Pulse spectrum parameter partitioning method, device, electronic device and storage medium

Abstract

The present invention discloses a method, device, electronic device, and storage medium for spectral parameter partitioning. The method includes: obtaining each spectral parameter of the current carbon load spectral map, and determining the number of road spectrum data corresponding to each spectral parameter; determining the number of partitions for spectral partitioning the spectral parameters, and determining the partition boundary parameters of each spectral partition based on the number of partitions and the number of road spectrum data; determining the target spectral partition of the spectral parameter based on the partition boundary parameters; wherein the target spectral partition is used to correct the spectral parameters of the current carbon load spectral map. Through the technical solution disclosed in the present invention, the calibration result of the carbon load is improved, thereby improving the model accuracy of the carbon load estimation model, and further improving the accuracy of the carbon load estimation result.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic calibration of carbon loading, and in particular to a pulse spectrum parameter partitioning method, device, electronic equipment and storage medium. Background Art

[0002] Current carbon load measurement systems are high-tech mechatronic products, and calibration is extremely complex. For example, the transient carbon load correction map and passive regeneration map within the carbon load estimation strategy require calibration data to undergo bench calibration, vehicle calibration, three-high calibration, road testing, and market validation before mass product adoption. Calibration data must be adapted to all vehicle operating conditions, a complex process that often fails to fully adapt to the full vehicle operating conditions. Therefore, offline simulation is currently the most commonly used calibration method. However, the deviation between offline simulation data and test data can sometimes be significant, resulting in poor accuracy of the subsequent carbon load estimation model and, in turn, reduced accuracy of the estimation results. Summary of the Invention

[0003] The present invention provides a pulse spectrum parameter partitioning method, device, electronic device and storage medium to solve the problem in the prior art that the carbon load estimation model obtained based on the calibration results is poor in accuracy, which leads to reduced accuracy of the estimation results obtained during the estimation process. The method improves the calibration results of the carbon load, thereby improving the model accuracy of the carbon load estimation model, and further improving the accuracy of the carbon load estimation results.

[0004] In a first aspect, an embodiment of the present invention provides a method for partitioning pulse spectrum parameters, the method comprising:

[0005] Obtaining each spectrum parameter of the current carbon load spectrum map, and determining the number of road spectrum data corresponding to each spectrum parameter;

[0006] Determining the number of partitions for partitioning the map spectrum parameters, and determining a partition boundary parameter of each map spectrum partition based on the number of partitions and the number of each road spectrum data;

[0007] A target spectrum partition of the spectrum parameter is determined based on the partition boundary parameter; wherein the target spectrum partition is used to correct the spectrum parameter of the current carbon loading spectrum map.

[0008] Optionally, the determining the amount of road spectrum data corresponding to each map spectrum parameter includes:

[0009] Obtaining road spectrum data of the current carbon loading spectrum map;

[0010] For any map parameter, determining at least one road spectrum data corresponding to the current map parameter;

[0011] The number of road spectrum data corresponding to the current pulse spectrum parameter is determined based on the number of each road spectrum data.

[0012] Optionally, the current carbon load spectrum is used as a model parameter of a carbon load estimation model;

[0013] Accordingly, the determining of the number of partitions for partitioning the pulse spectrum parameters includes:

[0014] Obtaining the carbon load quantity of the carbon load value output by the carbon load estimation model;

[0015] The number of partitions of the pulse spectrum partition is determined based on the carbon load quantity and a preset quantity correspondence relationship.

[0016] Optionally, the determining of the partition boundary parameters of each of the pulse spectrum partitions based on the number of partitions and the amount of each of the road spectrum data includes:

[0017] Determining a total number of road spectra of the road spectrum data of the current carbon loading map;

[0018] Determining a threshold value of the number of road spectra of the pulse spectrum partition based on the total number of road spectra and the number of partitions;

[0019] Based on each of the patency parameters, the amount of road spectrum data corresponding to each of the patency parameters, and the road spectrum amount threshold, partition boundary parameters corresponding to each of the patency partitions are determined.

[0020] Optionally, determining a threshold value of the number of road spectra of the pulse spectrum partition based on the total number of road spectra and the number of partitions includes:

[0021] The total number of the road spectrum is compared with the number of the partitions to obtain the road spectrum mean of the pulse spectrum partition.

[0022] A preset road spectrum quantity deviation parameter is obtained, and a road spectrum quantity threshold of the pulse spectrum partition is determined based on the deviation parameter and the road spectrum mean.

[0023] Optionally, the determining the target pulse spectrum partition of the pulse spectrum parameter based on the partition boundary parameter includes:

[0024] Based on the maximum pulse spectrum parameter, the minimum pulse spectrum parameter and the partition boundary parameters of each pulse spectrum parameter, each pulse spectrum parameter is partitioned to obtain a target pulse spectrum partition.

[0025] Optionally, the correcting the spectrum parameters of the current carbon loading spectrum graph includes:

[0026] Initializing the initial correction factors corresponding to the target pulse spectrum partitions respectively;

[0027] Each initial correction factor is optimized to obtain each target correction factor, and the pulse spectrum parameters in each target pulse spectrum partition are corrected based on each target correction factor.

[0028] In a second aspect, an embodiment of the present invention further provides a pulse spectrum parameter partitioning device, the device comprising:

[0029] A road spectrum data quantity determination module is used to obtain each spectrum parameter of the current carbon load spectrum map and respectively determine the number of road spectrum data corresponding to each spectrum parameter;

[0030] a partition boundary parameter determination module, configured to determine the number of partitions for partitioning the pulse spectrum parameters, and determine a partition boundary parameter of each pulse spectrum partition based on the number of partitions and the amount of each road spectrum data;

[0031] A target spectrum partition determination module is used to determine a target spectrum partition of the spectrum parameter based on the partition boundary parameter; wherein the target spectrum partition is used to correct the spectrum parameter of the current carbon loading spectrum map.

[0032] In a third aspect, an embodiment of the present invention further provides an electronic device, including:

[0033] at least one processor; and

[0034] a memory communicatively connected to the at least one processor; wherein,

[0035] The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the pulse spectrum parameter partitioning method according to any embodiment of the present invention.

[0036] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the pulse spectrum parameter partitioning method of any embodiment of the present invention when executed.

[0037] The technical solution of the embodiment of the present invention obtains each spectral parameter of the current carbon load spectral map and determines the number of road spectrum data corresponding to each spectral parameter; determines the number of partitions for spectral partitioning the spectral parameters, and determines the partition boundary parameters of each spectral partition based on the number of partitions and the number of road spectrum data; and determines the target spectral partition of the spectral parameter based on the partition boundary parameters; wherein the target spectral partition is used to correct the spectral parameters of the current carbon load spectral map. The above technical solution partitions the spectral parameters by the number of road spectra corresponding to each spectral parameter, thereby solving the problem in the prior art of poor accuracy of the carbon load estimation model obtained based on calibration results, which in turn leads to reduced accuracy of the estimation results obtained during the estimation process. It improves the calibration results of the carbon load, thereby improving the model accuracy of the carbon load estimation model, and further improving the accuracy of the carbon load estimation results.

[0038] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0040] Figure 1 This is a flow chart of a pulse spectrum parameter partitioning method provided in accordance with the first embodiment of the present invention;

[0041] Figure 2 This is a flow chart of a pulse spectrum parameter partitioning method provided in accordance with the second embodiment of the present invention;

[0042] Figure 3 This is a structural diagram of a pulse spectrum parameter partitioning device provided according to the third embodiment of the present invention;

[0043] Figure 4 It is a structural diagram of an electronic device for implementing the pulse spectrum parameter partitioning method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, such that the embodiments of the present invention described herein can be practiced in an order other than that illustrated or described herein.

[0046] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0047] It is understandable that before using the technical solutions disclosed in the various embodiments of this disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved in this disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0048] For example, in response to a user's active request, a prompt message is sent to the user to clearly inform the user that the operation requested will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the electronic device, application, server, storage medium, or other software or hardware that performs the operations of the disclosed technical solution based on the prompt message.

[0049] As an optional but non-limiting implementation, in response to receiving a user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. Furthermore, the pop-up window may also contain a selection control for the user to select "agree" or "disagree" to provide personal information to the electronic device.

[0050] It is understandable that the above notification and user authorization process are merely illustrative and do not limit the implementation of the present disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0051] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) must comply with the requirements of relevant laws, regulations and relevant provisions.

[0052] Example 1

[0053] Figure 1 A flowchart of a pulse spectrum parameter partitioning method is provided for the first embodiment of the present invention. This embodiment is applicable to partitioning the pulse spectrum parameters of carbon loading. The method can be executed by a pulse spectrum parameter partitioning device. The pulse spectrum parameter partitioning device can be implemented in the form of hardware and / or software. The pulse spectrum parameter partitioning device can be configured in a smart terminal and a cloud server.

[0054] In some other embodiments, during the process of partitioning the pulse spectrum parameters in the carbon load pulse spectrum diagram, the pulse spectrum parameters are evenly divided based on the number of pulse spectrum parameters and the required number of partitions to obtain a partitioning result. Based on the above partitioning method, the road spectrum data of each pulse spectrum partition in the partitioning result obtained is not equal, so it cannot adapt to the operating conditions of the whole vehicle, so that the model accuracy of the carbon load estimation model obtained based on this is poor, and then the accuracy of the carbon load estimation result obtained based on the model is low. In order to solve the above technical problems, the technical solution of the embodiment of the present invention provides a pulse spectrum parameter partitioning method, which performs pulse spectrum partitioning based on the number of road spectra corresponding to each pulse spectrum parameter in the carbon load pulse spectrum diagram, so that the road spectrum data corresponding to each pulse spectrum partition is in a roughly equal state, and the pulse spectrum parameters are corrected based on this partitioning result to obtain a carbon load estimation model with improved performance, thereby improving the accuracy of the carbon load estimation result. Figure 1 As shown, the method specifically includes:

[0055] S110 , obtaining each map parameter of the current carbon load map, and determining the number of road spectrum data corresponding to each map parameter.

[0056] In an embodiment of the present invention, the carbon loading estimation model may include a carbon particle primary discharge module, an active regeneration module, and a passive regeneration module. Specifically, both the carbon particle primary discharge module and the active regeneration module include a carbon loading spectrum map. Optionally, the module to which the current carbon loading spectrum map belongs is determined, for example, the carbon particle primary discharge module or the active regeneration module to which the current carbon loading spectrum map belongs, and the carbon loading spectrum map in the module is read to obtain the spectrum parameters of the spectrum map.

[0057] Specifically, based on the determination of each map parameter, engine road spectrum data corresponding to the map parameter is collected, the road spectrum data corresponding to each map parameter is determined, and the number of road spectrum data corresponding to each map data is determined. Optionally, the method for determining the number of road spectrum data corresponding to each map parameter may include: obtaining road spectrum data of a current carbon loading map; for any map parameter, determining at least one road spectrum data corresponding to the current map parameter, and determining the number of road spectrum data corresponding to the current map parameter based on the number of each road spectrum data.

[0058] It should be noted that the road spectrum parameters include but are not limited to engine speed, engine fuel injection amount, engine transient excess air coefficient, exhaust gas mass flow, PDF temperature, nitrogen dioxide mass flow and other engine-related characteristic data. Specifically, when obtaining each pulse spectrum parameter in the carbon load estimation model, the engine road spectrum data corresponding to this pulse spectrum parameter is collected. Among them, each pulse spectrum parameter is a parameter corresponding to each pulse spectrum operating condition interval and each road spectrum data is partitioned and statistically processed. For any pulse spectrum parameter, the various road spectrum data of the current pulse spectrum parameter are determined, and the number of each road spectrum data is counted to determine the number of each road spectrum data corresponding to the current pulse spectrum parameter. Optionally, based on the above implementation method, the road spectrum data corresponding to each pulse spectrum parameter are counted respectively to determine the number of road spectrum data corresponding to each pulse spectrum parameter.

[0059] S120: Determine the number of partitions for partitioning the pulse spectrum parameters, and determine the partition boundary parameters of each pulse spectrum partition based on the number of partitions and the number of spectrum data of each channel.

[0060] In the embodiment of the present invention, each spectrum parameter is partitioned so that each spectrum parameter in the same partition shares the same correction factor for parameter correction, thereby obtaining a stable and accurate carbon loading estimation model.

[0061] Optionally, the method for determining the number of partitions for partitioning the spectrum parameters may include: obtaining the carbon loading quantity of the carbon loading value output by the carbon loading estimation model; and determining the number of partitions for the spectrum partitioning based on the carbon loading quantity and a preset quantity correspondence. This embodiment can be advantageous in that the corresponding quantity facilitates subsequent determination of a correction factor, thereby facilitating correction of the spectrum parameters, ultimately resulting in an accurate carbon loading estimation model.

[0062] Specifically, based on determining the number of partitions for the spectrum parameters, each spectrum parameter is partitioned based on the number of partitions to obtain a target partition result. Specifically, the partitioning method may include, but is not limited to, determining partition boundary parameters for each spectrum partition, and then partitioning each spectrum parameter based on the partition boundary parameters. Optionally, the method for determining the partition boundary parameters for each spectrum partition based on the number of partitions and the number of each spectrum data may include: determining the total number of spectrum data for the current carbon load spectrum map; determining a spectrum number threshold for the spectrum partition based on the total number of spectrum data and the number of partitions; and determining the partition boundary parameters corresponding to each spectrum partition based on each spectrum parameter, the number of spectrum data corresponding to each spectrum parameter, and the spectrum number threshold.

[0063] Specifically, the total number of road spectra of the collected road spectrum data is determined, and based on the total number of road spectra and the number of partitions, a road spectrum number threshold for each pulse spectrum partition in the process of partitioning each pulse spectrum parameter is determined. Optionally, the method for determining the threshold may include: performing a ratio processing on the total number of road spectra and the number of partitions to obtain a road spectrum mean for the pulse spectrum partition; obtaining a preset road spectrum number deviation parameter, and determining the road spectrum number threshold for the pulse spectrum partition based on the deviation parameter and the road spectrum mean.

[0064] Specifically, the following expression is used to determine the threshold value of the number of road spectra of the pulse spectrum partition. Exemplarily, the expression includes:

[0065]

[0066] pjz=pjz_cs±pjz_pc

[0067] Where pjz_cs represents the road spectrum mean, N represents the total number of road spectra, n represents the number of partitions, pjz represents the road spectrum number threshold, and pjz_pc represents the road spectrum number deviation parameter.

[0068] It should be noted that based on experience, the deviation parameter is usually set to 1%. The effect of setting this parameter is that it not only ensures the accuracy of the threshold, but also conforms to the actual situation, making the results more reliable. Of course, other data can also be set based on experience, and this embodiment is not limited to this.

[0069] Optionally, on the basis of determining the road spectrum quantity threshold of the pulse spectrum partition, the partition boundaries corresponding to each pulse spectrum partition are determined based on each pulse spectrum parameter, the number of road spectrum data corresponding to each pulse spectrum parameter, and the road spectrum quantity threshold.

[0070] Specifically, sort each pulse spectrum parameter and determine the minimum pulse spectrum parameter among each pulse spectrum parameter. Use the minimum pulse spectrum parameter as the minimum partition boundary parameter of the first pulse spectrum partition, and determine whether the number of road spectra corresponding to the minimum pulse spectrum parameter reaches the road spectrum number threshold of the pulse spectrum partition. If it reaches, the minimum pulse spectrum parameter is used as the maximum partition boundary parameter of the current pulse spectrum partition at the same time; otherwise, if it does not reach, determine the adjacent next pulse spectrum parameter, and accumulate the road spectrum numbers corresponding to the two pulse spectrum parameters to determine whether the accumulated road spectrum number reaches the road spectrum number threshold of the pulse spectrum partition. Optionally, if it reaches, use the adjacent pulse spectrum parameter as the maximum partition boundary parameter of the current pulse spectrum partition. Otherwise, if it does not reach, determine the adjacent next pulse spectrum parameter again, and whether the accumulated road spectrum number reaches the road spectrum number threshold, until the maximum partition boundary parameter of the current pulse spectrum partition is determined.

[0071] Optionally, based on determining the maximum partition boundary parameter of the current pulse spectrum partition, the next pulse spectrum parameter adjacent to the current pulse spectrum parameter is used as the minimum partition boundary parameter of the next pulse spectrum partition, and the maximum partition boundary parameter of the next pulse spectrum partition is further determined based on the accumulated number of road spectra. The partition boundary parameters of each pulse spectrum partition are determined based on the above operations.

[0072] On the basis of the above implementation method, for the current pulse spectrum partition, if the cumulative road spectrum number of the current pulse spectrum parameter and the previous pulse spectrum parameters does not reach the road spectrum number threshold, but the cumulative road spectrum number of the next pulse spectrum parameter adjacent to the current pulse spectrum parameter and the previous pulse spectrum parameters exceeds the road spectrum number threshold, in this case, determine the difference between the two cumulative road spectrum numbers and the road spectrum number threshold, and use the pulse spectrum parameter corresponding to the road spectrum number with the smaller difference as the maximum partition boundary parameter of the current pulse spectrum partition.

[0073] S130, determining a target spectrum partition of the spectrum parameters based on the partition boundary parameters; wherein the target spectrum partition is used to correct the spectrum parameters of the current carbon loading spectrum diagram.

[0074] In the embodiment of the present invention, on the basis of determining the boundary parameters of each pulse spectrum partition, each pulse spectrum parameter is partitioned based on the minimum partition boundary parameter and the maximum partition boundary parameter of each pulse spectrum partition to obtain the target pulse spectrum partition of the pulse spectrum parameter.

[0075] The technical solution of the embodiment of the present invention obtains each spectral parameter of the current carbon load spectral map and determines the number of road spectrum data corresponding to each spectral parameter; determines the number of partitions for spectral partitioning the spectral parameters, and determines the partition boundary parameters of each spectral partition based on the number of partitions and the number of road spectrum data; and determines the target spectral partition of the spectral parameter based on the partition boundary parameters; wherein the target spectral partition is used to correct the spectral parameters of the current carbon load spectral map. The above technical solution partitions the spectral parameters by the number of road spectra corresponding to each spectral parameter, thereby solving the problem in the prior art of poor accuracy of the carbon load estimation model obtained based on calibration results, which in turn leads to reduced accuracy of the estimation results obtained during the estimation process. It improves the calibration results of the carbon load, thereby improving the model accuracy of the carbon load estimation model, and further improving the accuracy of the carbon load estimation results.

[0076] Example 2

[0077] Figure 2 This is a flow chart of a spectrum parameter partitioning method provided in the second embodiment of the present invention. Based on the above embodiment, this embodiment optionally corrects the spectrum parameters of the current carbon loading spectrum, including:

[0078] Initialize the initial correction factors corresponding to each target pulse spectrum partition;

[0079] Each initial correction factor is optimized to obtain each target correction factor, and the pulse spectrum parameters in each target pulse spectrum partition are corrected based on each target correction factor. Figure 2 As shown, the method includes:

[0080] S210: Acquire each map parameter of the current carbon load map, and determine the number of road spectrum data corresponding to each map parameter.

[0081] S220: Determine the number of partitions for partitioning the pulse spectrum parameters, and determine the partition boundary parameters of each pulse spectrum partition based on the number of partitions and the number of spectrum data of each path.

[0082] S230 , determining a target spectrum partition of the spectrum parameters based on the partition boundary parameters; wherein the target spectrum partition is used to correct the spectrum parameters of the current carbon loading spectrum map.

[0083] S240 , initializing initial correction factors corresponding to each target pulse spectrum partition, optimizing each initial correction factor to obtain each target correction factor, and correcting each pulse spectrum parameter in each target pulse spectrum partition based on each target correction factor.

[0084] In this embodiment of the present invention, regions are divided according to the number of road spectra corresponding to the spectral map parameters, ensuring that the number of road spectra in each of the n regions is roughly equal. A correction factor is initialized for each region, and an optimization algorithm is used to optimize these n correction factors to obtain a target correction factor. Based on each target correction factor, the spectral map parameters in each target spectral map partition are then modified, ensuring that the carbon load estimation result based on the spectral map data is closer to the target carbon load weighing result.

[0085] The technical solution of the embodiment of the present invention solves the problem in the prior art that the carbon load estimation model obtained based on the calibration results has poor accuracy, which in turn leads to reduced accuracy of the estimation results obtained during the estimation process. It achieves the goal of improving the calibration results of the carbon load, thereby improving the model accuracy of the carbon load estimation model, and further improving the accuracy of the carbon load estimation results.

[0086] Example 3

[0087] Figure 3 This is a schematic diagram of the structure of a pulse spectrum parameter partitioning device provided by the third embodiment of the present invention. Figure 3 As shown, the device includes: a road spectrum data quantity determination module 310, a partition boundary parameter determination module 320 and a target pulse spectrum partition determination module 330; wherein,

[0088] The road spectrum data quantity determination module 310 is used to obtain each map parameter of the current carbon load map and determine the number of road spectrum data corresponding to each map parameter;

[0089] a partition boundary parameter determination module 320 for determining the number of partitions for partitioning the pulse spectrum parameters, and determining a partition boundary parameter of each pulse spectrum partition based on the number of partitions and the number of road spectrum data;

[0090] The target spectrum partition determining module 330 is configured to determine a target spectrum partition of the spectrum parameter based on the partition boundary parameter; wherein the target spectrum partition is used to correct the spectrum parameter of the current carbon loading spectrum map.

[0091] Based on the above embodiments, optionally, the road spectrum data quantity determination module 310 includes:

[0092] a road spectrum data acquisition unit, configured to acquire road spectrum data of the current carbon loading spectrum map;

[0093] The road spectrum data quantity determining unit is used to determine, for any map spectrum parameter, at least one road spectrum data corresponding to the current map spectrum parameter, and determine the number of road spectrum data corresponding to the current map spectrum parameter based on the number of each road spectrum data.

[0094] Based on the above embodiments, optionally, the current carbon loading spectrum is used as a model parameter of the carbon loading estimation model;

[0095] Accordingly, the partition boundary parameter determination module 320 includes:

[0096] a carbon load quantity acquisition unit, configured to acquire the carbon load quantity of the carbon load value output by the carbon load estimation model;

[0097] A partition quantity determining unit is used to determine the partition quantity of the pulse spectrum partition based on the carbon loading quantity and a preset quantity correspondence relationship.

[0098] Based on the above embodiments, optionally, the partition boundary parameter determination module 320 includes:

[0099] a total number of road spectra determining unit, configured to determine the total number of road spectra of the road spectrum data of the current carbon loading map;

[0100] a road spectrum quantity threshold determination unit, configured to determine a road spectrum quantity threshold of the pulse spectrum partition based on the total number of road spectra and the number of partitions;

[0101] The partition boundary parameter determining unit is configured to determine the partition boundary parameters corresponding to each of the pulsation spectrum partitions based on each of the pulsation spectrum parameters, the amount of road spectrum data corresponding to each of the pulsation spectrum parameters, and the road spectrum amount threshold.

[0102] Based on the above embodiments, optionally, the road spectrum quantity threshold determination unit includes:

[0103] a road spectrum mean determination subunit, configured to perform a ratio processing on the total number of road spectra and the number of partitions to obtain a road spectrum mean of the pulse spectrum partition;

[0104] The road spectrum quantity threshold determination subunit is configured to obtain a preset road spectrum quantity deviation parameter, and determine the road spectrum quantity threshold of the pulse spectrum partition based on the deviation parameter and the road spectrum mean.

[0105] Based on the above embodiments, optionally, the target pulse spectrum partition determination module 330 includes:

[0106] The target pulse spectrum partition determining unit is configured to partition each of the pulse spectrum parameters based on the maximum pulse spectrum parameter, the minimum pulse spectrum parameter and each partition boundary parameter to obtain a target pulse spectrum partition.

[0107] Based on the above embodiments, optionally, the target pulse spectrum partition determination module 330 includes:

[0108] an initial correction factor determining unit, configured to initialize the initial correction factors corresponding to the target pulse spectrum partitions;

[0109] The pulse spectrum parameter correction unit is used to optimize each initial correction factor to obtain each target correction factor, and to correct the pulse spectrum parameters in each target pulse spectrum partition based on each target correction factor.

[0110] The pulse spectrum parameter partitioning device provided by the embodiment of the present invention can execute the pulse spectrum parameter partitioning method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0111] Example 4

[0112] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0113] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0114] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0115] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the pulse spectrum parameter partitioning method.

[0116] In some embodiments, the pulse spectrum parameter partitioning method can be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the pulse spectrum parameter partitioning method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the pulse spectrum parameter partitioning method in any other appropriate manner (e.g., by means of firmware).

[0117] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0118] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0119] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0120] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0121] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0122] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0123] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0124] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for partitioning pulse spectrum parameters, characterized in that: include: Obtaining each spectrum parameter of the current carbon load spectrum map, and determining the number of road spectrum data corresponding to each spectrum parameter; Determining the number of partitions for partitioning the map spectrum parameters, and determining a partition boundary parameter of each map spectrum partition based on the number of partitions and the number of each road spectrum data; Determining a target spectrum partition of the spectrum parameter based on the partition boundary parameter; wherein the target spectrum partition is used to correct the spectrum parameter of the current carbon loading spectrum map; The determining of the partition boundary parameters of each of the pulse spectrum partitions based on the number of partitions and the amount of each of the road spectrum data includes: Determine the total number of road spectra of the number of road spectra data of the current carbon loading map; Determining a threshold value of the number of road spectra of the pulse spectrum partition based on the total number of road spectra and the number of partitions; Determining partition boundary parameters corresponding to each of the map spectrum partitions based on each of the map spectrum parameters, the number of road spectrum data corresponding to each of the map spectrum parameters, and the road spectrum number threshold; The determining, based on the total number of road spectra and the number of partitions, a threshold value of the number of road spectra of the pulse spectrum partition includes: Performing a ratio processing on the total number of the road spectrum and the number of the partitions to obtain the road spectrum mean of the pulse spectrum partition; A preset road spectrum quantity deviation parameter is obtained, and a road spectrum quantity threshold of the pulse spectrum partition is determined based on the deviation parameter and the road spectrum mean.

2. The method according to claim 1, characterized in that The determining of the number of road spectrum data corresponding to each of the map spectrum parameters includes: Obtaining road spectrum data of the current carbon loading spectrum map; For any map spectrum parameter, at least one road spectrum data corresponding to the current map spectrum parameter is determined, and the number of road spectrum data corresponding to the current map spectrum parameter is determined based on the number of each road spectrum data.

3. The method according to claim 1, characterized in that The current carbon load spectrum is used as a model parameter of the carbon load estimation model; Accordingly, the determining of the number of partitions for partitioning the pulse spectrum parameters includes: Obtaining the number of carbon load values ​​output by the carbon load estimation model; The number of partitions of the pulse spectrum partition is determined based on the number of the carbon loading values ​​and a preset quantity correspondence relationship.

4. The method according to claim 1, wherein The determining the target pulse spectrum partition of the pulse spectrum parameter based on the partition boundary parameter includes: Based on the maximum pulse spectrum parameter, the minimum pulse spectrum parameter and the partition boundary parameters of each pulse spectrum parameter, each pulse spectrum parameter is partitioned to obtain a target pulse spectrum partition.

5. The method according to claim 1, wherein The modifying of the spectrum parameters of the current carbon loading spectrum graph includes: Initializing the initial correction factors corresponding to the target pulse spectrum partitions respectively; Each initial correction factor is optimized to obtain each target correction factor, and the pulse spectrum parameters in each target pulse spectrum partition are corrected based on each target correction factor.

6. A pulse spectrum parameter partitioning device, characterized in that: include: A road spectrum data quantity determination module is used to obtain each spectrum parameter of the current carbon load spectrum map and respectively determine the number of road spectrum data corresponding to each spectrum parameter; a partition boundary parameter determination module, configured to determine the number of partitions for partitioning the pulse spectrum parameters, and determine a partition boundary parameter of each pulse spectrum partition based on the number of partitions and the amount of each road spectrum data; a target spectrum partition determination module, configured to determine a target spectrum partition of the spectrum parameter based on the partition boundary parameter; wherein the target spectrum partition is used to correct the spectrum parameter of the current carbon loading spectrum map; The partition boundary parameter determination module includes: a total number of road spectra determining unit, configured to determine the total number of road spectra of the number of road spectra data of the current carbon load map; a road spectrum quantity threshold determination unit, configured to determine a road spectrum quantity threshold of the pulse spectrum partition based on the total number of road spectra and the number of partitions; a partition boundary parameter determining unit, configured to determine the partition boundary parameters corresponding to each of the pulsation spectrum partitions based on each of the pulsation spectrum parameters, the amount of road spectrum data corresponding to each of the pulsation spectrum parameters, and the road spectrum amount threshold; The road spectrum quantity threshold determination unit includes: a road spectrum mean determination subunit, configured to perform a ratio processing on the total number of road spectra and the number of partitions to obtain a road spectrum mean of the pulse spectrum partition; The road spectrum quantity threshold determination subunit is configured to obtain a preset road spectrum quantity deviation parameter, and determine the road spectrum quantity threshold of the pulse spectrum partition based on the deviation parameter and the road spectrum mean.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the pulse spectrum parameter partitioning method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the pulse spectrum parameter partitioning method according to any one of claims 1 to 5 when executed.

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