Vehicle acceleration parameter detection control method and system and electronic equipment

Abstract

The invention provides a vehicle acceleration parameter detection control method and system and electronic equipment, and relates to the field of vehicle detection control. According to the method, the transverse acceleration of a vehicle is estimated through the steering angle of a steering wheel and the wheel speed difference value of a front shaft and a rear shaft, and verification detection is conducted on the transverse acceleration and the actually-measured transverse acceleration; therefore, the transverse acceleration is comprehensively detected from the perspective of vehicle dynamics, interference signals generated when the vehicle runs unstably can be accurately recognized, the obtaining precision of the transverse acceleration of the vehicle is improved, and the false alarm probability of an electronic stability system of the vehicle is reduced.

Description

Technical Field

[0001] This invention relates to the field of vehicle detection and control, and in particular to a method, system, and electronic device for detecting and controlling vehicle acceleration parameters. Background Technology

[0002] Accurate acquisition of lateral acceleration signals is crucial for vehicles. For example, in certain driving conditions, when the electronic stability system needs to control the vehicle precisely, if the acceleration signal input by the inertial sensor to the electronic stability system cannot accurately reflect the real lateral acceleration of the vehicle, it may result in unstable vehicle control or even complete vehicle instability, posing a serious safety hazard.

[0003] Due to the complex driving environment, vehicles can interfere with inertial sensors when driving on bumpy or sloping roads. Current technologies have limited methods for detecting such interference, and the acceleration signals collected by inertial sensors are prone to interference when the vehicle is driving unstablely. This not only affects the accuracy of obtaining the vehicle's lateral acceleration, but also easily leads to false alarms in the vehicle's electronic stability system. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a vehicle acceleration parameter detection and control method, system and electronic device. The method estimates the lateral acceleration of the vehicle by using the steering wheel angle and the difference in wheel speed between the front and rear axles, and verifies and detects it with the measured lateral acceleration. Thus, the lateral acceleration is comprehensively detected from the perspective of vehicle dynamics. It can accurately identify interference signals when the vehicle is driving unstablely, thereby improving the accuracy of obtaining the lateral acceleration of the vehicle and reducing the false alarm probability of the vehicle electronic stability system.

[0005] In a first aspect, embodiments of the present invention provide a method for detecting and controlling vehicle acceleration parameters, the method comprising: The steering angle of the steering wheel and the wheel speed difference between the front and rear axles in the vehicle are obtained, and the vehicle's inertial sensors are used to obtain the measured lateral acceleration and measured yaw rate of the vehicle in real time. The first lateral acceleration of the vehicle is calculated using the steering angle, and the second lateral acceleration of the vehicle is calculated using the wheel speed difference. Calculate the difference between the first and second lateral accelerations and the measured lateral accelerations, respectively. The vehicle's tilt state was obtained by measuring the lateral acceleration, the first lateral acceleration, and the measured yaw rate. The detection results corresponding to the measured lateral acceleration are determined based on the difference detection results and the tilt state results.

[0006] Optionally, the first lateral acceleration of the vehicle is calculated using the steering angle, including: Obtain the vehicle's current speed, characteristic speed, and steering ratio; where the characteristic speed is the vehicle speed at which the yaw rate gain reaches its maximum value. The turning coefficient of the vehicle is calculated using the current vehicle speed, characteristic vehicle speed, and steering gear ratio. The first yaw rate of the vehicle is determined based on the first product of the steering angle and the turning coefficient. The first lateral acceleration of the vehicle is determined by the second product of the first yaw rate and the current vehicle speed.

[0007] Optionally, the second lateral acceleration of the vehicle is calculated using the wheel speed difference, including: Based on the wheel speed difference, the front axle wheel speed difference and the rear axle wheel speed difference are obtained respectively. The front axle yaw rate of the vehicle is calculated using the front axle wheel speed difference, and the rear axle yaw rate of the vehicle is calculated using the rear axle wheel speed difference. The first weighting coefficients corresponding to the front and rear axles are determined using the vehicle's real-time load distribution data; The second yaw rate of the vehicle is determined by the weighted sum of the front axle yaw rate and the rear axle yaw rate calculated by the first weighting factor; The estimated yaw rate of the vehicle is determined by the ratio of the measured lateral acceleration to the current vehicle speed. The reference yaw acceleration of the vehicle is calculated based on the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate. The second lateral acceleration corresponding to the vehicle is determined based on the third product of the reference yaw acceleration and the current vehicle speed.

[0008] Optionally, the step of calculating the vehicle's reference yaw acceleration based on the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate includes: Obtain the second weighting coefficient corresponding to the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate; wherein, the second weighting coefficient is the reciprocal of the product of any one of the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate with the difference between the other three yaw rates; The reference yaw acceleration of the vehicle is determined by the weighted sum of the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate calculated using the second weighting factor.

[0009] Optionally, the steps of obtaining the vehicle's tilt state results through measured lateral acceleration, first lateral acceleration, and measured yaw rate include: Calculate the first side slip angle of the vehicle under the current road surface using the measured lateral acceleration and measured yaw rate; The second lateral slip angle of the vehicle under the current road surface is calculated using the first lateral acceleration and the measured yaw rate. The vehicle's tilt state is obtained by comparing the first and second sideslip angles with a preset threshold.

[0010] Optionally, the step of calculating the first slip angle of the vehicle under the current road surface using the measured lateral acceleration and measured yaw rate includes: The third lateral acceleration of the vehicle is determined by the fourth product of the measured yaw rate and the current vehicle speed. Obtain the difference in lateral acceleration between the third lateral acceleration and the measured lateral acceleration, and use the arcsine result of the lateral acceleration difference to determine the first slip angle of the vehicle under the current road surface.

[0011] Optionally, the step of determining the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result includes: If the difference detection result meets the preset difference judgment relationship, then determine whether the tilt state result meets the preset tilt judgment relationship. When the tilt state result satisfies the tilt judgment relationship, the unreliable lateral acceleration fault debounce count corresponding to the inertial sensor is set. The detection result corresponding to the measured lateral acceleration is determined by using the unreliable fault debounce count of lateral acceleration.

[0012] Optionally, the step of determining the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result further includes: If the difference detection result does not meet the difference judgment relationship, or the tilt state result does not meet the tilt judgment relationship, the lateral acceleration unreliable fault debouncing count will be cleared to zero.

[0013] Secondly, the present invention provides a vehicle acceleration parameter detection and control system, the system comprising: The data acquisition module is used to acquire the steering angle of the steering wheel and the wheel speed difference between the front and rear axles in the vehicle, and to acquire the measured lateral acceleration and measured yaw rate of the vehicle in real time using the vehicle's inertial sensors. The lateral acceleration calculation module is used to calculate the vehicle's first lateral acceleration using the steering angle and the vehicle's second lateral acceleration using the wheel speed difference. The difference detection calculation module is used to calculate the difference detection results between the first lateral acceleration, the second lateral acceleration and the measured lateral acceleration, respectively. The tilt state acquisition module is used to obtain the vehicle's tilt state results through measured lateral acceleration, first lateral acceleration, and measured yaw rate; The detection result determination module is used to determine the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result.

[0014] Thirdly, embodiments of the present invention also provide an electronic device, which includes a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the steps of the vehicle acceleration parameter detection and control method provided in the first aspect.

[0015] Fourthly, embodiments of the present invention also provide a storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the steps of the vehicle acceleration parameter detection and control method provided in the first aspect.

[0016] This invention provides a vehicle acceleration parameter detection and control method, system, and electronic device. In the process of verifying and detecting vehicle acceleration signals collected by a vehicle inertial sensor, the method first acquires the steering angle of the steering wheel and the wheel speed difference between the front and rear axles, and then uses the vehicle's inertial sensor to acquire the measured lateral acceleration and measured yaw rate in real time. Next, it calculates the vehicle's first lateral acceleration using the steering angle and the second lateral acceleration using the wheel speed difference. Subsequently, it calculates the difference detection results between the first and second lateral accelerations and the measured lateral acceleration. Then, it obtains the vehicle's tilt state results using the measured lateral acceleration, the first lateral acceleration, and the measured yaw rate. Finally, it determines the detection result corresponding to the measured lateral acceleration based on the difference detection results and the tilt state results. This method estimates the lateral acceleration of a vehicle by using the steering wheel angle and the difference in wheel speed between the front and rear axles, and then verifies and detects it with the measured lateral acceleration. This allows for a comprehensive detection of lateral acceleration from the perspective of vehicle dynamics, enabling accurate identification of interference signals when the vehicle is driving unstablely. This improves the accuracy of obtaining the vehicle's lateral acceleration and reduces the false alarm probability of the vehicle's electronic stability system.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 A flowchart of a vehicle acceleration parameter detection and control method provided in an embodiment of the present invention; Figure 2 In step S102 of a vehicle acceleration parameter detection and control method provided in an embodiment of the present invention, a flowchart is shown for calculating the first lateral acceleration of the vehicle using the steering angle. Figure 3 In step S102 of a vehicle acceleration parameter detection and control method provided in an embodiment of the present invention, a flowchart is shown for calculating the second lateral acceleration of the vehicle using the wheel speed difference. Figure 4 This is a flowchart of step S305 in a vehicle acceleration parameter detection and control method provided in an embodiment of the present invention; Figure 5 This is a flowchart of step S104 in a vehicle acceleration parameter detection and control method provided in an embodiment of the present invention; Figure 6 This is a flowchart of step S501 in a vehicle acceleration parameter detection and control method provided in an embodiment of the present invention; Figure 7 This is a flowchart of step S105 in a vehicle acceleration parameter detection and control method provided in an embodiment of the present invention; Figure 8 A flowchart of another vehicle acceleration parameter detection and control method provided in an embodiment of the present invention; Figure 9 This is a schematic diagram illustrating the calculation principle of the first side deflection angle in a vehicle acceleration parameter detection and control method provided in an embodiment of the present invention. Figure 10 This is a schematic diagram of a vehicle acceleration parameter detection and control system provided in an embodiment of the present invention; Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0021] icon: 1010 - Data Acquisition Module; 1020 - Lateral Acceleration Calculation Module; 1030 - Difference Detection Calculation Module; 1040 - Tilt State Acquisition Module; 1050 - Detection Result Determination Module; 101 - Processor; 102 - Memory; 103 - Bus; 104 - Communication interface. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] To facilitate understanding of this embodiment, a vehicle acceleration parameter detection and control method disclosed in this embodiment of the invention will first be introduced, such as... Figure 1 As shown, the method includes: Step S101: Obtain the steering angle of the steering wheel and the wheel speed difference between the front and rear axles in the vehicle, and use the vehicle's inertial sensors to obtain the measured lateral acceleration and measured yaw rate of the vehicle in real time.

[0024] This step simultaneously collects two types of core parameters during vehicle operation: first, vehicle control and motion-related parameters, namely the real-time steering angle of the steering wheel (reflecting the driver's control intention) and the difference in wheel speed between the front and rear axles (reflecting the difference in motion state between the front and rear axles); second, inertial sensor measured parameters, which are obtained in real time by the inertial sensors on the vehicle to measure the lateral acceleration (directly characterizing the lateral motion acceleration of the vehicle) and the yaw rate (assisting in judging the vehicle's attitude stability), providing basic data support for subsequent lateral acceleration estimation and interference verification.

[0025] Step S102: Calculate the vehicle's first lateral acceleration using the steering angle, and calculate the vehicle's second lateral acceleration using the wheel speed difference.

[0026] Based on the different parameters collected in step S101, the vehicle's lateral acceleration is estimated from two independent dimensions: First, the first lateral acceleration (theoretical lateral acceleration derived from the driver's control intention) is calculated using the collected steering wheel angle in conjunction with the vehicle dynamics model; Second, the second lateral acceleration (lateral acceleration derived from the actual motion state of the vehicle) is calculated based on the correlation characteristics between the front and rear axle wheel speed difference and the vehicle's lateral motion, forming a dual estimation result to improve the reliability of subsequent verification.

[0027] Step S103: Calculate the difference detection results between the first lateral acceleration, the second lateral acceleration, and the measured lateral acceleration.

[0028] Using the measured lateral acceleration obtained in step S101 as a benchmark, the deviations between the two estimated values ​​and the measured values ​​are calculated to obtain the corresponding difference detection results. The core purpose of this step is to preliminarily determine the degree of agreement between the estimated and measured values ​​by quantifying the deviations, thus providing basic deviation data for subsequent identification of interference signals.

[0029] Step S104: Obtain the vehicle's tilt state results by measuring the lateral acceleration, the first lateral acceleration, and the measured yaw rate.

[0030] By combining three types of parameters—measured lateral acceleration, first lateral acceleration (derived value from control intention), and measured yaw rate—the vehicle's tilt state is obtained through vehicle attitude dynamics analysis. This step can accurately identify the vehicle's attitude changes when driving on bumpy or tilted road sections, determine whether the inertial sensors are affected by tilt interference, and provide a basis for attitude judgment to distinguish between real lateral acceleration and interference signals.

[0031] Step S105: Determine the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result.

[0032] Based on the difference detection results from step S103 (reflecting the degree of deviation between the estimation and the actual measurement) and the tilt state results from step S104 (reflecting whether the sensor is interfered with), a comprehensive analysis and judgment are performed to finally determine the detection result corresponding to the measured lateral acceleration. If it is determined that there is no interference and the deviation is within a reasonable range, the measured value is confirmed to be valid; if there is interference or abnormal deviation, the measured value is marked as unreliable, thereby achieving accurate filtering of interference signals and ensuring the accuracy of lateral acceleration acquisition.

[0033] Optionally, the vehicle's first lateral acceleration can be calculated using the steering angle, such as... Figure 2 As shown, it includes: Step S201: Obtain the vehicle's current speed, characteristic speed, and steering ratio; wherein, the characteristic speed is the vehicle speed at which the yaw rate gain reaches its maximum value.

[0034] This step precisely acquires three sets of key parameters related to vehicle steering and driving characteristics: first, the vehicle's current speed (reflecting the vehicle's real-time speed state); second, the vehicle's characteristic speed (defined as the speed at which the vehicle's yaw rate gain reaches its maximum value, and is one of the core parameters characterizing the vehicle's dynamics); and third, the vehicle's steering ratio (a key transmission parameter connecting the steering wheel angle and the wheel angle, reflecting the transmission efficiency of the driver's steering operation). These three sets of parameters together provide fundamental data support for subsequent calculations of the turning coefficient and derivation of lateral acceleration.

[0035] Step S202: Calculate the vehicle's turning coefficient using the current vehicle speed, characteristic vehicle speed, and steering gear ratio.

[0036] Based on the current vehicle speed, characteristic vehicle speed, and steering ratio collected in step S201, the vehicle's turning coefficient is calculated by substituting them into a preset vehicle dynamics calculation model. This turning coefficient is a core intermediate parameter that correlates steering wheel operation with the vehicle's turning motion state, such as the Ackermann constant. Its function is to transform the abstract steering angle parameter into a quantified coefficient that can be used for subsequent yaw rate calculations.

[0037] Step S203: Determine the first yaw rate of the vehicle based on the first product of the steering angle and the turning coefficient.

[0038] The steering wheel angle obtained in step S201 is multiplied by the turning coefficient calculated in step S202 to obtain the first product result, which is the first yaw rate of the vehicle. This yaw rate is a theoretical value derived from the driver's steering intention and reflects the yaw rate of the vehicle that should be generated by the corresponding steering operation under ideal driving conditions.

[0039] Step S204: Determine the first lateral acceleration of the vehicle based on the second product of the first yaw rate and the current vehicle speed.

[0040] The first yaw rate obtained in step S203 is multiplied by the current vehicle speed obtained in step S201 to obtain the second product result, which is the first lateral acceleration of the vehicle. From the perspective of dynamics, lateral acceleration is directly related to yaw rate and vehicle speed. This product operation can convert the theoretical yaw rate into the corresponding theoretical lateral acceleration, thus completing the estimation of lateral acceleration based on the steering angle.

[0041] Optionally, the second lateral acceleration of the vehicle can be calculated using the wheel speed difference, such as... Figure 3 As shown, it includes: Step S301: Based on the wheel speed difference, obtain the front axle wheel speed difference and the rear axle wheel speed difference respectively. Calculate the front axle yaw rate of the vehicle using the front axle wheel speed difference and calculate the rear axle yaw rate of the vehicle using the rear axle wheel speed difference.

[0042] This step first further breaks down the obtained wheel speed difference values ​​to obtain the front axle wheel speed difference value (the difference in wheel speed between the left and right wheels of the front axle) and the rear axle wheel speed difference value (the difference in wheel speed between the left and right wheels of the rear axle). Then, using the front axle wheel speed difference value and the rear axle wheel speed difference value, combined with inherent parameters such as the vehicle's track width, the front axle yaw rate (reflecting the rotational state of the front axle) and the rear axle yaw rate (reflecting the rotational state of the rear axle) of the vehicle are calculated through a dynamic model, providing axle data support for the subsequent synthesis of the whole vehicle yaw rate.

[0043] Step S302: Determine the first weighting coefficients corresponding to the front and rear axles using the vehicle's real-time load distribution data.

[0044] Real-time load distribution data during vehicle operation is collected (this data reflects the load distribution ratio between the front and rear axles, which is affected by factors such as vehicle load and driving posture). Based on this load distribution data, the first weighting coefficients corresponding to the front and rear axles are determined. The core of setting the weighting coefficients is to match the contribution of the front and rear axles to the yaw motion of the whole vehicle under different load distributions, so as to ensure that the subsequently synthesized yaw rate is more in line with the actual motion state of the vehicle.

[0045] Step S303: Determine the second yaw rate of the vehicle by the weighted sum of the front axle yaw rate and the rear axle yaw rate calculated by the first weighting coefficient.

[0046] The front axle yaw rate and rear axle yaw rate calculated in step S301 are multiplied by the corresponding first weighting coefficients determined in step S302, and then the two products are summed (i.e., weighted summation). This summation result is the vehicle's second yaw rate. This step integrates the rotational state information of the front and rear axles through weighted synthesis to obtain a comprehensive yaw rate that characterizes the yaw motion of the entire vehicle.

[0047] Step S304: Determine the estimated yaw rate of the vehicle based on the ratio of the measured lateral acceleration to the current vehicle speed.

[0048] The measured lateral acceleration obtained in step S101 is compared with the current vehicle speed obtained in step S201 to obtain the estimated yaw rate of the vehicle. From a dynamic perspective, there is a corresponding relationship between lateral acceleration, yaw rate, and vehicle speed. By using this ratio calculation, an estimated yaw rate that matches the measured lateral acceleration can be derived in reverse, providing supplementary data for subsequent calculation of the reference yaw acceleration.

[0049] Step S305: Calculate the reference yaw acceleration of the vehicle based on the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate.

[0050] Using the estimated yaw rate obtained in step S304, the second yaw rate obtained in step S303, the first yaw rate obtained in step S203, and the measured yaw rate as input parameters, the vehicle's reference yaw acceleration can be obtained through fusion calculation. The core purpose of this step is to integrate multi-dimensional angular velocity data, reduce the influence of errors from single data points, and obtain a more accurate and reliable yaw acceleration reference value.

[0051] Step S306: Determine the second lateral acceleration corresponding to the vehicle based on the third product of the reference yaw acceleration and the current vehicle speed.

[0052] The reference yaw acceleration calculated in step S305 is multiplied by the current vehicle speed obtained in step S201 to obtain a third product result, which is the second lateral acceleration corresponding to the vehicle. Through this product operation, the precise reference yaw acceleration is converted into the corresponding lateral acceleration, completing the lateral acceleration estimation based on the wheel speed difference, and providing another dimension of reliable estimation data for subsequent verification with the measured lateral acceleration.

[0053] Optionally, step S305, which calculates the vehicle's reference yaw acceleration based on the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate, is as follows: Figure 4 As shown, it includes: Step S401: Obtain the second weighting coefficient corresponding to the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate; wherein, the second weighting coefficient is the reciprocal of the product of any one of the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate with the difference between the other three yaw rates.

[0054] First, the second weighting coefficients for each of the four key angular velocity parameters (measured yaw rate, second yaw rate, estimated yaw rate, and first yaw rate) are obtained. The core definition of the second weighting coefficient is: for each type of angular velocity, the corresponding weighting coefficient is equal to the reciprocal of the product of the differences between that angular velocity and the other three types of angular velocities. The design logic of this weighting coefficient is that the greater the deviation of a certain type of angular velocity from the other three types, the larger the absolute value of its corresponding product, and the smaller the absolute value of the weighting coefficient, thus reducing the interference of large-deviation outlier data on subsequent calculation results.

[0055] In layman's terms, among the four yaw angular velocities—the measured yaw angular velocity, the second yaw angular velocity, the estimated yaw angular velocity, and the first yaw angular velocity—any one yaw angular velocity is selected. The difference between this yaw angular velocity and the other three yaw angular velocities is calculated, and the absolute value of each difference is obtained. Then, the product of these three absolute values ​​is calculated, and its reciprocal is taken as the second weighting coefficient corresponding to that yaw angle.

[0056] Step S402: Determine the reference yaw acceleration of the vehicle by weighting the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate calculated by the second weighting coefficient.

[0057] The four types of angular velocity parameters are each multiplied by their corresponding second weighting coefficients, and then the four product results are summed (i.e., a weighted sum). This summation is the vehicle's reference yaw acceleration. This step integrates multi-dimensional angular velocity data through weighted fusion, which effectively balances the reliability of various data types, filters out errors from individual data, and ultimately obtains a more accurate and stable reference yaw acceleration.

[0058] Optionally, step S104, which obtains the vehicle's tilt state results through measured lateral acceleration, first lateral acceleration, and measured yaw rate, is as follows: Figure 5 As shown, it includes: Step S501: Calculate the first slip angle of the vehicle under the current road surface using the measured lateral acceleration and measured yaw rate.

[0059] Using the measured lateral acceleration and yaw rate collected by inertial sensors as the core input parameters, and substituting them into a preset vehicle sideslip angle calculation model, the first sideslip angle corresponding to the vehicle under the current road driving conditions is obtained. This sideslip angle directly reflects the actual sideslip state of the vehicle derived from the sensor measurement data and is the basic measured basis for judging the vehicle attitude.

[0060] Step S502: Calculate the second slip angle of the vehicle under the current road surface using the first lateral acceleration and the measured yaw rate.

[0061] Using the first lateral acceleration derived in step S204 (a theoretical estimate based on the steering wheel angle) and the measured yaw rate collected by the inertial sensor as input parameters, and substituting them into the same sideslip angle calculation model as in step S501, the second sideslip angle corresponding to the vehicle's current road driving conditions is obtained. This sideslip angle is a theoretical sideslip state derived based on the driver's steering intention, used to compare with the measured sideslip angle to identify abnormal interference factors.

[0062] Step S503: Obtain the vehicle tilt state result based on the comparison result of the first slip angle and the second slip angle with the preset threshold.

[0063] A threshold value for the sideslip angle deviation is preset (this threshold value is calibrated based on vehicle dynamics characteristics and actual test data, and is used to distinguish between normal sideslip and abnormal sideslip caused by disturbance). The difference between the first sideslip angle obtained in step S501 and the second sideslip angle obtained in step S502 is calculated, and then the difference result is compared with the preset threshold value. If the difference result exceeds the preset threshold value, it is determined that the vehicle is under disturbance conditions such as tilting or bumping; if the difference result is within the preset threshold value range, it is determined that the vehicle is not affected by tilting disturbance and the driving posture is stable, and finally the corresponding vehicle tilt state result is output.

[0064] Optionally, step S501, which calculates the first slip angle of the vehicle under the current road surface using the measured lateral acceleration and measured yaw rate, is as follows: Figure 6 As shown, it includes: Step S601: Determine the third lateral acceleration of the vehicle by using the fourth product of the measured yaw rate and the current vehicle speed. Using the measured yaw rate collected by inertial sensors and the vehicle's current speed during travel as core input parameters, the two parameters are multiplied (i.e., the fourth product result), and the third lateral acceleration of the vehicle is obtained through this calculation. This third lateral acceleration is a theoretical lateral acceleration derived based on the vehicle's yaw motion characteristics. It reflects the theoretical value of lateral acceleration that matches the measured yaw rate under ideal conditions (no road tilt, no sensor interference), providing a benchmark reference for subsequent deviation analysis.

[0065] Step S602: Obtain the difference in lateral acceleration between the third lateral acceleration and the measured lateral acceleration, and use the arcsine result of the difference in lateral acceleration to determine the first slip angle of the vehicle under the current road surface.

[0066] First, the difference between the third lateral acceleration obtained in step S601 and the measured lateral acceleration collected by the inertial sensor is calculated to obtain the lateral acceleration difference value. Then, an arcsine function operation is performed on this lateral acceleration difference value, and the result is the first sideslip angle corresponding to the vehicle under the current road driving conditions. The physical significance of this sideslip angle is that it quantitatively characterizes the degree of deviation between the measured lateral acceleration and the lateral acceleration derived from the ideal yaw motion, thereby reflecting the attitude deviation of the vehicle caused by road tilt or sensor interference.

[0067] The calculation principle diagram for the first side deflection angle is as follows: Figure 9 As shown, Figure 9 In This represents the difference in lateral acceleration. It is the acceleration due to gravity. The first side slip angle; there is a sinusoidal relationship between the first side slip angle and the ratio of the difference in lateral acceleration to gravitational acceleration.

[0068] Similarly, the calculation process of the second side slip angle of the vehicle under the current road surface using the first lateral acceleration and the measured yaw rate in step S502 can be referred to in steps S601 and S602. It also has a sinusoidal relationship, so it will not be described again.

[0069] Optionally, step S105, which determines the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result, is as follows: Figure 7 As shown, it includes: Step S701: If the difference detection result satisfies the preset difference judgment relationship, then determine whether the tilt state result satisfies the preset tilt judgment relationship.

[0070] First, the difference detection result obtained in step S103 (i.e., the quantified deviation values ​​of the first lateral acceleration and the second lateral acceleration from the measured lateral acceleration) is retrieved, and it is determined whether the difference detection result meets the preset difference judgment relationship. The preset difference judgment relationship here refers to the pre-calibrated deviation threshold range, which is used to define whether the deviation between the estimated value and the measured value is within a reasonable range. If the difference detection result meets the relationship, the tilt state result obtained in step S104 is further retrieved, and it is determined whether it meets the preset tilt judgment relationship (i.e., whether the vehicle is in a tilted, bumpy, or other disturbing working condition), thus forming a progressive judgment logic of deviation reasonableness and working condition interference.

[0071] Step S702: When the tilt state result satisfies the tilt judgment relationship, the unreliable lateral acceleration fault de-jitter count corresponding to the inertial sensor is set.

[0072] When the tilt state result in step S701 meets the preset tilt judgment relationship (i.e., the vehicle is determined to be in an interference condition), the anti-shake counting for the unreliable lateral acceleration fault of the inertial sensor is immediately initiated. The core function of this anti-shake counting mechanism is to filter instantaneous interference signals, avoid misjudgments caused by occasional conditions such as single road bumps or brief tilts, and ensure the stability and reliability of fault judgment. During the counting process, the count is accumulated according to a preset time step. If the interference condition persists, the count increases; if the interference disappears, the count is reset to zero.

[0073] Step S703: Determine the detection result corresponding to the measured lateral acceleration using the unreliable fault debounce count of lateral acceleration.

[0074] Based on the anti-shake count value of the unreliable lateral acceleration fault obtained in step S702, and combined with the preset counting threshold, the final detection result corresponding to the measured lateral acceleration is determined. The specific judgment rule is as follows: if the anti-shake count value reaches the preset threshold, it indicates that the interference condition lasts for a long time, and the measured lateral acceleration collected by the inertial sensor is severely affected by the interference, and the measured value is judged to be unreliable; if the anti-shake count value does not reach the preset threshold, it indicates that the interference is a transient and occasional situation, and the measured lateral acceleration is judged to be reliable and can be used as a valid input parameter of the vehicle electronic stability system.

[0075] Optionally, the step of determining the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result further includes: if the difference detection result does not meet the difference judgment relationship, or the tilt state result does not meet the tilt judgment relationship, the unreliable lateral acceleration fault de-vibration count is cleared to zero. If in step S701 it is determined that the difference detection result does not meet the preset difference judgment relationship (i.e., the deviation between the first and second lateral accelerations and the measured lateral acceleration exceeds a reasonable threshold, indicating that the measured value may be abnormal), or the tilt state result does not meet the preset tilt judgment relationship (i.e., the vehicle is not in a tilted, bumpy, or other interfering condition, and there are no interfering factors causing the measured value deviation), then the unreliable lateral acceleration fault de-vibration count corresponding to the inertial sensor is immediately cleared to zero. The core purpose of this reset mechanism is to avoid occasional deviation fluctuations or the accumulation of invalid counts under non-interfering conditions, ensuring that the fault de-vibration count is only effectively counted under continuous interference conditions, thereby improving the accuracy of subsequent measured lateral acceleration reliability determination.

[0076] The control flow in the above embodiments can be referred to as follows: Figure 8 The flowchart of another vehicle acceleration parameter detection and control method shown includes: Step S801: Calculate the absolute value of the difference between the measured lateral acceleration and the estimated lateral acceleration based on the steering wheel angle.

[0077] The measured lateral acceleration collected by the inertial sensor and the first lateral acceleration derived from the steering wheel angle (i.e., the lateral acceleration estimated by the steering wheel angle) are retrieved, and the absolute value of the difference between the two parameters is calculated. This absolute value quantifies the degree of deviation between the theoretical lateral acceleration derived from the driver's driving intention and the lateral acceleration measured by the sensor, providing the first set of core data for subsequent judgment of the reasonableness of the deviation.

[0078] Step S802: Calculate the absolute value of the difference between the measured lateral acceleration and the reference lateral acceleration estimated from the wheel speed difference.

[0079] Based on vehicle dynamics theory, a yaw rate is estimated separately using the wheel speed difference of the front axle and another using the wheel speed difference of the rear axle. Then, the real-time load distribution coefficient of the vehicle is used as a weighting factor, and the weighted sum of the two yaw rates estimated by wheel speed difference is obtained as the yaw rate estimated by wheel speed difference. Next, the measured lateral acceleration is divided by the vehicle speed to obtain the yaw rate estimated by lateral acceleration. For each of the measured yaw rate, the yaw rate estimated by wheel speed difference, the yaw rate estimated by measured lateral acceleration, and the yaw rate estimated by steering wheel angle, a weighting factor is calculated, resulting in four weighting factors. These four yaw rates are then multiplied by these four weighting factors and summed to obtain a weighted sum of yaw rates. This weighted sum is then divided by the sum of the four weighting factors to obtain the reference yaw acceleration. Finally, the reference lateral acceleration is obtained by multiplying the reference yaw acceleration by the current vehicle speed.

[0080] Step S803: Calculate the maximum permissible difference between the measured lateral acceleration and the estimated lateral acceleration.

[0081] By combining the vehicle's own dynamic characteristics, sensor accuracy parameters, and real-vehicle road test data, the maximum permissible difference between the measured lateral acceleration and various estimated lateral accelerations is pre-calibrated. This threshold is the core criterion for defining whether the deviation is within a reasonable range or abnormal, ensuring that subsequent judgments accurately reflect actual vehicle driving conditions. Specifically, this difference can be related to vehicle speed; between vehicle speeds of 8 m / s and 22 m / s, the maximum permissible difference can change linearly; at vehicle speeds below 8 m / s, the maximum permissible difference is fixed at 5 m / s. 2 For vehicle speeds greater than 22 m / s, the maximum permissible difference is fixed at 2.2 m / s. 2 .

[0082] Step S804: Determine whether the difference between the two lateral accelerations exceeds the maximum allowable difference; if yes, proceed to step S805; if no, proceed to step S807.

[0083] The two absolute values ​​of deviation calculated in steps S801 and S802 are compared with the maximum permissible difference calibrated in step S803 to determine whether the two deviations exceed the maximum permissible difference. If any one or both absolute values ​​of deviation exceed the maximum permissible difference, the deviation is determined to be abnormal, and the process proceeds to the next step of the working condition judgment procedure (step S805); if neither absolute value of deviation exceeds the maximum permissible difference, the deviation is determined to be within a reasonable range, and the count reset operation is directly executed (step S807).

[0084] Step S805: Determine whether the road surface is sloping; if yes, proceed to step S806; if no, proceed to step S807.

[0085] Based on the vehicle tilt state results obtained from the aforementioned side slip angle comparison, it is determined whether the vehicle is currently driving on a sloping road surface or experiencing disturbances such as bumps. The core purpose of this determination is to distinguish between deviations caused by sensor interference and deviations caused by the vehicle's normal movement, providing a basis for subsequent fault counting.

[0086] Step S806: Perform lateral acceleration unreliable fault debounce counting.

[0087] If step S805 determines that the vehicle is in a disturbing condition such as an inclined road surface, then the lateral acceleration unreliable fault de-vibration counting is initiated. The counting process accumulates according to a preset time step, counting only for continuously existing disturbing conditions, thereby filtering out misjudgments caused by occasional disturbances such as single bumps and instantaneous tilts, and improving the stability of fault determination.

[0088] Step S807: Lateral acceleration unreliable fault debounce count reset to 0.

[0089] If step S804 determines that the deviation does not exceed the maximum permissible difference, or step S805 determines that the vehicle is not in a tilted road surface disturbance condition, then the lateral acceleration unreliable fault de-jitter count is immediately reset to 0. This reset mechanism avoids the accumulation of invalid counts under disturbance-free conditions, ensuring that the count only applies to real, continuous disturbances.

[0090] Step S808: Has the lateral acceleration unreliable fault debounce count been completed?

[0091] The current fault debouncing count is compared with a preset counting threshold to determine whether the counting is complete. The counting threshold here is calibrated based on the required duration of the interference; for example, setting the condition of being in the interference condition for three consecutive time steps is considered a completion condition for counting.

[0092] Step S809: If so, report a lateral acceleration unreliable fault.

[0093] If step S808 determines that the fault de-shake counting is complete, a formal report of an unreliable lateral acceleration fault is submitted. At this time, the vehicle's electronic stability system can trigger corresponding fault-tolerant strategies, such as switching to control logic based on estimated values, to avoid control instability caused by invalid measured data and ensure vehicle driving safety.

[0094] As can be seen from the above vehicle acceleration parameter detection and control method, this method estimates the lateral acceleration of the vehicle by using the steering wheel angle and the difference in wheel speed between the front and rear axles, and verifies and detects it with the measured lateral acceleration. Thus, it can comprehensively detect the lateral acceleration from the perspective of vehicle dynamics, accurately identify interference signals when the vehicle is driving unstablely, thereby improving the accuracy of obtaining the vehicle's lateral acceleration and reducing the false alarm probability of the vehicle's electronic stability system.

[0095] Corresponding to the above embodiments of the vehicle acceleration parameter detection and control method, this invention also provides a vehicle acceleration parameter detection and control system, such as... Figure 10 As shown, the system includes: The data acquisition module 1010 is used to acquire the steering angle of the steering wheel and the wheel speed difference between the front and rear axles in the vehicle, and to acquire the measured lateral acceleration and measured yaw rate of the vehicle in real time using the vehicle's inertial sensors. The lateral acceleration calculation module 1020 is used to calculate the first lateral acceleration of the vehicle using the steering angle and the second lateral acceleration of the vehicle using the wheel speed difference. The difference detection calculation module 1030 is used to calculate the difference detection results between the first lateral acceleration, the second lateral acceleration and the measured lateral acceleration, respectively. The tilt state acquisition module 1040 is used to acquire the tilt state results of the vehicle through measured lateral acceleration, first lateral acceleration and measured yaw rate; The detection result determination module 1050 is used to determine the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result.

[0096] As can be seen from the above-mentioned vehicle acceleration parameter detection and control system, the system estimates the lateral acceleration of the vehicle by using the steering wheel angle and the difference in wheel speed between the front and rear axles, and verifies and detects it with the measured lateral acceleration. Thus, it comprehensively detects the lateral acceleration from the perspective of vehicle dynamics, and can accurately identify interference signals when the vehicle is driving unstablely, thereby improving the accuracy of obtaining the vehicle's lateral acceleration and reducing the false alarm probability of the vehicle's electronic stability system.

[0097] The vehicle acceleration parameter detection and control system provided in this embodiment of the invention has the same implementation principle and technical effect as the aforementioned vehicle acceleration parameter detection and control method embodiment. For the sake of brevity, any parts not mentioned in the system embodiment can be referred to the corresponding content in the aforementioned vehicle acceleration parameter detection and control method embodiment.

[0098] This embodiment also provides an electronic device, the structural schematic diagram of which is shown below. Figure 11 As shown, the device includes a processor 101 and a memory 102; wherein, the memory 102 is used to store one or more computer instructions, which are executed by the processor to implement the steps of the above-described vehicle acceleration parameter detection and control method.

[0099] Figure 11 The electronic device shown also includes a bus 103 and a communication interface 104, with the processor 101, communication interface 104 and memory 102 connected via the bus 103.

[0100] The memory 102 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. The bus 103 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 11 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0101] The communication interface 104 is used to connect to at least one user terminal and other network units through a network interface, and to send encapsulated IPv4 packets or IPv4 packets to the user terminal through the network interface.

[0102] Processor 101 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 101 or by instructions in software form. The processor 101 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this disclosure can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 102. The processor 101 reads the information in memory 102 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0103] This invention also provides a storage medium storing a computer program, which, when executed by a processor, performs the steps of the vehicle acceleration parameter detection and control method described in the foregoing embodiments.

[0104] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, devices, and methods can be implemented in other ways. The system embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0105] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0106] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0107] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, electronic device, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0108] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for detecting and controlling vehicle acceleration parameters, characterized in that, The method includes: The steering angle of the steering wheel and the wheel speed difference between the front and rear axles in the vehicle are obtained, and the measured lateral acceleration and measured yaw rate of the vehicle are obtained in real time using the vehicle's inertial sensors. The first lateral acceleration of the vehicle is calculated using the steering angle, and the second lateral acceleration of the vehicle is calculated using the wheel speed difference. Calculate the difference detection results between the first lateral acceleration and the second lateral acceleration and the measured lateral acceleration, respectively; The tilt state of the vehicle is obtained by measuring the lateral acceleration, the first lateral acceleration, and the measured yaw rate. The detection result corresponding to the measured lateral acceleration is determined based on the difference detection result and the tilt state result.

2. The vehicle acceleration parameter detection and control method according to claim 1, characterized in that, Calculating the first lateral acceleration of the vehicle using the steering angle includes: The current vehicle speed, characteristic vehicle speed, and steering ratio of the vehicle are obtained; wherein, the characteristic vehicle speed is the vehicle speed at which the yaw rate gain of the vehicle reaches its maximum value. The turning coefficient of the vehicle is calculated using the current vehicle speed, the characteristic vehicle speed, and the steering gear ratio; The first yaw rate of the vehicle is determined based on the first product of the steering angle and the turning coefficient. The first lateral acceleration of the vehicle is determined based on the second product of the first yaw rate and the current vehicle speed.

3. The vehicle acceleration parameter detection and control method according to claim 2, characterized in that, Calculating the second lateral acceleration of the vehicle using the wheel speed difference includes: Based on the wheel speed difference, the front axle wheel speed difference and the rear axle wheel speed difference are obtained respectively. The front axle yaw rate of the vehicle is calculated using the front axle wheel speed difference, and the rear axle yaw rate of the vehicle is calculated using the rear axle wheel speed difference. The first weighting coefficients corresponding to the front and rear axles are determined using the real-time load distribution data of the vehicle. The second yaw rate of the vehicle is determined by the weighted sum of the front axle yaw rate and the rear axle yaw rate calculated using the first weighting coefficient. The estimated yaw rate of the vehicle is determined based on the ratio of the measured lateral acceleration to the current vehicle speed. The reference yaw acceleration of the vehicle is calculated based on the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate. The second lateral acceleration corresponding to the vehicle is determined based on the third product of the reference yaw acceleration and the current vehicle speed.

4. The vehicle acceleration parameter detection and control method according to claim 3, characterized in that, The steps for calculating the reference yaw acceleration of the vehicle based on the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate include: Obtain the second weighting coefficient corresponding to the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate; wherein, the second weighting coefficient is the reciprocal of the product of any one of the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate with the difference between the other three yaw rates; The reference yaw acceleration of the vehicle is determined by the weighted sum of the measured yaw rate, the second yaw rate, the estimated yaw rate, and the first yaw rate calculated using the second weighting coefficient.

5. The vehicle acceleration parameter detection and control method according to claim 1, characterized in that, The steps for obtaining the vehicle's tilt state result using the measured lateral acceleration, the first lateral acceleration, and the measured yaw rate include: The first side slip angle of the vehicle under the current road surface is calculated using the measured lateral acceleration and the measured yaw rate. The second side slip angle of the vehicle under the current road surface is calculated using the first lateral acceleration and the measured yaw rate. The tilt state of the vehicle is obtained by comparing the first and second sideslip angles with a preset threshold.

6. The vehicle acceleration parameter detection and control method according to claim 5, characterized in that, The step of calculating the first sideslip angle of the vehicle under the current road surface using the measured lateral acceleration and the measured yaw rate includes: The third lateral acceleration of the vehicle is determined by the fourth product of the measured yaw rate and the current vehicle speed. The difference between the third lateral acceleration and the measured lateral acceleration is obtained, and the arcsine result of the difference in lateral acceleration is used to determine the first side slip angle of the vehicle under the current road surface.

7. The vehicle acceleration parameter detection and control method according to claim 1, characterized in that, The step of determining the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result includes: If the difference detection result satisfies the preset difference judgment relationship, then determine whether the tilt state result satisfies the preset tilt judgment relationship; When the tilt state result satisfies the tilt judgment relationship, the anti-jitter count of the unreliable lateral acceleration fault corresponding to the inertial sensor is set. The detection result corresponding to the measured lateral acceleration is determined by using the unreliable fault debounce count of the lateral acceleration.

8. The vehicle acceleration parameter detection and control method according to claim 7, characterized in that, The step of determining the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result further includes: If the difference detection result does not meet the difference judgment relationship, or the tilt state result does not meet the tilt judgment relationship, the lateral acceleration unreliable fault debouncing count will be cleared to zero.

9. A vehicle acceleration parameter detection and control system, characterized in that, The system includes: The data acquisition module is used to acquire the steering angle of the steering wheel and the wheel speed difference between the front and rear axles in the vehicle, and to acquire the measured lateral acceleration and measured yaw rate of the vehicle in real time using the vehicle's inertial sensors. A lateral acceleration calculation module is used to calculate the first lateral acceleration of the vehicle using the steering angle, and to calculate the second lateral acceleration of the vehicle using the wheel speed difference. The difference detection calculation module is used to calculate the difference detection results between the first lateral acceleration and the second lateral acceleration and the measured lateral acceleration, respectively. The tilt state acquisition module is used to acquire the tilt state result of the vehicle through the measured lateral acceleration, the first lateral acceleration and the measured yaw rate; The detection result determination module is used to determine the detection result corresponding to the measured lateral acceleration based on the difference detection result and the tilt state result.

10. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the steps of the vehicle acceleration parameter detection and control method according to any one of claims 1 to 8.

Images