Electric drive efficiency data processing method, electronic equipment and medium

Abstract

The invention relates to the field of vehicle electric drive testing, in particular to an electric drive efficiency data processing method, electronic equipment and a medium. The electric drive efficiency data processing method comprises the following steps: carrying out sliding scanning on electric drive test data by adopting a preset sliding window to obtain a plurality of electric drive test data fragments; determining a data mean value of the electric drive test data fragments according to the electric drive test data fragments; determining data tolerance according to the data mean value and the data trend; determining stable data points in the electric drive test data fragment according to the data points, the data mean value and the data tolerance in the electric drive test data fragment; drawing an electric drive efficiency Map according to the stable data points; the electric drive efficiency Map comprises stable data points and electric drive efficiency points containing color filling, and colors between different electric drive efficiency points are in a gradual change trend. According to the method, the stable data points can be efficiently and reliably screened out, the data processing result is more visually displayed, the abnormal condition can be quickly identified, and the data analysis efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle electric drive testing, and more specifically, to an electric drive efficiency data processing method, electronic equipment, and medium. Background Art

[0002] In existing motor testing technology, it is usually necessary to obtain multiple efficiency data points to evaluate the performance of the prototype. However, the current efficiency data processing method has significant shortcomings. For example, for efficiency points that include multiple speeds and torques, the number of data points is usually more than 500 to 600. In this case, after each experiment, a lot of time is required to manually process the data to draw the efficiency map and analyze abnormal situations, which is time-consuming and labor-intensive. The existing efficiency map generation method cannot effectively detect mutation points and trend errors, resulting in some abnormal data cannot be identified and corrected in time. In addition, due to the lack of automation and accuracy in data screening and processing of existing methods, the identification of stable points is inaccurate, and stable efficiency points cannot be quickly screened out, which affects the reliability and accuracy of the test results.

[0003] In view of this, this application is hereby filed. Summary of the invention

[0004] The purpose of the present application is to provide an electric drive efficiency data processing method, electronic device and medium to solve the problem that the prior art cannot quickly and effectively screen stable efficiency points.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions: In a first aspect, the present application provides a method for processing electric drive efficiency data, comprising: Sliding scan the electric drive test data using a preset sliding window to obtain a plurality of electric drive test data segments; and determining a data mean of the electric drive test data segments according to the electric drive test data segments; Determine the data tolerance according to the data mean and the data trend; Determining stable data points in the electric drive test data segment according to the data points in the electric drive test data segment, the data mean, and the data tolerance; An electric drive efficiency map is drawn according to the stable data points; the electric drive efficiency map includes the stable data points and electric drive efficiency points filled with colors, and the colors between different electric drive efficiency points show a gradual trend.

[0006] In some technical solutions, the electric drive test data includes speed data and torque data; Determining the data tolerance according to the data mean and the data trend includes: Determine the speed data tolerance based on the speed data mean and data trend; The torque data tolerance is determined based on the torque data mean.

[0007] In some technical solutions, when the data mean of the rotation speed data is in a low speed interval and the data trend is increasing, the rotation speed data tolerance is determined to be a first tolerance; When the data mean of the speed data is in the low speed range and the data trend is decreasing, the speed data tolerance is determined to be the second tolerance. An absolute value of the first tolerance is greater than an absolute value of the second tolerance; When the mean value of the speed data is in the medium speed range and the data trend is increasing, the speed data tolerance is determined to be the third tolerance.

[0008] When the mean value of the speed data is in the medium speed range and the data trend is decreasing, the speed data tolerance is determined to be the fourth tolerance. The absolute value of the third tolerance is greater than the absolute value of the fourth tolerance; When the mean value of the speed data is in the high speed range and the data trend is increasing, the speed data tolerance is determined to be the fifth tolerance.

[0009] When the mean value of the speed data is in the high speed range and the data trend is decreasing, the speed data tolerance is determined to be the sixth tolerance. The absolute value of the fifth tolerance is greater than the absolute value of the sixth tolerance; When the mean value of the torque data is in the low torque range, the torque data tolerance is determined to be the seventh tolerance.

[0010] When the mean value of the torque data is in the middle torque range, the torque data tolerance is determined to be the eighth tolerance.

[0011] When the data mean of the torque data is in the high torque range, the torque data tolerance is determined to be the ninth tolerance; the absolute value of the seventh tolerance, the absolute value of the eighth tolerance, and the absolute value of the ninth tolerance increase in sequence.

[0012] In some technical solutions, determining the stable data points in the electric drive test data segment according to the data points in the electric drive test data segment, the data mean and the data tolerance includes: When a difference between a data point in the electric drive test data segment and the data mean is within a data tolerance range, determining the data point as a stable data point in the electric drive test data segment; When the difference between the data point in the electric drive test data segment and the data mean is not within the data tolerance range, the data point is determined to be an unstable data point in the electric drive test data segment.

[0013] In some technical solutions, drawing an electric drive efficiency map according to the stable data points includes: Determining a corrected stable data point according to the stable data point and a preset target sequence; sorting the corrected stable data points in chronological order to create an empty efficiency matrix; filling electric drive efficiency points in the empty efficiency matrix according to the corrected stable data points; A filling color of the electric drive efficiency point is generated according to the electric drive efficiency point.

[0014] In some technical solutions, determining the corrected stable data point according to the stable data point and a preset target sequence includes: The absolute value of the difference between the stable data point and each target value in the preset target sequence is calculated, and the target value corresponding to the minimum value of the absolute value of the difference is used as the corrected stable data point.

[0015] In some technical solutions, filling the electric drive efficiency points in the empty efficiency matrix according to the corrected stable data points includes: Inputting the corrected stable data points into an electric drive efficiency algorithm to fill in the electric drive efficiency points in the empty efficiency matrix; The step of generating a filling color of the electric drive efficiency point according to the electric drive efficiency point includes: The electric drive efficiency point is input into an electric drive efficiency color algorithm to generate a filling color for the electric drive efficiency point.

[0016] In some technical solutions, after drawing the electric drive efficiency map according to the stable data points, the method further includes: Traverse the electric drive efficiency Map in sequence in a specified direction; When the difference between the current electric drive efficiency point and the previous electric drive efficiency point is greater than or equal to a preset first threshold, determining the current electric drive efficiency point as a mutation point; When the change trend of three adjacent electric drive efficiency points increases first, then decreases, and then increases again, and the difference between every two adjacent electric drive efficiency points is less than a preset first threshold, the middle electric drive efficiency point of the three adjacent electric drive efficiency points is determined as a trend error abnormal point.

[0017] In a second aspect, the present application provides an electronic device, including: at least one processor, and a memory communicatively coupled to at least one of the processors; The memory stores instructions that can be executed by at least one of the processors, and the instructions are executed by at least one of the processors so that at least one of the processors can perform the above method.

[0018] In a third aspect, the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to enable a computer to execute the above method.

[0019] Compared with the prior art, the beneficial effects of this application are: The electric drive efficiency data processing method provided by the present application includes: using a preset sliding window to slide scan the electric drive test data to obtain multiple electric drive test data fragments; according to the electric drive test data fragments, determining the data mean of the electric drive test data fragments; according to the data mean and data trend, determining the data tolerance; according to the data points in the electric drive test data fragments, the data mean and the data tolerance, determining the stable data points in the electric drive test data fragments; according to the stable data points, drawing the electric drive efficiency Map; the electric drive efficiency Map contains the stable data points and the electric drive efficiency points filled with colors, and the colors between different electric drive efficiency points show a gradual trend. Based on the sliding window, this method can capture the changes of the electric drive test data in time, and can analyze all changes one by one; the use of data tolerance can improve the accuracy of data judgment, thereby effectively screening out stable data points; the electric drive efficiency Map drawn based on stable data points can make the data processing results more intuitive, which is convenient for quickly identifying abnormal situations and improving data analysis efficiency.

[0020] Furthermore, the present application can identify mutation points and trend error abnormal points based on adjacent electric drive efficiency points and a preset first threshold. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 is a flow chart of the electric drive efficiency data processing method provided in this application; Figure 2 is a structural schematic diagram of the electric drive efficiency data processing device provided by the present application; Figure 3It is a structural schematic diagram of the electronic device provided by this application. DETAILED DESCRIPTION

[0023] The following is a description of exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0024] As mentioned in the background technology, the existing technology has the problem of being unable to quickly and effectively screen stable efficiency points, and the reliability and accuracy of data screening needs to be improved. In this regard, the present application screens out stable data points based on preset sliding windows, data trends, data tolerances, etc., and then draws an electric drive efficiency map based on the stable data points. The electric drive efficiency map contains the stable data points and electric drive efficiency points filled with colors. The colors between different electric drive efficiency points show a gradual trend, which achieves the effect of quickly and effectively screening efficiency points. The present application is further described in detail below in conjunction with the embodiments.

[0025] Example 1 Figure 1 It is a flowchart of an electric drive efficiency data processing method provided in this embodiment. The method can be executed by an electric drive efficiency data processing device. The device can be composed of software and / or hardware and is generally integrated in an electronic device. The electronic device can be an electronic computer or other terminal that can be used for data processing. For ease of understanding, each step in the method of this embodiment is executed by an electronic computer.

[0026] like Figure 1 As shown, this embodiment provides a method for processing electric drive efficiency data, comprising the following steps: S110 , performing sliding scanning on the electric drive test data using a preset sliding window to obtain a plurality of electric drive test data segments; and determining a data mean of the electric drive test data segments according to the electric drive test data segments.

[0027] The “preset sliding window” is a sliding window with a preset fixed time length, such as 2 seconds, so as to better capture short-term changes in data.

[0028] Because the electric drive test data is real-time and not dotted, it is necessary to extract the electric drive test data and screen to obtain stable values ​​such as those that are stable for more than 2 seconds. In this embodiment, a preset sliding window is used, and the window slides point by point, such as moving one data point each time, and judging whether it is stable based on the comparison of the change amplitude and tolerance between the data. By capturing short-term changes through a sliding window of, for example, 2 seconds, stable data points can be effectively screened out. Assume that 10 data points are collected per second during the continuous sampling of the motor. In order to judge the stability of the data, a 2-second time window is equivalent to 20 data points. Within the 2-second time window, one data point is slid each time to ensure that all changes in the short term are analyzed one by one. For example, the window slides from point 1 to point 20, then from point 2 to point 21, and so on. Each sliding scan of the window corresponds to an electric drive test data segment, such as a data segment from point 1 to point 20, a data segment from point 2 to point 21, and so on.

[0029] After obtaining multiple electric drive test data segments, this step further calculates the data mean of the electric drive test data segments to reflect the overall situation of each data segment. The mean value can be calculated in any way that can be implemented in the art, and this application does not impose any special restrictions on this. For example, the arithmetic mean value of the data in the data segment can be used.

[0030] S120: Determine a data tolerance according to the data mean and the data trend.

[0031] Among them, "data trend" refers to the changing trend of data in an electric drive test data segment, such as gradually increasing or decreasing. "Data tolerance" refers to the range of the difference between two adjacent data that can be allowed. Within this range, the latter of the two adjacent data is stable, and beyond this range, the latter of the two adjacent data is unstable.

[0032] This embodiment determines the data tolerance based on the data mean and data trend, avoiding the occurrence of data misjudgment. For example, the allowable speed fluctuation during acceleration may be greater than the fluctuation during deceleration, which can be close to the actual dynamic response of the motor, thereby more accurately judging the stability.

[0033] In an optional implementation, the electric drive test data includes rotation speed data and torque data; Determining the data tolerance according to the data mean and the data trend includes: Determine the speed data tolerance based on the speed data mean and data trend; The torque data tolerance is determined based on the torque data mean.

[0034] The electric drive test data in this embodiment mainly considers the rotational speed data and the torque data, and adopts different methods to determine the corresponding data tolerances of the two types of data, which has higher reliability.

[0035] In an optional implementation, when the data mean of the rotation speed data is in a low speed interval and the data trend is increasing, the rotation speed data tolerance is determined to be a first tolerance; When the data mean of the speed data is in the low speed range and the data trend is decreasing, the speed data tolerance is determined to be the second tolerance. An absolute value of the first tolerance is greater than an absolute value of the second tolerance; When the mean value of the speed data is in the medium speed range and the data trend is increasing, the speed data tolerance is determined to be the third tolerance.

[0036] When the mean value of the speed data is in the medium speed range and the data trend is decreasing, the speed data tolerance is determined to be the fourth tolerance. The absolute value of the third tolerance is greater than the absolute value of the fourth tolerance; When the mean value of the speed data is in the high speed range and the data trend is increasing, the speed data tolerance is determined to be the fifth tolerance.

[0037] When the mean value of the speed data is in the high speed range and the data trend is decreasing, the speed data tolerance is determined to be the sixth tolerance. The absolute value of the fifth tolerance is greater than the absolute value of the sixth tolerance; When the mean value of the torque data is in the low torque range, the torque data tolerance is determined to be the seventh tolerance.

[0038] When the mean value of the torque data is in the middle torque range, the torque data tolerance is determined to be the eighth tolerance.

[0039] When the data mean of the torque data is in the high torque range, the torque data tolerance is determined to be the ninth tolerance; the absolute value of the seventh tolerance, the absolute value of the eighth tolerance, and the absolute value of the ninth tolerance increase in sequence.

[0040] The low speed range is, for example, less than 5000 rpm, the medium speed range is, for example, 5000 rpm to 10000 rpm (including the endpoint value), and the high speed range is, for example, greater than 5000 rpm. The low torque is, for example, less than or equal to 100Nm, the medium torque is, for example, 100Nm to 300Nm (excluding 100Nm and including 300Nm), and the high torque is, for example, greater than 300Nm. The first tolerance is, for example, 3rpm, the second tolerance is, for example, 2 rpm, the third tolerance is, for example, 4 rpm, the fourth tolerance is, for example, 3 rpm, the fifth tolerance is, for example, 5 rpm, the sixth tolerance is, for example, 4 rpm, the seventh tolerance is, for example, 3 Nm, the eighth tolerance is, for example, 4 Nm, the ninth tolerance is, for example, 5 Nm. This implementation method classifies the different intervals to which the speed data and torque data belong, as well as the data trend of the speed data, and then sets a specific tolerance based on the classification, thereby further improving the accuracy of data screening.

[0041] For example, if the mean value of the speed data is 6000 rpm and the data trend is decreasing, the speed data tolerance is 4 rpm; if the mean value of the torque data is 200Nm, the torque data tolerance is 4Nm.

[0042] S130 , determining stable data points in the electric drive test data segment according to the data points in the electric drive test data segment, the data mean, and the data tolerance.

[0043] Among them, "stable data points" refer to data points that do not have obvious deviations compared to the surrounding data. As for which cases are considered to have obvious deviations (i.e., which are unstable data points) and which cases are considered to have no obvious deviations (i.e., which are stable data points), please refer to the following text.

[0044] In an optional implementation, determining the stable data points in the electric drive test data segment according to the data points in the electric drive test data segment, the data mean and the data tolerance includes: When a difference between a data point in the electric drive test data segment and the data mean is within a data tolerance range, determining the data point as a stable data point in the electric drive test data segment; When the difference between the data point in the electric drive test data segment and the data mean is not within the data tolerance range, the data point is determined to be an unstable data point in the electric drive test data segment.

[0045] For example, if a data point in the electric drive test data segment is a speed of 5002 rpm, the speed data mean is 5003 rpm, and the speed data tolerance is 4 rpm, then the data point is considered to be a stable data point; if a data point in the electric drive test data segment is 5009 rpm, the speed data mean is 5003 rpm, and the speed data tolerance is 4 rpm, the data point is considered unstable.

[0046] In addition, for problems such as insufficient stable data points, data fluctuations exceeding the data tolerance, and excessive rate of change, different warnings can be triggered for each situation. Level 1 warning: used to identify light data micro-fluctuations or smaller change problems, the rate of change (referring to the change slope defined in the process of the test bench raising and lowering the speed and torque, such as speed 1000rpm / s, torque response 50ms) exceeds the normal range by 20%, or the variance (referring to the variance of the data in a sliding window) is slightly higher than the expected range. Level 2 warning: Stable data points are less than 2s (that is, if there are unstable data points within the 2s range, it is considered that the stable data points are less than 2s). Level 3 warning (advanced warning): The data cannot be stabilized, which usually occurs at high speeds. Different warning messages are output according to the warning level to facilitate timely understanding of data quality during the processing process.

[0047] S140 . Draw an electric drive efficiency map according to the stable data points; the electric drive efficiency map includes the stable data points and electric drive efficiency points filled with colors, and the colors between different electric drive efficiency points show a gradual trend.

[0048] Among them, the "motor efficiency map" is a map that can reflect the distribution of motor efficiency at different speeds and torques, also known as a motor efficiency distribution map. This step draws the electric drive efficiency map based on stable data points, avoiding the adverse effects of unstable data points on the calculation results of the electric drive efficiency. Since the colors between different electric drive efficiency points show a gradual trend, if the color of a certain efficiency point is obviously different from the color of the adjacent efficiency point in front of it, it means that the efficiency point is a mutation point. For example, a certain efficiency point is positive red, and the color of the efficiency point adjacent to its left is positive yellow. The color deviation between the two is large, indicating that the efficiency point is a mutation point; if the color of a certain efficiency point is obviously different from the two adjacent efficiency points, it means that the efficiency point is a trend error abnormal point. For example, the color of a certain efficiency point is light red (its color gradient trend is that the red value gradually decreases), the color of the efficiency point adjacent to its left is positive red (its color gradient trend is that the red value gradually increases), and the color of the efficiency point adjacent to its right is positive red (its color gradient trend is that the red value gradually increases). At this time, the efficiency point is a trend error abnormal point.

[0049] In an optional implementation manner, drawing an electric drive efficiency map according to the stable data points includes: Determining a corrected stable data point according to the stable data point and a preset target sequence; sorting the corrected stable data points in chronological order to create an empty efficiency matrix; filling electric drive efficiency points in the empty efficiency matrix according to the corrected stable data points; A filling color of the electric drive efficiency point is generated according to the electric drive efficiency point.

[0050] This embodiment provides a method for drawing an electric drive efficiency map. First, based on stable data points and preset target sequences, corrected stable data points are determined to ensure that the data is aligned to specific experimental points so that the data is more in line with the experimental objectives. Then, an empty efficiency matrix is ​​created, electric drive efficiency points are filled, and electric drive efficiency point filling colors are generated, so that the electric drive efficiency map can fully and visually present the distribution of motor efficiency.

[0051] The reason why the corrected stable data points are determined first is that the measured electric drive test data may not be an integer and may deviate from the specific experimental points. If the uncorrected data points are directly used to calculate the electric drive efficiency, the deviation from the actual situation will be further increased.

[0052] Optionally, a sort function can be selected when sorting.

[0053] In an optional implementation, determining the corrected stable data point according to the stable data point and a preset target sequence includes: The absolute value of the difference between the stable data point and each target value in the preset target sequence is calculated, and the target value corresponding to the minimum value of the absolute value of the difference is used as the corrected stable data point.

[0054] The “preset target sequence” refers to a sequence of preset target values. It can be understood that the preset target sequence includes a preset speed target sequence and a preset torque target sequence.

[0055] Exemplarily, if the stable data point includes a rotation speed of 5002rpm, and the target values ​​in the preset target sequence include 4500, 5000, 5500, 6000rpm, etc., then the difference between 5002 and each target value (such as 4500, 5000, 5500, 6000rpm) is calculated respectively, and the absolute values ​​of the differences are 502, 2, 498, and 998rpm respectively. The target value 5000rpm corresponding to the minimum value of 2rpm in the absolute value of the difference is selected as the corrected stable data point, that is, the stable data point 5002rpm, and its corrected stable data point is 5000rpm.

[0056] In an optional implementation, filling the electric drive efficiency points in the empty efficiency matrix according to the corrected stable data points comprises: Inputting the corrected stable data points into an electric drive efficiency algorithm to fill in the electric drive efficiency points in the empty efficiency matrix; The step of generating a filling color of the electric drive efficiency point according to the electric drive efficiency point includes: The electric drive efficiency point is input into an electric drive efficiency color algorithm to generate a filling color for the electric drive efficiency point.

[0057] This implementation adopts a specific algorithm to calculate the electric drive efficiency points and fill colors respectively, so as to achieve the effect of quickly filling the motor efficiency map.

[0058] Optionally, the electric drive efficiency algorithm is as follows: Electric drive efficiency (%) = (output power / input power) × 100%. Output power = torque collected at the motor end * speed / 9550. Input power = DC voltage at the motor input end * DC current.

[0059] Optionally, the electric drive efficiency color algorithm uses an imagesc function.

[0060] In an optional implementation manner, after drawing the electric drive efficiency Map according to the stable data points, the method further includes: Traverse the electric drive efficiency Map in sequence in a specified direction; When the difference between the current electric drive efficiency point and the previous electric drive efficiency point is greater than or equal to a preset first threshold, determining the current electric drive efficiency point as a mutation point; When the change trend of three adjacent electric drive efficiency points increases first, then decreases, and then increases again, and the difference between every two adjacent electric drive efficiency points is less than a preset first threshold, the middle electric drive efficiency point of the three adjacent electric drive efficiency points is determined as a trend error abnormal point.

[0061] Among them, the "specified direction" includes two directions, from left to right and from top to bottom, so the traversal is a double loop traversal of all rows and columns of the matrix to ensure that each efficiency point is compared with its adjacent points. The "preset first threshold" is a pre-set threshold used to reflect whether the difference between two connected efficiency points is too large. If it is greater than or equal to the preset first threshold, it means that the difference between the two adjacent efficiency points is too large, and the efficiency point behind is determined as a mutation point. If it is less than the preset first threshold, it means that the difference between the two adjacent efficiency points is within a reasonable range. If the change trend of the three adjacent electric drive efficiency points shows an increase first, then a decrease, and then an increase, and the difference between each two adjacent electric drive efficiency points is less than the preset first threshold, it means that there is a trend error, and the middle efficiency point is an efficiency point with an abnormal trend error. When the change trend of the three adjacent electric drive efficiency points is to increase first and then decrease, or to decrease or increase first, the middle efficiency point is an efficiency point with a normal trend.

[0062] Optionally, after identifying the mutation points and trend error anomaly points, these points, the corresponding matrix, the corresponding rotation speed and their positions can be extracted to facilitate correction in subsequent experiments.

[0063] Optionally, when traversing, it is also necessary to first determine whether there is an adjacent efficiency point to the right or below a certain efficiency point to avoid exceeding the efficiency matrix boundary, and then determine the mutation point and trend error anomaly point, thereby achieving two-level determination. In the first-level determination, the isnan function can be used to check whether the current efficiency point is a valid value to ensure that only mutation and trend detection are performed on valid efficiency points to avoid null value interference with the results.

[0064] The above method is based on a sliding window, which can capture the changes in the electric drive test data in a timely manner and analyze all changes one by one; the use of data tolerance can improve the accuracy of data judgment, thereby effectively screening out stable data points; the electric drive efficiency map drawn based on stable data points can make the data processing results more intuitive, facilitate rapid identification of abnormal situations, and improve data analysis efficiency.

[0065] Example 2 like Figure 2 As shown, this embodiment provides an electric drive efficiency data processing device, including: The data mean value determination module 201 is used to perform sliding scanning on the electric drive test data using a preset sliding window to obtain a plurality of electric drive test data segments; and determine the data mean value of the electric drive test data segment according to the electric drive test data segment; A data tolerance determination module 202, configured to determine a data tolerance according to the data mean and the data trend; A stable data point determination module 203, configured to determine a stable data point in the electric drive test data segment according to the data point in the electric drive test data segment, the data mean and the data tolerance; The electric drive efficiency map drawing module 204 is used to draw an electric drive efficiency map according to the stable data points; the electric drive efficiency map includes the stable data points and electric drive efficiency points filled with colors, and the colors between different electric drive efficiency points show a gradual trend.

[0066] The device is used to execute the above method, and thus has at least functional modules and beneficial effects corresponding to the above method.

[0067] Example 3 like Figure 3 As shown, this embodiment provides an electronic device, including: at least one processor; and a memory communicatively connected to at least one of the processors; wherein, The memory stores instructions executable by at least one of the processors, and the instructions are executed by at least one of the processors to enable at least one of the processors to perform the above method. At least one processor in the electronic device can perform the above method, and thus has at least the same advantages as the above method.

[0068] Optionally, the electronic device also includes interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on a memory to display graphical information of a GUI (Graphical User Interface) on an external input / output device (such as a display device coupled to an interface). In other embodiments, if necessary, multiple processors can be used together with multiple memories, and / or multiple buses can be used together with multiple memories. Similarly, multiple electronic devices can be connected (for example, as a server array, a group of blade servers, or a multi-processor system), and each device provides some necessary operations. Figure 3 A processor 301 is taken as an example.

[0069] The memory 302, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the electric drive efficiency data processing method in the embodiment of the present application (for example, a data mean determination module, a data tolerance determination module, a stable data point determination module, and an electric drive efficiency map drawing module in the electric drive efficiency data processing device). The processor 301 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 302, that is, realizes the above-mentioned electric drive efficiency data processing method.

[0070] The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 302 may further include a memory remotely arranged relative to the processor 301, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0071] The electronic device may further include: an input device 303 and an output device 304. The processor 301, the memory 302, the input device 303 and the output device 304 may be connected via a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0072] The input device 303 can receive input digital or character information, and the output device 304 can include a display device, an auxiliary lighting device (e.g., LED), and a tactile feedback device (e.g., a vibration motor), etc. The display device can include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display, and a plasma display. In some embodiments, the display device can be a touch screen.

[0073] Example 4 This embodiment provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to enable a computer to execute the above method. The computer instructions on the computer-readable storage medium are used to enable a computer to execute the above method, and thus have at least the same advantages as the above method.

[0074] The medium in this application may adopt any combination of one or more computer-readable media. The medium may be a computer-readable signal medium or a computer-readable storage medium. The medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of the medium (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, the medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device, or device.

[0075] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0076] The program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, RF (Radio Frequency), etc., or any suitable combination of the above.

[0077] Computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "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 separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through 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., using an Internet service provider to connect through the Internet).

[0078] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution disclosed in this application can be achieved, and this document is not limited here.

[0079] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for processing electric drive efficiency data, characterized in that: include: A preset sliding window is used to slide scan the electric drive test data to obtain multiple electric drive test data fragments; Determining a data mean of the electric drive test data segment according to the electric drive test data segment; Determine the data tolerance according to the data mean and the data trend; Determining stable data points in the electric drive test data segment according to the data points in the electric drive test data segment, the data mean, and the data tolerance; An electric drive efficiency map is drawn according to the stable data points; the electric drive efficiency map includes the stable data points and electric drive efficiency points filled with colors, and the colors between different electric drive efficiency points show a gradual trend.

2. The electric drive efficiency data processing method according to claim 1, characterized in that: The electric drive test data includes speed data and torque data; Determining the data tolerance according to the data mean and the data trend includes: Determine the speed data tolerance based on the speed data mean and data trend; The torque data tolerance is determined based on the torque data mean.

3. The electric drive efficiency data processing method according to claim 2, characterized in that: When the data mean of the rotation speed data is in the low speed interval and the data trend is increasing, determining the rotation speed data tolerance to be the first tolerance; When the data mean of the rotation speed data is in the low speed interval and the data trend is decreasing, determining the rotation speed data tolerance to be the second tolerance; the absolute value of the first tolerance is greater than the absolute value of the second tolerance; When the data mean of the rotation speed data is in the medium speed range and the data trend is increasing, the rotation speed data tolerance is determined to be the third tolerance; When the data mean of the rotation speed data is in the medium speed interval and the data trend is decreasing, determining the rotation speed data tolerance to be the fourth tolerance; the absolute value of the third tolerance is greater than the absolute value of the fourth tolerance; When the data mean of the rotation speed data is in the high speed range and the data trend is increasing, the rotation speed data tolerance is determined to be the fifth tolerance; When the data mean of the rotation speed data is in the high speed range and the data trend is decreasing, the rotation speed data tolerance is determined to be the sixth tolerance; the absolute value of the fifth tolerance is greater than the absolute value of the sixth tolerance; When the data mean of the torque data is in the low torque interval, determining the torque data tolerance to be the seventh tolerance; When the data mean of the torque data is in the middle torque range, determining the torque data tolerance to be the eighth tolerance; When the data mean of the torque data is in the high torque range, the torque data tolerance is determined to be the ninth tolerance; the absolute value of the seventh tolerance, the absolute value of the eighth tolerance, and the absolute value of the ninth tolerance increase in sequence.

4. The electric drive efficiency data processing method according to claim 1, characterized in that: The step of determining stable data points in the electric drive test data segment according to the data points in the electric drive test data segment, the data mean, and the data tolerance includes: If the difference between the data point in the electric drive test data segment and the data mean is within the data tolerance range, determining the data point as a stable data point in the electric drive test data segment; When the difference between the data point in the electric drive test data segment and the data mean is not within the data tolerance range, the data point is determined to be an unstable data point in the electric drive test data segment.

5. The electric drive efficiency data processing method according to claim 1, characterized in that: Drawing an electric drive efficiency map according to the stable data points includes: Determining a corrected stable data point according to the stable data point and a preset target sequence; sorting the corrected stable data points in chronological order to create an empty efficiency matrix; filling electric drive efficiency points in the empty efficiency matrix according to the corrected stable data points; A filling color of the electric drive efficiency point is generated according to the electric drive efficiency point.

6. The electric drive efficiency data processing method according to claim 5, characterized in that: The step of determining the corrected stable data point according to the stable data point and a preset target sequence includes: The absolute value of the difference between the stable data point and each target value in the preset target sequence is calculated, and the target value corresponding to the minimum value of the absolute value of the difference is used as the corrected stable data point.

7. The electric drive efficiency data processing method according to claim 5, characterized in that: Filling the electric drive efficiency points in the empty efficiency matrix according to the corrected stable data points comprises: Inputting the corrected stable data points into an electric drive efficiency algorithm to fill in the electric drive efficiency points in the empty efficiency matrix; The step of generating a filling color of the electric drive efficiency point according to the electric drive efficiency point includes: The electric drive efficiency point is input into an electric drive efficiency color algorithm to generate a filling color for the electric drive efficiency point.

8. The electric drive efficiency data processing method according to claim 1, characterized in that: After drawing the electric drive efficiency map according to the stable data points, the method further includes: Traverse the electric drive efficiency Map in sequence in a specified direction; When the difference between the current electric drive efficiency point and the previous electric drive efficiency point is greater than or equal to a preset first threshold, determining the current electric drive efficiency point as a mutation point; When the change trend of three adjacent electric drive efficiency points increases first, then decreases, and then increases again, and the difference between every two adjacent electric drive efficiency points is less than a preset first threshold, the middle electric drive efficiency point of the three adjacent electric drive efficiency points is determined as a trend error abnormal point.

9. An electronic device, characterized in that: include: at least one processor, and a memory communicatively coupled to at least one of the processors; The memory stores instructions executable by at least one of the processors, and the instructions are executed by at least one of the processors so that the at least one processor can execute the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 8.

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