping relationship, and the data cleaning rules.

[0068] The selection module 20 is further configured to read the test report file based on the data source location information and the file type of the test report file, determine the target parameters; perform parameter mapping based on the target parameters and the parameter mapping relationship to obtain standardized data; and perform data cleaning on the standardized data based on the data cleaning rules to obtain test data.

[0069] The reading module 30 is further configured to determine the header style, parameter arrangement order, derived fields, and chart to be generated based on the data statistics template; and to generate a data statistics file based on the experimental data, the header style, the parameter arrangement order, the derived fields, and the chart to be generated.

[0070] The reading module 30 is further configured to obtain derived field data based on the derived field and the test data; obtain chart data based on the chart to be generated and the test data; and generate a data statistics file based on the parameter arrangement order, the header style, the derived field data, the chart data, and the chart data.

[0071] The selection module 20 is also used to determine the location information of the new data source, the mapping relationship of the new parameter, and the data cleaning rules based on user needs; determine the new test template based on the location information of the new data source, the mapping relationship of the new parameter, and the data cleaning rules; and update the test report template library based on the new test template.

[0072] The reading module 30 is further configured to determine, based on user requirements, the new header style, the new parameter arrangement order, the new derived fields, and the new chart to be generated; determine, based on the new header style, the new parameter arrangement order, the new derived fields, and the new chart to be generated, the new data statistics template; and update the data statistics template library based on the new data statistics template.

[0073] This application provides a hybrid vehicle emission data batch statistics and analysis device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the hybrid vehicle emission data batch statistics and analysis method in the above embodiment 1.

[0074] The following is for reference. Figure 4 This document illustrates a structural schematic diagram of a hybrid vehicle emission data batch statistics and analysis device suitable for implementing embodiments of this application. The hybrid vehicle emission data batch statistics and analysis device in this application embodiment may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The illustrated hybrid vehicle emissions data batch statistics and analysis device is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0075] like Figure 4 As shown, the hybrid vehicle emissions data batch statistics and analysis device may include a processing unit 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into random access memory (RRAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the hybrid vehicle emissions data batch statistics and analysis device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the hybrid vehicle emissions data batch statistics and analysis equipment to exchange data wirelessly or via wired communication with other devices. Although the figure shows a hybrid vehicle emissions data batch statistics and analysis equipment with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0076] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0077] The hybrid vehicle emission data batch statistical analysis device provided in this application, employing the hybrid vehicle emission data batch statistical analysis method in the above embodiments, can solve the technical problem of how to improve the analysis efficiency of hybrid vehicle emission test reports with multi-source heterogeneous formats. Compared with the prior art, the beneficial effects of the hybrid vehicle emission data batch statistical analysis device provided in this application are the same as those of the hybrid vehicle emission data batch statistical analysis method provided in the above embodiments, and other technical features in the hybrid vehicle emission data batch statistical analysis device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0078] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0079] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0080] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the hybrid vehicle emission data batch statistics and analysis method in the above embodiments.

[0081] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0082] The aforementioned computer-readable storage medium may be included in the hybrid vehicle emission data batch statistics and analysis device; or it may exist independently and not be installed in the hybrid vehicle emission data batch statistics and analysis device.

[0083] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the hybrid vehicle emission data batch statistics and analysis device, the hybrid vehicle emission data batch statistics and analysis device performs the following actions: acquiring user-input vehicle model information, emission type, test site, test report file, and data statistics template; determining a target test template based on the vehicle model information, the test site, and the emission type; reading the test report file based on the target test template to obtain test data; and obtaining a data statistics file based on the data statistics template and the test data.

[0084] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0085] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0086] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0087] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described method for batch statistical analysis of hybrid vehicle emission data. This method can solve the technical problem of how to improve the analysis efficiency of hybrid vehicle emission test reports in multi-source heterogeneous formats. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the batch statistical analysis method for hybrid vehicle emission data provided in the above embodiments, and will not be repeated here.

[0088] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for batch statistical analysis of hybrid vehicle emission data.

[0089] The computer program product provided in this application solves the technical problem of how to improve the analysis efficiency of hybrid vehicle emission test reports in multi-source heterogeneous formats. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the batch statistical analysis method for hybrid vehicle emission data provided in the above embodiments, and will not be repeated here.

[0090] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A hybrid vehicle emission data batch statistics and analysis method, characterized in that, The method comprises: acquiring vehicle type information, emission type, test site, test report file and data statistical template input by a user; determining a target test template according to the vehicle type information, the test site and the emission type; reading the test report file based on the target test template to obtain test data; obtaining a data statistical file based on the data statistical template and the test data.

2. The method of claim 1, wherein, The reading of the test report file based on the target test template to obtain test data comprises: determining data source positioning information, parameter mapping relationship and data cleaning rules based on the target test template; reading the test report file based on the data source positioning information, the parameter mapping relationship and the data cleaning rules to obtain test data.

3. The method of claim 2, wherein, The reading of the test report file based on the data source positioning information, the parameter mapping relationship and the data cleaning rules to obtain test data comprises: reading the test report file based on the data source positioning information and the file type of the test report file to determine target parameters; performing parameter mapping based on the target parameters and the parameter mapping relationship to obtain standardized data; performing data cleaning on the standardized data based on the data cleaning rules to obtain test data.

4. The method of claim 1, wherein, The obtaining of the data statistical file based on the data statistical template and the test data comprises: determining a table header style, parameter arrangement order, derived field and to-be-generated chart based on the data statistical template; generating a data statistical file based on the test data, the table header style, the parameter arrangement order, the derived field and the to-be-generated chart.

5. The method of claim 4, wherein, The generation of the data statistical file based on the test data, the table header style, the parameter arrangement order, the derived field and the to-be-generated chart comprises: obtaining derived field data based on the derived field and the test data; obtaining chart data based on the to-be-generated chart and the test data; generating a data statistical file based on the parameter arrangement order, the table header style, the derived field data, the chart data and the chart data.

6. The method of claim 1, wherein, After the reading of the test report file based on the target test template to obtain test data, the method further comprises: determining new data source positioning information, new parameter mapping relationship and new data cleaning rules based on user demand; determining a new test template based on the new data source positioning information, the new parameter mapping relationship and the new data cleaning rules; updating a test report template library based on the new test template.

7. The method of claim 1, wherein, After the obtaining of the data statistical file based on the data statistical template and the test data, the method comprises: determining new table header style, new parameter arrangement order, new derived field and new to-be-generated chart based on user demand; determining a new data statistical template based on the new table header style, the new parameter arrangement order, the new derived field and the new to-be-generated chart; updating a data statistical template library based on the new data statistical template.

8. A hybrid vehicle emission data batch statistics and analysis device, characterized by, The device comprises: The input module is configured to acquire vehicle type information, emission type, test site, test report file and data statistical template input by a user; The selection module is configured to determine a target test template according to the vehicle type information, the test site and the emission type; The reading module is configured to read the test report file based on the target test template to obtain test data; The output module is configured to obtain a data statistical file based on the data statistical template and the test data.

9. A hybrid vehicle emission data batch statistics and analysis device, characterized by, The device comprises a memory, a processor and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the hybrid vehicle emission data batch statistics and analysis method according to any one of claims 1 to 7.

10. A storage medium, characterized by The storage medium is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the hybrid vehicle emission data batch statistics and analysis method according to any one of claims 1 to 7.

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