Methods, devices, equipment and media for calibrating the energy recovery traction of vehicles

Abstract

This invention relates to the field of vehicle technology and provides a method, apparatus, equipment, and medium for calibrating the energy recovery traction force of a vehicle. The method includes: acquiring the vehicle's latitude and longitude information and operating data within a preset time period, including vehicle speed data, traction force data, energy consumption data, and energy recovery data; determining the vehicle's working path based on the latitude and longitude information and vehicle speed data, the working path being divided into multiple plots according to a preset length value; identifying unloaded uphill plots from the multiple plots based on the traction force data, and determining the slope level of each unloaded uphill plot; and determining the vehicle's energy recovery traction force calibration strategy based on the energy consumption data and energy recovery data of the unloaded uphill plots with different slope levels. This invention can improve the energy recovery capability of electric construction machinery vehicles.

Description

Technical Field

[0001] This invention belongs to the field of vehicle technology, and in particular relates to a method, device, equipment and medium for calibrating the energy recovery traction force of a vehicle. Background Technology

[0002] With increasing environmental awareness, the market demand for green and low-carbon construction machinery is gradually increasing. Traditional fuel vehicles are gradually being replaced by new energy products. However, new energy products have concerns about range compared to traditional fuel vehicles.

[0003] Vehicle energy recovery technology is a technique that converts and stores the kinetic energy generated during vehicle deceleration or braking, thereby improving energy efficiency and extending driving range. The capability of vehicle energy recovery depends on the proper calibration of the energy recovery traction force. For electric construction machinery vehicles, due to complex operating and road conditions, energy recovery is often insufficient. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method, apparatus, equipment and medium for calibrating the energy recovery traction force of a vehicle, so as to improve the energy recovery capability of electric engineering machinery vehicles.

[0005] A first aspect of the present invention provides a method for calibrating the energy recovery traction of a vehicle, comprising:

[0006] The vehicle's latitude and longitude information and operating data are acquired within a preset time period. The operating data includes vehicle speed data, traction force data, energy consumption data, and energy recovery data.

[0007] Based on the latitude and longitude information and the vehicle speed data, the working path of the vehicle is determined, and the working path is divided into multiple plots according to a preset length value;

[0008] Based on the traction data, identify unloaded uphill plots from the plurality of plots, and determine the slope grade of each unloaded uphill plot;

[0009] Based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades, the energy recovery traction calibration strategy of the vehicle is determined.

[0010] In conjunction with the first aspect, in one possible implementation of the first aspect, determining the vehicle's working path based on the latitude and longitude information and the vehicle speed data includes:

[0011] Based on the latitude and longitude information, the entire route of the vehicle is determined, and the entire route is divided into multiple plots according to the length value;

[0012] From all the paths, a first target plot is identified whose average passing speed is greater than a preset speed threshold, and a transportation route is determined based on the first target plot;

[0013] From the transportation route, a second target plot with a total mileage greater than a preset mileage threshold is determined, and the working route of the vehicle is determined based on the second target plot.

[0014] In conjunction with the first aspect, in one possible implementation of the first aspect, determining the unloaded uphill plot from the plurality of plots based on the traction force data includes:

[0015] Based on the sign of the traction data for each plot, plots with slopes are identified from the multiple plots to obtain the third target plot;

[0016] For each third target plot, it is determined whether it is an unloaded uphill plot based on the magnitude of its positive and negative traction force data.

[0017] In conjunction with the first aspect, in one possible implementation of the first aspect, determining the plots with slopes from the plurality of plots based on the sign of the traction data for each plot, to obtain the third target plot, includes:

[0018] If the traction force data of the plot is positive in the first direction and negative in the second direction, then the plot is determined to be a plot with a slope.

[0019] The first direction and the second direction are opposite.

[0020] In conjunction with the first aspect, in one possible implementation of the first aspect, determining whether each third target plot is an unloaded uphill plot based on the magnitude of its positive and negative traction force data includes:

[0021] The average value of the traction force data with positive values ​​is determined to obtain the first average value;

[0022] The average value of the negative traction force data is determined to obtain the second average value;

[0023] Determine the ratio of the first average value to the second average value;

[0024] If the absolute value of the ratio is less than 1, then it is determined to be an unloaded uphill plot.

[0025] In conjunction with the first aspect, in one possible implementation of the first aspect, determining the slope grade of each vacant uphill plot includes:

[0026] Based on the distribution of traction force data for all unloaded uphill plots, multiple slope grades and the corresponding traction force range for each slope grade are determined.

[0027] The slope grade of each unloaded uphill plot is determined based on the first average value of each unloaded uphill plot and the traction range corresponding to each slope grade.

[0028] In conjunction with the first aspect, in one possible implementation of the first aspect, determining the energy recovery traction calibration strategy for the vehicle based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades includes:

[0029] Based on the energy consumption data of the unloaded uphill plots at each slope level, the unit mileage consumption of the unloaded uphill plots at each slope level is determined.

[0030] Based on the energy recovery data of the unloaded uphill plots for each slope grade, the unit mileage recovery of the unloaded uphill plots for each slope grade is determined.

[0031] The energy recovery traction calibration strategy for the vehicle is determined based on the unit mileage consumption and unit mileage recovery for each gradient level.

[0032] A second aspect of the present invention provides a vehicle energy recovery traction calibration device, comprising:

[0033] The acquisition module is used to acquire the vehicle's latitude and longitude information and operating data within a preset time period. The operating data includes vehicle speed data, traction force data, energy consumption data, and energy recovery data.

[0034] The first processing module is used to determine the working path of the vehicle based on the latitude and longitude information and the vehicle speed data, wherein the working path is divided into multiple plots according to a preset length value;

[0035] The second processing module is used to determine the unloaded uphill plots from the plurality of plots based on the traction force data, and to determine the slope grade of each unloaded uphill plot.

[0036] The third processing module is used to determine the energy recovery traction calibration strategy of the vehicle based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades.

[0037] In conjunction with the second aspect, in one possible implementation of the second aspect, the first processing module is used to:

[0038] Based on the latitude and longitude information, the entire route of the vehicle is determined, and the entire route is divided into multiple plots according to the length value;

[0039] From all the paths, a first target plot is identified whose average passing speed is greater than a preset speed threshold, and a transportation route is determined based on the first target plot;

[0040] From the transportation route, a second target plot with a total mileage greater than a preset mileage threshold is determined, and the working route of the vehicle is determined based on the second target plot.

[0041] In conjunction with the second aspect, in one possible implementation of the second aspect, the second processing module is used to:

[0042] Based on the sign of the traction data for each plot, plots with slopes are identified from the multiple plots to obtain the third target plot;

[0043] For each third target plot, it is determined whether it is an unloaded uphill plot based on the magnitude of its positive and negative traction force data.

[0044] In conjunction with the second aspect, in one possible implementation of the second aspect, the second processing module is used to:

[0045] If the traction force data of the plot is positive in the first direction and negative in the second direction, then the plot is determined to be a plot with a slope.

[0046] The first direction and the second direction are opposite.

[0047] In conjunction with the second aspect, in one possible implementation of the second aspect, the second processing module is used to:

[0048] The average value of the traction force data with positive values ​​is determined to obtain the first average value;

[0049] The average value of the negative traction force data is determined to obtain the second average value;

[0050] Determine the ratio of the first average value to the second average value;

[0051] If the absolute value of the ratio is less than 1, then it is determined to be an unloaded uphill plot.

[0052] In conjunction with the second aspect, in one possible implementation of the second aspect, the second processing module is used to:

[0053] Based on the distribution of traction force data for all unloaded uphill plots, multiple slope grades and the corresponding traction force range for each slope grade are determined.

[0054] The slope grade of each unloaded uphill plot is determined based on the first average value of each unloaded uphill plot and the traction range corresponding to each slope grade.

[0055] In conjunction with the second aspect, in one possible implementation of the second aspect, the third processing module is used for:

[0056] Based on the energy consumption data of the unloaded uphill plots at each slope level, the unit mileage consumption of the unloaded uphill plots at each slope level is determined.

[0057] Based on the energy recovery data of the unloaded uphill plots for each slope grade, the unit mileage recovery of the unloaded uphill plots for each slope grade is determined.

[0058] The energy recovery traction calibration strategy for the vehicle is determined based on the unit mileage consumption and unit mileage recovery for each gradient level.

[0059] A third aspect of the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect or any implementation thereof.

[0060] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any implementation thereof.

[0061] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows:

[0062] This invention first acquires the vehicle's latitude and longitude information and operational data within a preset time period. The operational data includes vehicle speed data, traction force data, energy consumption data, and energy recovery data. Then, based on the latitude and longitude information and vehicle speed data, the vehicle's working path during this time period can be determined. By focusing on analyzing the working path, subsequent optimization calibration can be better supported. Furthermore, using the traction force data, empty uphill sections are identified from multiple sections along the working path. These empty uphill sections are also heavy downhill sections, where energy recovery is significant. Therefore, the data from these empty uphill sections is used as a reference for optimization calibration. Finally, by determining the slope level of each empty uphill section, and using the energy consumption and energy recovery data from empty uphill sections with different slope levels, the rationality of the vehicle's energy recovery under different slopes can be analyzed, thereby guiding the energy recovery traction calibration and improving the vehicle's energy recovery capability. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is a schematic diagram illustrating an application scenario of the vehicle energy recovery traction calibration method provided in this embodiment of the invention;

[0065] Figure 2 This is a schematic diagram of the implementation process of the vehicle energy recovery traction calibration method provided in this embodiment of the invention. Figure 1 ;

[0066] Figure 3 This is a schematic diagram of land parcel distribution provided in an embodiment of the present invention. Figure 1 ;

[0067] Figure 4 This is a schematic diagram of the implementation process of the vehicle energy recovery traction calibration method provided in this embodiment of the invention. Figure 2 ;

[0068] Figure 5 This is a schematic diagram of land parcel distribution provided in an embodiment of the present invention. Figure 2 ;

[0069] Figure 6 This is a schematic diagram of traction force data distribution provided in an embodiment of the present invention;

[0070] Figure 7 This is a schematic diagram of land parcel distribution provided in an embodiment of the present invention. Figure 3 ;

[0071] Figure 8 This is a schematic diagram illustrating the energy consumption and energy recovery per unit mileage for five types of slope plots provided in this embodiment of the invention. Figure 1 ;

[0072] Figure 9 This is a schematic diagram of energy recovery traction calibration provided in an embodiment of the present invention. Figure 1 ;

[0073] Figure 10 This is a schematic diagram of energy recovery traction calibration provided in an embodiment of the present invention. Figure 2 ;

[0074] Figure 11 This is a schematic diagram illustrating the energy consumption and energy recovery per unit mileage for five types of slope plots provided in this embodiment of the invention. Figure 2 ;

[0075] Figure 12This is a schematic diagram of the structure of the vehicle energy recovery traction calibration device provided in an embodiment of the present invention;

[0076] Figure 13 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0077] The present application will be described more clearly below with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the function of the present application, but do not limit the present application in any way. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application. These all fall within the protection scope of the present application.

[0078] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0079] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0080] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0081] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0082] Furthermore, the term "multiple" mentioned in the embodiments of this application should be interpreted as two or more.

[0083] This invention is primarily applied to electric wide-body vehicles. Wide-body vehicles are a type of engineering machinery vehicle that combines highway heavy truck and engineering machinery technologies, offering high cargo capacity and economy. They are typically used in open-pit coal mines, metal mines, building material mines, and large-scale hydropower projects.

[0084] Regenerative braking systems are widely used in electric wide-body vehicles. When the vehicle decelerates or brakes, the electric motor converts into a generator, converting the vehicle's kinetic energy into electrical energy and storing it in the battery. This process not only reduces energy waste but also extends battery life, while reducing wear and heat generation in the braking system. However, existing energy recovery technologies have insufficient energy recovery capabilities. For electric wide-body vehicles operating under complex conditions and road conditions, a more reasonable multi-stage energy recovery traction calibration should be adopted to maximize energy recovery capabilities while ensuring operational safety, thereby maximizing both economy and applicability.

[0085] To this end, this invention develops a road condition recognition and classification algorithm for wide-body vehicles based on big data of electric construction machinery vehicles. The algorithm identifies and classifies the working road conditions of wide-body vehicles, and then optimizes the energy recovery traction calibration to maximize energy recovery.

[0086] Figure 1 This is a schematic diagram of an application scenario for the vehicle energy recovery traction calibration method provided in this embodiment of the invention. In this embodiment, for any vehicle, various operating data (such as motor speed, torque, reduction ratio, tire radius, etc.) can be obtained based on the vehicle's CAN bus. High-frequency location information such as latitude, longitude, azimuth, and altitude can be obtained through GPS or other positioning systems to ensure the accuracy of road condition identification and classification.

[0087] Here, the electronic device can be the vehicle's main controller, which analyzes operational data and location information to optimize and set the energy recovery traction calibration. Alternatively, the electronic device can be a server, in which case the operational data and location information are first transmitted to the server via a network, the server performs the optimization calculation for the energy recovery traction calibration, and sends the result to the vehicle's main controller for setting. This embodiment does not limit the type of electronic device.

[0088] The following is combined Figure 1 Application scenarios, refer to Figure 2 This application describes a method for calibrating the energy recovery traction of a vehicle according to exemplary embodiments thereof. It should be noted that the above application scenarios are shown only to facilitate understanding of the spirit and principles of this application, and the embodiments of this application are not limited in any way. Rather, the embodiments of this application can be applied to any applicable scenario.

[0089] The following is combined Figure 2 The method of this embodiment will be described in detail below:

[0090] Step S201: Obtain the vehicle's latitude and longitude information and operating data within a preset time period. The operating data includes vehicle speed data, traction data, energy consumption data, and energy recovery data.

[0091] Typically, wide-body trucks operate in a fixed area for a period of time, such as carrying out transportation operations in the same mine for several consecutive months. The preset time can be a period of time during which the wide-body truck will operate in that area, and the specific length of time is not limited, ranging from a few days to several tens of days.

[0092] Here, vehicle latitude and longitude information, vehicle speed data, traction force data, energy consumption data, and energy recovery data can be collected to achieve optimized calibration of energy recovery traction force.

[0093] Step S202: Determine the vehicle's working path based on latitude and longitude information and vehicle speed data. The working path is divided into multiple plots according to a preset length value.

[0094] In this embodiment, the working path refers to the path that the vehicle takes when transporting minerals.

[0095] First, based on latitude and longitude information, a user-end operation road condition map can be drawn for the vehicle during this period, for example... Figure 3 As shown.

[0096] The user-side operational road condition map contains the entire path of the vehicle within the work area. This path can be divided into plots of a certain size, based on... Figure 3 The color distribution shows that some greenish plots have average vehicle speeds close to 0. These are likely charging points, loading points, and unloading points. Vehicles are typically charging or waiting to load / unload at these plots. Because the vehicles are not moving, there is very little energy recovery data, which is not very helpful for optimizing the calibration of energy recovery traction. These plots can be removed. In addition, charging points can be determined by charging status (vehicles have different charging statuses during operation and charging), and loading / unloading points can be determined by altitude and user surveys.

[0097] Additionally, it's necessary to filter work sites, meaning only analyzing and identifying sites along the vehicle's work path. For example, if a user completes their work in a day and makes one round trip to the charging point, this route is a non-work path, corresponding to a non-work site. However, a user's work path typically involves more than 30 round trips per day per vehicle. Therefore, the total mileage of the sites (e.g., ...) can be used to identify work sites. Figure 3 The data column height (representing the cumulative mileage of a plot) or the number of times a plot has been traversed helps identify plots along the work path. By focusing on analyzing road conditions and energy recovery along the work path, better support can be provided for optimization and calibration.

[0098] The plots of land selected above form the working routes for vehicles.

[0099] Step S203: Based on the traction data, identify the unloaded uphill plots from multiple plots and determine the slope grade of each unloaded uphill plot.

[0100] An unloaded uphill plot is the same as a heavily loaded downhill plot. When a vehicle is heavily loaded and going downhill, the energy recovery effect is obvious. Therefore, the data from the unloaded uphill plot is used as a reference to optimize the calibration.

[0101] Generally, a vehicle's traction force is positive when going uphill and negative when going downhill. The traction force under heavy load is much greater than that under no-load conditions, and the greater the slope, the greater the traction force. Therefore, for each plot of land, whether it is uphill or downhill, whether the vehicle is heavily loaded or empty, and the magnitude of the slope can all be determined through analysis of the motor's traction force data. Furthermore, this embodiment classifies slopes of different magnitudes, such as small slopes, medium-small slopes, medium slopes, medium-large slopes, and large slopes. The specific classification criteria can be preset or calculated based on actual road conditions; this embodiment does not impose any limitations.

[0102] Step S204: Based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades, determine the energy recovery traction calibration strategy for vehicles.

[0103] The principle of energy recovery is as follows: when the required braking torque of the vehicle is less than the rated torque for energy recovery, the mechanical braking system is relied upon entirely to meet the vehicle's deceleration requirements, and no energy recovery occurs. When the required braking torque of the vehicle is greater than the rated torque for energy recovery, energy recovery is activated first to provide counter-traction force, with the excess force provided by the mechanical braking system. Therefore, setting a reasonable threshold for the energy recovery traction force is crucial for ensuring sufficient energy recovery.

[0104] Here, by analyzing the energy consumption and energy recovery data of unloaded uphill plots with different slope grades, it is possible to determine whether vehicles can fully recover energy on different slopes, thereby allowing for appropriate adjustment of the calibration threshold of energy recovery traction or setting of multi-stage calibration, etc.

[0105] This invention first acquires the vehicle's latitude and longitude information and operational data within a preset time period. The operational data includes vehicle speed data, traction force data, energy consumption data, and energy recovery data. Then, based on the latitude and longitude information and vehicle speed data, the vehicle's working path during this time period can be determined. By focusing on analyzing the working path, subsequent optimization calibration can be better supported. Furthermore, using the traction force data, empty uphill sections are identified from multiple sections along the working path. These empty uphill sections are also heavy downhill sections, where energy recovery is significant. Therefore, the data from these empty uphill sections is used as a reference for optimization calibration. Finally, by determining the slope level of each empty uphill section, and using the energy consumption and energy recovery data from empty uphill sections with different slope levels, the rationality of the vehicle's energy recovery under different slopes can be analyzed, thereby guiding the energy recovery traction calibration and improving the vehicle's energy recovery capability.

[0106] For ease of understanding this solution, please refer to the following: Figure 4 As shown, the process of this solution is described in detail through a more specific embodiment.

[0107] Step S401: Obtain the vehicle's latitude and longitude information and operating data within a preset time period. The operating data includes vehicle speed data, traction data, energy consumption data, and energy recovery data.

[0108] For details on how to implement this step, please refer to [link / reference]. Figure 2 The descriptions in the embodiments will not be repeated in this embodiment.

[0109] Step S402: Determine the working path of the vehicle based on latitude and longitude information and vehicle speed data. The working path is divided into multiple plots according to a preset length value.

[0110] This step includes:

[0111] Based on latitude and longitude information, the entire vehicle route is determined, and the entire route is divided into multiple plots based on its length, such as... Figure 3 As shown.

[0112] From all paths, identify the first target plot whose average passing speed is greater than a preset speed threshold (i.e., Figure 3 (The data bars in the middle are red plots), and the transportation route is determined based on the first target plot.

[0113] From the transportation route, identify the second target plot (i.e., plot whose total mileage exceeds a preset mileage threshold) Figure 3 For plots where the height of the data column is greater than a certain value, the working path of the vehicle is determined based on the second target plot, and the final working path of the vehicle is as follows: Figure 5 The blue plot in the middle.

[0114] The speed and mileage thresholds here can be set according to actual needs.

[0115] Step S403: Based on the positive or negative value of the traction data for each plot, determine the plot with a slope from multiple plots to obtain the third target plot.

[0116] This step includes: if the traction force data of the plot in the first direction is positive and the traction force data in the second direction is negative, then the plot is determined to be a plot with a slope; wherein the first direction and the second direction are opposite.

[0117] It is understandable that for a plot of land with a slope, in the two directions of the round trip, one is uphill and the other is downhill, and the traction force is positive and negative respectively. Therefore, when the traction force data of the plot in one direction is all positive and the traction force data in the opposite direction is all negative, the plot can be determined to be a plot of land with a slope.

[0118] Step S404: For each third target plot, determine whether it is an unloaded uphill plot based on the magnitude of its positive traction force data and the magnitude of its negative traction force data.

[0119] This step includes:

[0120] The average value of the traction force data with positive values ​​is determined to obtain the first average value;

[0121] The average value of the negative traction force data is determined to obtain the second average value;

[0122] Determine the ratio of the first average to the second average;

[0123] If the absolute value of the ratio is less than 1, then it is determined to be an unloaded uphill plot.

[0124] In this embodiment, when the vehicle is working, it travels back and forth on the path. When it passes a plot of land with a slope, if it is an uphill slope with no load and a downhill slope with a load, the traction force is positive and negative respectively. The traction force of the uphill slope with no load is less than the traction force of the downhill slope with a load. Therefore, if the ratio of the first average value and the second average value is less than 1, it can be determined that it is an uphill plot with no load.

[0125] Similarly, when a vehicle passes through a sloping plot of land, if it is going uphill with a load and going downhill without a load, the traction force will be positive and negative respectively, and the traction force of going uphill with a load is greater than the traction force of going downhill without a load. Therefore, if the ratio of the first average value and the second average value is greater than 1, it can be determined that it is a plot of land going uphill with a load.

[0126] Since unloaded uphill plots correspond to loaded downhill plots, they typically have higher energy recovery efficiency, making them more suitable for studying the performance of energy recovery systems.

[0127] Step S405: Determine the slope grade of each unloaded uphill plot.

[0128] In one implementation, the traction force range corresponding to different slope grades can be determined in advance through vehicle testing. Then, the slope grade of each unloaded uphill plot can be determined directly according to the pre-defined traction force range corresponding to different slope grades.

[0129] In another implementation, multiple slope grades and the corresponding traction force ranges for each slope grade can be determined based on the magnitude distribution of traction force data for all unloaded uphill plots; and the slope grade of each unloaded uphill plot can be determined based on the first average value of each unloaded uphill plot and the corresponding traction force ranges for each slope grade.

[0130] See Figure 6 As shown in the traction force data distribution map, the traction force data of unloaded uphill plots exhibits a multi-peak normal distribution. Based on the peak values, the slope can be divided into 5 categories: ① Xiaopo ② Small and medium slopes ③ Middle slope ④ Zhongdapo ⑤ Slope. It should be noted that the slope division is only illustrative and can be divided into more or fewer classes, and the traction range of each class can also be adjusted.

[0131] Finally, a 5-level color visualization map of the plot's slope was obtained, as shown below. Figure 7 As shown.

[0132] Step S406: Based on the energy consumption data of the unloaded uphill plots at each slope level, determine the unit mileage consumption of the unloaded uphill plots at each slope level; based on the energy recovery data of the unloaded uphill plots at each slope level, determine the unit mileage recovery of the unloaded uphill plots at each slope level; based on the unit mileage consumption and unit mileage recovery of each slope level, determine the vehicle's energy recovery traction calibration strategy.

[0133] For example, the energy consumption per unit mile and the energy recovery per unit mile for the above five types of slope plots (e.g., how much electricity is consumed to climb one kilometer of a small slope unloaded, and how much electricity is recovered to climb one kilometer of a small slope under heavy load) are as follows: Figure 8 As shown, the energy recovery capacity of medium slopes, medium-large slopes, and large slopes is sufficient, but the energy recovery capacity of small slopes and medium-small slopes is insufficient, requiring optimization of energy recovery traction force calibration.

[0134] The reason is: before optimization, this model used a two-stage calibration for energy recovery traction, such as... Figure 9As shown, however, the user's road conditions are relatively complex. Therefore, the total braking traction required for small and medium-sized slopes is rarely greater than a and b, resulting in relatively weak energy recovery capabilities.

[0135] The optimized system adopts a third-order calibration of energy recovery traction force, such as... Figure 10 As shown, with the addition of a threshold c, the energy consumption per unit mile and the energy recovery per unit mile are as follows: Figure 11 As shown, the optimized third-order energy recovery traction calibration significantly improves the energy recovery capacity of small and medium-sized slopes.

[0136] Increased energy recovery capability improves the vehicle's operating range and is more cost-effective compared to vehicles with weaker energy recovery capabilities, thus significantly enhancing the vehicle's applicability and economy. It's important to note that while increasing the energy recovery traction calibration level can improve energy recovery capability, more levels are not always better. Too many levels or too low a threshold calibration can increase vehicle vibration due to frequent switching of energy recovery traction levels. Since wide-body vehicles are heavy, continuous vibration during heavy-load downhill driving can be extremely dangerous and may lead to loss of vehicle control. Therefore, when optimizing energy recovery traction calibration, it's essential to consider the user's actual road conditions for appropriate calibration.

[0137] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0138] Figure 12 This is a schematic diagram of the structure of the vehicle energy recovery traction calibration device 120 provided in an embodiment of the present invention, including:

[0139] The acquisition module 121 is used to acquire the vehicle's latitude and longitude information and operating data within a preset time period. The operating data includes vehicle speed data, traction data, energy consumption data, and energy recovery data.

[0140] The first processing module 122 is used to determine the working path of the vehicle based on latitude and longitude information and vehicle speed data. The working path is divided into multiple plots according to a preset length value.

[0141] The second processing module 123 is used to determine the unloaded uphill plots from multiple plots based on traction data, and to determine the slope grade of each unloaded uphill plot.

[0142] The third processing module 124 is used to determine the energy recovery traction calibration strategy of the vehicle based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades.

[0143] As one possible implementation, the first processing module 122 is used for:

[0144] Based on latitude and longitude information, the entire route of the vehicle is determined, and the entire route is divided into multiple plots according to its length.

[0145] From all the routes, identify the first target plot whose average passing speed is greater than a preset speed threshold, and determine the transportation route based on the first target plot;

[0146] From the transportation route, identify a second target plot whose total mileage exceeds a preset mileage threshold, and determine the vehicle's working route based on the second target plot.

[0147] As one possible implementation, the second processing module 123 is used for:

[0148] Based on the positive or negative value of the traction data for each plot, the plot with a slope is identified from multiple plots to obtain the third target plot;

[0149] For each third target plot, it is determined whether it is an unloaded uphill plot based on the magnitude of its positive and negative traction force data.

[0150] As one possible implementation, the second processing module 123 is used for:

[0151] If the traction force data of the plot is positive in the first direction and negative in the second direction, then the plot is determined to be a plot with a slope.

[0152] The first direction and the second direction are opposite.

[0153] In conjunction with the second aspect, in one possible implementation of the second aspect, the second processing module is used for:

[0154] The average value of the traction force data with positive values ​​is determined to obtain the first average value;

[0155] The average value of the negative traction force data is determined to obtain the second average value;

[0156] Determine the ratio of the first average to the second average;

[0157] If the absolute value of the ratio is less than 1, then it is determined to be an unloaded uphill plot.

[0158] As one possible implementation, the second processing module 123 is used for:

[0159] Based on the distribution of traction force data for all unloaded uphill plots, multiple slope grades and the corresponding traction force range for each slope grade are determined.

[0160] The slope grade of each unloaded uphill plot is determined based on the first average value of each unloaded uphill plot and the traction range corresponding to each slope grade.

[0161] As one possible implementation, the third processing module 124 is used for:

[0162] Based on the energy consumption data of empty uphill plots at each slope level, the unit mileage consumption of empty uphill plots at each slope level is determined.

[0163] Based on the energy recovery data of unloaded uphill plots at each slope level, the unit mileage recovery of unloaded uphill plots at each slope level is determined.

[0164] The energy recovery traction calibration strategy for the vehicle is determined based on the unit mileage consumption and unit mileage recovery for each gradient level.

[0165] This invention first acquires the vehicle's latitude and longitude information and operational data within a preset time period. The operational data includes vehicle speed data, traction force data, energy consumption data, and energy recovery data. Then, based on the latitude and longitude information and vehicle speed data, the vehicle's working path during this time period can be determined. By focusing on analyzing the working path, subsequent optimization calibration can be better supported. Furthermore, using the traction force data, empty uphill sections are identified from multiple sections along the working path. These empty uphill sections are also heavy downhill sections, where energy recovery is significant. Therefore, the data from these empty uphill sections is used as a reference for optimization calibration. Finally, by determining the slope level of each empty uphill section, and using the energy consumption and energy recovery data from empty uphill sections with different slope levels, the rationality of the vehicle's energy recovery under different slopes can be analyzed, thereby guiding the energy recovery traction calibration and improving the vehicle's energy recovery capability.

[0166] Figure 13 This is a schematic diagram of an electronic device 130 provided according to an embodiment of the present invention. Figure 13 As shown, the electronic device 130 of this embodiment includes: a processor 131, a memory 132, and a computer program 133 stored in the memory 132 and executable on the processor 131, such as a vehicle energy recovery traction calibration program. When the processor 131 executes the computer program 133, it implements the steps in the above-described embodiments of the vehicle energy recovery traction calibration methods, for example... Figure 2 The steps S201 to S204 are shown. Alternatively, when the processor 131 executes the computer program 133, it implements the functions of each module in the above-described device embodiments, for example... Figure 12 The functions of modules 121 to 124 are shown.

[0167] For example, the computer program 133 can be divided into one or more modules / units, which are stored in the memory 132 and executed by the processor 131 to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 133 in the electronic device 130. For example, the computer program 133 can be divided into an acquisition module 121, a first processing module 122, a second processing module 123, and a third processing module 124 (a module in a virtual device), with the specific functions of each module as follows:

[0168] The acquisition module 121 is used to acquire the vehicle's latitude and longitude information and operating data within a preset time period. The operating data includes vehicle speed data, traction data, energy consumption data, and energy recovery data.

[0169] The first processing module 122 is used to determine the working path of the vehicle based on latitude and longitude information and vehicle speed data. The working path is divided into multiple plots according to a preset length value.

[0170] The second processing module 123 is used to determine the unloaded uphill plots from multiple plots based on traction data, and to determine the slope grade of each unloaded uphill plot.

[0171] The third processing module 124 is used to determine the energy recovery traction calibration strategy of the vehicle based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades.

[0172] The electronic device 130 may be a desktop computer, laptop, handheld computer, or cloud server, etc. The electronic device 130 may include, but is not limited to, a processor 131 and a memory 132. Those skilled in the art will understand that... Figure 13 This is merely an example of electronic device 130 and does not constitute a limitation on electronic device 130. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 130 may also include input / output devices, network access devices, buses, etc.

[0173] The processor 131 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0174] The memory 132 can be an internal storage unit of the electronic device 130, such as a hard disk or memory of the electronic device 130. The memory 132 can also be an external storage device of the electronic device 130, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the electronic device 130. Furthermore, the memory 132 can include both internal and external storage units of the electronic device 130. The memory 132 is used to store the computer program and other programs and data required by the electronic device 130. The memory 132 can also be used to temporarily store data that has been output or will be output.

[0175] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0176] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0177] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0178] In the embodiments provided by this invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0179] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0180] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0181] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0182] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for calibrating the energy recovery traction force of a vehicle, characterized in that, include: The vehicle's latitude and longitude information and operating data are acquired within a preset time period. The operating data includes vehicle speed data, traction force data, energy consumption data, and energy recovery data. Based on the latitude and longitude information and the vehicle speed data, the working path of the vehicle is determined, and the working path is divided into multiple plots according to a preset length value; Based on the traction data, identify unloaded uphill plots from the plurality of plots, and determine the slope grade of each unloaded uphill plot; Based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades, the energy recovery traction calibration strategy of the vehicle is determined.

2. The method for calibrating the energy recovery traction force of a vehicle as described in claim 1, characterized in that, Determining the vehicle's working path based on the latitude and longitude information and the vehicle speed data includes: Based on the latitude and longitude information, the entire route of the vehicle is determined, and the entire route is divided into multiple plots according to the length value; From all the paths, a first target plot is identified whose average passing speed is greater than a preset speed threshold, and a transportation route is determined based on the first target plot; From the transportation route, a second target plot with a total mileage greater than a preset mileage threshold is determined, and the working route of the vehicle is determined based on the second target plot.

3. The method for calibrating the energy recovery traction force of a vehicle as described in claim 1, characterized in that, The step of determining the unloaded uphill plot from the plurality of plots based on the traction force data includes: Based on the sign of the traction data for each plot, plots with slopes are identified from the multiple plots to obtain the third target plot; For each third target plot, it is determined whether it is an unloaded uphill plot based on the magnitude of its positive and negative traction force data.

4. The method for calibrating the energy recovery traction force of a vehicle as described in claim 3, characterized in that, The process of determining the plots with slopes from the plurality of plots based on the positive or negative sign of the traction data for each plot, to obtain the third target plot, includes: If the traction force data of the plot is positive in the first direction and negative in the second direction, then the plot is determined to be a plot with a slope. The first direction and the second direction are opposite.

5. The method for calibrating the energy recovery traction force of a vehicle as described in claim 3, characterized in that, For each third target plot, determining whether it is an unloaded uphill plot based on the magnitude of its positive and negative traction force data includes: The average value of the traction force data with positive values ​​is determined to obtain the first average value; The average value of the negative traction force data is determined to obtain the second average value; Determine the ratio of the first average value to the second average value; If the absolute value of the ratio is less than 1, then it is determined to be an unloaded uphill plot.

6. The method for calibrating the energy recovery traction force of a vehicle as described in claim 5, characterized in that, The determination of the slope grade of each vacant uphill plot includes: Based on the distribution of traction force data for all unloaded uphill plots, multiple slope grades and the corresponding traction force range for each slope grade are determined. The slope grade of each unloaded uphill plot is determined based on the first average value of each unloaded uphill plot and the traction range corresponding to each slope grade.

7. The method for calibrating the energy recovery traction force of a vehicle as described in claim 1, characterized in that, The process of determining the energy recovery traction calibration strategy for the vehicle based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades includes: Based on the energy consumption data of the unloaded uphill plots at each slope level, the unit mileage consumption of the unloaded uphill plots at each slope level is determined. Based on the energy recovery data of the unloaded uphill plots for each slope grade, the unit mileage recovery of the unloaded uphill plots for each slope grade is determined. The energy recovery traction calibration strategy for the vehicle is determined based on the unit mileage consumption and unit mileage recovery for each gradient level.

8. A vehicle energy recovery traction calibration device, characterized in that, include: The acquisition module is used to acquire the vehicle's latitude and longitude information and operating data within a preset time period. The operating data includes vehicle speed data, traction force data, energy consumption data, and energy recovery data. The first processing module is used to determine the working path of the vehicle based on the latitude and longitude information and the vehicle speed data, wherein the working path is divided into multiple plots according to a preset length value; The second processing module is used to determine the unloaded uphill plots from the plurality of plots based on the traction force data, and to determine the slope grade of each unloaded uphill plot. The third processing module is used to determine the energy recovery traction calibration strategy of the vehicle based on the energy consumption data and energy recovery data of unloaded uphill plots with different slope grades.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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