Multi-dimensional vehicle actual change rollover early warning method fusing steering intention

Abstract

The invention provides a multi-dimensional vehicle actual change rollover early warning method fused with a steering intention, which comprises the following steps: acquiring vehicle driving parameters of a vehicle at the current moment, if the vehicle driving parameters meet an early warning judgment condition, executing the next step, and if the vehicle driving parameters meet the early warning judgment condition, executing the next step; wherein the vehicle driving parameters comprise a real-time vehicle speed, a steering wheel angle size, a steering wheel angle speed, a vehicle inclination angle, a vehicle angle speed and a road adhesion coefficient; dynamically matching an LTR dynamic threshold database based on the vehicle driving parameters to obtain a rollover early warning threshold of the vehicle at the current moment, and calculating a transverse load transfer rate of the vehicle at the current moment; the rollover early warning time of the vehicle at the current moment is calculated according to the transverse load transfer rate and the rollover early warning threshold value, the rollover risk level is determined based on the rollover early warning time, the TTR serves as one of judgment bases of rollover early warning and is fused with the steering intention of a driver, so that the accuracy and adaptability of vehicle rollover early warning are improved, and the vehicle rollover early warning efficiency is improved. And optimization of anti-rollover control intervention opportunity is of great significance.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle rollover warning, in particular to a multi-dimensional vehicle real-time rollover warning method fusing steering intention. BACKGROUND

[0002] Vehicle rollover, as a typical instability accident with extremely high fatality rate, the accuracy and reliability of its warning system are crucial to improving the active safety performance of vehicles. The core of the warning system lies in building an evaluation index that can accurately represent the degree of rollover danger. Lateral-load Transfer Ratio (LTR) has become the most effective and widely used rollover warning evaluation index because it can directly reflect the transfer state of vertical load between left and right wheels and has clear physical meaning. Based on this, existing rollover warning technologies mostly use a fixed LTR threshold as the warning trigger condition. However, the vehicle dynamics behavior is influenced by multiple factors such as vehicle driving state speed and external environment. The application of a fixed LTR threshold as a warning trigger condition has certain limitations. In low-risk conditions, false positives may occur due to excessive sensitivity. In high-risk conditions such as high speed, low adhesion, or sharp turns, the warning may be delayed due to excessive conservatism, making it difficult to ensure sufficient reaction time.

[0003] To further optimize the LTR threshold, patent CN110040146A incorporates road surface parameters to make the LTR threshold adaptively adjust with vehicle speed and road surface environment. This method is suitable for both stumble-type and non-stumble-type rollovers. Patent CN115406669A considers the optimization of non-sprung mass LTR calculation and builds a fitting relationship between the warning threshold and vehicle speed and road adhesion coefficient. However, the above methods achieve dynamic threshold adjustment but do not incorporate the real-time steering intention (steering wheel angle and angular velocity) of the driver, resulting in the same warning value being used for both smooth and emergency steering conditions, which makes it difficult to actively predict and affects the accuracy and reliability in complex conditions.

[0004] In addition, LTR can only judge the current or short-term rollover risk of the vehicle and lacks reasonable prediction ability, making it difficult to ensure sufficient prevention time and having certain limitations. Therefore, scholars have proposed using Time to rollover (TTR) as one of the rollover evaluations to dynamically predict risks based on body roll angle or LTR threshold and set an upper limit for TTR to ensure prevention time. For example, patent CN119636689A calculates TTR based on roll angle, determines the risk level in combination with vehicle speed, and adopts different control strategies. However, the roll angle threshold varies with vehicle models and lacks universality. Patent CN202510168027.X calculates TTR based on LTR (fixed threshold of 1) and Zero Moment Point (ZMP), but at this time the wheels have already left the ground, making it impossible to provide early warning. However, such patents still fail to consider the steering intention of the driver, resulting in low accuracy of vehicle rollover warning. SUMMARY

[0005] The present application aims to provide a multi-dimensional vehicle real-time rollover warning method fusing steering intention, taking TTR as one of the evaluation criteria for rollover warning and fusing the driver's steering intention, which is of great significance to improve the accuracy and adaptability of vehicle rollover warning and optimize the intervention timing of rollover prevention control.

[0006] To achieve the above purpose, the technical scheme provides a multi-dimensional vehicle real-time rollover warning method fusing steering intention, comprising the following steps: S1: obtaining the vehicle driving parameters of the vehicle at the current time, if the vehicle driving parameters meet the warning judgment condition, then executing step S2, wherein the vehicle driving parameters include real-time vehicle speed, steering wheel angle, steering wheel angle speed, vehicle inclination angle, vehicle angular velocity and road adhesion coefficient; S2: dynamically matching the LTR dynamic threshold database based on the vehicle driving parameters to obtain the rollover warning threshold of the vehicle at the current time, and calculating the lateral load transfer rate of the vehicle at the current time; S3: calculating the rollover warning time of the vehicle at the current time according to the lateral load transfer rate and the rollover warning threshold, and determining the rollover risk level based on the rollover warning time.

[0007] Compared with the prior art, the technical scheme has the following characteristics and beneficial effects: 1. The present application comprehensively considers the parameters of road adhesion coefficient, vehicle speed, steering wheel angle and steering wheel angle speed, breaks through the limitation of existing rollover warning technology which only relies on vehicle speed and road adhesion coefficient, can accurately distinguish operation scenarios such as smooth steering and emergency steering, and makes up for the defects of insufficient warning accuracy and reliability under complex working conditions.

[0008] 2. The present application takes the dynamic LTR threshold as the judgment condition, calculates TTR combined with the first-order change rate of LTR, can quantify the required time to trigger warning under the current state and change trend, more directly reflects the risk urgency, provides accurate intervention timing for the subsequent active rollover prevention control, and according to the TTR interval, divides the risk level, matches the controllable differential braking measures, realizes the targeted rollover prevention control, and effectively improves the driving safety. BRIEF DESCRIPTION OF DRAWINGS

[0009] Figure 1 is the flowchart of the multi-dimensional vehicle real-time rollover warning method fusing steering intention of the present application.

[0010] Figure 2 is a logic diagram based on the condition that the vehicle driving parameters meet the warning judgment condition.

[0011] Figure 3 is a schematic diagram of the dynamic model of a rollover vehicle.

[0012] Figure 4 This is a schematic diagram of a four-degree-of-freedom vehicle dynamics model.

[0013] Figure 5 This is a logic diagram for determining the rollover warning time of a vehicle.

[0014] Figure 6 This is a logic diagram for determining risk levels.

[0015] Figure 7 This is the logic diagram for differential braking control.

[0016] Figure 8 This is a schematic diagram of the electronic device. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention are within the scope of protection of the present invention.

[0018] It should be noted that the steps of the corresponding methods are not necessarily performed in the order shown and described in this specification in other embodiments. In some other embodiments, the methods may include more or fewer steps than described in this specification. Furthermore, a single step described in this specification may be broken down into multiple steps in other embodiments; and multiple steps described in this specification may be combined into a single step in other embodiments.

[0019] Example 1 like Figure 1 As shown, this solution provides a multi-dimensional vehicle rollover warning method that integrates steering intent, including the following steps: S1: Obtain the vehicle driving parameters at the current moment. If the vehicle driving parameters meet the warning judgment conditions, then execute step S2. The vehicle driving parameters include real-time vehicle speed, steering wheel angle, steering wheel angular velocity, vehicle tilt angle, vehicle angular velocity, and road surface adhesion coefficient. S2: Based on the vehicle driving parameters, dynamically match the LTR dynamic threshold database to obtain the vehicle's rollover warning threshold at the current moment, and calculate the vehicle's lateral load transfer rate at the current moment. S3: Calculate the rollover warning time of the vehicle at the current moment based on the lateral load transfer rate and the rollover warning threshold, and determine the rollover risk level based on the rollover warning time.

[0020] The step S1 of the scheme comprehensively considers many vehicle driving parameters such as real-time vehicle speed, steering wheel angle size, steering wheel angle speed, vehicle inclination angle, vehicle angular velocity and road adhesion coefficient to make preliminary judgment for early warning, in particular, the steering wheel angle size and the steering wheel angle speed are used as the steering intention of the driver, which breaks through the limitation of the existing rollover early warning technology that only relies on vehicle speed and road adhesion coefficient, can accurately distinguish operation scenes such as smooth steering and emergency steering, and makes up for the defects of insufficient early warning accuracy and reliability under complex working conditions.

[0021] In step S1, the real-time vehicle speed is obtained in real time by a wheel speed sensor, the steering wheel angle size and the steering wheel angle speed are obtained in real time by a steering force and angle sensor, the vehicle inclination angle and the vehicle angular velocity are obtained in real time by a dynamic inclination sensor, and the road adhesion coefficient is calculated by a road adhesion coefficient estimation unit.

[0022] Specifically, the real-time vehicle speed is obtained in real time by a wheel speed sensor, the wheel speed sensor installed at the hub of each wheel of the vehicle detects the number of wheel rotation and frequency in real time, and the real-time vehicle speed is calculated in combination with the rolling radius of the wheel.

[0023] The steering wheel angle size and the steering wheel angle speed are obtained in real time by a steering force and angle sensor, the steering force and angle sensor is integrated at the steering column, optical encoding technology is used to capture the change of the light signal when the steering shaft rotates, the mechanical angle is converted into a digital signal, and the steering wheel angle speed is calculated in real time by the ratio of the angle difference to the time interval in the adjacent sampling period to identify the steering intention of the driver “small angle slow steering” (smooth working condition) and “large angle fast steering” (emergency working condition).

[0024] The vehicle inclination angle and the vehicle angular velocity are obtained in real time by a dynamic inclination sensor, the dynamic inclination sensor is installed at the body frame directly above the center of mass of the vehicle, and the data fusion algorithm of a micro-electro-mechanical system combined with a gyroscope and an accelerometer is used to output the inclination angle and the inclination angular velocity of the vehicle around the horizontal axis in real time, which can effectively capture the tendency of the vehicle to roll in the conditions of a curve, a lane change or an uneven road.

[0025] The road adhesion coefficient is calculated and obtained by a road adhesion coefficient estimation unit, the road adhesion coefficient is obtained by the difference in the wheel speed collected by the wheel speed sensor, the lateral acceleration collected by a lateral acceleration sensor (integrated with the dynamic inclination sensor) and the tire magic formula model, and the adhesion ability of the current road is obtained by using Kalman filtering.

[0026] The present scheme introduces the steering wheel angle size and the steering wheel angle velocity to represent the driving intention of the driver, and determines whether the driver operation belongs to dangerous steering based on the steering wheel angle size and the steering wheel angle velocity.

[0027] Specifically, the content of the early warning judgment condition is as follows: When the real-time vehicle speed is not greater than the low vehicle speed threshold, the early warning judgment condition is not met, and at this time it is determined that the vehicle steering does not have the risk of rollover, that is, the rollover early warning does not need to be started; When the real-time vehicle speed is greater than the low vehicle speed threshold but not greater than the high vehicle speed threshold, and the steering wheel steering is not greater than the high steering size threshold or the steering wheel angle velocity is not greater than the high steering velocity threshold, the early warning judgment condition is not met, at this time it is determined that the vehicle belongs to the stable steering working condition, otherwise the early warning judgment condition is met; When the real-time vehicle speed is greater than the high vehicle speed threshold, and the steering wheel steering is not greater than the low steering size threshold or the steering wheel angle velocity is not greater than the low steering velocity threshold, the early warning judgment condition is not met, at this time it is determined that the vehicle belongs to the stable steering working condition, otherwise the early warning judgment condition is met.

[0028] It should be noted that when the real-time vehicle speed is not greater than the low vehicle speed threshold, the lateral inertial force of the vehicle is small, and the risk of rollover is extremely low, so there is no need for early warning judgment; when the real-time vehicle speed is greater than the low vehicle speed threshold but not greater than the high vehicle speed threshold, it is a medium-speed driving, if the steering wheel steering is not greater than the high steering size threshold or the steering wheel angle velocity is not greater than the high steering velocity threshold, it represents that the driver is in the stable steering condition, at this time there is also no need for early warning judgment; when the real-time vehicle speed is greater than the high vehicle speed threshold, it is a high-speed driving, and the sensitivity to vehicle rollover is improved under high-speed driving.

[0029] In a specific embodiment, as shown in Figure 2 The early warning judgment condition is as follows: (1) If the real-time vehicle speed ≤50km / h, at this time the vehicle steering does not have the risk of rollover, and it is determined that the rollover early warning does not need to be started; (2) If 50km / h ≤90km / h, if the steering wheel angle size ≤100° or the angle velocity ≤180° / s, it belongs to the stable steering working condition, and it is determined that the rollover early warning is not needed; otherwise, it belongs to the emergency steering working condition, and it is determined that the rollover early warning is needed; (3) If >90km / h, at this time it is a high-speed driving, if the steering wheel angle size ≤60° or the angle velocity ≤120° / s, it belongs to the stable steering working condition, and it is determined that the rollover early warning is not needed; otherwise, it belongs to the emergency steering working condition, and it is determined that the rollover early warning is needed.

[0030] Step S2 of this scheme is based on the LTR dynamic threshold database constructed from massive simulations, and adaptively adjusts the warning threshold according to the real-time vehicle driving parameters that incorporate the driver's real-time steering intentions.

[0031] Specifically, in step S2, the vehicle rollover warning threshold at the current moment is obtained by dynamically matching the LTR dynamic threshold database based on real-time vehicle speed, road surface adhesion coefficient, steering wheel angle and steering wheel angular velocity.

[0032] The LTR dynamic threshold database of this scheme records the relationship between real-time vehicle speed, road surface adhesion coefficient, steering wheel angle and steering wheel angular velocity and rollover warning threshold. Therefore, the rollover warning threshold can be determined in the LTR dynamic threshold database based on real-time vehicle speed, road surface adhesion coefficient, steering wheel angle and steering wheel angular velocity.

[0033] The method for constructing the LTR dynamic threshold database is as follows: An inertial coordinate system is established, and a mechanical equilibrium equation is established based on the forces acting on the vehicle on the x-axis, y-axis, and z-axis to construct a four-degree-of-freedom vehicle dynamics model. The four-degree-of-freedom dynamics model includes the vehicle's longitudinal motion, lateral motion, yaw motion, and roll motion. Real-time vehicle speed, road surface adhesion coefficient, steering wheel angle, and steering wheel angular velocity are input as variables into a four-degree-of-freedom vehicle dynamics model to simulate a "fishhook steering" test condition to induce vehicle rollover. If the vehicle rolls over, the lateral load transfer rate value of 0.1 before the lateral load transfer rate reaches 1 is used as the rollover warning threshold. If the vehicle does not roll over, the rollover warning threshold is 1. The rollover warning thresholds under different real-time vehicle speeds, road surface adhesion coefficients, steering wheel angles, and steering wheel angular velocities are integrated to form an LTR dynamic threshold database.

[0034] like Figure 3 and Figure 4 As shown, an inertial coordinate system XOY is established with the current vehicle's center of mass position as the origin O, the vehicle's longitudinal axis as the x-axis, and the vehicle's transverse axis as the y-axis. Based on the forces acting on the vehicle in the four directions of the x, y, and z axes, the following mechanical equilibrium equations are established: Longitudinal movement: ; Lateral movement: ; Lateral motion: ; Lateral tilting motion: ; Where m is the total vehicle mass, ms Let g be the sprung mass, a and b be the distances from the vehicle's center of gravity to the front and rear axles respectively, and b be the wheelbase. s I is the height of the center of mass of the sprung mass. x with I z These are the vehicle's roll inertia and yaw inertia, respectively. For the vehicle tilt angle, This is the equivalent roll stiffness of the suspension. For the equivalent roll damping of the suspension, v x With v y These represent the longitudinal and lateral velocities of the vehicle, respectively. x With a y These are the longitudinal and lateral accelerations of the entire vehicle, respectively. f is the yaw rate of the vehicle. xfl f is the longitudinal force acting on the left front wheel. yfl The left front wheel is subjected to a lateral force; f xfr f is the longitudinal force acting on the right front wheel. yfr The right front wheel is subjected to a lateral force; f xrl f is the longitudinal force acting on the left rear wheel. yrl The left rear wheel is subjected to a lateral force; f xrr f is the longitudinal force acting on the right rear wheel. yrr The right rear wheel is subjected to a lateral force.

[0035] After constructing a four-degree-of-freedom vehicle dynamics model, this scheme obtains the relationship between the vehicle rollover warning threshold and real-time vehicle speed, road surface adhesion coefficient, steering wheel angle, and steering wheel angular velocity in advance through dynamic simulation offline.

[0036] Specifically, the road surface adhesion coefficient is increased from 0.1 to 1 in a predetermined increment, and the real-time vehicle speed is increased from a low threshold to 120 km / h in a predetermined increment. Different steering wheel angles and angular velocities are also set to obtain the lateral load transfer rate under different vehicle driving parameters. It should be noted that only one variable is controlled for real-time vehicle speed, road surface adhesion coefficient, steering wheel angle, and steering wheel angular velocity to obtain the lateral load transfer rate under different vehicle driving parameters. That is, with any three of these parameters fixed, the remaining parameter is adjusted as a variable.

[0037] In some specific embodiments, the road surface adhesion coefficient is increased from 0.1 to 1 in increments of 0.05, and the real-time vehicle speed is increased from 50 km / h to 120 km / h in increments of 10 km / h.

[0038] This scheme uses the CarSim / Simulink co-simulation platform to simulate a "fishhook steering" test condition on a four-degree-of-freedom vehicle dynamics model to induce vehicle rollover. This allows for the acquisition of vehicle rollover scenarios under different real-time vehicle speeds, road adhesion coefficients, steering wheel angles, and steering wheel angular velocities. If the vehicle does not rollover, a rollover warning threshold (LTR) is defined. th The initial value is 1, but if the vehicle rolls over, the rollover warning threshold (LTR) is set to 0.1, the value of the lateral load transfer rate before it reaches 1. th .

[0039] This scheme integrates a large number of discrete data points obtained from simulations, and constructs a structured four-dimensional lookup table, namely the LTR dynamic threshold database, using MATLAB to combine four input variables (real-time vehicle speed, road surface adhesion coefficient, steering wheel angle, and steering wheel angular velocity) and their corresponding rollover warning thresholds. It should be noted that rollover warning thresholds not present in the four-dimensional lookup table can be obtained through linear interpolation.

[0040] In addition, the lateral load transfer rate of the vehicle at the current moment is calculated based on the vehicle tilt angle and vehicle angular velocity, using the following formula:

[0041] in For the vehicle tilt angle, This is the equivalent roll stiffness of the suspension. For the equivalent roll damping of the suspension, the vehicle angular velocity m is the total mass of the vehicle, g is the acceleration due to gravity, and B is the track width.

[0042] Step S3 of this scheme calculates the rollover warning time of the vehicle at the current moment based on the lateral load transfer rate and the rollover warning threshold. Furthermore, step S3 of this scheme combines the first-order rate of change of the lateral load transfer rate to calculate the rollover warning time, which can quantify the time required to trigger the warning under the current state and changing trend.

[0043] Specifically, such as Figure 5 As shown, the first-order rate of change of the lateral load transfer rate is calculated. If the lateral load transfer rate is less than the rollover warning threshold and the first-order rate of change of the lateral load transfer rate is equal to 0, the rollover warning time is 2s; if the lateral load transfer rate is greater than the rollover warning threshold and the first-order rate of change of the lateral load transfer rate is equal to 0s, the rollover warning time is 0; if the first-order rate of change of the lateral load transfer rate is not 0, the quotient of the difference between the rollover warning threshold and the lateral load transfer rate and the first-order rate of change of the lateral load transfer rate is used as the rollover warning time.

[0044] Specifically, the formula for calculating the rollover warning time of the vehicle at the current moment based on the lateral load transfer rate and the rollover warning threshold is as follows: ; in This is the first-order rate of change of the lateral load transfer rate. For lateral load transfer rate, The threshold for rollover warning.

[0045] The rollover warning time calculated by this scheme directly reflects the urgency of the rollover risk. A shorter rollover warning time indicates a greater risk of rollover in the current dynamic state. The upper limit of the rollover warning time is set to 2, indicating no risk of rollover; the lower limit is set to 0, indicating a very high risk of rollover. Detailed explanations regarding the upper and lower limits of the rollover warning time are as follows: (1) When the vehicle is in a stable driving state, such as when it is driving in a straight line at a constant speed, its body posture is stable and the load on the left and right sides is almost transferred. Therefore, the lateral load transfer rate is close to 0, and since there is no tendency to increase the side tilt, its rate of change is also close to 0. In this case, since the denominator in the calculation formula is close to 0, the value of the rollover warning time is close to infinity. In order to facilitate the calculation, the rollover warning time in this case is set to an upper limit of 2s, which means that the vehicle does not currently have a risk of rollover.

[0046] (2) When the lateral load transfer rate reaches the rollover warning threshold and continues to increase, and the system still does not take intervention measures, the first-order rate of change of the lateral load transfer rate is greater than 0. At this time, the rollover warning time is negative. In order to facilitate the warning, the rollover warning time in this case is set to the lower limit of 0s, indicating that this moment is the latest moment when the anti-rollover control strategy intervenes. If the system still does not take intervention measures at this time, the vehicle will roll over.

[0047] Furthermore, such as Figure 6 As shown, this scheme determines the rollover risk level based on the rollover warning time. If the rollover warning time is equal to 2s, the risk level is defined as 0; if the rollover warning time is less than 2s and not less than 1s, the risk level is defined as 1; if the rollover warning time is less than 1s and greater than or equal to 0, the risk level is defined as 2.

[0048] Right now: (1) If TTR=2, then the vehicle has no risk of rollover and the output risk level is 0. (2) If If the vehicle has a relatively low risk of rolling over, the risk level is output as 1. (3) If 0≤TTR<1, the vehicle has a greater risk of rollover at this time, the risk level is output as 2, and the rollover warning ends.

[0049] In addition, the multi-dimensional vehicle rollover warning method that integrates steering intent in this solution includes the following step: S4: Implement differentiated differential braking control based on risk level.

[0050] like Figure 7 As shown, if the risk level is 0, differential braking control is not executed; if the risk level is 1, low-intensity differential braking control is executed; and if the risk level is 2, high-intensity differential braking control is executed. Furthermore, this scheme inputs the differential braking intensity level into the wheel braking force calculation unit to calculate the required braking force for each wheel, and the EMB outputs the braking force to achieve differential braking anti-rollover control.

[0051] As mentioned earlier, the multi-dimensional vehicle real-change rollover warning method that integrates steering intention provided by this solution is a vehicle real-change LTR / TTR rollover warning method that takes into account the driver's steering intention. It can solve the problem that the warning threshold is fixed or only changes with vehicle speed and road surface in the existing technology, and cannot identify the driver's steering intention, resulting in warning lag or false alarm. Compared with fixed warning threshold, it can make rollover warning earlier, leaving more reaction time for vehicle anti-rollover control, thereby effectively improving driving safety.

[0052] The following is a specific example to illustrate this: The vehicle model used in this application to construct the LTR dynamic threshold database is a sport utility vehicle (SUV). The specific simulation vehicle parameters are shown in Table 1. Table 1 Simulation Vehicle Parameter Table .

[0053] The road surface adhesion coefficient μ is set to increase from 0.1 to 1 in increments of 0.05, and the vehicle speed V... x All speeds increase from 50 km / h to 120 km / h in increments of 10 km / h, and are adjusted according to the steering wheel angle. and steering wheel angular velocity The different conditions are divided into 4 different groups: Working condition 1: Corner size 90°, angular velocity 300° / s; Working condition 2: Corner size 150°, angular velocity 300° / s; Operating Condition 3: Corner Size 90°, angular velocity 200° / s; Operating Condition 4: Corner Size 150°, angular velocity It is 200° / s.

[0054] The process of constructing the LTR dynamic threshold database through offline simulation is as follows: By combining four key input variables—vehicle speed, road adhesion coefficient, steering wheel angle, and steering velocity—the "fishhook steering" test condition is simulated to induce vehicle rollover, and the vehicle rollover warning threshold (LTR) is accurately determined for each combination of conditions. th For test scenarios involving vehicle rollover, the definition is... The LTR value 0.1 seconds before the vehicle first reaches 1 is the rollover warning threshold. If the vehicle will not rollover, the rollover warning threshold is recorded as 1. The simulation data were then processed to obtain the following four sets of dynamic LTR thresholds for different operating conditions, as shown in Tables 2 to 5: Table 2. Dynamic Thresholds of LTR under Operating Condition 1 .

[0055] Table 3. Dynamic Threshold Table of LTR under Operating Condition 2 .

[0056] Table 4. Dynamic Threshold Table for LTR under Operating Condition 3 .

[0057] Table 5. Dynamic Threshold Table for LTR under Operating Condition 4 .

[0058] As shown in Tables 2 to 5, the LTR dynamic threshold tables indicate that vehicles are more prone to rollover when the road adhesion coefficient is higher and the turning speed is higher. Therefore, four sets of tests were conducted to verify the optimization effect of the rollover warning threshold under different vehicle speeds and road adhesion coefficients at a steering wheel angle of 120° and a turning speed of 240° / s. The road adhesion coefficients and vehicle speeds for the four sets of tests were 0.9 and 85 km / h, 0.9 and 95 km / h, 0.95 and 85 km / h, and 0.95 and 95 km / h, respectively. The value before optimization was a fixed value of 0.85, and the value after optimization was obtained based on the LTR dynamic threshold table of this scheme. The comparison results of the rollover warning threshold before and after optimization are shown in Table 6. Table 6 Comparison of rollover warning thresholds before and after optimization .

[0059] Furthermore, the optimization effects of rollover warning time and rollover time were verified under four different vehicle speeds and road adhesion coefficients at a steering wheel angle of 120° and a turning velocity of 240° / s. Before optimization, the latest intervention time for rollover warning was the moment when the TTR value was 0 when LTRth was set to a fixed value of 0.85; that is, the ratio of the difference between the fixed LTR value of 0.85 and the current LTR to the first-order rate of change of LTR. After optimization, the latest intervention time for rollover warning was the moment when the TTR value was 0 when LTRth was set to a dynamic threshold according to this scheme; the rollover time was the moment when the TTR value was 0 when LTRth was set to 1. The comparison results of rollover warning time before and after optimization are shown in Table 7: Table 7 Comparison Results of Rollover Warning Time Before and After Optimization .

[0060] The comparison results in Tables 6 and 7 show that the larger the road adhesion coefficient μ and the faster the vehicle speed Vx, the higher the risk of vehicle rollover. This is consistent with vehicle dynamics characteristics, namely, a higher adhesion coefficient allows for greater lateral force without skidding, but this actually increases the likelihood of the vehicle tripping and rolling over. Therefore, considering different vehicle speeds, road adhesion coefficients, steering wheel angles, and angular velocities, rollover warning thresholds can provide more reaction time for vehicle rollover prevention control. Furthermore, under the four set operating conditions, with the same vehicle speed and road adhesion coefficient, compared to the fixed warning threshold of 0.85, the optimized dynamic thresholds were reduced by 0.0902, 0.1294, 0.1279, and 0.1544, respectively. This smaller threshold resulted in earlier warning times, advancing the latest intervention time by 0.03s, 0.04s, 0.04s, and 0.046s, respectively. For high-center-of-gravity SUVs, the rollover process can happen in an instant under extreme conditions. These tens of milliseconds of lead time are crucial, as they provide an opportunity for the driver to make corrective actions or for the vehicle's active safety systems to intervene.

[0061] Example 3 This embodiment also provides an electronic device, see reference. Figure 8 It includes a memory 404 and a processor 402. The memory 404 stores a computer program, and the processor 402 is configured to run the computer program to perform the steps in any of the above method embodiments. The memory 404 can be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 402.

[0062] The processor 402 reads and executes computer program instructions stored in the memory 404 to implement any of the multi-dimensional vehicle rollover warning methods that integrate steering intentions in the above embodiments.

[0063] Optionally, the electronic device may further include a transmission device 406 and an input / output device 408, wherein the transmission device 406 is connected to the processor 402, and the input / output device 408 is connected to the processor 402. The transmission device 406 can be used to receive or send data via a network. The input / output device 408 is used to input or output information. In this embodiment, the input information may be vehicle driving parameters, etc., and the output information may be rollover warning time, rollover warning threshold, or rollover risk level, etc.

[0064] Optionally, in this embodiment, the processor 402 can be configured to perform the following steps via a computer program: S1: Obtain the vehicle driving parameters at the current moment. If the vehicle driving parameters meet the warning judgment conditions, then execute step S2. The vehicle driving parameters include real-time vehicle speed, steering wheel angle, steering wheel angular velocity, vehicle tilt angle, vehicle angular velocity, and road surface adhesion coefficient. S2: Based on the vehicle driving parameters, dynamically match the LTR dynamic threshold database to obtain the vehicle's rollover warning threshold at the current moment, and calculate the vehicle's lateral load transfer rate at the current moment. S3: Calculate the rollover warning time of the vehicle at the current moment based on the lateral load transfer rate and the rollover warning threshold, and determine the rollover risk level based on the rollover warning time.

[0065] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0066] Generally, various embodiments can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects of the invention can be implemented in hardware, while others can be implemented by firmware or software executed by a controller, microprocessor, or other computing device, but the invention is not limited thereto. Although various aspects of the invention may be shown and described as block diagrams, flowcharts, or using some other graphical representation, it should be understood that, by way of non-limiting example, these blocks, apparatuses, systems, techniques, or methods described herein can be implemented in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0067] Embodiments of the present invention can be implemented by computer software, which may be executable by a data processor of a mobile device, such as a processor entity, or by hardware, or by a combination of software and hardware. Computer software or programs (also referred to as program products), including software routines, applets, and / or macros, can be stored in any device-readable data storage medium, and they include program instructions for performing specific tasks. A computer program product may include one or more computer-executable components configured to perform embodiments when the program is run. One or more computer-executable components may be at least one piece of software code or a portion thereof. Additionally, it should be noted that any block in the logical flow of the figures may represent a program step, or interconnected logical circuitry, blocks and functions, or a combination of program steps and logical circuitry, blocks and functions. The software may be stored on physical media such as memory chips or blocks of storage implemented within a processor, magnetic media such as hard disks or floppy disks, and optical media such as, for example, DVDs and their data variants, CDs, etc. The physical medium is a non-transient medium.

Claims

1. A multi-dimensional vehicle real-time roll-over warning method fusing steering intention, characterized in that, The method comprises the following steps: S1: obtaining vehicle driving parameters of the vehicle at the current time, and if the vehicle driving parameters meet the pre-warning judgment condition, executing step S2, wherein the vehicle driving parameters include real-time vehicle speed, steering wheel angle size, steering wheel angle speed, vehicle inclination angle, vehicle angular speed, and road adhesion coefficient; S2: dynamically matching the LTR dynamic threshold database based on the vehicle driving parameters to obtain the vehicle rollover pre-warning threshold at the current time, and calculating the lateral load transfer rate of the vehicle at the current time; S3: calculating the vehicle rollover pre-warning time at the current time according to the lateral load transfer rate and the rollover pre-warning threshold, and determining the rollover risk level based on the rollover pre-warning time.

2. The multi-dimension vehicle real-time rollover warning method fusing steering intention according to claim 1, characterized in that, The real-time vehicle speed is obtained in real time by a wheel speed sensor, the steering wheel angle size and the steering wheel angle speed are obtained in real time by a steering force angle sensor, the vehicle inclination angle and the vehicle angular speed are obtained in real time by a dynamic inclination angle sensor, and the road adhesion coefficient is calculated by a road adhesion coefficient estimation unit.

3. The multi-dimension vehicle real-time rollover warning method fusing steering intention according to claim 1, characterized in that, When the real-time vehicle speed is not greater than the low vehicle speed threshold, the pre-warning judgment condition is not met; when the real-time vehicle speed is greater than the low vehicle speed threshold but not greater than the high vehicle speed threshold, and the steering wheel turning is not greater than the high steering size threshold or the steering wheel angle speed is not greater than the high steering speed threshold, the pre-warning judgment condition is not met; when the real-time vehicle speed is greater than the high vehicle speed threshold, and the steering wheel turning is not greater than the low steering size threshold or the steering wheel angle speed is not greater than the low steering speed threshold, the pre-warning judgment condition is not met.

4. The multi-dimension vehicle real-time rollover warning method fusing steering intention according to claim 1, characterized in that, The LTR dynamic threshold database is dynamically matched based on the real-time vehicle speed, the road adhesion coefficient, the steering wheel angle size, and the steering wheel angle speed to obtain the vehicle rollover pre-warning threshold at the current time.

5. The multi-dimension vehicle real-time roll-over warning method fusing steering intention according to claim 1, wherein, The relationship between the real-time vehicle speed, the road adhesion coefficient, the steering wheel angle size, the steering wheel angle speed, and the rollover pre-warning threshold is recorded in the LTR dynamic threshold database, so the rollover pre-warning threshold can be determined in the LTR dynamic threshold database according to the real-time vehicle speed, the road adhesion coefficient, the steering wheel angle size, and the steering wheel angle speed.

6. The multi-dimension vehicle real-time rollover warning method fusing steering intention according to claim 1, characterized in that, The construction method of the LTR dynamic threshold database is as follows: An inertial coordinate system is established, and a four-degree-of-freedom vehicle dynamics model is constructed according to the force received by the vehicle on the x-axis, the y-axis, and the z-axis, wherein the four-degree-of-freedom dynamics model includes the longitudinal motion, the lateral motion, the yaw motion, and the roll motion of the vehicle; The real-time vehicle speed, the road adhesion coefficient, the steering wheel angle size, and the steering wheel angle speed are input as variables into the four-degree-of-freedom vehicle dynamics model, a "fishhook turning" test condition is simulated to induce vehicle rollover, the value of the lateral load transfer rate before the vehicle rolls over to reach 1 at 0.1 of the lateral load transfer rate is taken as the rollover pre-warning threshold, if the vehicle does not roll over, the rollover pre-warning threshold is 1, and the rollover pre-warning thresholds under different real-time vehicle speeds, road adhesion coefficients, steering wheel angle sizes, and steering wheel angle speeds are integrated to form the LTR dynamic threshold database.

7. The multi-dimension vehicle real-time roll-over warning method fusing steering intention according to claim 1, wherein, A first order change rate of the lateral load transfer ratio is calculated, if the lateral load transfer ratio is less than the rollover early warning threshold and the first order change rate of the lateral load transfer ratio is equal to 0, the rollover early warning time is 2s; if the lateral load transfer ratio is greater than the rollover early warning threshold and the first order change rate of the lateral load transfer ratio is equal to 0, the rollover early warning time is 0; if the first order change rate of the lateral load transfer ratio is not equal to 0, a difference value between the rollover early warning threshold and the lateral load transfer ratio and a quotient value of the first order change rate of the lateral load transfer ratio are calculated as the rollover early warning time.

8. The multi-dimension vehicle real-time rollover warning method fusing steering intention according to claim 7, characterized in that, A rollover risk level is determined based on the rollover early warning time, if the rollover early warning time is equal to 2s, the risk level is defined as 0; if the rollover early warning time is less than 2s and not less than 1s, the risk level is defined as 1; If the rollover early warning time is less than 1s and not less than 0, the risk level is defined as 2.

9. The multi-dimension vehicle real-time roll-over warning method fusing steering intention according to claim 1, wherein, The method further comprises S4: realizing differentiated differential braking control based on the risk level. 10.An electronic device comprising a memory and a processor, the electronic device characterized by, The memory stores a computer program, and the processor is configured to run the computer program to execute the multi-dimensional vehicle real-time rollover early warning method of fusion steering intention. The memory stores a computer program, and the processor is configured to run the computer program to execute the multi-dimensional vehicle real-time rollover early warning method of fusion steering intention.

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