A method and device for monitoring wheel yaw resistance energy consumption based on new energy vehicles

Abstract

The present invention discloses a method and device for monitoring wheel deviation resistance energy consumption based on new energy vehicles, belonging to the technical field of new energy vehicle tires. The method is used to solve the technical problems of existing wheel deviation resistance monitoring of new energy vehicles, such as the difficulty in achieving online monitoring while the vehicle is driving, and the additional energy consumption caused by wheel deviation resistance also easily affects the prediction of remaining mileage. The method includes: performing three-dimensional tire modeling perception of the wheel running state of the new energy vehicle under straight-line driving to determine the abnormal wheel deviation tire of the new energy vehicle; calculating and processing the characteristic parameters of the tread contact plane diagram under the squeeze area based on the geometric characteristics and mechanical characteristics between the tread and the ground to obtain the abnormal wheel deviation parameters of the abnormal wheel deviation tire; performing global contact coupling stiffness calculation on the abnormal wheel deviation parameters to determine the tire stress of the abnormal wheel deviation tire; inputting the tire stress into the tire rolling resistance model to obtain the tire rolling resistance of the abnormal wheel deviation tire.

Description

Technical Field

[0001] The present application relates to the field of new energy vehicle tires, and in particular to a method and device for monitoring wheel slip resistance and energy consumption based on new energy vehicles. Background Art

[0002] As new energy vehicles become more and more popular, their configuration, safety, and intelligence are also gradually improving. However, during long-term use, wheels are prone to deviation. The main reasons for this are:

[0003] 1) Four-wheel alignment misalignment: After a vehicle has been driven for a period of time, the four-wheel alignment values ​​will change, especially in bad road conditions or when the vehicle frequently goes up and down curbs. This will cause the vehicle to deviate.

[0004] 2) Tire Issues: Inconsistent Tire Pressure: If the tire pressure on each side of the vehicle is different, for example, the left tire has less pressure than the right, the vehicle may veer off the road. Inconsistent Tire Tread Wear: Uneven tread wear can also cause the vehicle to veer off the road. Replace or adjust the tires. Inconsistent Tire Model: Use the same model for all four tires, at least on the front and rear axles, with consistent tread depth.

[0005] 3) Suspension System Issues: Front shock absorber failure: A failed front shock absorber can cause the two suspensions to have different heights while driving, resulting in uneven force distribution and causing the vehicle to veer off course. Suspension System Damage: Loose or damaged suspension system components, such as the shock absorber, ball joint, or suspension arm, can cause the vehicle to veer off course. Front shock absorber spring deformation: Inconsistent deformation of the front shock absorber spring on both sides results in inconsistent cushioning, causing the vehicle to veer off course.

[0006] In existing technologies, wheel deviation is generally detected based on the driver's own driving experience or can only be used for online warnings for a single fixed situation. Real-time online monitoring is not possible, that is, it is difficult to achieve online monitoring of wheel deviation during vehicle operation, which increases tire resistance and battery energy consumption of new energy vehicles. It is impossible to accurately predict the remaining mileage and provide effective wheel deviation warning information to the driver, which easily reduces the driver's driving experience of the intelligent new energy vehicle. In addition, the wheel deviation problem cannot be corrected in time and is likely to cause safety hazards. Summary of the Invention

[0007] The embodiments of the present application provide a method and device for monitoring wheel pulley resistance energy consumption based on new energy vehicles, which are used to solve the following technical problems: the existing wheel pulley resistance monitoring of new energy vehicles is difficult to achieve online monitoring while the vehicle is driving, and the additional energy consumption caused by wheel pulley resistance is also likely to affect the prediction of the remaining mileage, which is not conducive to improving the driving experience and vehicle safety performance.

[0008] The embodiments of this application adopt the following technical solutions:

[0009] On the one hand, the embodiment of the present application provides a method for monitoring wheel deviation resistance and energy consumption based on new energy vehicles, comprising: based on the magnetic encoder in the suspension system of the new energy vehicle, the wheel running state of the new energy vehicle is perceived based on the tire three-dimensional modeling under straight-line driving, and the abnormal wheel deviation tire of the new energy vehicle is determined; through a preset visual model, the tire with abnormal wheel deviation is identified and segmented in the relevant tire body deformation area to obtain a tread contact plane diagram; and based on the geometric characteristics and mechanical characteristics between the tread and the ground, the characteristic parameters of the tread contact plane diagram under the extrusion area are calculated and processed to obtain the abnormal wheel deviation parameters of the abnormal wheel deviation tire; based on the tire characterization parameters of the new energy vehicle, the abnormal wheel deviation is detected. The parameters are used to calculate the global contact coupling stiffness between the tire's own contact parameters and the degree of discreteness of ground particles to determine the tire stress of the abnormal wheel deviation tire; the tire stress is input into a pre-trained tire rolling resistance model, and based on the weighted connection space mapping from the input layer to the hidden layer in the tire rolling resistance model, the tire rolling resistance of the abnormal wheel deviation tire is calculated and obtained; according to the tire rolling resistance and the corresponding tire amplitude, the energy consumption loss of a single tire of the abnormal wheel deviation tire is compared to determine the additional wheel deviation energy consumption; the additional wheel deviation energy consumption is integrated with the remaining mileage management system of the new energy vehicle to obtain the remaining mileage prediction data of the new energy vehicle under abnormal wheel deviation.

[0010] The embodiments of the present application use magnetic encoders to sense the wheel's operating status, enabling real-time monitoring of the tire's operating status and helping to promptly detect tire anomalies. Visual models can also be used to identify and segment the carcass deformation area of ​​tires with abnormal wheel deviation, accurately locating the location and extent of the abnormal tire. By calculating characteristic parameters based on the tread contact plane, the mechanical properties of the tire in the squeeze zone can be analyzed, providing a basis for subsequent energy consumption calculations. Calculating tire stress based on tire characterization parameters and contact parameters allows for a more comprehensive assessment of tire stress conditions. The tire's rolling resistance can also be predicted, providing data support for energy consumption analysis. Furthermore, by comparing the energy loss of a single tire, the excess wheel deviation energy consumption can be determined, helping to improve energy efficiency. Combining this excess wheel deviation energy consumption with the remaining range management system of new energy vehicles can more accurately predict the remaining range of new energy vehicles with abnormal wheel deviation, improving driving safety. Furthermore, by monitoring tire abnormalities and energy consumption, potential safety hazards can be detected in advance, improving driving safety.

[0011] In a feasible embodiment, according to the magnetic encoder in the suspension system of the new energy vehicle, the wheel running state of the new energy vehicle is perceived based on the three-dimensional modeling of the tire under straight-line driving, and the abnormal wheel deviation tire of the new energy vehicle is determined, specifically including: pre-installing the magnetic encoder on the kingpin shaft of the suspension system of the new energy vehicle, and arranging the preset chip locator on the inner side of the wheel hub of the vacuum inner tube of the new energy vehicle; wherein, the chip locator is used to determine the coordinates when the wheel moves; the magnetic encoder is used to measure the distance parameters; when it is detected that the new energy vehicle is in a straight-line driving state, the data signals of the magnetic encoder and the chip locator are received by the central control system of the new energy vehicle; through the magnetic encoder, the distance between the wheel hub and the kingpin shaft when the wheel moves is continuously identified to determine the horizontal spacing distance curve based on the current time node; and the inclination angle between the kingpin axis and the vertical line of the ground is calculated for the point with peak change in the spacing distance curve to determine the kingpin inclination angle of the abnormal tire and the corresponding kingpin inclination angle abnormal wheel; wherein, the point with peak change It means that the car wheel deviation has occurred; through the magnetic encoder, the distance between the kingpin axis and the ground is identified when the wheel moves, and the ground spacing distance at the current time node is obtained; and the ground spacing distance at the current time node is compared with the historical ground spacing distance. If there is a difference, the kingpin caster angle of the abnormal tire corresponding to the ground spacing distance at the current time node is recorded, and it is determined to be the wheel with abnormal kingpin caster angle; through the coordinate signals emitted by several chip locators, a three-dimensional tire cross-sectional diagram of the new energy vehicle is established; wherein, the three-dimensional tire cross-sectional diagram is a vector circular diagram generated based on multiple coordinate signals; according to the relative distance between each three-dimensional tire cross-section in the three-dimensional tire cross-sectional diagram, the abnormal driving state of the wheel of the new energy vehicle is judged to obtain the wheel with abnormal movement angle; wherein, the wheel with abnormal movement angle includes: wheel inclination angle wheel and wheel toe angle wheel; the wheel with abnormal kingpin inclination angle, the wheel with abnormal kingpin caster angle and the wheel with abnormal movement angle are integrated and processed to determine the tire with abnormal wheel deviation.

[0012] The embodiments of the present application use magnetic encoders and chip locators to accurately monitor the motion state of the wheels, including wheel deviation, camber angle, and toe angle, providing accurate data support for tire abnormalities. The magnetic encoder can measure the distance changes between the wheel and the kingpin axis, as well as the distance between the wheel and the ground, in real time during straight-line driving, ensuring the real-time and accuracy of the data. It can also automatically identify abnormal wheels with abnormal kingpin inclination, kingpin castor, and abnormal motion angles (such as wheel camber and toe angle), helping to promptly detect potential problems. The coordinate signals emitted by multiple chip locators can be used to create a three-dimensional tire cross-sectional diagram, providing intuitive tire status visualization, making it easier for technicians to understand and analyze. By generating a vector pie chart, the shape and size of the tire can be accurately represented, which helps analyze the tire's geometric state. By integrating multiple abnormal parameters, the abnormal driving state of the wheel can be comprehensively assessed, improving the accuracy and reliability of the judgment. By detecting tire abnormalities early, traffic accidents caused by tire problems can be reduced and vehicle driving safety can be improved.

[0013] In a feasible implementation manner, the abnormal driving state of the wheel of the new energy vehicle is judged according to the relative distance between each three-dimensional tire section in the three-dimensional tire cross-sectional view, and the wheel with abnormal motion angle is obtained, which specifically includes: performing intersection calculation on the vector plane corresponding to the three-dimensional tire cross-sectional view and the vertical plane corresponding to the vertical line of the ground to obtain the intersection plane angle; and performing threshold judgment on the intersection plane angle; if the intersection plane angle is greater than or equal to a first preset threshold, the wheel inclination angle wheel corresponding to the three-dimensional tire cross-sectional view is determined as the wheel with abnormal motion angle; extracting the wheel vector plane pair in the three-dimensional tire cross-sectional view; wherein the wheel vector plane pair is the new energy vehicle a pair of driving wheels or a pair of driven wheels; performing translational overlap processing on the first wheel vector plane and the second wheel vector plane in the wheel vector plane pair based on the center points of the two planes; if there is a plane angle between the first wheel vector plane and the second wheel vector plane, performing plane overlap comparison and judgment on the first wheel vector plane and the second wheel vector plane respectively with the standard wheel vector plane; wherein, the standard wheel vector plane is a vector plane consistent with the forward direction; if there is a wheel vector plane that does not conform to the standard wheel vector plane, the abnormal wheel corresponding to the wheel vector plane pair is determined as the wheel with the wheel toe angle, and the abnormal wheel is determined as the wheel with the abnormal motion angle.

[0014] In a feasible embodiment, the abnormal wheel deviation tire is identified and segmented with respect to the carcass deformation area through a preset visual model to obtain a tread contact plane map, specifically comprising: collecting the sidewall image of the abnormal wheel deviation tire; marking the inner and outer offset point coordinates of the sidewall image based on the axle center coordinate point through the SAM visual model to obtain a wheel contour image; wherein the inner offset point coordinates are evenly distributed in the wheel hub, and the outer offset point coordinates are evenly distributed in the sidewall tire; according to the wheel hub features corresponding to the inner offset point coordinates and the tire rubber ring features corresponding to the outer offset point coordinates, a segmentation mask is generated for the wheel hub area in the wheel contour image to obtain a wheel hub segmentation mask area; based on the foreground point sequence of the sidewall tire area in the wheel contour image, the wheel hub segmentation mask area is segmented. The edge contour is segmented based on the focal loss function to obtain a sidewall tire area image; the sidewall deformation area image in the sidewall tire area image is identified and marked; the grayscale pixel area is divided into different textures according to the horizontal distribution sequence of grayscale pixels in the sidewall deformation area image to obtain a sidewall horizontal texture image; wherein the horizontal texture in the sidewall horizontal texture image represents the force and extrusion condition of the sidewall; the sidewall deformation area image is subjected to image symmetric extension processing related to the tire body deformation area to obtain an estimated tread contact plane map; wherein the image symmetric extension processing is to perform image symmetric replication processing on the sidewall deformation area image based on the sidewall tire edge; the sidewall horizontal texture image is symmetrically mapped to the estimated tread contact plane map to generate the tread contact plane map.

[0015] The embodiments of the present application process tire sidewall images using the SAM visual model to accurately identify and mark carcass deformation areas, providing high-precision data for tire deformation analysis. Using a preset visual model, the deformed areas of the tire can be quickly detected, improving detection efficiency and speed. The automated detection process reduces reliance on manual inspection, reduces the possibility of human error, and improves the automation level of tire detection. Image processing technology generates a tread contact plane map, providing an intuitive graphical representation for tire force analysis. Furthermore, the sidewall horizontal texture image visually demonstrates the sidewall's compression and compression conditions, helping to understand the tire's stress state. Texture segmentation based on the horizontal distribution sequence of grayscale pixels allows for further analysis of tire wear and deformation patterns. Symmetrical extension processing of the sidewall deformation area image can also be used to estimate the tread contact plane map. This simple and effective processing method allows for the estimation of the tread contact plane map. The generated tread contact plane map and sidewall horizontal texture image can be used for more in-depth data analysis, such as predicting the remaining service life of the tire or evaluating tire performance.

[0016] In a feasible embodiment, according to the geometric characteristics and mechanical characteristics between the tread and the ground, the characteristic parameters of the tread contact plane map under the extrusion area are calculated and processed to obtain the abnormal wheel deviation parameters of the abnormal wheel deviation tire, specifically including: calculating the area of ​​the texture area in the tread contact plane map based on the extrusion area between the tire and the ground to obtain the contact area; determining the multi-directional wheel axle length of the extrusion area according to the unit pixel length of the texture area in the tread contact plane map; wherein the multi-directional wheel axle length is the horizontal and vertical edge length of the texture area; based on the multi-directional wheel axle length, calculating the concave and convex shape of the texture area with respect to the inner angle radian value to determine the shape of the texture area; wherein the concave and convex shape includes: an outer convex texture shape and an inner concave texture shape; according to the basic parameters of the new energy vehicle and based on the abnormal wheel deviation The average contact pressure and the corresponding maximum contact pressure of the abnormal wheel-deviation tire are determined based on the contact area of ​​the tire and the density of grayscale pixels in the texture area; wherein, the area of ​​the area corresponding to the density of the grayscale pixels is related to the maximum contact pressure; the basic parameters include at least: vehicle weight, vehicle acceleration, total tire moment of inertia and dynamic wheel radius; through the average contact pressure and the corresponding maximum contact pressure, and based on the multi-directional wheel axle length and the shape of the texture area, the pressure distribution of the texture area is discretely calculated to obtain the contact pressure deviation value; wherein, the contact pressure deviation value is used to characterize the degree of discreteness of the pressure distribution between the tread and the ground; the contact area, the average contact pressure, the maximum contact pressure and the contact pressure deviation value are integrated to obtain the abnormal wheel deviation parameters of the abnormal wheel-deviation tire.

[0017] The embodiments of the present application can accurately analyze the geometric and mechanical characteristics of the tire's contact with the ground by calculating the characteristic parameters in the tread contact plane. The ability to accurately measure the tire's contact area is crucial for understanding the tire's ground contact performance. By determining the horizontal and vertical edge lengths of the textured area, a more comprehensive understanding of the tire's contact shape and pressure distribution can be obtained. Analyzing the concave and convex shapes of the textured area helps identify tire wear patterns and uneven force distribution. By calculating the discrete pressure distribution, a contact pressure deflection value can be obtained, which helps assess whether the tire's pressure distribution is uniform. Determining the tire's average contact pressure and maximum contact pressure is crucial for assessing the tire's load-bearing capacity and durability. Combined with the basic parameters of new energy vehicles (such as vehicle weight, acceleration, moment of inertia, and wheel radius), the tire's force conditions can be more comprehensively simulated and analyzed. At the same time, the contact pressure deflection value, as an indicator of the degree of discreteness of the pressure distribution, can be used to predict tire wear and performance degradation. In other words, the specific parameters of tires with abnormal wheel deviation can be determined, which helps diagnose tire abnormalities.

[0018] In a feasible implementation, based on the tire characterization parameters of the new energy vehicle, the abnormal wheel deviation parameters are calculated based on the global contact coupling stiffness between the tire's own contact parameters and the degree of discreteness of ground particles, and the tire stress of the abnormal wheel deviation tire is determined, specifically including: collecting the tire characterization parameters under the current tire model of the new energy vehicle; wherein, the tire characterization parameters include at least: material elasticity, material plasticity, surface pattern characteristics, material wear, maximum material fracture parameter, maximum material slip parameter and maximum material friction parameter; through a preset continuous-discontinuous unit method, and based on the tire characterization parameters, the abnormal wheel deviation parameters are calculated based on the tire's own contact parameters and the degree of discreteness of ground particles. The node force of the tire body contact parameters is calculated to obtain the node resultant force; wherein, the node resultant force includes: the node damping force based on the tire characterization parameters, the contact surface contribution node force based on the contact area, the node force contributed by the finite element unit deformation based on the average contact pressure, and the node external force based on the maximum contact pressure; based on the physical quantities of the motion state of the new energy vehicle at the current time node, the abnormal wheel deviation parameters are subjected to contact force calculation based on the degree of discreteness of ground particles to obtain the particle contact force; wherein, the particle contact force includes: the normal contact force between particles and the tangential contact force between particles; the node resultant force and the particle contact force are coupled and calculated to obtain the tire stress of the tire with abnormal wheel deviation.

[0019] By combining the tire's own contact parameters with the degree of ground particle dispersion, the present embodiment can more accurately calculate the stress distribution of the tire during driving. This method takes into account multiple tire characterization parameters, such as material elasticity, plasticity, surface pattern characteristics, wear, maximum fracture parameter, maximum slip parameter, and maximum friction parameter, thereby providing a comprehensive analysis of tire performance. The use of the continuous-discontinuous element method can more accurately simulate the contact between the tire and the ground, which is crucial for analyzing tire behavior under complex operating conditions. Furthermore, by calculating the nodal resultant forces, including damping force, nodal forces contributed by the contact surface, nodal forces contributed by finite element element deformation, and nodal external forces, the internal stress conditions of the tire can be analyzed in detail. The contact force calculation, combined with the degree of ground particle dispersion, can more realistically reflect the stress conditions of the tire on actual road surfaces. Furthermore, by calculating the normal and tangential contact forces between particles, the friction and interaction between the tire and the ground can be evaluated. Finally, the nodal resultant forces and particle contact forces are coupled to calculate the overall stress distribution of the tire.

[0020] In a feasible implementation, the tire stress is input into a pre-trained tire rolling resistance model, and based on the weighted connection space mapping from the input layer to the hidden layer in the tire rolling resistance model, the tire rolling resistance of the abnormal wheel deviation tire is calculated and obtained, specifically comprising: inputting the tire stress into the trained tire rolling resistance model; wherein the tire rolling resistance model is a neural network model; wherein the training data in the tire rolling resistance model is nonlinearly transformed into the hidden layer space through the input layer space, and linearly transformed into the output layer space through the hidden layer space; through the input layer in the tire rolling resistance model, the tire stress and the basic parameters of the new energy vehicle are subjected to hidden layer direct space mapping processing based on the kernel function; according to The additional rolling resistance F due to wheel deviation is obtained; wherein J1 is the total tire moment of inertia corresponding to the basic parameter; J2 is the tire moment of inertia of the tire with abnormal wheel deviation; ε is the ground contact area of ​​the abnormal wheel deviation parameter; r1 is the average ground contact pressure of the abnormal wheel deviation parameter; and r2 is the maximum ground contact pressure of the abnormal wheel deviation parameter. is the contact pressure deflection value of the abnormal wheel deviation parameter; f is the tire stress; tan -1 δ is the tire characterization parameter; v is the wheel deviation contact deformation area volume in the abnormal wheel deviation parameter; d t is the time variation; F m is the total rolling resistance of the new energy vehicle; R d is the ideal average rolling resistance of each tire of the new energy vehicle; the wheel deviation additional rolling resistance is added to the wheel rolling resistance of the normal tires in the new energy vehicle to obtain the tire rolling resistance based on the abnormal wheel deviation tire.

[0021] In a feasible embodiment, the energy consumption loss of a single tire of the abnormal wheel deviation tire is compared based on the tire rolling resistance and the corresponding tire amplitude to determine the additional wheel deviation energy consumption, specifically including: obtaining the abnormal tire amplitude curve of the abnormal wheel deviation tire; and constructing an abnormal tire amplitude function based on the abnormal tire amplitude curve; calculating the amplitude difference between the normal tire amplitude function of the new energy vehicle and the abnormal tire amplitude function to determine the amplitude difference interval; calculating the ratio of the tire rolling resistance of the abnormal wheel deviation tire to the tire resistance of the normal tire to determine the rolling resistance coefficient; estimating the energy loss per unit normal energy consumption loss of the normal tire through a preset envelope function, and obtaining the additional wheel deviation energy consumption of the abnormal wheel deviation tire based on the closed area between the upper envelope function and the lower envelope function; wherein the lower envelope function corresponds to the amplitude difference interval, and the upper envelope function corresponds to the rolling resistance coefficient.

[0022] By comparing the rolling resistance and amplitude of tires with abnormal wheel deviation, the embodiment of the present application can accurately calculate the energy loss of a single tire and provide data support for tire energy consumption management. In addition, obtaining and analyzing the abnormal tire amplitude curve helps to understand the vibration characteristics of the tire under abnormal wheel deviation, which is very important for tire performance analysis. An amplitude function is constructed based on the abnormal tire amplitude curve, providing a mathematical model for subsequent energy loss calculations. The abnormal tire amplitude function can also be compared with the normal tire amplitude function to reveal the impact of abnormal wheel deviation on tire performance. Then, by determining the amplitude difference range, the vibration changes caused by abnormal wheel deviation can be quantified, thereby evaluating its impact on energy consumption. And by calculating the rolling resistance coefficient, the friction between the tire and the ground can be more accurately evaluated, thereby affecting energy consumption. At the same time, the preset envelope function is used to estimate the unit energy loss, which is effective for calculating the additional wheel deviation energy consumption of the abnormal wheel deviation tire.

[0023] In a feasible implementation manner, the additional wheel deviation energy consumption and the remaining mileage management system of the new energy vehicle are integrated and processed to obtain the remaining mileage prediction data of the new energy vehicle under abnormal wheel deviation, specifically including: extracting the current remaining mileage data in the remaining mileage management system; performing a proportional calculation on the additional wheel deviation energy consumption and the current remaining mileage energy consumption under the current remaining mileage data to obtain the abnormal energy consumption proportional coefficient; performing data prediction processing on the current remaining mileage data based on the abnormal energy consumption proportional coefficient to determine the remaining mileage prediction data of the new energy vehicle under abnormal wheel deviation.

[0024] On the other hand, an embodiment of the present application also provides a wheel pulley resistance energy consumption monitoring device based on new energy vehicles, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, so that the at least one processor can execute a wheel pulley resistance energy consumption monitoring method based on new energy vehicles as described in any of the above embodiments.

[0025] The present invention provides a method and device for monitoring wheel yaw resistance energy consumption in new energy vehicles. Compared with the prior art, the present invention has the following beneficial technical effects:

[0026] 1. Real-time monitoring of tire status: The magnetic encoder senses the wheel operating status, enabling real-time monitoring of the tire operating status, helping to detect tire abnormalities in a timely manner.

[0027] 2. Accurately identify abnormal tires: Using visual models to identify and segment the carcass deformation area of ​​tires with abnormal wheel deviation, the position and degree of abnormal tires can be accurately located.

[0028] 3. Parameter calculation and characteristic analysis: By calculating the characteristic parameters of the tread contact plane, the mechanical properties of the tire in the squeeze area can be analyzed, providing a basis for subsequent energy consumption calculations.

[0029] 4. Global contact coupling stiffness calculation: Based on tire characterization parameters and contact parameters, tire stress is calculated to more comprehensively evaluate the tire's stress conditions.

[0030] 5. Rolling resistance model prediction: Inputting tire stress into a pre-trained rolling resistance model can predict the tire's rolling resistance, providing data support for energy consumption analysis.

[0031] 6. Energy loss assessment: By comparing the energy loss of a single tire, the additional wheel offset energy loss can be determined, which helps improve energy efficiency.

[0032] 7. Remaining mileage prediction: Combining the excess wheel deviation energy consumption with the remaining mileage management system of new energy vehicles can more accurately predict the remaining mileage of new energy vehicles under abnormal wheel deviation, improving driving safety.

[0033] 8. Improve driving safety: By monitoring the abnormal status and energy consumption of tires, potential safety hazards can be discovered in advance and driving safety can be improved.

[0034] 9. Early warning: Provides data support for tire maintenance, helps remind drivers of wheel deviation failures, and ensures vehicle performance and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments described in the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0036] Figure 1 A flow chart of a method for monitoring wheel yaw resistance and energy consumption based on new energy vehicles provided in an embodiment of the present application;

[0037] Figure 2 A schematic structural diagram of a wheel with a toe angle provided in an embodiment of the present application;

[0038] Figure 3 A schematic diagram of a wheel-biased tire provided in an embodiment of the present application;

[0039] Figure 4 A schematic diagram of a tread contacting the ground provided in an embodiment of the present application;

[0040] Figure 5 A schematic structural diagram of a wheel drag energy consumption monitoring device based on a new energy vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the technical solutions in this application, the following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0042] The embodiment of the present application provides a method for monitoring wheel deflection resistance energy consumption based on new energy vehicles, such as Figure 1 As shown, the method for monitoring wheel yaw resistance energy consumption based on new energy vehicles specifically includes steps S101-S106:

[0043] S101. Using a magnetic encoder in a suspension system of a new energy vehicle, the running state of the wheels of the new energy vehicle is perceived based on three-dimensional tire modeling under straight-line driving, and abnormal wheel deviation of the new energy vehicle is determined.

[0044] Specifically, a magnetic encoder is pre-installed on the kingpin of the new energy vehicle's suspension system, and a pre-set chip locator is placed on the inside of the wheel hub of the new energy vehicle's vacuum inner tube. The chip locator is used to determine the coordinates of the wheel during movement, while the magnetic encoder is used to measure distance parameters.

[0045] It's important to note that magnetic encoders use the principle of magnetic field induction to determine an object's position by detecting changes in the magnetic field. Compared to photoelectric encoders, magnetic encoders offer stronger interference immunity and higher reliability, enabling stable operation in harsh environments. They are widely used in fields such as industrial automation and aerospace, playing a vital role in the precise control and positioning of equipment.

[0046] Furthermore, when it is detected that the new energy vehicle is in a straight-line driving state, the data signals of the magnetic encoder and the chip locator are received by the new energy vehicle central control system.

[0047] Furthermore, a magnetic encoder can be used to continuously identify the distance between the wheel hub and the kingpin axis during wheel motion, determining a horizontal separation distance curve based on the current time point. Points with peak changes in the separation distance curve are then used to calculate the inclination angle between the kingpin axis and the ground vertical line, identifying the abnormal tire's kingpin inclination angle and the corresponding wheel with the abnormal kingpin inclination angle. Peak changes in these points indicate wheel deviation.

[0048] Furthermore, the magnetic encoder is used to identify the distance between the kingpin axis and the ground during wheel motion, determining the ground clearance distance at the current time point. The ground clearance distance at the current time point is compared with the historical ground clearance distances to determine changes. If there is a difference, the caster angle of the abnormal tire corresponding to the ground clearance distance at the current time point is recorded and the wheel with the abnormal caster angle is determined.

[0049] Furthermore, a three-dimensional tire cross-section diagram of the new energy vehicle is created using the coordinate signals emitted by multiple chip locators. The three-dimensional tire cross-section diagram is a vector circular diagram generated based on multiple coordinate signals. Based on the relative distances between each three-dimensional tire section in the three-dimensional tire cross-section diagram, the abnormal driving state of the new energy vehicle's wheels is determined, and the wheels with abnormal motion angles are determined. These wheels with abnormal motion angles include wheels with camber angles and wheels with toe angles.

[0050] In one embodiment, Figure 2 A schematic structural diagram of a wheel with a toe angle provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, through the chip locator, the three-dimensional tire cross-section of the tire during driving can be established, that is, a vector plane diagram can be established, and then according to the relative position relationship of the vector diagram, that is, the relative distance and the relative angle of the vector plane, it can be determined whether there is a problem with the wheel toe angle of the wheel pair corresponding to the wheel vector plane.

[0051] As a feasible implementation method, the vector plane corresponding to the three-dimensional tire cross-section image and the vertical plane corresponding to the vertical line of the ground can be intersected to obtain the angle between the intersecting planes. A threshold value is then determined for the angle between the intersecting planes:

[0052] If the angle between the intersecting planes is greater than or equal to a first preset threshold, the wheel with the wheel camber angle corresponding to the 3D tire cross-sectional image is determined to be a wheel with an abnormal motion angle. A wheel vector plane pair is extracted from the 3D tire cross-sectional image. The wheel vector plane pair represents a pair of driving wheels or a pair of driven wheels of a new energy vehicle. The first and second wheel vector planes in the wheel vector plane pair are then subjected to a translational alignment based on the center points of the two planes.

[0053] If there is an included angle between the first wheel vector plane and the second wheel vector plane, the first wheel vector plane and the second wheel vector plane are respectively compared with a standard wheel vector plane for plane coincidence determination. The standard wheel vector plane is a vector plane aligned with the forward direction.

[0054] If there is a wheel vector plane that does not conform to the standard wheel vector plane, the abnormal wheel corresponding to the wheel vector plane alignment is determined as the wheel with the wheel toe angle, and the abnormal wheel is determined as the wheel with the abnormal motion angle.

[0055] Furthermore, data of wheels with abnormal kingpin inclination angles, wheels with abnormal kingpin caster angles, and wheels with abnormal motion angles are integrated and processed to determine the tire with abnormal wheel deviation.

[0056] S102. Using a preset visual model, the tire with abnormal wheel deviation is identified and segmented in the carcass deformation area to obtain a tread contact plane diagram; and based on the geometric and mechanical properties between the tread and the ground, the characteristic parameters of the tread contact plane diagram in the extrusion area are calculated and processed to obtain the abnormal wheel deviation parameters of the tire with abnormal wheel deviation.

[0057] Specifically, the vehicle's onboard image acquisition equipment is used to capture sidewall images of tires with abnormal wheel deviation. The SAM visual model is then used to label the sidewall images with inner and outer deviation coordinates based on the axle center coordinates, generating a wheel profile image. The inner deviation coordinates are evenly distributed within the wheel hub, while the outer deviation coordinates are evenly distributed within the sidewall tire.

[0058] In one embodiment, Figure 3 A schematic diagram of a wheel-biased tire provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, based on the abnormal wheel deviation tires determined by the wheels with abnormal kingpin inclination angles, the wheels with abnormal kingpin caster angles, and the wheels with abnormal motion angles, it can be clearly seen that the inner area has been deformed, and the tire deformation shape represented is also different from the normal tire form. The SAM visual model is then used to perform subsequent sidewall image segmentation on the identified abnormal tires and wheels. First, through the pre-defined N inner and outer deviation point coordinates, that is, the deviation point coordinates evenly distributed in the wheel hub and the outer deviation point coordinates evenly distributed in the sidewall tire, the visual model can then focus on the structural features of the tire for independent segmentation. These inner and outer deviation points serve as input prompts to guide the model to accurately identify and process the edge and surface features of the tire.

[0059] Furthermore, it is necessary to generate a segmentation mask for the hub area in the wheel profile image according to the hub features corresponding to the inner bias point coordinates and the tire rubber ring features corresponding to the outer bias point coordinates to obtain the hub segmentation mask area.

[0060] Furthermore, the foreground point sequence of the sidewall tire area in the wheel contour image is used to perform segmentation processing on the edge contour of the hub segmentation mask area based on the focal loss function to obtain the sidewall tire area image.

[0061] In one embodiment, the tire edge is segmented using the center point of a sequence of foreground points to obtain a segmentation region and a segmentation score. This method not only improves the edge segmentation quality but also optimizes the overall accuracy of the segmentation result. Specifically, a linear combination of the focal loss function and the block loss function of the segmentation score is used to segment the edge contour of the wheel segmentation mask area. Based on the continuously adjusted weight parameter of the focal loss function contribution, the boundary between the sidewall tire and the wheel hub is identified, thereby segmenting the sidewall tire area image.

[0062] Furthermore, the sidewall deformation region image within the sidewall tire region image is identified and marked. Based on the horizontal distribution sequence of grayscale pixels within the sidewall deformation region image, the grayscale pixel region is divided into different textures to generate a sidewall horizontal texture image. The horizontal textures within the sidewall horizontal texture image represent the stress and compression conditions of the sidewall.

[0063] Furthermore, the image of the sidewall deformation region is symmetrically extended relative to the carcass deformation region to generate an estimated tread contact plane. This symmetrical extension process involves symmetrically replicating the image of the sidewall deformation region based on the tire edge. Finally, the sidewall horizontal texture image is symmetrically mapped onto the estimated tread contact plane to generate the tread contact plane.

[0064] In a real-time example, Figure 4 A schematic diagram of a tread contact plane provided in an embodiment of the present application, such as Figure 4 As shown in the figure, at standard inflation pressure, when the tire is unloaded and not in contact with the road, the tire carcass expands outward due to the inflation pressure. When loaded and in contact with the road, the direction of the force applied to the area where the tire is in contact with the road changes. The area where the direction of the contact pressure between the tread and the carcass changes is called the contact zone. The contact characteristics between the tread and the carcass vary depending on the tire's operating conditions, tread pattern, and carcass structure. In the case of wheel deviation, the sidewall deformation area of ​​the tire will be more obvious, and the distribution of grayscale pixels in the sidewall deformation area image will also show obvious pixel changes. Wheel deviation is generally an over-wear area, so the ground contact area of ​​this area is correlated with the changes in the tire side. Therefore, according to the horizontal distribution sequence of grayscale pixels in the sidewall deformation area image, the grayscale pixel area is first divided into different textures to obtain the sidewall horizontal texture image, and then the sidewall tire is symmetrically replicated about the edge axis to determine the specific geometric shape and mechanical characteristics of the carcass deformation area of ​​the tire with abnormal wheel deviation, thereby predicting and estimating the tread ground contact plane that can best reflect the actual situation.

[0065] Furthermore, based on the obtained tread contact map, the area of ​​the textured area in the tread contact map is calculated based on the area under the compression zone between the tire and the ground to obtain the contact area. The multi-directional axle length of the compression zone is then determined based on the unit pixel length of the textured area in the tread contact map. The multi-directional axle length refers to the length of the horizontal and vertical edges of the textured area. Based on the multi-directional axle length, the concave-convex shape of the textured area is calculated based on the inner angle radian value to determine the textured area shape. The concave-convex shape includes both convex and concave texture shapes.

[0066] Furthermore, using the basic parameters of new energy vehicles as fundamental data, and based on the contact area of ​​the tire with abnormal wheel deviation and the density of grayscale pixels in the texture area, the average contact pressure and corresponding maximum contact pressure of the tire with abnormal wheel deviation are determined. The area corresponding to the density of grayscale pixels is correlated with the maximum contact pressure. Basic parameters include at least vehicle weight, vehicle acceleration, total tire moment of inertia, and dynamic wheel radius.

[0067] Furthermore, the average contact pressure and the corresponding maximum contact pressure are used to discretize the pressure distribution within the textured area based on the multi-directional axle length and the textured area shape, resulting in a contact pressure deflection value. The contact pressure deflection value represents the degree of pressure dispersion between the tread and the ground.

[0068] Furthermore, the contact area, average contact pressure, maximum contact pressure and contact pressure deviation values ​​are integrated, that is, all the data are integrated and stored to obtain abnormal wheel deviation parameters of the tire with abnormal wheel deviation.

[0069] As a feasible implementation method, it is necessary to further conduct a detailed analysis of the geometric and mechanical characteristics of the tread contact plane diagram, and combine it with the basic parameters of new energy vehicles to calculate the abnormal wheel deviation parameters of the contact area, multi-directional axle length and texture area shape contained in the tread contact plane diagram. That is, it is necessary to convert the pixel conditions of the texture area in the tread contact plane diagram, the density of grayscale pixels in the texture area, etc. into abnormal wheel deviation parameters for characterizing tires with abnormal wheel deviation.

[0070] S103. Based on the tire characterization parameters of the new energy vehicle, the abnormal wheel deviation parameters are calculated based on the global contact coupling stiffness between the tire's own contact parameters and the degree of ground particle dispersion, and the tire stress of the tire with abnormal wheel deviation is determined.

[0071] Specifically, based on standard tire parameters, tire characterization parameters for the current tire model of a new energy vehicle are collected. These tire characterization parameters include at least: material elasticity, material plasticity, surface pattern characteristics, material abrasion resistance, maximum material fracture parameter, maximum material slip parameter, and maximum material friction parameter.

[0072] Furthermore, using a preset continuous-discontinuous element method and based on tire characterization parameters, the abnormal wheel deviation parameters are applied to calculate nodal forces based on the tire's own contact parameters, resulting in a nodal resultant force. This nodal resultant force includes: nodal damping forces based on tire characterization parameters, contact surface contribution nodal forces based on contact area, nodal forces contributed by finite element deformation based on average contact pressure, and nodal external forces based on maximum contact pressure.

[0073] As a feasible implementation method, the Continuum Discontinuum Element Method (CDEM) is an explicit dynamic numerical analysis method that combines finite elements and discrete elements, and its theoretical basis is the Lagrange equation. The Continuum Discontinuum Element Method consists of two parts: blocks and interfaces. The blocks are composed of finite element units; the interfaces are the common boundaries between blocks, which respectively characterize the continuous characteristics such as material elasticity, material plasticity, surface pattern characteristics, material wear, and discontinuous characteristics such as the maximum parameters of material fracture, the maximum parameters of material slip, and the maximum parameters of material friction. The contact coupling stiffness between the ground and the tire itself adopts a global value, and then based on the tire characterization parameters, the abnormal wheel deviation parameters are calculated based on the node force of the tire's own contact parameters:

[0074] That is, the node resultant force is obtained by using the node force = node damping force A + contact surface contribution node force B + finite element unit deformation contribution node force C + node external force D, and the core control equations of node motion: node acceleration, node velocity, node displacement increment, node mass and calculation time step, etc., thereby realizing the mechanical characterization of the tire under its own contact parameters.

[0075] Furthermore, based on the physical quantities of the new energy vehicle's motion state at the current time point, the abnormal wheel deviation parameters are then combined with contact forces based on the discreteness of ground particles to obtain the particle contact force. This particle contact force comprises the normal contact force between particles and the tangential contact force between particles. Finally, the nodal resultant force and the particle contact force are coupled to calculate the tire stress of the tire with abnormal wheel deviation.

[0076] In one embodiment, by considering the discreteness of the ground particles and the motion state of the tire, the stress distribution of the tire can be calculated more accurately, which is crucial for predicting the fatigue life and wear pattern of the tire. At the same time, accurate stress analysis helps to identify the weak points that may appear in the tire under abnormal wheel deviation, thereby improving the safety of vehicle driving. And through the specific analysis of the tire itself and the road particles and then force coupling, it is possible to complete a dynamic coupled force analysis of the abnormal wheel deviation tire of a new energy vehicle in motion, which is conducive to the subsequent analysis of the rolling resistance caused by the abnormal wheel deviation tire, that is, to provide accurate basic force data.

[0077] S104: Input the tire stress into the pre-trained tire rolling resistance model, and calculate and obtain the tire rolling resistance of the tire with abnormal wheel deviation based on the weighted connection space mapping from the input layer to the hidden layer in the tire rolling resistance model.

[0078] Specifically, a tire rolling resistance model is pre-trained using a historical tire rolling resistance dataset. Tire stresses are then input into the trained tire rolling resistance model. The tire rolling resistance model is a neural network model. The training data in the tire rolling resistance model undergoes a nonlinear transformation from the input layer space to the hidden layer space, and then a linear transformation from the hidden layer space to the output layer space.

[0079] Furthermore, the tire stress and basic parameters of the new energy vehicle are processed by direct spatial mapping of the hidden layer based on the kernel function through the input layer of the tire rolling resistance model.

[0080] Furthermore, using the formula: The additional rolling resistance F of the wheel deviation is obtained; where J1 is the total tire moment of inertia corresponding to the basic parameters; J2 is the tire moment of inertia of the tire with abnormal wheel deviation; ε is the ground contact area of ​​the abnormal wheel deviation parameter; r1 is the average ground contact pressure of the abnormal wheel deviation parameter; r2 is the maximum ground contact pressure of the abnormal wheel deviation parameter; is the contact pressure deviation value of the abnormal wheel deviation parameter; f is the tire stress; tan -1 δ is the tire characterization parameter; v is the wheel deviation contact deformation area volume in the abnormal wheel deviation parameter; d t is the time variation; F m is the total rolling resistance of new energy vehicles; R d The ideal average rolling resistance for each tire of a new energy vehicle.

[0081] Furthermore, the extra rolling resistance of the wheel deviation is added to the wheel rolling resistance of the normal tire in the new energy vehicle, that is, after the two resistances are superimposed, the tire rolling resistance based on the abnormal wheel deviation tire can be obtained.

[0082] As a feasible implementation method, the tire rolling resistance model trained using kernel functions and activation functions can transform vectors from linearly inseparable to linearly separable. In this way, the nonlinear mapping of the network from input to output becomes a linear adjustable parameter in the network output. Since the weights of the network can be directly obtained by solving a set of linear equations, the problem of local minima can be avoided, and the learning speed can be greatly accelerated, thereby achieving a more accurate calculation of the additional rolling resistance of the wheel deviation, and reducing the calculation error and the problem of reducing the calculation volume. Since the resistance of a tire with abnormal wheel deviation is generally greater than that of a normal tire, the wheel rolling resistance of a normal tire and the additional rolling resistance of the wheel deviation calculated by the model can be used to maximize the true tire rolling resistance of the tire with abnormal wheel deviation.

[0083] S105 , comparing the energy loss of a single tire of the abnormally deflected tire based on the tire rolling resistance and the corresponding tire amplitude, and determining the additional deflection energy consumption.

[0084] Specifically, the amplitude sensor in the new energy vehicle is used to obtain the abnormal tire amplitude curve of the abnormal wheel deviation tire, and based on the abnormal tire amplitude curve, an abnormal tire amplitude function is constructed.

[0085] Furthermore, it is necessary to calculate the amplitude difference between the amplitude function of the normal tire and the amplitude function of the abnormal tire of the new energy vehicle to determine the amplitude difference range. In addition, the ratio of the rolling resistance of the abnormal tire to the tire resistance of the normal tire is calculated to determine the rolling resistance coefficient.

[0086] It should be noted that the envelope function is a mathematical tool used to describe the changes in the local maximum value of a signal, and is commonly used in the field of electronic engineering. Specifically, the envelope function can be understood as a graph interwoven by many elliptical curves. The envelope theorem involves the relationship between the maximum function and the objective function. The envelope theorem states that when the parameters are given, the selected variables in the objective function can take any value. If the variable happens to take the optimal value, the objective function is equal to the maximum function. That is, by using the correspondence between the lower envelope function and the amplitude difference interval and the correspondence between the upper envelope function and the rolling resistance coefficient, the unit normal energy loss of a normal tire is estimated, and the maximum function of the unit normal energy loss is used to complete the target generation calculation of the additional wheel deviation energy consumption.

[0087] Furthermore, a preset envelope function is used to estimate the energy loss per unit of normal tire energy consumption. The additional wheel deviation energy consumption of the abnormally deviated tire is then calculated based on the enclosed area between the upper and lower envelope functions. The lower envelope function corresponds to the amplitude difference range, while the upper envelope function corresponds to the rolling resistance coefficient.

[0088] As a feasible implementation method, because the amplitude of a tire with abnormal wheel deviation is generally large and in an unbalanced state, and because higher energy loss will cause the oscillation to decay faster (and therefore have a smaller area), the energy loss is estimated as the closed area between the two envelope lines, that is, the additional wheel deviation energy consumption of the tire with abnormal wheel deviation.

[0089] S106 , integrating the extra wheel deviation energy consumption with the remaining mileage management system of the new energy vehicle to obtain remaining mileage prediction data of the new energy vehicle under abnormal wheel deviation.

[0090] Specifically, the system first extracts the current remaining mileage data from the gap remaining mileage management system. Then, the ratio of the excess wheel deviation energy consumption to the current remaining mileage energy consumption is calculated to obtain the abnormal energy consumption ratio coefficient. Finally, based on the abnormal energy consumption ratio coefficient, the current remaining mileage data is predicted and processed to determine the predicted remaining mileage for a new energy vehicle with abnormal wheel deviation.

[0091] As a feasible implementation method, the remaining mileage prediction data and the determined abnormal wheel deviation tire information can also be processed as an alarm. When the remaining mileage prediction data is less than the alarm threshold, an alarm can be issued in advance, or when abnormal wheel deviation tire is detected and the tire rolling resistance exceeds the resistance threshold, an alarm message can also be generated to prompt the driver to perform maintenance or inform the current wheel deviation status of the vehicle, so that the driver can know the vehicle's driving conditions more accurately, thereby improving the safety, intelligence and driving comfort of new energy vehicles.

[0092] In addition, the embodiment of the present application also provides a wheel deflection resistance energy consumption monitoring device based on new energy vehicles, such as Figure 5 As shown, the wheel deviation resistance energy consumption monitoring device 500 based on a new energy vehicle specifically includes:

[0093] At least one processor 501. And a memory 502 in communication with the at least one processor 501. The memory 502 stores instructions that can be executed by the at least one processor 501, so that the at least one processor 501 can execute:

[0094] Using the magnetic encoder in the suspension system of new energy vehicles, the tire's three-dimensional modeling perception of the new energy vehicle's wheel running status under straight-line driving is performed to determine abnormal wheel deviation of the new energy vehicle;

[0095] Using a preset visual model, the abnormal wheel deviation tire's carcass deformation area is identified and segmented to obtain a tread contact plane diagram. Based on the geometric and mechanical properties between the tread and the ground, the characteristic parameters of the tread contact plane diagram in the squeeze area are calculated and processed to obtain the abnormal wheel deviation parameters of the abnormal wheel deviation tire.

[0096] Based on the tire characterization parameters of new energy vehicles, the abnormal wheel deviation parameters are calculated based on the global contact coupling stiffness between the tire's own contact parameters and the degree of ground particle dispersion, and the tire stress of the abnormal wheel deviation tire is determined;

[0097] The tire stress is input into the pre-trained tire rolling resistance model, and based on the weighted connection space mapping from the input layer to the hidden layer in the tire rolling resistance model, the tire rolling resistance of the abnormal wheel deviation tire is calculated and obtained;

[0098] Based on the tire rolling resistance and the corresponding tire amplitude, the energy loss of a single tire is compared for the abnormal wheel deviation tire to determine the additional wheel deviation energy loss;

[0099] The data of the extra wheel deviation energy consumption and the remaining mileage management system of the new energy vehicle are integrated and processed to obtain the remaining mileage prediction data of the new energy vehicle under abnormal wheel deviation.

[0100] The embodiments of the present application use magnetic encoders to sense the wheel's operating status, enabling real-time monitoring of the tire's operating status and helping to promptly detect tire anomalies. Visual models can also be used to identify and segment the carcass deformation area of ​​tires with abnormal wheel deviation, accurately locating the location and extent of the abnormal tire. By calculating characteristic parameters based on the tread contact plane, the mechanical properties of the tire in the squeeze zone can be analyzed, providing a basis for subsequent energy consumption calculations. Calculating tire stress based on tire characterization parameters and contact parameters allows for a more comprehensive assessment of tire stress conditions. The tire's rolling resistance can also be predicted, providing data support for energy consumption analysis. Furthermore, by comparing the energy loss of a single tire, the excess wheel deviation energy consumption can be determined, helping to improve energy efficiency. Combining this excess wheel deviation energy consumption with the remaining range management system of new energy vehicles can more accurately predict the remaining range of new energy vehicles with abnormal wheel deviation, improving driving safety. Furthermore, by monitoring tire abnormalities and energy consumption, potential safety hazards can be detected in advance, improving driving safety.

[0101] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simple. For relevant portions, refer to the descriptions of the method embodiments.

[0102] The foregoing description describes specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0103] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the embodiments of the present application may have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for monitoring wheel yaw resistance energy consumption based on new energy vehicles, characterized in that: The method comprises: Using a magnetic encoder in the suspension system of the new energy vehicle, the wheel running state of the new energy vehicle is perceived based on three-dimensional tire modeling under straight-line driving, thereby determining the abnormal wheel deviation of the new energy vehicle; Using a preset visual model, the abnormal wheel deviation tire is identified and segmented in the carcass deformation area to obtain a tread contact plane diagram; and based on the geometric and mechanical properties between the tread and the ground, characteristic parameters of the tread contact plane diagram in the squeeze area are calculated and processed to obtain abnormal wheel deviation parameters of the abnormal wheel deviation tire; Based on the tire characterization parameters of the new energy vehicle, the abnormal wheel deviation parameter is calculated based on the global contact coupling stiffness between the tire's own contact parameters and the degree of ground particle dispersion to determine the tire stress of the abnormal wheel deviation tire; Inputting the tire stress into a pre-trained tire rolling resistance model, and calculating and obtaining the tire rolling resistance of the abnormal wheel deviation tire based on a weighted connection space mapping from an input layer to a hidden layer in the tire rolling resistance model; Comparing the energy loss of a single tire of the abnormally deflected tire based on the tire rolling resistance and the corresponding tire amplitude to determine the additional deflection energy loss; The additional wheel deviation energy consumption is integrated with the remaining mileage management system of the new energy vehicle to obtain the remaining mileage prediction data of the new energy vehicle under abnormal wheel deviation.

2. The method for monitoring wheel yaw resistance energy consumption based on new energy vehicles according to claim 1, characterized in that: Using a magnetic encoder in a suspension system of a new energy vehicle, the wheel running state of the new energy vehicle is perceived based on a three-dimensional tire model under straight-line driving, and abnormal wheel deviation of the new energy vehicle is determined, specifically including: The magnetic encoder is pre-installed on the kingpin shaft of the new energy vehicle suspension system, and a preset chip locator is arranged on the inner side of the wheel hub of the new energy vehicle vacuum inner tube; wherein the chip locator is used to determine the coordinates when the wheel moves; the magnetic encoder is used to measure the distance parameter; When it is detected that the new energy vehicle is in a straight-line driving state, the data signal of the magnetic encoder and the chip locator is received by the new energy vehicle central control system; The magnetic encoder continuously identifies the distance between the wheel hub and the kingpin axis during wheel movement, and determines a horizontal separation distance curve based on the current time node; and calculates the inclination angle between the kingpin axis and the ground vertical line at the point where a peak change occurs in the separation distance curve, thereby determining the kingpin inclination angle of the abnormal tire and the corresponding wheel with the abnormal kingpin inclination angle; wherein the point where the peak change occurs represents the occurrence of vehicle wheel deviation; The magnetic encoder is used to identify the distance between the kingpin axis and the ground when the wheel is moving, thereby obtaining a ground clearance distance at a current time node; and a change is determined between the ground clearance distance at the current time node and a historical ground clearance distance. If a difference exists, the castor angle of the abnormal tire corresponding to the ground clearance distance at the current time node is recorded, and the wheel is determined to have an abnormal castor angle. A three-dimensional tire cross-sectional diagram of the new energy vehicle is established by using the coordinate signals emitted by the plurality of chip locators; wherein the three-dimensional tire cross-sectional diagram is a vector circular diagram generated based on the plurality of coordinate signals; According to the relative distance between each three-dimensional tire cross-section in the three-dimensional tire cross-section diagram, the abnormal driving state of the wheel of the new energy vehicle is judged to obtain the wheel with abnormal movement angle; wherein the wheel with abnormal movement angle includes: a wheel with a wheel camber angle and a wheel with a wheel toe angle; Data of the wheel with abnormal kingpin inclination angle, the wheel with abnormal kingpin caster angle and the wheel with abnormal motion angle are integrated and processed to determine the tire with abnormal wheel deviation.

3. The method for monitoring wheel yaw resistance energy consumption based on new energy vehicles according to claim 2, characterized in that: According to the relative distance between each three-dimensional tire cross section in the three-dimensional tire cross section diagram, the abnormal driving state of the wheel of the new energy vehicle is judged to obtain the wheel with abnormal movement angle, specifically including: Calculating the intersection of a vector plane corresponding to the three-dimensional tire cross-sectional image and a vertical plane corresponding to a vertical line on the ground to obtain an angle between the intersecting planes; and performing a threshold determination on the angle between the intersecting planes; If the angle between the intersecting planes is greater than or equal to a first preset threshold, determining the wheel with the wheel inclination angle corresponding to the three-dimensional tire cross-sectional image as the wheel with the abnormal motion angle; Extracting a wheel vector plane pair from the three-dimensional tire cross-sectional view; wherein the wheel vector plane pair is a pair of driving wheels or a pair of driven wheels of the new energy vehicle; Performing a translation and overlap processing on the first wheel vector plane and the second wheel vector plane in the wheel vector plane alignment based on the center points of the two planes; If there is an included angle between the first wheel vector plane and the second wheel vector plane, then performing a plane coincidence comparison between the first wheel vector plane and the second wheel vector plane and a standard wheel vector plane; wherein the standard wheel vector plane is a vector plane consistent with the forward direction; If there is a wheel vector plane that does not conform to the standard wheel vector plane, the abnormal wheel corresponding to the wheel vector plane pair is determined as the wheel with the toe angle, and the abnormal wheel is determined as the wheel with the abnormal motion angle.

4. The method for monitoring wheel yaw resistance energy consumption based on new energy vehicles according to claim 1, characterized in that: Using a preset visual model, the abnormal wheel deviation tire is identified and segmented in the carcass deformation area to obtain a tread contact plane map, specifically including: collecting a sidewall image of the tire with abnormal wheel deviation; Using the SAM visual model, the sidewall image is marked with inner and outer offset coordinates based on the center coordinates of the wheel axle to obtain a wheel profile image; wherein the inner offset coordinates are evenly distributed in the wheel hub, and the outer offset coordinates are evenly distributed in the sidewall tire; generating a segmentation mask for the wheel hub region in the wheel contour image according to the wheel hub features corresponding to the inner bias point coordinates and the tire rubber rim features corresponding to the outer bias point coordinates, thereby obtaining a wheel hub segmentation mask region; Based on the foreground point sequence of the sidewall tire area in the wheel contour image, performing segmentation processing on the edge contour of the hub segmentation mask area based on the focus loss function to obtain a sidewall tire area image; Identifying and marking a sidewall deformation region image in the sidewall tire region image; According to the horizontal distribution sequence of grayscale pixels in the sidewall deformation area image, the grayscale pixel area is divided into different textures to obtain a sidewall horizontal texture image; wherein the horizontal texture in the sidewall horizontal texture image represents the force and compression of the sidewall; Performing image symmetry extension processing on the sidewall deformation region image relative to the tire body deformation region to obtain an estimated tread contact plane image; wherein the image symmetry extension processing is performing image symmetry replication processing on the sidewall deformation region image based on the sidewall tire edge; The sidewall horizontal texture image is symmetrically mapped onto the estimated tread contact plane map to generate the tread contact plane map.

5. The method for monitoring wheel yaw resistance energy consumption based on new energy vehicles according to claim 1, characterized in that: Calculating and processing characteristic parameters of the tread contact plane diagram in the squeeze area based on the geometric and mechanical properties between the tread and the ground to obtain abnormal wheel deviation parameters of the abnormal wheel deviation tire specifically includes: Calculating the area of ​​the texture area in the tread contact plane based on the area under the squeeze area between the tire and the ground to obtain a contact area; Determining the multi-directional axle length of the extrusion area based on the unit pixel length of the texture area in the tread contact plane image; wherein the multi-directional axle length is the horizontal and vertical edge lengths of the texture area; Based on the multi-directional wheel axle length, the concave-convex shape of the texture area is calculated based on the inner angle radian value to determine the shape of the texture area; wherein the concave-convex shape includes: an outer convex texture shape and an inner concave texture shape; Determining, based on basic parameters of the new energy vehicle and the contact area of ​​the abnormally deviated tire and the density of grayscale pixels in a texture area, an average contact pressure and a corresponding maximum contact pressure of the abnormally deviated tire; wherein the area corresponding to the density of the grayscale pixels is related to the maximum contact pressure; the basic parameters include at least vehicle weight, vehicle acceleration, total tire moment of inertia, and dynamic wheel radius; A pressure distribution discretization calculation is performed on the texture area based on the average contact pressure and the corresponding maximum contact pressure, the multi-directional axle length, and the shape of the texture area to obtain a contact pressure deflection value; wherein the contact pressure deflection value is used to represent the degree of pressure distribution discretization between the tread and the ground; The abnormal wheel deviation parameter of the abnormal wheel deviation tire is obtained by integrating the contact area, the average contact pressure, the maximum contact pressure, and the contact pressure deviation value.

6. The method for monitoring wheel yaw resistance energy consumption based on new energy vehicles according to claim 1, characterized in that: Based on the tire characterization parameters of the new energy vehicle, the abnormal wheel deviation parameters are calculated based on the global contact coupling stiffness between the tire's own contact parameters and the degree of ground particle dispersion to determine the tire stress of the abnormal wheel deviation tire, specifically including: Collecting the tire characterization parameters of the current tire model of the new energy vehicle; wherein the tire characterization parameters include at least: material elasticity, material plasticity, surface pattern characteristics, material abrasion, maximum material fracture parameter, maximum material slip parameter, and maximum material friction parameter; Using a preset continuous-discontinuous element method and based on the tire characterization parameters, the abnormal wheel deviation parameters are subjected to nodal force calculation based on the tire's own contact parameters to obtain a nodal resultant force; wherein the nodal resultant force includes: a nodal damping force based on the tire characterization parameters, a contact surface contribution nodal force based on the contact area, a nodal force contributed by finite element unit deformation based on the average contact pressure, and a nodal external force based on the maximum contact pressure; Based on the physical quantities of the motion state of the new energy vehicle at the current time node, the abnormal wheel deviation parameter is subjected to contact force calculation based on the degree of dispersion of ground particles to obtain particle contact force; wherein the particle contact force includes: normal contact force between particles and tangential contact force between particles; The node resultant force and the particle contact force are coupled and calculated to obtain the tire stress of the abnormal wheel deviation tire.

7. The method for monitoring wheel yaw resistance energy consumption based on new energy vehicles according to claim 1, characterized in that: Inputting the tire stress into a pre-trained tire rolling resistance model, and calculating and obtaining the tire rolling resistance of the abnormal wheel deviation tire based on a weighted connection space mapping from an input layer to a hidden layer in the tire rolling resistance model, specifically comprising: Inputting the tire stress into the trained tire rolling resistance model; wherein the tire rolling resistance model is a neural network model; wherein the training data in the tire rolling resistance model is nonlinearly transformed into a hidden layer space through an input layer space, and linearly transformed into an output layer space through the hidden layer space; Through the input layer of the tire rolling resistance model, the tire stress and the basic parameters of the new energy vehicle are subjected to hidden layer direct space mapping processing based on the kernel function; according to The additional rolling resistance F due to wheel deviation is obtained; wherein J1 is the total tire moment of inertia corresponding to the basic parameter; J2 is the tire moment of inertia of the tire with abnormal wheel deviation; ε is the ground contact area of ​​the abnormal wheel deviation parameter; r1 is the average ground contact pressure of the abnormal wheel deviation parameter; and r2 is the maximum ground contact pressure of the abnormal wheel deviation parameter. is the contact pressure deflection value of the abnormal wheel deviation parameter; f is the tire stress; tan -1 δ is the tire characterization parameter; v is the wheel deviation contact deformation area volume in the abnormal wheel deviation parameter; d t is the time variation; F m is the total rolling resistance of the new energy vehicle; R d is the ideal average rolling resistance of each tire of the new energy vehicle; The extra rolling resistance of the wheel deviation is added to the wheel rolling resistance of the normal tire in the new energy vehicle to obtain the tire rolling resistance based on the abnormal wheel deviation.

8. The method for monitoring wheel yaw resistance energy consumption based on new energy vehicles according to claim 1, characterized in that: Based on the tire rolling resistance and the corresponding tire amplitude, the energy loss of a single tire of the abnormally deviated tire is compared to determine the additional deviating energy consumption, specifically including: Acquiring an abnormal tire amplitude curve of the abnormal wheel deviation tire; and constructing an abnormal tire amplitude function based on the abnormal tire amplitude curve; Calculating the amplitude difference between the normal tire amplitude function of the new energy vehicle and the abnormal tire amplitude function to determine the amplitude difference interval; Calculating the ratio of the tire rolling resistance of the abnormally deviated tire to the tire resistance of a normal tire to determine a rolling resistance coefficient; The energy loss per unit normal energy consumption loss of the normal tire is estimated through a preset envelope function, and the additional wheel deviation energy consumption of the abnormal wheel deviation tire is obtained based on the closed area between the upper envelope function and the lower envelope function; wherein the lower envelope function corresponds to the amplitude difference interval, and the upper envelope function corresponds to the rolling resistance coefficient.

9. The method for monitoring wheel sway resistance energy consumption based on new energy vehicles according to claim 1, characterized in that: The additional wheel deviation energy consumption is integrated with the remaining mileage management system of the new energy vehicle to obtain the remaining mileage prediction data of the new energy vehicle under abnormal wheel deviation, specifically including: extracting current remaining mileage data from the remaining mileage management system; Calculating the ratio of the additional wheel deviation energy consumption to the current remaining mileage energy consumption under the current remaining mileage data to obtain an abnormal energy consumption ratio coefficient; According to the abnormal energy consumption proportional coefficient, data prediction processing is performed on the current remaining mileage data to determine the remaining mileage prediction data of the new energy vehicle under the abnormal wheel deviation condition.

10. A wheel resistance energy consumption monitoring device based on new energy vehicles, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, so that the at least one processor can execute the wheel pulley resistance energy consumption monitoring method based on new energy vehicles according to any one of claims 1-9.

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