A vehicle bridge system and a vehicle operation control method

Abstract

This application provides a vehicle bridge system and a vehicle operation control method, relating to the field of electric engineering machinery. The system includes: a front axle comprising a swing-connected support structure and a connecting structure, with first mounting positions at both ends of the support structure along a first direction; and a rear axle with second mounting positions at both ends along the first direction. The method includes: determining the load data of the left and right wheels of the front axle based on driving state data and a preset state prediction equation, thereby determining the structural off-center load state of the vehicle; further determining the reference wheel and non-reference wheel among the front and rear wheels based on the driving state data; further determining the slippage state of each front wheel and each rear wheel; and determining the vehicle control strategy based on the structural off-center load state and the slippage state. This application solves the technical problem in the prior art where traditional bridge systems have poor adaptability to complex road surfaces and current control technologies have poor dynamic response capabilities, resulting in low vehicle operation control efficiency.

Description

Technical Field

[0001] This application relates to the field of electric engineering machinery, and more particularly to a vehicle bridge system and a method for controlling vehicle operation. Background Technology

[0002] In complex working environments such as tunnel and mine construction, electric construction machinery often needs to perform low-speed, high-precision driving operations in rugged and narrow terrain.

[0003] Traditional bridge structures typically employ suspension systems with full roll stiffness to provide sufficient support and stability. Existing vehicle control technologies mainly include: independently detecting wheel slippage through fixed torque distribution rules, triggering control strategies through traction control systems (TCS), or using pre-control models derived from cross-axle data.

[0004] However, in existing technologies, traditional bridges have poor adaptability to complex road surfaces, and current control technologies have poor dynamic response capabilities, resulting in low vehicle operation control efficiency. Summary of the Invention

[0005] This application provides a vehicle bridge system and a vehicle operation control method to solve the problem that traditional bridges have poor adaptability to complex road surfaces and current control technologies have poor dynamic response capabilities, resulting in low vehicle operation control efficiency.

[0006] In a first aspect, this application provides a vehicle bridge system, comprising:

[0007] The front axle includes a swing-connected support structure and a connecting structure. The support structure has first mounting positions at both ends along a first direction. The first mounting positions are used to mount the front wheel. The connecting structure is used to connect to the vehicle frame. The support structure can swing relative to the connecting structure in a first plane. The first plane is parallel to the first direction.

[0008] The rear axle has second mounting positions at both ends along the first direction. The second mounting positions are used to mount the rear wheels. The rear axle is fixedly connected to the vehicle frame.

[0009] In one possible design, the support structure and the connecting structure are rotatably connected, and the central axis of rotation of the support structure relative to the connecting structure is perpendicular to the first plane.

[0010] In one possible design, the swing angle of the support structure relative to the connecting structure is less than or equal to 6°.

[0011] Secondly, this application provides a method for controlling the operation of a vehicle, the vehicle including the bridge system as described in the first aspect of the invention, the method comprising:

[0012] Obtain vehicle driving status data;

[0013] Based on driving status data and preset state prediction equations, determine the load data of the left and right front axle wheels of the vehicle;

[0014] Based on the load data of the left and right front axle wheels, determine the structural off-center load condition of the vehicle;

[0015] Based on driving status data, the reference wheel and non-reference wheels are determined among the front and rear wheels;

[0016] Based on the driving status data of the reference wheel and the driving status data of the non-reference wheel, determine the slippage state of each front wheel and each rear wheel;

[0017] Based on the structural off-center load and slippage conditions, the vehicle control strategy is determined; the control strategy includes a warning strategy and an electric drive torque distribution strategy.

[0018] In one possible design, the vehicle control strategy is determined based on the structural off-center loading state and the slippage state, including:

[0019] Determine the vehicle's early warning strategy based on the structural off-center load condition;

[0020] The electric drive torque distribution strategy for the vehicle is determined based on the structural off-center load and slippage conditions.

[0021] In one possible design, structural off-center loading conditions include the presence of structural off-center loading risk and the presence of temporary load fluctuations;

[0022] Accordingly, based on the structural off-center loading condition, a vehicle early warning strategy is determined, including:

[0023] If the structural off-center loading condition indicates a risk of structural off-center loading, then a front axle load imbalance alarm will be triggered.

[0024] If the structural off-center loading condition is characterized by temporary load fluctuations, the front axle load imbalance alarm will not be triggered.

[0025] In one possible design, the structural off-center loading state of the vehicle is determined based on the load data of the left and right front axle wheels, including:

[0026] Determine the load deviation values ​​of the left and right wheels of the front axle based on the load data of the left and right wheels of the front axle;

[0027] If the load deviation between the left and right wheels of the front axle is greater than the preset deviation threshold, then the structural off-center loading state is determined to be a structural off-center loading risk.

[0028] If the load deviation between the left and right wheels of the front axle is not greater than the preset deviation threshold, then it is determined that there is a temporary load fluctuation.

[0029] In one possible design, driving status data includes front and rear wheel speeds, front axle sway angle, vehicle acceleration, vehicle angular velocity, and tire vertical load observations.

[0030] Accordingly, based on the driving state data and the preset state prediction equation, the load data of the left and right front axle wheels of the vehicle are determined, including:

[0031] Obtain the preset state prediction equation; wherein the preset state prediction equation is determined based on the vehicle's dynamic state space model and the Kalman filter dynamic estimation algorithm;

[0032] The front and rear wheel speeds, front axle sway angle, vehicle acceleration, and vehicle angular velocity are used as state inputs. Based on the preset state prediction equation, the predicted load data of the left and right front axle wheels of the vehicle are output.

[0033] Based on the observed vertical load values ​​of the tires, the predicted load data of the left and right front axles are corrected to obtain the load data of the left and right front axles of the vehicle.

[0034] In one possible design, the driving status data also includes the front axle sway angle;

[0035] Accordingly, based on the driving state data of the reference wheel and the driving state data of the non-reference wheels, the slippage state of each front wheel and each rear wheel is determined, including:

[0036] Based on the front axle sway angle, construct the terrain curvature factor;

[0037] Based on the terrain curvature factor, the driving status data of the reference wheel, and the driving status data of the non-reference wheels, determine the wheel slip risk value for each front wheel and each rear wheel;

[0038] Based on the wheel slip risk value, determine the slip state of the front wheel and each rear wheel; the slip state includes symmetrical slip and asymmetrical slip.

[0039] In one possible design, the vehicle control strategy is determined based on the structural off-center loading state and the slippage state, including:

[0040] If the slippage is symmetrical, the electric drive torque distribution strategy is determined based on the structural off-center load and wheel slippage risk value.

[0041] If the slippage is asymmetrical, a preset terrain compensation distribution strategy is adopted, and the electric drive torque distribution strategy is determined based on the structural off-center load and wheel slippage risk value.

[0042] In one possible design, the electric drive torque distribution strategy is determined based on the structural off-center loading condition and wheel slippage risk value, including:

[0043] Obtain the preset vertical load distribution weights, preset penalty compensation torque coupling mechanisms, and preset safety boundary constraints;

[0044] Based on the preset vertical load distribution weights, preset penalty compensation torque coupling mechanisms, preset safety boundary constraints, structural off-center load conditions, and wheel slippage risk values, the electric drive torque distribution values ​​for each front wheel and each rear wheel are calculated.

[0045] In one possible design, a preset terrain compensation distribution strategy is adopted. Based on the structural off-center loading state and wheel slippage risk value, the electric drive torque distribution strategy is determined, including:

[0046] A preset terrain compensation allocation strategy is adopted to establish a target wheel speed control loop and a torque amplitude limiting loop;

[0047] Based on the target wheel speed control loop, torque amplitude limiting loop, structural off-center load condition, and wheel slippage risk value, calculate the electric drive torque distribution value for each front wheel and each rear wheel.

[0048] Thirdly, this application provides a vehicle operation control device, wherein the vehicle includes a bridge system as described in the first aspect of the invention, and the device includes:

[0049] The acquisition module is used to acquire vehicle driving status data;

[0050] The first determining module is used to determine the load data of the left and right front axles of the vehicle based on the driving status data and the preset state prediction equation;

[0051] The second determining module is used to determine the structural off-center load state of the vehicle based on the load data of the left and right wheels of the front axle;

[0052] The third determination module is used to determine the reference wheel and non-reference wheel among the front and rear wheels based on the driving status data;

[0053] The fourth determination module is used to determine the slippage state of each front wheel and each rear wheel based on the driving state data of the reference wheel and the driving state data of the non-reference wheel.

[0054] The fifth determination module is used to determine the vehicle's control strategy based on the structural off-center load state and slippage state; the control strategy includes a warning strategy and an electric drive torque distribution strategy.

[0055] Fourthly, this application provides a vehicle operation control device, including: a memory and a processor;

[0056] The memory stores instructions that the computer executes;

[0057] The processor executes computer execution instructions stored in memory, causing the processor to perform the vehicle operation control method as described in the second aspect of the invention.

[0058] Fifthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the vehicle operation control method as described in the second aspect of the invention.

[0059] In a sixth aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements the vehicle operation control method described in the second aspect of the invention.

[0060] This application provides a vehicle bridge system and a vehicle operation control method. The vehicle bridge system includes: a front axle, comprising a swing-connected support structure and a connecting structure, wherein the support structure has first mounting positions at both ends along a first direction for mounting the front wheels, and the connecting structure is used to connect to the vehicle frame. The support structure can swing relative to the connecting structure in a first plane, the first plane being parallel to the first direction; and a rear axle, having second mounting positions at both ends along the first direction for mounting the rear wheels, and the rear axle being fixedly connected to the vehicle frame. The vehicle operation control method, wherein the vehicle includes the bridge system, includes: acquiring vehicle driving state data; determining the load data of the left and right front axle wheels based on the driving state data and a preset state prediction equation; determining the structural off-center load state of the vehicle based on the load data of the left and right front axle wheels; determining reference wheels and non-reference wheels among the front and rear wheels based on the driving state data; determining the slippage state of each front wheel and each rear wheel based on the driving state data of the reference wheels and the non-reference wheels; and determining the vehicle control strategy based on the structural off-center load state and the slippage state. Compared to existing technologies, traditional bridge structures have poor adaptability to complex road surfaces, and current control technologies still have shortcomings in real-time response, independent control, and dynamic adaptation, resulting in low vehicle operation control efficiency. This application achieves a breakthrough in configuration by using an asymmetrical bridge structure with a front axle (hydraulic limit pivot hinge, ±6° vertical swing) and a rear axle (leaf spring rigid connection), resolving the adaptability contradiction of traditional structures in rugged terrain. Based on a multi-sensor fusion system combined with a Kalman filter algorithm, wheel load and adhesion coefficient can be estimated in real time, and the reference vehicle speed can be independently calculated through the rear wheel speed; adaptive torque distribution is performed based on dynamic perception data to achieve optimized response of the front axle and precise control of the rear axle, and a unique differential pre-distribution strategy is created for steering conditions; through dual closed-loop control of target wheel speed constraint and torque amplitude constraint, as well as a yaw rate error feedback mechanism, the passability and operational stability of complex terrain are ensured simultaneously, thereby improving the vehicle's operation control efficiency. Attached Figure Description

[0061] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0062] Figure 1 A schematic diagram of the system architecture of a vehicle bridge system provided in an embodiment of this application;

[0063] Figure 2 A schematic diagram of the front axle structure of a vehicle bridge system provided in this application embodiment;

[0064] Figure 3 A schematic diagram of the rear axle structure of a vehicle bridge system provided in this application embodiment;

[0065] Figure 4 A schematic flowchart of a vehicle operation control method provided in this application embodiment. Figure 1 ;

[0066] Figure 5 A schematic flowchart of a vehicle operation control method provided in this application embodiment. Figure 2 ;

[0067] Figure 6 A schematic flowchart of a vehicle operation control method provided in this application embodiment. Figure 3 ;

[0068] Figure 7 A schematic diagram of the structure of the vehicle operation control device provided in the embodiments of this application;

[0069] Figure 8 This is a schematic diagram of the structure of a vehicle operation control device provided in an embodiment of this application.

[0070] Figure label:

[0071] 10-Cable tray system;

[0072] 11-Front axle; 12-Rear axle;

[0073] 111 - Supporting structure;

[0074] 21-Connecting structure; 22-Swing bridge web; 23-First lower support plate rib; 24-First lower support base plate; 25-First steering connecting rib plate; 26-First upper ear plate bending piece; 27-First lower ear plate bending piece; 28-First steering ear plate; 29-First mounting position;

[0075] 301-Web plate; 302-Rigid bridge top plate; 303-Second lower support plate rib; 304-Welded pin; 305-Second lower support base plate; 306-Top plate; 307-Second steering connecting rib plate; 308-Second upper ear plate bending piece; 309-Second lower ear plate bending piece; 310-Second steering ear plate; 311-Second mounting position; 312-Connecting plate; 313-Rib plate; 314-Hydraulic rod;

[0076] 71 - Acquisition Module; 72 - First Determination Module; 73 - Second Determination Module; 74 - Third Determination Module; 75 - Fourth Determination Module; 76 - Fifth Determination Module;

[0077] 80 - Vehicle operation control equipment; 81 - Processor; 82 - Memory; 83 - Communication components; 84 - Bus. Detailed Implementation

[0078] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0079] In the embodiments of this application, the terms "first" and "second" are used to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, nor do they necessarily imply difference. It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner. In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more.

[0080] It should be noted that the phrase "at...time" in the embodiments of this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; the embodiments of this application do not specifically limit this. Furthermore, the vehicle operation control method provided in the embodiments of this application is merely an example, and vehicle operation control methods may include more or fewer elements.

[0081] To facilitate a clear description of the technical solutions in the embodiments of this application, some terms and technologies involved in the embodiments of this application will be briefly introduced below:

[0082] Traction Control System (TCS): An active safety system for automobiles, primarily used to optimize the distribution of traction force to prevent the drive wheels from spinning or slipping during start-up, acceleration, or driving on slippery surfaces, thereby improving driving stability and handling safety.

[0083] In complex working environments such as tunnel and mine construction, electric construction machinery often needs to perform low-speed, high-precision driving operations in rugged and narrow terrain.

[0084] Currently, traditional bridge structures typically employ suspension systems with full roll stiffness to provide sufficient support and stability. However, in working conditions such as tunnels and mines where there are uneven ground, significant elevation changes, and limited space, a full roll structure can lead to insufficient vehicle maneuverability, an inability to adapt to terrains with large local height differences, wheels that cannot fully adapt to changes in ground height, and a risk of tires being suspended in the air. This cannot guarantee the stability of the vehicle during construction on rough and uneven road surfaces.

[0085] However, existing vehicle control technologies have several key shortcomings:

[0086] On the one hand, some solutions adopt a fixed torque distribution rule, which can independently detect wheel slippage, but does not dynamically assess the adhesion potential of non-slipping wheels, resulting in insufficient power utilization on the high-adhesion side under split road conditions.

[0087] On the one hand, some control strategies that rely on TCS system triggering have a double delay risk: they are limited by the TCS response speed, resulting in intervention lag, and the distribution accuracy is affected by the target torque calculation deviation.

[0088] On the other hand, the pre-control model derived from cross-axle data fails when the road surface of the front and rear axles is inconsistent. For example, low-adhesion front wheel data may incorrectly limit the torque of the rear wheels, or high-adhesion front wheel data may lead to insufficient pre-control of the rear wheels.

[0089] To address the aforementioned issues, the inventors, during their research on the low efficiency of vehicle operation control, discovered that existing technologies suffer from poor adaptability to complex road surfaces and inadequate dynamic response capabilities in traditional bridge systems. Therefore, the inventors considered an asymmetrical bridge structure with a front axle (hydraulic limit pivot hinge, ±6° vertical swing) and a rear axle (leaf spring rigid connection), achieving a breakthrough in "flexible front, rigid rear" configuration and resolving the inherent limitations of traditional structures in rugged terrain. Based on a multi-sensor fusion system combined with a Kalman filter algorithm, wheel load and adhesion coefficient can be estimated in real time, and the reference vehicle speed can be independently calculated using the rear wheel speed. Adaptive torque distribution is executed based on dynamic perception data, achieving optimized response of the front axle and precise control of the rear axle, and a unique differential pre-distribution strategy is implemented for steering conditions. Through dual closed-loop control with target wheel speed constraints and torque amplitude constraints, as well as a yaw rate error feedback mechanism, both passability and operational stability in complex terrain are simultaneously ensured. Based on this, this application provides a vehicle bridge system and a vehicle operation control method, applicable to the field of electric engineering machinery, aiming to solve the problem of low operation control efficiency in existing vehicles.

[0090] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0091] Figure 1 This is a schematic diagram of the system architecture of a vehicle bridge system provided in an embodiment of this application. The vehicle bridge system is a mechanical device. Figure 1 In the above-mentioned architecture, the cable tray system 10 includes a front axle 11 and a rear axle 12.

[0092] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the bridge system architecture of a vehicle. In other feasible embodiments of this application, the above architecture may include more or fewer components than illustrated, or combine some components, or divide some components, or arrange different components, which can be determined according to the actual application scenario and is not limited here.

[0093] The front axle 11 includes a swing-type support structure 111 and a connecting structure 21.

[0094] Specifically, the support structure 111 is used to support the front wheels of the vehicle.

[0095] Specifically, the connection structure 21 is used to connect to the vehicle frame.

[0096] The support structure 111 and the connecting structure 21 are rotatably connected, and the central axis of rotation of the support structure 111 relative to the connecting structure 21 is perpendicular to the first plane.

[0097] Optionally, the connecting structure 21 and the supporting structure 111 are welded together to form a box-shaped structure, which disperses the impact of ton-level loads and improves torsional stiffness.

[0098] The support structure 111 can swing relative to the connecting structure 21 in a first plane.

[0099] The first plane is parallel to the first direction.

[0100] Wherein, the swing angle of the support structure 111 relative to the connecting structure 21 is less than or equal to .

[0101] Optionally, the connecting structure 21 is directly hinged to the frame via a pivot connector with a limiting structure, forming... Vertical swing degree of freedom.

[0102] Optional, Figure 2 This is a schematic diagram of the front axle structure of a vehicle bridge system provided in an embodiment of this application.

[0103] like Figure 2 As shown, the connecting structure 21 is a swing bridge seat.

[0104] Specifically, the swing axle mount serves as the connection base between the front axle and the frame, allowing... It swings vertically to adapt to the terrain.

[0105] like Figure 2 As shown, the support structure 111 has first mounting positions 29 at both ends along the first direction, and the first mounting positions 29 are used to mount the front wheel.

[0106] Specifically, the first mounting position 29 is the first connecting plate, used to transmit bidirectional torque.

[0107] like Figure 2 As shown, the support structure 111 also includes a swing bridge web 22, a first lower support plate 23, a first lower support base plate 24, a first steering connecting rib 25, a first upper ear plate bending piece 26, a first lower ear plate bending piece 27, and a first steering ear plate 28.

[0108] Specifically, the swing bridge seat and the swing bridge web 22 are welded into a box-shaped structure to disperse the impact of ton-level loads and improve torsional stiffness.

[0109] Specifically, the swing bridge web 22 is used to enhance the impact resistance of the swing bridge seat, with a load capacity of 30 tons.

[0110] Specifically, the first lower support plate rib 23 is used to form a box-shaped structure with the first lower support base plate 24 to improve torsional stiffness.

[0111] Specifically, the first steering connecting stiffener 25 is used to transmit steering torque.

[0112] Specifically, the first upper ear plate bending piece 26 and the first lower ear plate bending piece 27 achieve the hinge connection between the steering mechanism and the bridge frame through the double ear plate structure.

[0113] For example, during operation, the first upper ear plate bending member 26 and the first lower ear plate bending member 27 will be subjected to shearing forces generated by frequent turning.

[0114] Specifically, the first steering lug 28 serves as the force transmission center, directly connecting the steering mechanism and the wheel.

[0115] Specifically, the first steering ear plate 28 is bolted to the first steering connecting stiffener 25, the first upper ear plate bending member 26 and the first lower ear plate bending member 27 to form a triangular stable structure.

[0116] Specifically, angular constraints are achieved through the first lower support plate rib 23, the first upper ear plate bending piece 26, and the first lower ear plate bending piece 27.

[0117] Optional, Figure 3 This is a schematic diagram of the rear axle structure of a vehicle bridge system provided in an embodiment of this application.

[0118] like Figure 3 As shown, the rear axle 12 has second mounting positions 311 at both ends along the first direction.

[0119] The second mounting position 311 is used to mount the rear wheel, and the rear axle 12 is fixedly connected to the vehicle frame.

[0120] Specifically, the second mounting position 311 is the second connecting plate.

[0121] like Figure 3 As shown, the rear axle 12 also includes: a web plate 301, a rigid bridge top plate 302, a second lower support plate rib 303, a welded pin 304, a second lower support bottom plate 305, a top plate 306, a second steering connecting rib plate 307, a second upper ear plate bending piece 308, a second lower ear plate bending piece 309, a second steering ear plate 310, a connecting plate 312, a rib plate 313, and a hydraulic rod 314.

[0122] Specifically, the web 301 serves as the main load-bearing frame of the rear axle 12, bearing vertical / horizontal composite loads. Through the box-type structure, the impact force is evenly transmitted to the entire axle shell to prevent local deformation.

[0123] Specifically, the rigid axle top plate 302 serves as a reinforcing cover plate on the top of the bridge frame, enhancing torsional stiffness and working in conjunction with the leaf spring to limit lateral displacement of the axle housing, ensuring stable rear wheel grip.

[0124] Specifically, the second lower support plate 303 and the second lower support base plate 305 constitute the double-insurance support at the bottom of the rear axle 12. When climbing slopes, the plate ribs distribute the axial load to the base plate, preventing the bridge frame from tilting forward due to gravity; when passing over uneven road surfaces, the base plate bears the impact of the wheels, protecting the main body of the axle shell.

[0125] Specifically, the welded pin 304 is used to realize the movable connection between the axle housing and the suspension system. On continuously bumpy roads, the welded pin 304 allows the leaf spring assembly to swing up and down, absorbing vertical impact energy while transmitting driving force to the wheels.

[0126] Specifically, the top plate 306, together with the web plate 301 and the second lower support plate rib 303, forms the rear axle frame structure, which together bears the weight of the vehicle body, road impact and steering torque.

[0127] Optionally, the top plate 306 forms a continuous weld with the web plate 301 and the rigid bridge top plate 302 to ensure that the force transmission is uninterrupted.

[0128] Specifically, the second steering connecting rib 307 serves as the core channel for transmitting steering force in the rear axle 12, precisely transmitting steering wheel commands.

[0129] Specifically, the second upper ear plate bending component 308 and the second lower ear plate bending component 309 reinforce the connection node between the rear axle 12 and the vehicle body, and disperse the stress at the connection point through the arc structure to prevent the bolts from loosening or breaking.

[0130] Specifically, the second steering ear plate 310 is welded between the rigid bridge top plate 302 and the second lower support plate rib 303 to form a box-shaped anti-torsion structure.

[0131] Specifically, the second steering lug 310 serves as a structural reinforcement component for the rear axle 12. Although it does not directly participate in steering, it enhances the deformation resistance of the bridge frame through rigid connection. Under heavy-load conditions, it prevents the rear axle from twisting due to longitudinal / lateral impact forces.

[0132] Specifically, the second mounting position 311 and the connecting plate 312 form a dual-function node for power transmission and structural fixation of the rear axle 12. The second mounting position 311 serves as a drive shaft interface, transmitting torque during motor drive; the connecting plate 312 fixes the axle housing and subframe with an array of bolts to resist torsional forces during driving.

[0133] Specifically, stiffener 313 serves as a local stress dispersion reinforcement component. It is added at the weld of the cable tray to improve fatigue life and adapt to high-frequency vibration conditions.

[0134] Specifically, the hydraulic rod 314, as a hydraulic shock absorber and energy absorption device, can compress and absorb vertical impacts when passing through potholes, and work with the leaf spring to achieve secondary shock absorption, thereby improving ride comfort.

[0135] It should be noted that by eliminating the lateral stabilizer bar and traditional suspension structure, the front axle can actively conform to uneven ground, thereby effectively improving tire contact performance, reducing the risk of suspension, and improving the vehicle's passability in rough terrain.

[0136] It should be noted that the rear axle is rigidly connected to the vehicle body via a leaf spring assembly and is fixedly installed at the rear of the frame, without any degree of freedom of movement. By giving the rear axle high rigidity and stability, it is suitable for supporting the body of electric construction machinery and stabilizing construction operation platforms.

[0137] It should be noted that the overall layout of the vehicle's axle breaks away from the traditional four-wheel symmetrical independent suspension system, innovatively adopting a " The combination of these two approaches effectively integrates the dual performance requirements of terrain adaptability and structural stability.

[0138] This application provides a vehicle bridge system, comprising: a front axle, including a swing-connected support structure and a connecting structure; the support structure has first mounting positions at both ends along a first direction for mounting the front wheels; the connecting structure is used to connect to the vehicle frame; the support structure can swing relative to the connecting structure in a first plane, the first plane being parallel to the first direction; and a rear axle, having second mounting positions at both ends along the first direction for mounting the rear wheels; the rear axle is fixedly connected to the vehicle frame. Compared to existing technologies, traditional bridges have poor adaptability to complex road surfaces, and current control technologies still have shortcomings in real-time response, independent control, and dynamic adaptation, resulting in low vehicle operation control efficiency. This application addresses this issue by using a front axle (hydraulic limit pivot hinge)... The asymmetrical bridge structure of the vertical swing axle and the rear axle (rigid connection with leaf springs) achieves a breakthrough in the "flexible front and rigid rear" configuration, resolving the inherent limitations of traditional structures in rugged terrain. This, in turn, improves the vehicle's operational control efficiency.

[0139] The technical solution of this application will be described in detail below with reference to specific embodiments:

[0140] Figure 4 A schematic flowchart of a vehicle operation control method provided in this application embodiment. Figure 1 ,like Figure 4 As shown, the vehicle includes Figure 1 , Figure 2 and Figure 3 The cable tray system in the example includes the following methods:

[0141] S401. Obtain vehicle driving status data.

[0142] In this embodiment, the vehicle's driving status data is acquired, that is, the vehicle's driving status data is collected: the front and rear wheel speeds are acquired; the vehicle body acceleration and angular velocity are detected; the steering wheel angle and front axle sway angle are acquired; and the wheel end torque and tire vertical load are collected.

[0143] The target vehicle is an electric construction machine equipped with various sensors. Wheel speed sensors are installed at all four wheels to detect the rotational speed of each wheel, thereby obtaining the wheel speed of the front and rear wheels.

[0144] The front axle pivot joint is equipped with a swing angle sensor to measure the axle swing angle and thus obtain the front axle swing angle.

[0145] Load sensors are installed on the front axle suspension hydraulic cylinder and the rear axle leaf spring assembly to monitor the vertical load on the front and rear axles, thereby obtaining the vertical load on the tires.

[0146] The vehicle frame is equipped with an Inertial Measurement Unit (IMU) in the middle (center of gravity) to sense changes in vehicle attitude such as acceleration, angular velocity, and pitch, thereby obtaining the vehicle's acceleration and angular velocity.

[0147] S402. Determine the load data of the left and right front axles of the vehicle based on the driving status data and the preset state prediction equation.

[0148] S403. Determine the structural off-center load status of the vehicle based on the load data of the left and right wheels of the front axle.

[0149] The driving status data includes front and rear wheel speeds, front axle sway angle, vehicle acceleration, vehicle angular velocity, and tire vertical load observations.

[0150] Specifically, the load deviation values ​​of the left and right wheels of the front axle are determined based on the load data of the left and right wheels of the front axle.

[0151] Optionally, if the load deviation between the left and right wheels of the front axle is greater than a preset deviation threshold, the structural off-center loading state is determined to be a structural off-center loading risk.

[0152] Optionally, if the load deviation between the left and right wheels of the front axle is not greater than a preset deviation threshold, then it is determined that there is a temporary load fluctuation.

[0153] For example, when the estimated deviation of the load between the left and right front axles exceeds the preset deviation threshold, a front axle load imbalance alarm is triggered, and the front axle sway angle θ data is associated with it.

[0154] Furthermore, if both conditions are met... If a structural off-center load risk is identified, the structural off-center load state is determined to be in danger, and the torque redistribution system is activated.

[0155] Furthermore, if It was determined to be a temporary load fluctuation, and only the operating condition data was recorded.

[0156] S404. Based on the driving status data, determine the reference wheel and non-reference wheel among the front and rear wheels.

[0157] Specifically, taking advantage of the load stability of the rigid structure of the rear axle, the rear wheel with the largest safety margin and the rear wheel with a wheel position risk value lower than the set threshold are selected as the reference wheel.

[0158] The formula for calculating the safety margin is as follows:

[0159]

[0160] in, To estimate the adhesion coefficient; For real-time vertical load; This is the torque for the current wheel drive; The rolling radius; For safety margin.

[0161] Among them, through dynamic constraint torque in, ,reserve The upper limit of the adhesion margin ensures that the adhesion utilization rate of the reference wheel is low.

[0162] It should be noted that by calculating the deviation value based on the load data of the left and right wheels of the front axle and comparing it with the preset threshold, the structural off-center load risk and temporary load fluctuation can be accurately distinguished. This provides a reliable basis for vehicle condition monitoring, active safety warning and dynamic adjustment of control strategies, and effectively improves the vehicle driving stability and safety risk identification capabilities.

[0163] It should also be noted that after selecting the reference wheel, the basic wheel speed is diagnosed.

[0164] Specifically, when a certain wheel rotates at a certain speed continued seconds (Example: (Higher than the speed of the wheels on the opposite side of the same axle) The above, and the estimated load At that time, the wheel is marked as having low adhesion and a tendency to slip.

[0165] Optionally, if the wheel exhibiting the slippage tendency is the drive wheel, further compare the slip ratios. :

[0166]

[0167] in, For the tire radius, Source: Positioning module. If the above inequality is satisfied, slippage is confirmed.

[0168] Furthermore, when load estimation shows a front and rear axle load ratio And pitch angle At that time, a risk warning for a head tilting upwards was triggered.

[0169] It should also be noted that, for cases where the front axle has no roll stiffness, the vertical loads on the left and right wheels remain equal during steering. However, the inner wheel needs to bear a larger lateral force, resulting in a reduction in its longitudinal adhesion margin for driving. Based on the steering wheel angle and slippage status, when the steering wheel angle exceeds a threshold and there is no slippage, torque is pre-distributed, giving the outer wheel more torque to fully utilize its excess adhesion, while the torque on the inner wheel is reduced to avoid [further issues]. Exceeding the limit and slipping prematurely ensures that the inner wheel slips later than the outer wheel.

[0170] S405. Based on the driving status data of the reference wheel and the driving status data of the non-reference wheel, determine the slippage state of each front wheel and each rear wheel.

[0171] The driving status data also includes the front axle sway angle.

[0172] Specifically, the terrain curvature factor is constructed based on the front axle sway angle.

[0173] Specifically, based on the terrain curvature factor, the driving status data of the reference wheel, and the driving status data of the non-reference wheels, the wheel slip risk value of each front wheel and each rear wheel is determined.

[0174] Specifically, based on the wheel slip risk value, the slip state of the front wheel and each rear wheel is determined; the slip state includes symmetrical slip and asymmetrical slip.

[0175] In this embodiment, the skidding state of the target vehicle is determined based on the speed and terrain load verification.

[0176] For example, after acquiring the rotational speed of each wheel, it can be sent to the vehicle control system. The control system can compare the rotational speeds of each wheel, determine the speed of the slowest wheel, and check if the difference between the rotational speeds of the remaining wheels and the slowest wheel's speed exceeds a preset threshold and lasts for a duration exceeding a preset time. For example, if the difference exceeds 30% of the slowest wheel's speed and lasts for 0.5 seconds, then that wheel can be considered to be slipping. At this point, terrain load coupling verification is performed.

[0177] Specifically, construct the terrain curvature factor. :

[0178]

[0179] in, This refers to the front axle sway angle; The pitch angle; It is the lateral angle.

[0180] Furthermore, the risk value of wheel slippage is calculated based on the sigmoid function. :

[0181]

[0182] Among them, when and Or the difference between left and right risk At that time, it was confirmed to be asymmetrical slippage.

[0183] It should be noted that by constructing a terrain curvature factor based on the front axle sway angle and combining the driving state data of the reference wheel and non-reference wheel to quantify the wheel slip risk value, the accurate identification and classification of symmetrical and asymmetrical slip states are achieved. This provides key criteria for the dynamic anti-skid control, driving trajectory optimization and active safety intervention of vehicles in complex terrain, and effectively improves the vehicle's passability and stability control on unstructured roads.

[0184] S406. Determine the vehicle control strategy based on the structural off-center load state and slippage state.

[0185] The control strategies include early warning strategies and electric drive torque distribution strategies.

[0186] It should be noted that the modular algorithm is adapted to extreme working conditions such as mines / tunnels, supports the integration of on-board electronic control units (ECUs) and the retrofitting of existing vehicles, and expands application scenarios.

[0187] This embodiment provides a vehicle operation control method. The vehicle includes a bridge system. The method includes: acquiring vehicle driving state data; determining the load data of the left and right front axle wheels based on the driving state data and a preset state prediction equation; determining the structural off-center load state of the vehicle based on the load data of the left and right front axle wheels; identifying reference wheels and non-reference wheels among the front and rear wheels based on the driving state data; determining the slippage state of each front wheel and each rear wheel based on the driving state data of the reference wheels and the non-reference wheels; and determining the vehicle control strategy based on the structural off-center load state and the slippage state. Compared to existing technologies, traditional bridge systems have poor adaptability to complex road surfaces, and current control technologies still have shortcomings in real-time response, independent control, and dynamic adaptation, resulting in low vehicle operation control efficiency. This application, based on a multi-sensor fusion system combined with a Kalman filter algorithm, can estimate wheel load and adhesion coefficient in real time, and independently calculate the reference vehicle speed through the rear wheel speed; it performs adaptive torque distribution based on dynamic perception data to achieve optimized response of the front axle and precise control of the rear axle, and has created a unique differential pre-distribution strategy for steering conditions; through dual closed-loop control of target wheel speed constraint and torque amplitude constraint, as well as a yaw rate error feedback mechanism, it simultaneously ensures the passability and operational stability of complex terrain, thereby improving the vehicle's operation control efficiency.

[0188] Figure 5 A schematic flowchart of a vehicle operation control method provided in this application embodiment. Figure 2 ,like Figure 5 As shown, the driving status data includes front and rear wheel speeds, front axle sway angle, vehicle acceleration, vehicle angular velocity, and tire vertical load observations; therefore, step S402 specifically includes:

[0189] S501. Obtain the preset state prediction equation.

[0190] The preset state prediction equation is determined based on the vehicle's dynamic state-space model and the Kalman filter dynamic estimation algorithm.

[0191] Specifically, a dynamic state-space model of the vehicle is designed based on a Kalman filter-based dynamic estimation algorithm, thereby obtaining the state prediction equation:

[0192]

[0193] in, The predicted state value at time k (based on (Time information); Here is the state transition matrix. for Optimal state estimation at time 1; To control the input matrix; For external control input.

[0194] Furthermore, based on the state prediction equation, the covariance prediction equation is obtained:

[0195]

[0196] in, The error covariance matrix for the predicted state; for The error covariance matrix at time t; Let be the process noise covariance matrix.

[0197] It should be noted that the front axle structure can cause load offset and wheel speed differences. By using Kalman filtering to estimate the vertical load of each wheel, risks such as uneven front axle load, slippage tendency, or attitude instability can be identified.

[0198] It should be noted that by using Kalman filtering to estimate the load and adhesion coefficient of each wheel in real time and dynamically distributing torque to avoid the risk of instability caused by oversaturation of adhesion on a single wheel, a breakthrough in intelligent control has been achieved.

[0199] S502: Taking the front and rear wheel speeds, front axle sway angle, vehicle acceleration, and vehicle angular velocity as state inputs, and outputting the predicted load data of the left and right front axle wheels of the vehicle according to the preset state prediction equation.

[0200] Specifically, the front and rear wheel speeds are obtained in real time through wheel speed sensors; the front axle sway angle is obtained in real time through front axle sway angle sensors; and the vehicle body acceleration and angular velocity are obtained in real time through the output data of the vehicle body attitude sensor.

[0201] S503. Based on the observed vertical load values ​​of the tires, correct the predicted load data of the left and right front axle wheels to obtain the load data of the left and right front axle wheels of the vehicle.

[0202] In this embodiment, during the update phase, the predicted load data of the left and right front axle wheels are corrected based on the observed vertical load values ​​of the tires to obtain a more accurate state estimate, namely the load data of the left and right front axle wheels of the vehicle.

[0203] In this embodiment, a state prediction equation is constructed based on a vehicle dynamics state space model and a Kalman filter dynamic estimation algorithm. This equation integrates multi-dimensional state inputs such as front and rear wheel speeds, front axle sway angle, vehicle acceleration, and angular velocity to predict loads. Furthermore, the predicted data is dynamically corrected using tire vertical load observations. This achieves high-precision real-time acquisition and improved reliability of the loads on the left and right front axles of the vehicle. It provides key data support for vehicle dynamics control, driving stability optimization, and active safety system design, thereby improving the vehicle's operational control efficiency.

[0204] Figure 6 A schematic flowchart of a vehicle operation control method provided in this application embodiment.Figure 3 ,like Figure 6 As shown, a structural off-center load condition includes the presence of structural off-center load risk and the presence of temporary load fluctuations; therefore, the specific implementation steps of S406 above include:

[0205] S601. If the structural off-center loading condition indicates a risk of structural off-center loading, then a front axle load imbalance alarm will be triggered.

[0206] S602. If the structural off-center load condition is characterized by temporary load fluctuations, the front axle load imbalance alarm will not be triggered.

[0207] S603. Determine the electric drive torque distribution strategy for the vehicle based on the structural off-center load and slippage conditions.

[0208] It should be noted that the specific implementation steps of S406 above also include:

[0209] Specifically, if the slippage is symmetrical, the electric drive torque distribution strategy is determined based on the structural off-center load and the wheel slippage risk value.

[0210] Specifically, if the slippage is asymmetrical, a preset terrain compensation distribution strategy is adopted. Based on the structural off-center load and wheel slippage risk value, the electric drive torque distribution strategy is determined:

[0211] Optionally, preset vertical load distribution weights, preset penalty compensation torque coupling mechanisms, and preset safety boundary constraints can be obtained.

[0212] The preset vertical load allocation weights are dynamic. Ensure weight Adjust dynamically according to road conditions.

[0213] Among them, the preset penalty compensation torque coupling mechanism: the torque reduction of the slipping wheel is proportionally transferred to the high-adhesion wheel on the same axle or side.

[0214] Among them, safety boundary constraints:

[0215]

[0216] Optionally, the electric drive torque distribution value for each front wheel and each rear wheel can be calculated based on the preset vertical load distribution weight, preset penalty compensation torque coupling mechanism, preset safety boundary constraints, structural off-center load state and wheel slippage risk value.

[0217] For example, if asymmetrical slippage occurs, terrain-compensated torque distribution is implemented, using a terrain-compensated distribution strategy:

[0218]

[0219] Furthermore, add a dynamic transfer factor: And calculate the final torque transfer amount:

[0220]

[0221] For example, if symmetrical slippage occurs, the electric drive torque is allocated based on the identification results:

[0222] Optional, for handling single-wheel slippage: immediately reduce the drive torque of the slipping wheel; reduce the torque... Dynamically transfer to the wheel with the optimal coaxial adhesion conditions.

[0223] Optionally, for handling multi-wheel slippage: redistribute the total torque according to the real-time vertical load ratio of each wheel (vertical load distribution weight), and if the total slip ratio continues to deteriorate, gradually reduce the upper limit of the vehicle's drive torque.

[0224] Specifically, when multiple slippages occur, the total torque is distributed according to the real-time vertical load ratio:

[0225] More specifically, the load weighting factor is calculated to obtain the real-time vertical load value of each drive wheel. Then calculate the load percentage of a single wheel. :

[0226]

[0227] Furthermore, the total torque demand of the entire vehicle is weighted and distributed to each wheel:

[0228]

[0229] Among them, for the slipper: additional application .

[0230] For high-adhesion wheels: increase .

[0231] Furthermore, establish By comparing the actual wheel speed with the ideal wheel speed, dynamic adjustments are made to prevent slippage or insufficient traction. At the same time, the upper limit of adhesion is estimated to limit the torque to not exceed the wheel's tolerance range. Yaw rate error is introduced to stabilize and suppress slippage and maintain vehicle body stability.

[0232] Optionally, a preset terrain compensation allocation strategy can be adopted to establish a target wheel speed control loop and a torque amplitude limiting loop.

[0233] Specifically, based on the vehicle's steering angle, throttle opening, and vehicle speed, the ideal rotational speed of each wheel is calculated. Establish a target wheel speed control loop.

[0234] Specifically, by integrating vertical load and road surface temperature and humidity data, the maximum tire adhesion force can be estimated in real time. Calculate the safe torque threshold Establish a torque amplitude limiting loop.

[0235] It also includes dynamic anti-slip adjustment: when the actual wheel speed... Furthermore, after 0.5 seconds, slippage suppression is triggered, gradually reducing the wheel torque until the actual wheel speed is reached. return Within the range.

[0236] This also includes traction compensation, based on the actual wheel speed. At that time, traction enhancement is triggered, and the torque is increased proportionally to the load. To avoid exceeding the safe torque threshold. .

[0237] Optionally, the electric drive torque distribution value for each front wheel and each rear wheel can be calculated based on the target wheel speed control loop, torque amplitude limiting loop, structural off-center load state, and wheel slippage risk value.

[0238] It should be noted that yaw stability intervention has also been added.

[0239] Specifically, based on speed control, proportional-integral-derivative (PID) control of yaw rate is added.

[0240] Furthermore, the target yaw rate was calculated based on the Ackermann steering geometry model. :

[0241]

[0242] in, For steering angle, This represents the actual yaw rate.

[0243] Furthermore, an adaptive control gain is added based on the magnitude of the slip ratio, when the slip ratio... When calculating the slip ratio influence factor yaw rate control gain It becomes:

[0244]

[0245] In this way, an adaptive control gain is added based on the slip ratio, thereby preventing the controller from overreacting in high slip states.

[0246] It should be noted that by utilizing the non-rolling characteristics of the front axle to pre-distribute the torque difference between the inner and outer wheels, combined with yaw rate closed-loop control to suppress steering drift and improve trajectory accuracy, active steering control is achieved.

[0247] It should be noted that by simultaneously adjusting wheel speed tracking constraints and torque limiting, the driving efficiency and adhesion matching are optimized, thereby achieving coordinated suppression of slippage and instability.

[0248] In this embodiment, by distinguishing between structural off-center load risks and temporary load fluctuations triggering differentiated front axle load imbalance alarms, and combining symmetrical / asymmetrical slippage states, a multi-dimensional control strategy is employed, utilizing vertical load distribution weights, penalty compensation torque coupling mechanisms, and safety boundary constraints. This achieves precise dynamic distribution of electric drive torque and synergistic optimization of vehicle driving stability, effectively improving active safety control capabilities and powertrain efficiency under complex operating conditions. Consequently, the vehicle's operational control efficiency is enhanced.

[0249] Figure 7 This is a schematic diagram of the structure of the vehicle operation control device provided in the embodiments of this application, as shown below. Figure 7 As shown, the device includes: an acquisition module 71, a first determination module 72, a second determination module 73, a third determination module 74, a fourth determination module 75, and a fifth determination module 76.

[0250] The acquisition module 71 is used to acquire vehicle driving status data;

[0251] The first determining module 72 is used to determine the load data of the left and right front axles of the vehicle based on the driving state data and the preset state prediction equation;

[0252] The second determining module 73 is used to determine the structural off-center load state of the vehicle based on the load data of the left and right wheels of the front axle;

[0253] The third determining module 74 is used to determine the reference wheel and non-reference wheel among the front wheels and rear wheels based on the driving status data;

[0254] The fourth determining module 75 is used to determine the slippage state of each front wheel and each rear wheel based on the driving state data of the reference wheel and the driving state data of the non-reference wheel.

[0255] The fifth determining module 76 is used to determine the vehicle's control strategy based on the structural off-center load state and slippage state; wherein, the control strategy includes a warning strategy and an electric drive torque distribution strategy.

[0256] In one possible design, the vehicle control strategy is determined based on the structural off-center loading state and the slippage state, including:

[0257] The fifth determining module 76 is also used to determine the vehicle's early warning strategy based on the structural off-center load state;

[0258] The electric drive torque distribution strategy for the vehicle is determined based on the structural off-center load and slippage conditions.

[0259] In one possible design, structural off-center loading conditions include the presence of structural off-center loading risk and the presence of temporary load fluctuations;

[0260] Accordingly, based on the structural off-center loading condition, a vehicle early warning strategy is determined, including:

[0261] The fifth determination module 76 is also used to trigger a front axle load imbalance alarm if the structural off-center loading state indicates a risk of structural off-center loading.

[0262] If the structural off-center loading condition is characterized by temporary load fluctuations, the front axle load imbalance alarm will not be triggered.

[0263] In one possible design, the structural off-center loading state of the vehicle is determined based on the load data of the left and right front axle wheels, including:

[0264] The second determining module 73 is also used to determine the load deviation value of the left and right wheels of the front axle based on the load data of the left and right wheels of the front axle;

[0265] If the load deviation between the left and right wheels of the front axle is greater than the preset deviation threshold, then the structural off-center loading state is determined to be a structural off-center loading risk.

[0266] If the load deviation between the left and right wheels of the front axle is not greater than the preset deviation threshold, then it is determined that there is a temporary load fluctuation.

[0267] In one possible design, driving status data includes front and rear wheel speeds, front axle sway angle, vehicle acceleration, vehicle angular velocity, and tire vertical load observations.

[0268] Accordingly, based on the driving state data and the preset state prediction equation, the load data of the left and right front axle wheels of the vehicle are determined, including:

[0269] The first determining module 72 is also used to obtain a preset state prediction equation; wherein the preset state prediction equation is determined based on the vehicle's dynamic state space model and the dynamic estimation algorithm of Kalman filtering.

[0270] The front and rear wheel speeds, front axle sway angle, vehicle acceleration, and vehicle angular velocity are used as state inputs. Based on the preset state prediction equation, the predicted load data of the left and right front axle wheels of the vehicle are output.

[0271] Based on the observed vertical load values ​​of the tires, the predicted load data of the left and right front axles are corrected to obtain the load data of the left and right front axles of the vehicle.

[0272] In one possible design, the driving status data also includes the front axle sway angle;

[0273] Accordingly, based on the driving state data of the reference wheel and the driving state data of the non-reference wheels, the slippage state of each front wheel and each rear wheel is determined, including:

[0274] The fourth determining module 75 is also used to construct the terrain curvature factor based on the front axle sway angle;

[0275] Based on the terrain curvature factor, the driving status data of the reference wheel, and the driving status data of the non-reference wheels, determine the wheel slip risk value for each front wheel and each rear wheel;

[0276] Based on the wheel slip risk value, determine the slip state of the front wheel and each rear wheel; the slip state includes symmetrical slip and asymmetrical slip.

[0277] In one possible design, the vehicle control strategy is determined based on the structural off-center loading state and the slippage state, including:

[0278] The fifth determining module 76 is also used to determine the electric drive torque distribution strategy based on the structural off-center load state and wheel slip risk value if the slip state is symmetrical slip.

[0279] If the slippage is asymmetrical, a preset terrain compensation distribution strategy is adopted, and the electric drive torque distribution strategy is determined based on the structural off-center load and wheel slippage risk value.

[0280] In one possible design, the electric drive torque distribution strategy is determined based on the structural off-center loading condition and wheel slippage risk value, including:

[0281] The fifth determining module 76 is also used to obtain the preset vertical load distribution weight, the preset penalty compensation torque coupling mechanism, and the preset safety boundary constraints;

[0282] Based on the preset vertical load distribution weights, preset penalty compensation torque coupling mechanisms, preset safety boundary constraints, structural off-center load conditions, and wheel slippage risk values, the electric drive torque distribution values ​​for each front wheel and each rear wheel are calculated.

[0283] In one possible design, a preset terrain compensation distribution strategy is adopted. Based on the structural off-center loading state and wheel slippage risk value, the electric drive torque distribution strategy is determined, including:

[0284] The fifth determining module 76 is also used to establish a target wheel speed control loop and a torque amplitude limiting loop by adopting a preset terrain compensation allocation strategy;

[0285] Based on the target wheel speed control loop, torque amplitude limiting loop, structural off-center load condition, and wheel slippage risk value, calculate the electric drive torque distribution value for each front wheel and each rear wheel.

[0286] This embodiment provides a vehicle operation control device that can execute a vehicle operation control method described in the above embodiment. Its implementation principle and technical effects are similar, and will not be repeated here.

[0287] In a specific implementation of the aforementioned vehicle operation control method, each module can be implemented as a processor. The processor can execute computer execution instructions stored in the memory, thereby enabling the processor to execute the aforementioned vehicle operation control method.

[0288] Figure 8 This is a schematic diagram of the structure of a vehicle operation control device provided in an embodiment of this application. Figure 8 As shown, the vehicle operation control device 80 includes at least one processor 81 and a memory 82. The vehicle operation control device 80 also includes a communication component 83. The processor 81, memory 82, and communication component 83 are connected via a bus 84.

[0289] In the specific implementation process, at least one processor 81 executes computer execution instructions stored in memory 82, causing at least one processor 81 to execute a method in the field of electric engineering machinery as executed by the vehicle operation control device.

[0290] The specific implementation process of processor 81 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0291] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0292] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage.

[0293] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0294] The above description of the functions implemented by the vehicle operation control equipment and main control equipment illustrates the solutions provided by the embodiments of the present invention. It is understood that, in order to achieve the above functions, the vehicle operation control equipment or main control equipment includes hardware structures and / or software modules corresponding to the execution of each function. By combining the units and algorithm steps of the various examples described in the embodiments of the present invention, the embodiments of the present invention can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware 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 implementation should not be considered beyond the scope of the technical solutions of the embodiments of the present invention.

[0295] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method in the field of electric engineering machinery as described above.

[0296] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0297] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Alternatively, the readable storage medium can be an integral part of the processor. Both the processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the vehicle's operation control equipment or main control equipment.

[0298] This application also provides a computer program product, which includes: a computer program stored in a readable storage medium, at least one processor of a vehicle operation control device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to cause the vehicle operation control device to perform the scheme provided in any of the above embodiments.

[0299] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disk, or optical disk.

[0300] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. The above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit them. Although this application 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 or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for controlling the operation of a vehicle, characterized in that, The vehicle includes a bridge system, and the method includes: Acquire the vehicle's driving status data; the driving status data includes front and rear wheel speeds, front axle sway angle, vehicle acceleration, vehicle angular velocity, and tire vertical load observations; Obtain a preset state prediction equation; wherein the preset state prediction equation is determined based on the vehicle's dynamic state space model and the Kalman filter dynamic estimation algorithm; Using the front and rear wheel speeds, the front axle sway angle, the vehicle body acceleration, and the vehicle body angular velocity as state inputs, the vehicle outputs the predicted load data of the left and right front axle wheels according to the preset state prediction equation. Based on the observed vertical load values ​​of the tires, the predicted load data of the left and right front axles are corrected to obtain the load data of the left and right front axles of the vehicle. Based on the load data of the left and right front axle wheels, the structural off-center load state of the vehicle is determined; Based on the driving status data, the reference wheel and non-reference wheels are determined among the front wheels and rear wheels; Based on the driving state data of the reference wheel and the driving state data of the non-reference wheels, determine the slippage state of each front wheel and each rear wheel; Based on the structural off-center load state and the slippage state, a control strategy for the vehicle is determined; wherein, the control strategy includes a warning strategy and an electric drive torque distribution strategy; The driving status data also includes the front axle sway angle; Accordingly, determining the slippage state of each front wheel and each rear wheel based on the driving state data of the reference wheel and the driving state data of the non-reference wheels includes: Based on the aforementioned front axle sway angle, a terrain curvature factor is constructed; Based on the terrain curvature factor, the driving state data of the reference wheel, and the driving state data of the non-reference wheels, determine the wheel slip risk value for each of the front wheels and each of the rear wheels; Based on the wheel slip risk value, the slip state of the front wheel and each of the rear wheels is determined; wherein the slip state includes symmetrical slip and asymmetrical slip.

2. The method according to claim 1, characterized in that, The step of determining the vehicle control strategy based on the structural off-center load state and the slippage state includes: Based on the structural off-center loading state, determine the early warning strategy for the vehicle; The electric drive torque distribution strategy of the vehicle is determined based on the structural off-center load state and the slippage state.

3. The method according to claim 2, characterized in that, The structural off-center loading condition includes the presence of structural off-center loading risk and the presence of temporary load fluctuations; Accordingly, determining the early warning strategy for the vehicle based on the structural off-center load state includes: If the structural off-center loading condition indicates a risk of structural off-center loading, then a front axle load imbalance alarm is triggered. If the structural off-center load condition is a temporary load fluctuation, then the front axle load imbalance alarm will not be triggered.

4. The method according to claim 3, characterized in that, The step of determining the structural off-center load state of the vehicle based on the load data of the left and right front axles includes: Based on the load data of the left and right front axles, determine the load deviation values ​​of the left and right front axles. If the load deviation between the left and right wheels of the front axle is greater than a preset deviation threshold, then the structural off-center loading state is determined to be a structural off-center loading risk. If the load deviation between the left and right wheels of the front axle is not greater than the preset deviation threshold, then it is determined that there is a temporary load fluctuation.

5. The method according to claim 1, characterized in that, The step of determining the vehicle control strategy based on the structural off-center load state and the slippage state includes: If the slippage state is symmetrical slippage, then the electric drive torque distribution strategy is determined based on the structural off-center load state and the wheel slippage risk value. If the slippage is asymmetrical, a preset terrain compensation distribution strategy is adopted, and the electric drive torque distribution strategy is determined based on the structural off-center load state and the wheel slippage risk value.

6. The method according to claim 5, characterized in that, The step of determining the electric drive torque distribution strategy based on the structural off-center load state and the wheel slippage risk value includes: Obtain the preset vertical load distribution weights, preset penalty compensation torque coupling mechanisms, and preset safety boundary constraints; Based on the preset vertical load distribution weight, the preset penalty compensation torque coupling mechanism, the preset safety boundary constraints, the structural off-center load state, and the wheel slippage risk value, calculate the electric drive torque distribution value for each of the front wheels and each of the rear wheels.

7. The method according to claim 5, characterized in that, The method employs a preset terrain compensation distribution strategy, which determines the electric drive torque distribution strategy based on the structural off-center load state and the wheel slippage risk value, including: A preset terrain compensation allocation strategy is adopted to establish a target wheel speed control loop and a torque amplitude limiting loop; Based on the target wheel speed control loop, the torque amplitude limiting loop, the structural off-center load state, and the wheel slippage risk value, calculate the electric drive torque distribution value for each of the front wheels and each of the rear wheels.

8. A bridge system for a vehicle, characterized in that, The cable tray system is used to perform the method described in any one of claims 1-7, including: The front axle includes a swing-connected support structure and a connecting structure. The support structure has first mounting positions at both ends along a first direction for mounting the front wheel. The connecting structure is used to connect to the vehicle frame. The support structure can swing relative to the connecting structure in a first plane, which is parallel to the first direction. The rear axle has second mounting positions at both ends along the first direction, the second mounting positions being used to mount the rear wheels, and the rear axle being fixedly connected to the vehicle frame.

9. The vehicle bridge system according to claim 8, characterized in that, The supporting structure and the connecting structure are rotatably connected, and the central axis of rotation of the supporting structure relative to the connecting structure is perpendicular to the first plane.

10. The vehicle bridge system according to claim 9, characterized in that, The swing angle of the support structure relative to the connecting structure is less than or equal to 6°.

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