A method and system for analyzing the stability of a loader in motion

Abstract

The application relates to a loader running stability analysis method and system, which comprises four key links: real-time monitoring and critical threshold calculation, virtual potential field construction and threshold correction, unstable state determination and active intervention strategy, the links form a closed loop control, effectively solve the defects of the traditional method, such as reaction lag and poor adaptability, the core lies in dynamic adjustment of a critical inclination threshold value, the critical inclination threshold value is corrected in real time through a virtual potential field, through calculation of a mass potential barrier and a sliding vector, key factors such as a shovel load and wheel slip are brought into a stability evaluation system to correct the critical inclination threshold value, the stability limit of the loader under different road conditions and in different postures can be more accurately reflected, the lag problem of the traditional fixed threshold method is avoided, and finally, the shovel posture adjustment is used as a priority stability compensation means, and combined with speed regulation, the side turning risk can be reduced through rapid response in the initial stage of body instability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of loaders, in particular to a loader running stability analysis method and system. BACKGROUND

[0002] As an important equipment in the field of engineering machinery, the running stability of the loader is directly related to the safety and efficiency of the operation. Under complex working conditions, especially in the slope operation environment, the loader faces severe stability challenges.

[0003] In actual operation, lateral slip under slope running working condition is the most common and dangerous instability form. When the loader performs steering operation on the inclined road surface, due to the influence of dynamic change of the center of gravity position, the combined instability phenomenon of lateral slip and longitudinal overturning is prone to occur.

[0004] At present, the industry mainly improves the running stability by optimizing the mechanical structure (such as reducing the center of gravity of the vehicle body) or adopting the electronic stability system (such as the anti-rollover control algorithm); however, these methods have obvious limitations: the mechanical structure optimization is limited by the design space, needs to change the structure of the loader itself, and is difficult to adapt to variable working conditions; and the existing electronic stability system mostly relies on fixed threshold value judgment, only adjusts the output power according to the slope size to control the speed of the loader, and cannot dynamically adapt to the real-time state change of the loader under different vehicle body postures, resulting in control lag or misjudgment, affecting the operation efficiency and safety. SUMMARY

[0005] Therefore, the present application provides a loader running stability analysis method and system, the core of the method is to dynamically adjust the critical inclination threshold value, and the critical inclination threshold value is corrected in real time through a virtual potential field, which can more accurately reflect the stability limit of the loader under different road conditions, avoid the hysteresis problem of the traditional fixed threshold value method, and correct the critical inclination threshold value by taking the key factors such as the load of the bucket and the wheel slip into the stability evaluation system through the calculation of the mass potential barrier and the slip vector. Finally, the bucket posture adjustment is used as a priority stability compensation means, and combined with the speed regulation, the side overturning risk can be reduced by quickly responding in the early stage of vehicle body instability.

[0006] To solve the above technical problems, the present application provides a loader running stability analysis method, comprising the following steps:

[0007] Real-time monitoring of the vehicle body inclination of the loader, combining with the slope data of the current road surface, and using a dynamic balance algorithm to calculate the critical inclination threshold value under the current working condition;

[0008] A virtual potential field is constructed according to the attitude of the loader body for dynamically correcting the critical inclination threshold, wherein: the virtual potential field determines a potential field base plane according to the body pitch angle and the body roll angle, calculates a mass distribution offset based on the bucket angle and the bucket height of the loader, generates a corresponding mass potential barrier in the potential field, derives a potential slip vector according to the speed difference between the drive wheels and the non-drive wheels, and forms a potential field gradient direction;

[0009] If the body inclination exceeds the corrected critical inclination threshold, it is determined that the state is unstable;

[0010] When it is determined that the state is unstable, the bucket rotation direction is first determined based on the potential field gradient direction, the bucket rotation angle and height are determined based on the mass potential barrier, and if the state is still unstable, the driving speed of the loader is gradually adjusted to match the current road conditions.

[0011] In an embodiment of the present application, the dynamic balance algorithm gradually adjusts the critical inclination threshold by simulating the trend of the center of gravity offset of the loader at different slopes, so that the critical inclination threshold decreases as the slope increases and increases as the slope decreases.

[0012] In an embodiment of the present application, the specific steps of dynamically correcting the critical inclination threshold include:

[0013] A three-dimensional coordinate system is established based on the potential field base plane, and the real-time monitored body inclination is projected into the coordinate system;

[0014] According to the distribution position and intensity of the mass potential barrier, a corresponding threshold correction amount is applied at the projection position, wherein the greater the mass potential barrier intensity, the greater the correction amount;

[0015] Threshold offset compensation is performed along the potential field gradient direction, and the correction amount is increased when the gradient direction is consistent with the body inclination direction, and the correction amount is decreased when the gradient direction is opposite to the body inclination direction.

[0016] In an embodiment of the present application, the dynamic correction of the critical inclination threshold further includes: establishing a mapping relationship table of potential field parameters and threshold correction amounts, wherein:

[0017] The inclination angle of the potential field base plane is increased by 1 degree, and the critical inclination threshold is correspondingly reduced by 0.5-0.8 degrees;

[0018] The mass potential barrier intensity is increased by one level, and the critical inclination threshold is reduced by 1-1.5 degrees;

[0019] When the included angle between the potential field gradient direction and the body inclination direction is less than 30 degrees, the critical inclination threshold is reduced by 1.2-1.8 degrees.

[0020] In one embodiment of the present application, the calculation of the mass distribution offset includes: obtaining the weight distribution data of the material in the bucket, combining the lifting height of the bucket and the rotation angle, and calculating the offset vector of the center of gravity of the material relative to the reference position of the vehicle body.

[0021] In one embodiment of the present application, the determination process of the potential field gradient direction further includes:

[0022] Monitoring tire pressure data;

[0023] When one side tire pressure is abnormal, a compensation vector is applied to the potential field gradient direction on the corresponding drive wheel side, and the compensation vector size is adjusted according to the tire pressure deviation degree, which is used to correct the critical inclination threshold.

[0024] In one embodiment of the present application, the determination of the bucket rotation direction includes: when a roll tendency is detected, the bucket position is adjusted in the opposite direction of the potential field gradient; when a pitch tendency is detected, the lifting height of the bucket is adjusted.

[0025] In one embodiment of the present application, when it is determined that the unstable state, the severity classification of the unstable state includes:

[0026] Based on the corrected critical inclination threshold, the percentage amplitude of the vehicle body inclination exceeding the reference is calculated:

[0027] First level instability: the percentage amplitude is greater than 5%, only adjust the bucket position;

[0028] Second level instability: the percentage amplitude is greater than 10%, adjust the bucket position and driving speed synchronously;

[0029] Third level instability: the percentage amplitude is greater than 20%, immediately execute emergency braking and issue sound and light alarm.

[0030] In one embodiment of the present application, under the condition of wet and slippery road surface, the tire slip ratio parameter is additionally introduced:

[0031] The real-time slip ratio is calculated by the wheel speed sensor;

[0032] When the slip ratio continues to increase, the unstable state determination is triggered in advance;

[0033] The road surface adhesion coefficient compensation vector is superimposed in the direction of the potential field gradient, which is used to correct the critical inclination threshold.

[0034] To solve the above technical problems, the present application also provides a loader running stability analysis system, comprising:

[0035] An inclination monitoring module for real-time monitoring of the vehicle body inclination of the loader and collecting the slope data of the current road surface;

[0036] A dynamic balance calculation module is connected with the inclination monitoring module and is configured to calculate a critical inclination threshold in a current working condition by using a dynamic balance algorithm.

[0037] A virtual potential field construction module is connected with the dynamic balance calculation module and is configured to construct a virtual potential field according to a body posture of the loader to dynamically correct the critical inclination threshold, wherein:

[0038] The virtual potential field determines a potential field base plane based on a body pitch angle and a body roll angle, calculates a mass distribution offset based on a bucket angle and a bucket height of the loader to generate a corresponding mass potential barrier in the potential field, and derives a potential slip vector based on a speed difference between a driving wheel and a non-driving wheel to form a potential field gradient direction.

[0039] A stability determination module is connected with the virtual potential field construction module and is configured to determine that the loader is in an unstable state when the body inclination exceeds the corrected critical inclination threshold.

[0040] An active adjustment module is connected with the stability determination module and is configured to perform the following operations when the unstable state is determined:

[0041] determining a bucket rotation direction based on the potential field gradient direction, determining a bucket rotation angle and height based on the mass potential barrier, and gradually adjusting a driving speed of the loader according to a severity of the unstable state to match the current road condition.

[0042] The above technical solution of the present application has the following advantages compared with the prior art:

[0043] The loader driving stability analysis method provided by the present application first calculates the critical inclination threshold by using the dynamic balance algorithm, so that the critical inclination threshold is adaptively adjusted according to the slope change, thereby avoiding the false judgment caused by the fixed threshold, and then the virtual potential field is constructed to comprehensively consider the body posture, the bucket load distribution and the wheel slip trend, so that the critical inclination threshold is corrected in real time, and the stability judgment is more accurate. Finally, when the unstable state is detected, the system intelligently adjusts the bucket angle and height based on the potential field gradient direction, compensates the body offset by using the mass distribution of the bucket, and adjusts the driving speed in stages to ensure smooth transition to a safe state.

[0044] Compared with the prior art, the present application has the following advantages:

[0045] 1. The virtual potential field is used to correct the critical inclination threshold in real time, which can more accurately reflect the stability limit of the loader under different road conditions, and avoid the hysteresis problem of the traditional fixed threshold method.

[0046] 2. The calculation of the mass potential barrier and the slip vector integrates the key factors such as the bucket load and the wheel slip into the stability evaluation system, and further improves the stability determination accuracy.

[0047] 3. Active compensation control: first use the bucket posture adjustment as a stability compensation means, and finally combine with the speed grading regulation, which can quickly respond in the early stage of body instability and reduce the risk of rollover. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to make the content of the present application more easily understood, the present application will be further described in detail below according to specific embodiments of the present application and in conjunction with the drawings, in which:

[0049] Figure 1 is a step flow chart of the loader running stability analysis method of the present application;

[0050] Figure 2 is a step flow chart of the specific implementation process of dynamically correcting the critical inclination threshold value of the present application;

[0051] Figure 3 is a step flow chart of the determination process of incorporating tire pressure monitoring into the potential field gradient direction of the present application;

[0052] Figure 4 is a structure block diagram of the hierarchical response mechanism processing of the present application;

[0053] Figure 5 is a structure block diagram of the loader running stability analysis system of the present application. DETAILED DESCRIPTION

[0054] The present application will be further described below in conjunction with the drawings and specific embodiments, so that those skilled in the art can better understand the present application and implement it, but the embodiments are not limiting to the present application.

[0055] Referring to Figure 1 , the present application discloses a loader running stability analysis method, characterized by comprising the following steps:

[0056] Real-time monitoring of the body inclination of the loader, combined with the current road slope data, using a dynamic balance algorithm to calculate the critical inclination threshold value under the current working condition;

[0057] According to the body posture of the loader, a virtual potential field is constructed for dynamically correcting the critical inclination threshold value, wherein: the virtual potential field determines the potential field base plane according to the body pitch angle and roll angle, calculates the mass distribution offset based on the bucket angle and bucket height of the loader, generates the corresponding mass potential barrier in the potential field, and derives the potential slip vector based on the speed difference between the drive wheels and the non-drive wheels to form the potential field gradient direction;

[0058] If the body inclination exceeds the corrected critical inclination threshold value, it is determined as an unstable state;

[0059] When it is determined that the state is unstable, the direction of the bucket rotation is determined based on the potential field gradient direction, the rotation angle and height of the bucket are determined based on the mass potential barrier, and if the state is still unstable, the driving speed of the loader is gradually adjusted to match the driving speed of the loader with the current road condition.

[0060] The core technology of the loader driving stability analysis method is to construct an intelligent evaluation system that responds to the working state changes of the loader in real time.

[0061] The technical scheme of the present application includes four key links: real-time monitoring and critical threshold calculation, virtual potential field construction and threshold correction, unstable state determination and active intervention strategy.

[0062] The first technical innovation of the present application lies in the application of the dynamic balance algorithm.

[0063] The construction of the virtual potential field is the second technical innovation point of the present application.

[0064] The potential field base plane is determined by the pitch angle and roll angle of the vehicle body, which reflects the overall attitude reference of the loader.

[0065] The mass potential barrier is the mapping of the mass distribution offset calculated by the bucket angle and height data in the potential field, which accurately characterizes the influence of the change of the bucket position on the center of gravity and stability of the whole vehicle, and unlike the traditional fixed posture frame, the mass distribution of the loader will change with the change of the relative angle and position of the bucket, the method combines the bucket angle and height data to calculate the real-time change of the center of gravity position, in the virtual potential field, the change of the mass distribution is shown as the change of the height and shape of the potential barrier, which directly affects the shape of the stability boundary, through data calibration, the influence degree of the mass distribution on the stability can be accurately reflected;

[0066] The potential field gradient direction is derived from the analysis of the speed difference between the driving wheel and the non-driving wheel, which can predict the potential sliding direction, the traditional method usually only evaluates the size of stability, but ignores the directional characteristics of instability, the application identifies the potential sliding direction by analyzing the speed difference between the driving wheel and the non-driving wheel, and represents it as a gradient direction in the virtual potential field, this information is crucial for subsequent generation of recommended operation vectors, which enables the system to provide accurate operation suggestions for specific instability trends;

[0067] Through the mutual coupling of the potential field base plane, the mass potential barrier and the potential field gradient direction, a dynamically evolving stability evaluation space is formed, which can further accurately reflect the stability state combined with the current vehicle body posture.

[0068] Further, through the gradient direction analysis in the virtual potential field, the application can predict the potential sliding risk when the actual inclination angle of the vehicle body has not yet exceeded the safety threshold, specifically, the system can sensitively capture the small changes in traction force distribution by monitoring the speed difference between the driving wheel and the non-driving wheel, these changes are often the precursor of subsequent serious instability; when such subtle changes are detected, the corresponding gradient direction is formed in the virtual potential field, providing a basis for subsequent decision-making, this prediction ability based on the precursor characteristics enables the system to issue an early warning several seconds in advance, leaving valuable reaction time for the driver or automatic control system.

[0069] The third technical innovation point of the present application is embodied in the intervention strategy in the unstable state. When the system detects that the body inclination angle exceeds the corrected critical threshold, the hierarchical intervention strategy is triggered immediately. Unlike the traditional simple alarm, the intervention measures proposed by the present application have clear directionality and gradualness. The system first determines the best rotation direction of the bucket based on the potential field gradient direction, which is equivalent to using the bucket as a balance regulator to offset the sliding trend by changing its position. Then, according to the strength of the mass potential barrier, the specific rotation angle and lifting height of the bucket are determined to ensure that the adjustment force and the instability degree are accurately matched. Finally, the system gradually adjusts the driving speed according to the severity of the unstable state, forming a hierarchical and step-by-step intervention strategy for body posture adjustment and driving state, which can restore the stability of the loader in the shortest time with the minimum operation cost, greatly improving the effectiveness of the correction measures.

[0070] Specifically, when the system detects an unstable state, it first determines the best adjustment direction of the bucket based on the potential field gradient direction. If the predicted sliding direction is to the left, the system may suggest swinging the bucket to the right to generate a counter-torque. Then, according to the strength of the mass potential barrier, the angle and height of the bucket rotation are accurately calculated to ensure that the intervention force and the instability degree are accurately matched. Finally, the system gradually adjusts the driving speed according to the severity of the unstable state to avoid the risk of secondary instability caused by sudden deceleration. This multi-level and differentiated intervention strategy can achieve the best stability effect with minimal impact on work efficiency compared to traditional speed control.

[0071] In this embodiment, a dynamic balance algorithm is used as the core method for calculating the critical inclination threshold, and its specific implementation directly affects the accuracy and reliability of the entire stability analysis system. To clarify the specific working mechanism of this algorithm and its coordination with the overall technical solution, the dynamic balance algorithm is set to simulate the trend of the center of gravity of the loader under different slopes, establish a dynamic model of the center of gravity deviation of the loader, and dynamically adjust the critical inclination threshold by simulating the trend of the center of gravity of the loader under different slopes in real time.

[0072] Specifically, the algorithm first collects the slope data of the loader currently through sensors, establishes a corresponding relationship model between the slope and the theoretical center of gravity position. Then, based on the real-time motion state of the loader, including the body vibration frequency, steering acceleration and other parameters, the theoretical model is dynamically calibrated to make the model accurately reflect the change of the center of gravity under actual working conditions. Finally, according to the calibrated model, the critical inclination threshold under the current slope is output. This threshold will automatically decrease as the slope increases and correspondingly increase as the slope decreases.

[0073] The technical effects of this dynamic adjustment mechanism are reflected in three aspects: first, by establishing a corresponding relationship model between the slope and the position of the center of gravity, the theoretical basis for threshold calculation is ensured to be scientifically reliable; second, real-time motion parameters are introduced for dynamic calibration, enabling the algorithm to adapt to the actual operating state of the loader under different loads and different road conditions, avoiding the lack of adaptability of the fixed threshold algorithm under complex working conditions; finally, the dynamic change of the threshold with the slope makes the system able to take more stringent stability control strategies in advance under high-risk working conditions such as steep slopes, effectively preventing rollover accidents.

[0074] In this embodiment, the virtual potential field is constructed as a core technical means for dynamically correcting the critical inclination threshold, and its specific implementation process directly affects the accuracy and real-time performance of stability judgment. In order to reveal the internal mechanism between the virtual potential field and the critical inclination threshold, and make the innovation points of the entire technical scheme clearer and more explicit, as shown in Figure 2

[0075] The correction process first establishes a three-dimensional coordinate system based on the potential field base plane determined by the body pitch angle and roll angle. This step converts the spatial attitude of the loader into a quantifiable mathematical model, providing a reference framework for subsequent accurate calculations. By projecting the real-time monitored body inclination into the coordinate system, accurate mapping of the actual physical state and the virtual potential field is achieved, ensuring the accuracy of the subsequent correction amount calculation.

[0076] After obtaining the projection position, the system applies a corresponding threshold correction amount according to the distribution position and intensity of the mass potential barrier. The correction effect of the mass potential barrier is reflected in the secondary adjustment of the projection coordinates. The system calculates the mass distribution offset based on the bucket angle and height data, forming a mass potential barrier with directional and intensity characteristics in the virtual potential field. The position of this potential barrier in the three-dimensional coordinate system reflects the actual impact range of the center of gravity offset, and its intensity is proportional to the severity of the instability trend. The correction algorithm adds a vector component proportional to the intensity of the mass potential barrier to the projection coordinates, allowing the impact of the center of gravity offset on stability to be quantitatively evaluated. In particular, when the bucket is lifting materials, the system automatically increases the correction amount to reflect the risk of the center of gravity moving upward. This dynamic response mechanism addresses the lack of sensitivity to load changes in traditional methods.

[0077] Finally, the threshold offset compensation along the potential field gradient direction fully considers the potential slip trend reflected by the speed difference between the drive wheels and the non-drive wheels. When the gradient direction is consistent with the body inclination direction, it indicates that the slip trend exacerbates the instability risk, and increasing the correction amount can provide early warning and take control measures. Conversely, it indicates that the slip trend helps to offset the inclination risk, and appropriately reducing the correction amount can avoid overly conservative control strategies. ​

[0078] This dynamic correction mechanism based on multi-factor synergy ensures that the critical inclination threshold can accurately reflect the real stability state of the loader in real time, providing a scientific basis for subsequent stability judgment and control decisions, thus effectively solving the technical problem of the poor adaptability of the traditional fixed threshold method under complex working conditions.

[0079] In this embodiment, in order to further realize the quantitative dynamic correction of the critical inclination threshold, an accurate mapping relationship table between the potential field parameters and the threshold correction amount is established, providing a clear standard for parameter adjustment of the virtual potential field theory in actual engineering applications. The establishment of the mapping relationship table is based on a deep mechanism analysis of the factors affecting the stability of the loader, including:

[0080] When the loader is driving on a slope, the inclination angle of the potential field base plane directly reflects the basic influence of the road slope on stability. Experimental data show that for every 1 degree increase in the inclination of the base plane, the theoretical stability margin of the loader will decrease by 0.6-0.9 degrees. The mapping relationship table sets a threshold reduction of 0.5-0.8 degrees, which takes into account the safety margin and avoids overly conservative judgments.

[0081] The hierarchical correction mechanism of the mass potential barrier strength reflects a scientific evaluation of the load distribution. After calculating the mass distribution offset based on the bucket angle and height data, the system quantifies it into multiple strength levels, each level corresponding to a threshold reduction of 1-1.5 degrees. This non-linear relationship accurately simulates the actual impact of the center of gravity offset on stability. When the bucket lifts heavy objects, the mass potential barrier strength will jump 2-3 levels, triggering a significant reduction in the threshold, thereby warning of the risk of overturning in advance.

[0082] Further realize the coupling correction of the potential field gradient direction and the vehicle body inclination angle. When the angle between the potential field gradient direction generated by the speed difference between the driving wheels and the non-driving wheels and the actual inclination direction of the vehicle body is less than 30 degrees, it indicates that there is a synergistic effect that aggravates instability. At this time, the mapping relationship table specifies an additional threshold reduction of 1.2-1.8 degrees. This direction-sensitive correction can identify complex instability patterns that traditional methods cannot detect, such as when the lateral slip and longitudinal tipping trends are in the same direction. The system will activate the maximum correction amount, forming a multi-dimensional protection.

[0083] This quantitative correction mechanism based on multi-parameter synergy fundamentally breaks through the limitations of traditional empirical threshold setting. By establishing an accurate mathematical correspondence, it not only retains the adaptability of the virtual potential field theory to complex working conditions, but also realizes the standardization and repeatability of control parameters. In practical applications, the mapping relationship table can be parameter-matched with the loader model and the characteristics of the working environment to form a stability control scheme that is both universal and targeted, providing reliable technical support for the intelligent development of engineering machinery.

[0084] In the present embodiment, the mass distribution offset is a key dynamic parameter affecting the stability of the loader, and its calculation accuracy directly determines the accuracy of the mass potential barrier in the virtual potential field. In actual engineering, the dynamic distribution of the material in the bucket directly affects the quantitative evaluation of the mass potential barrier. In order to accurately calculate the influence of the dynamic distribution of the material, first, the real-time weight distribution data of the material is obtained through the weight sensor installed on the bucket. This basic data acquisition link ensures the accuracy of the source of the calculation. Then, the spatial geometric relationship model including the material position, the bucket posture and the reference position of the vehicle body is established by combining the bucket lifting height and the rotation angle parameters measured by the high-precision angle sensor. Finally, the offset vector of the center of gravity of the material relative to the reference position of the vehicle body is calculated based on the model. This vector result not only contains the offset distance information, but also retains the direction feature, providing complete dynamic load parameters for the subsequent construction of the virtual potential field.

[0085] Specifically, by obtaining the material weight distribution data in real time instead of using estimated values, the authenticity of the calculation results is greatly improved, especially for unevenly distributed materials. By including the bucket lifting height and the rotation angle in the calculation model, the influence of the bucket posture change on the center of gravity of the material during the operation is accurately reflected, avoiding errors caused by static assumptions. The calculation result of the offset vector directly corresponds to the spatial coordinate system of the virtual potential field, realizing the accurate conversion of physical parameters to the control model.

[0086] This refined mass distribution offset calculation method fundamentally solves the problem of rough load parameter estimation in traditional stability control systems, enabling the virtual potential field to accurately reflect the dynamic stability state of the loader during operation, providing reliable input data for subsequent critical inclination threshold correction, thereby ensuring that the entire control system can still maintain high-precision stability judgment ability in complex operating environments.

[0087] In actual engineering, the inconsistency of tire pressure on both sides of the loader will affect the speed difference, thereby affecting the accuracy of the potential field gradient direction determination. Therefore, the tire pressure monitoring is included in the determination process of the potential field gradient direction. This supplementary limitation can specifically solve the problem of stability judgment error of the engineering machinery under abnormal tire conditions. As shown in FIG. 8, the tire pressure data of each tire is monitored in real time by the pressure sensor installed in the tire. When the system detects unilateral tire pressure abnormality, a compensation vector opposite to the tire pressure deviation direction is immediately generated in the virtual potential field model. The size of the compensation vector is dynamically adjusted according to the percentage of the tire pressure deviation. The larger the deviation, the larger the compensation vector. Finally, this compensation vector is superimposed on the calculation result of the original potential field gradient direction, realizing the targeted correction of the critical inclination threshold. Figure 3

[0088] ​From the technical mechanism, tire pressure abnormalities can significantly change the contact characteristics between the tire and the ground, leading to uneven distribution of driving force on both sides of the vehicle, and thus affecting the stability performance of the vehicle. The traditional control system often ignores this important factor. In this embodiment, by introducing the tire pressure data into the potential field gradient calculation in real time, the system can perceive the potential risk of side slip caused by uneven tire pressure in advance, and actively apply a reverse compensation in the virtual potential field model, which is equivalent to pre-compensating the instability factors caused by tire pressure abnormalities at the algorithm level.

[0089] In this embodiment, when it is determined that the state is unstable, the bucket rotation direction is first determined based on the potential field gradient direction, and the instability mode of the loader is identified by analyzing the potential field gradient characteristics in real time. When the system detects an instability trend mainly caused by the roll moment, the control strategy preferentially drives the bucket to move in the opposite direction of the potential field gradient. This design cleverly uses the reverse moment generated by the bucket mass to offset the roll trend. When the instability characteristics in the pitch direction are identified, the bucket lifting height is preferentially adjusted, and the vehicle's gravity center height is adjusted by changing the vertical position of the bucket, thereby improving the longitudinal stability.

[0090] From the control mechanism, this differentiated processing fully considers the differences in the dynamics of the loader in different instability modes: for roll tendency, horizontal position adjustment of the bucket can most directly generate a reverse moment to resist rollover; and for pitch tendency, adjusting the bucket height can more effectively change the longitudinal weight distribution.

[0091] Referring to Figure 4 As shown in the figure, the application also introduces a hierarchical response mechanism in the active intervention strategy, realizing fine processing of the unstable state and effectively solving the problem of insufficient adaptability of the "one-size-fits-all" response mode in the traditional control system when dealing with different degrees of instability risk.

[0092] Specifically, this hierarchical control strategy first quantitatively evaluates the severity of the unstable state based on the percentage range of the body inclination angle exceeding the critical threshold value, and scientifically divides the risk level into three progressive levels:

[0093] When a first level of unstable state is detected, i.e., the percentage of the body inclination angle exceeding the corrected critical inclination threshold value is greater than 5%, only the most gentle intervention method of adjusting the bucket position is used for compensation. This conservative strategy is suitable for conditions where the threshold value is slightly exceeded, and can effectively correct the stability deviation while maximizing the continuity of the operation;

[0094] When upgrading to a second level of unstable state, i.e., the percentage of the body inclination angle exceeding the corrected critical inclination threshold value is greater than 10%, the cooperative control of the bucket position adjustment and the travel speed regulation is started, and a stronger stability compensation effect is formed through double intervention;

[0095] For the most dangerous three-level unstable state, that is, the body inclination angle exceeds the percentage of the corrected critical inclination threshold value greater than 20%, trigger the full range of safety protection measures including emergency braking and sound and light alarm.

[0096] The technical advantages of this grading response mechanism mainly reflect in three aspects: first, according to the risk degree, the control measures of corresponding intensity are matched, and the influence of excessive intervention on normal operation is avoided; second, the progressive control strategy provides multiple safety lines for the system, ensuring that the most appropriate response scheme can be taken under any risk level; finally, the clear grading standard makes the whole control process more standardized and predictable, which is convenient for operators to understand and cooperate with the system. From the control effect, this grading processing method not only guarantees the operation efficiency under the condition of slight instability, but also makes a quick and decisive response to serious dangerous conditions, achieving the best balance between safety and work efficiency.

[0097] In this embodiment, the wet road surface is also specially optimized, and the problem of response lag of the traditional stability control system under low adhesion road surface is effectively solved by introducing the tire slip rate monitoring and compensation mechanism. The technical scheme first calculates the slip rate of each tire in real time through a high-precision wheel speed sensor, and when the system detects that the slip rate shows a continuous upward trend, the unstable state determination is triggered in advance even if the body inclination angle has not reached the theoretical threshold value. This forward-looking judgment mechanism can seize the valuable control opportunity; at the same time, the system generates a compensation vector related to the road adhesion coefficient in the virtual potential field model according to the real-time slip data, the size of the compensation vector is proportional to the slip rate change rate, and the direction is related to the vehicle movement trend, and by superimposing it on the original potential field gradient direction, the dynamic down-regulation of the critical inclination threshold value is realized.

[0098] The low adhesion characteristics of the wet road surface can significantly reduce the stability limit of the loader, and the traditional system often reacts when the body is obviously inclined due to the lack of direct perception of the road conditions. By monitoring the tire slip rate, which directly reflects the road adhesion condition, the system can perceive the risk in advance and adjust the control strategy accordingly. Specifically, when the slip rate is continuously increasing, it means that the tire is losing grip, and triggering the instability determination in advance can gain more control response time; the compensation vector generated based on the slip rate is equivalent to simulating the influence of the decrease of the road adhesion coefficient on the vehicle stability at the algorithm level, so that the critical inclination threshold value can match the actual carrying capacity of the current road in real time.

[0099] Referring to Figure 5 In order to realize the above method, the present application further discloses a loader running stability analysis system, comprising:

[0100] An inclination monitoring module is configured to monitor the inclination of the vehicle body of the loader in real time and collect the slope data of the current road surface;

[0101] A dynamic balance calculation module is connected with the inclination monitoring module and configured to calculate the critical inclination threshold in the current working condition by using a dynamic balance algorithm;

[0102] A virtual potential field construction module is connected with the dynamic balance calculation module and configured to construct a virtual potential field to dynamically correct the critical inclination threshold according to the attitude of the vehicle body of the loader, wherein:

[0103] The virtual potential field determines a potential field base plane based on the pitch angle and the roll angle of the vehicle body, calculates a mass distribution offset based on the bucket angle and the bucket height of the loader, and generates a corresponding mass potential barrier in the potential field, and derives a potential slip vector based on the speed difference between the driving wheels and the non-driving wheels to form a potential field gradient direction;

[0104] A stability determination module is connected with the virtual potential field construction module and configured to determine that the loader is in an unstable state when the inclination of the vehicle body exceeds the corrected critical inclination threshold;

[0105] An active adjustment module is connected with the stability determination module and configured to perform the following operations when it is determined that the loader is in an unstable state:

[0106] determining the rotation direction of the bucket based on the potential field gradient direction, determining the rotation angle and height of the bucket based on the mass potential barrier, and gradually adjusting the driving speed of the loader according to the severity of the unstable state to match the current road condition.

[0107] Those skilled in the art will understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0108] The present application is described with reference to flowcharts and / or block diagrams according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as a combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a device that implements the flowcharts and / or block diagrams. Figure 1 one flow or multiple flows and / or blocksFigure 1 means for performing the function specified in the block or blocks.

[0109] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flow Figure 1 flow or flows and / or blocks Figure 1 means for performing the function specified in the block or blocks.

[0110] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flow Figure 1 flow or flows and / or blocks Figure 1 steps of means for performing the function specified in the block or blocks.

[0111] Obviously, the above-described embodiments are only examples and are not intended to limit the present application. Based on the above description, one of ordinary skill in the art can make other variations and changes without departing from the present application. It is not necessary to recite all the embodiments, and obvious changes or variations made from the present application are still within the scope of the present application.

Claims

1. A method of analyzing the travel stability of a loader, characterized by: The method comprises the following steps: Real-time monitoring of the body inclination angle of the loader, combined with the current road slope data, using a dynamic balance algorithm to calculate the critical inclination threshold under the current working condition; A virtual potential field is constructed according to the body posture of the loader for dynamic correction of the critical inclination threshold, wherein: the virtual potential field determines the potential field base plane according to the body pitch angle and roll angle, calculates the mass distribution offset based on the bucket angle and bucket height of the loader, generates the corresponding mass potential barrier in the potential field, and derives the potential slip vector according to the speed difference between the drive wheels and the non-drive wheels to form the potential field gradient direction; the specific steps of dynamically correcting the critical inclination threshold include: establishing a three-dimensional coordinate system based on the potential field base plane, projecting the real-time monitored body inclination angle into the coordinate system; according to the distribution position and intensity of the mass potential barrier, a corresponding threshold correction amount is applied at the projection position, wherein the greater the mass potential barrier intensity, the greater the correction amount; threshold offset compensation is performed along the potential field gradient direction, and the gradient direction is consistent with the body inclination direction, so the correction amount is increased, and vice versa; If the body inclination angle exceeds the corrected critical inclination threshold, it is determined to be an unstable state; When it is determined to be an unstable state, first, the bucket rotation direction is determined based on the potential field gradient direction, and the bucket rotation angle and height are determined based on the mass potential barrier, and if it is still in an unstable state, the driving speed of the loader is gradually adjusted to match the driving speed of the loader with the current road condition.

2. The loader ride stability analysis method of claim 1, characterized by: The dynamic balance algorithm simulates the trend of the center of gravity offset of the loader under different slopes, gradually adjusts the critical inclination threshold, so that it decreases as the slope increases and increases as the slope decreases.

3. The loader ride stability analysis method of claim 1, further characterized by: The dynamic correction of the critical inclination threshold further comprises: establishing a mapping relationship table of potential field parameters and threshold correction amount, wherein: The inclination angle of the potential field base plane increases by 1 degree, and the critical inclination threshold decreases by 0.5-0.8 degrees; The intensity of the mass potential barrier increases by one level, and the critical inclination threshold decreases by 1-1.5 degrees; When the included angle between the potential field gradient direction and the body inclination direction is less than 30 degrees, the critical inclination threshold decreases by 1.2-1.8 degrees.

4. The loader ride stability analysis method of claim 1, further characterized by: The calculation of the mass distribution offset includes: obtaining the weight distribution data of the material in the bucket, combining the bucket lifting height and the rotation angle, and calculating the offset vector of the material center of gravity relative to the body reference position.

5. The loader ride stability analysis method of claim 1, further characterized by: The determination process of the potential field gradient direction further comprises: Monitoring the tire pressure data; When one side of the tire pressure is abnormal, a compensation vector is applied to the potential field gradient direction on the corresponding drive wheel side, and the compensation vector size is adjusted according to the tire pressure deviation degree for correcting the critical inclination threshold.

6. The loader ride stability analysis method of claim 1, further characterized by: The determination of the bucket rotation direction includes: when the roll tendency is detected, the bucket position is adjusted in the opposite direction of the potential field gradient; when the pitch tendency is detected, the bucket lifting height is adjusted.

7. The loader ride stability analysis method of claim 1, further characterized by: When it is determined to be an unstable state, the severity classification of the unstable state includes: Taking the corrected critical inclination threshold as the reference, the percentage amplitude of the body inclination angle exceeding the reference is calculated: First level instability: the percentage amplitude is greater than 5%, only the bucket position is adjusted; Second level instability: the percentage amplitude is greater than 10%, the bucket position and driving speed are adjusted simultaneously; Level 3 instability: percentage amplitude greater than 20%, immediately execute emergency braking and issue sound and light alarm.

8. The loader ride stability analysis method of claim 1, further characterized by: Under the condition of wet and slippery road surface, the tire slip ratio parameter is additionally introduced: Real-time slip ratio is calculated through wheel speed sensor; When the slip ratio continues to increase, the instability state determination is triggered in advance; The road adhesion coefficient compensation vector is superimposed in the direction of the potential field gradient, which is used to modify the critical inclination threshold.

9. A loader ride stability analysis system characterized by: Comprise: An inclination monitoring module for monitoring the body inclination of the loader in real time and collecting the slope data of the current road surface; A dynamic balance calculation module connected with the inclination monitoring module for calculating the critical inclination threshold under the current working condition by using a dynamic balance algorithm; A virtual potential field construction module connected with the dynamic balance calculation module for constructing a virtual potential field according to the body posture of the loader to dynamically modify the critical inclination threshold, wherein: The virtual potential field determines a potential field base plane based on the body pitch angle and roll angle, calculates the mass distribution offset based on the bucket angle and height of the loader to generate a corresponding mass potential barrier in the potential field, and derives a potential slip vector based on the speed difference between the driving wheel and the non-driving wheel to form the direction of the potential field gradient; The specific steps of dynamically modifying the critical inclination threshold include: establishing a three-dimensional coordinate system based on the potential field base plane, projecting the real-time monitored body inclination to the coordinate system; according to the distribution position and intensity of the mass potential barrier, a corresponding threshold correction amount is applied at the projection position, wherein the greater the mass potential barrier intensity is, the greater the correction amount is; threshold offset compensation is performed along the direction of the potential field gradient, and the correction amount is increased when the gradient direction is consistent with the body inclination direction, and vice versa; A stability determination module connected with the virtual potential field construction module for determining that the loader is in an unstable state when the body inclination exceeds the modified critical inclination threshold; An active adjustment module connected with the stability determination module for performing the following operations when the unstable state is determined: Determine the rotation direction of the bucket based on the direction of the potential field gradient; determine the rotation angle and height of the bucket based on the mass potential barrier; and gradually adjust the driving speed of the loader according to the severity of the unstable state to match the current road condition.

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