Vehicle acceleration and slope signal separation method, electronic device and vehicle

Abstract

The application discloses a vehicle acceleration and slope signal separation method, an electronic device and a vehicle. The method comprises the following steps: calculating the vehicle speed according to the actual working condition of the vehicle and the wheel speed signal; calculating the wheel acceleration by using the five-point difference method based on the vehicle speed; and performing signal separation on the acceleration signal detected by the acceleration sensor according to the motion state of the vehicle and the wheel acceleration, so as to obtain the actual acceleration and the slope of the vehicle. The signal coupling error is significantly reduced by the working condition wheel speed processing and Kalman filtering. The five-point difference method is used to improve the acceleration calculation accuracy and adapt to dynamic working condition changes. Meanwhile, the low-pass filtering and delay compensation design are added, so that the noise is effectively inhibited and the real-time performance is improved.

Description

Technical Field

[0001] This invention belongs to the field of vehicle technology, specifically relating to a method for separating vehicle acceleration and gradient signals, electronic equipment, and a vehicle. Background Technology

[0002] In existing vehicle dynamics control, acceleration and gradient signals are coupled. Traditional methods mainly rely on a single sensor or simple filtering algorithms to separate the signals, but these methods suffer from the following problems: 1) Signal coupling error: The vertical components of vehicle acceleration and gradient both affect the acceleration sensor output, making direct separation impossible; 2) Poor adaptability to dynamic conditions: Wheel speed signals exhibit different noise and delay characteristics under different conditions (acceleration, braking, constant speed), and traditional methods do not process these conditions separately, leading to decreased accuracy; 3) Sensor noise and delay: Wheel speed signals are subject to noise introduced by tire slippage and uneven road surfaces, and acceleration sensors experience response delays, affecting real-time performance. Summary of the Invention

[0003] One object of the present invention is to provide a method, electronic device and vehicle for separating vehicle acceleration and gradient signals, which can solve the above-mentioned technical problems in the prior art.

[0004] According to a first aspect of the present invention, a method for separating vehicle acceleration and gradient signals is provided, comprising:

[0005] Calculate the vehicle speed based on the vehicle's actual operating conditions and wheel speed signals;

[0006] The wheel acceleration is calculated using the five-point difference method based on the vehicle speed.

[0007] Based on the vehicle's motion state and the wheel acceleration, the acceleration signal detected by the acceleration sensor is separated to obtain the vehicle's actual acceleration and gradient.

[0008] Optionally, the calculation of wheel acceleration based on the vehicle speed using the five-point difference method includes:

[0009] Calculate wheel acceleration using the following formula:

[0010] ;

[0011] in, For wheel acceleration, For time step, Indicates the current moment. For vehicle speed, for The speed of the car at any moment for The speed of the car at any moment for The speed of the car at any moment for The speed of the vehicle at any given moment.

[0012] Optionally, the step of separating the acceleration signal detected by the acceleration sensor based on the vehicle's motion state and the wheel acceleration to obtain the vehicle's actual acceleration and gradient includes:

[0013] When the vehicle is in motion, the state equation and observation equation of the vehicle are constructed based on the wheel acceleration.

[0014] Based on the vehicle's state equation and the observation equation, the acceleration signal detected by the acceleration sensor is separated by Kalman filtering to obtain the vehicle's actual acceleration and gradient.

[0015] When the vehicle is stationary, the actual acceleration of the vehicle is determined to be zero, and the slope is calculated based on the acceleration signal detected by the acceleration sensor.

[0016] Optionally, the state equation of the vehicle is:

[0017] ;

[0018] in, This is the actual acceleration of the vehicle. For wheel acceleration, It is the acceleration due to gravity. The slope angle, for The slope angle at any given moment for The slope angle at any given moment and This is process noise.

[0019] Optionally, the observation equation is:

[0020] ;

[0021] in, For the observation vector, The acceleration detected by the accelerometer. For wheel acceleration, This is the actual acceleration of the vehicle. It is the acceleration due to gravity. The slope angle, To observe noise.

[0022] Optionally, the method further includes:

[0023] A first-order delay model is introduced into the observation equation to correct the delay of the accelerometer signal.

[0024] ;

[0025] in, For the observation vector, The delayed observation vector, To delay time, These are variables in the complex frequency domain.

[0026] Optionally, calculating the vehicle speed based on the vehicle's actual operating conditions and wheel speed signals includes:

[0027] Under acceleration conditions, the average wheel speed of the non-driving wheels is taken as the vehicle speed;

[0028] Under braking conditions, the maximum value between the average value of the front wheel speed and the average value of the rear wheel speed is taken as the vehicle speed;

[0029] Under other operating conditions, the average wheel speed of all wheels is taken as the vehicle speed.

[0030] Optionally, the method further includes: applying a second-order Butterworth filter to the vehicle speed signal for low-pass filtering, wherein the second-order Butterworth filter is represented as follows:

[0031] ;

[0032] in, Let be the transfer function of the filter. The cutoff frequency, These are variables in the complex frequency domain.

[0033] According to a second aspect of the present invention, an electronic device is provided, including a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of a vehicle acceleration and gradient signal separation method as described in the first aspect of the present invention.

[0034] According to a third aspect of the present invention, a vehicle is provided, including an electronic device as described in the second aspect of the present invention.

[0035] The beneficial effects of this invention are as follows: By employing wheel speed processing under different operating conditions and Kalman filtering, this invention significantly reduces signal coupling errors. The five-point differential method improves the accuracy of acceleration calculation, adapting to dynamic changes in operating conditions. Simultaneously, the inclusion of low-pass filtering and delay compensation effectively suppresses noise and improves real-time performance. Attached Figure Description

[0036] Figure 1 This is a flowchart of a method for separating vehicle acceleration and gradient signals according to an embodiment of the present invention.

[0037] Figure 2This is a schematic diagram of a method for separating vehicle acceleration and gradient signals in an embodiment of the present invention.

[0038] Figure 3 This is a flowchart of vehicle speed calculation in an embodiment of the present invention. Detailed Implementation

[0039] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention.

[0040] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0041] Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0042] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0043] In the specification of this invention, the terms "first" and "second" may explicitly or implicitly include one or more of the same feature. In the description of this invention, unless otherwise stated, "multiple" means two or more. Furthermore, in the specification, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0044] like Figure 1 As shown in the figure, this embodiment introduces a method for separating vehicle acceleration and gradient signals, including steps 1100-1300.

[0045] Step 1100: Calculate the vehicle speed based on the actual operating conditions of the vehicle and the wheel speed signal.

[0046] Vehicles operate under various conditions during actual operation, such as acceleration and braking. In this invention, different methods are used to calculate vehicle speed under different conditions to improve the accuracy of the calculation results.

[0047] Wheel speed signals are acquired by the vehicle's wheel speed sensors. The vehicle in this invention is a four-wheeled passenger vehicle, with each wheel equipped with a corresponding wheel speed sensor. The wheel speed sensor signals include the wheel speed signals of all four wheels, such as... Figure 2 As shown, the wheel speed signals are V_lf for the left front wheel, V_rf for the right front wheel, V_lr for the left rear wheel, and V_rr for the right rear wheel.

[0048] Step 1200: Calculate wheel acceleration using the five-point difference method based on the vehicle speed.

[0049] The five-point difference method uses vehicle speeds at multiple different times before and after acceleration, and calculates acceleration through symmetrical difference. This can significantly reduce noise interference and improve accuracy.

[0050] Specifically, the wheel acceleration is calculated using the following formula:

[0051] ;

[0052] in, For wheel acceleration, For time step, Indicates the current moment. The speed is the vehicle speed. for The speed of the car at any moment for The speed of the car at any moment for The speed of the car at any moment for The speed of the vehicle at any given moment.

[0053] Step 1300: Based on the vehicle's motion state and the wheel acceleration, perform signal separation on the acceleration signal detected by the acceleration sensor to obtain the vehicle's actual acceleration and gradient.

[0054] Vehicles are typically equipped with an Inertial Measurement Unit (IMU), which includes an accelerometer and a gyroscope. The IMU measures acceleration, including both the actual acceleration and the gradient component to reflect the vehicle's actual motion. To ensure accurate vehicle control, the actual acceleration and gradient need to be separated. For example... Figure 2 As shown, A_x is the accelerometer sensor signal.

[0055] In this embodiment, step 1300 includes steps 1310-1330.

[0056] Step 1310: When the vehicle is moving, construct the vehicle's state equation and observation equation based on the wheel acceleration.

[0057] The vehicle's state equation is:

[0058] ;

[0059] in, This is the actual acceleration of the vehicle. For wheel acceleration, It is the acceleration due to gravity. The slope angle, for The slope angle at any given moment for The slope angle at any given moment and This is process noise.

[0060] The vehicle's state equations describe the changes in the vehicle's state. These equations reflect the relationship between the vehicle's actual acceleration and the calculated wheel acceleration and slope angle.

[0061] The observation equation is:

[0062] ;

[0063] in, For the observation vector, The acceleration detected by the accelerometer. For wheel acceleration, This is the actual acceleration of the vehicle. It is the acceleration due to gravity. The slope angle, To observe noise.

[0064] Step 1320: Based on the vehicle's state equation and the observation equation, the acceleration signal detected by the acceleration sensor is separated by Kalman filtering to obtain the vehicle's actual acceleration and gradient.

[0065] Kalman filtering is a highly efficient recursive state estimation algorithm that achieves optimal estimation of the state of a dynamic system by fusing system models and noisy observation data. In the signal separation process using Kalman filtering, the vehicle's state equation describes the dynamic changes in the vehicle's state and predicts the state at the next moment based on the physical model. The observation equation, on the other hand, correlates sensor measurements with state variables, providing indirect observations of the state and resolving signal coupling issues.

[0066] The observation matrix represents how the accelerometer signals are combined with the vehicle's actual acceleration and the gradient. The vehicle's actual acceleration... With the slope component of gravitational acceleration The acceleration is obtained by superimposing the data and then introducing observation noise. Wheel acceleration Only with the vehicle's actual acceleration Correlation provides independent information for signal decoupling. Using two independent observations, Kalman filtering can estimate the vehicle's actual acceleration. and slope angle .

[0067] Step 1330: When the vehicle is stationary, determine that the actual acceleration of the vehicle is zero, and calculate the slope based on the acceleration signal detected by the acceleration sensor.

[0068] When the wheel speed is zero, the vehicle is confirmed to be stationary. If the vehicle is stationary and on a horizontal surface, then the vehicle's actual acceleration is... And the slope is zero. If the vehicle is on a slope, the acceleration detected by the acceleration sensor is... acceleration due to gravity The slope can be calculated by analyzing the components along the slope surface.

[0069] The slope percentage is calculated using the following formula:

[0070] ;

[0071] in, This represents the percentage of slope.

[0072] In this embodiment, the method further includes: introducing a first-order delay model into the observation equation to correct the delay of the accelerometer signal.

[0073] ;

[0074] in, For the observation vector, The delayed observation vector, To delay time, These are variables in the complex frequency domain.

[0075] Accelerometer signals can be delayed due to various factors, such as lag in CAN (Controller Area Network) bus transmission and IMU signal processing. A first-order delay model is used to describe the time lag effect of signals during transmission or processing. Its core function is to quantify and compensate for signal delays to improve the accuracy of state estimation and control. By appropriately using the first-order delay model, the real-time performance of state estimation and the robustness of the control system in vehicle dynamics systems can be significantly improved.

[0076] In this embodiment, step 1100 includes steps 1110-1130.

[0077] Step 1110: Under acceleration conditions, take the average wheel speed of the non-drive wheels as the vehicle speed.

[0078] If the vehicle's drive wheels are the rear wheels, then the average wheel speed of the two front wheels is taken as the vehicle speed. The formula for calculating the vehicle speed is as follows:

[0079] ;

[0080] in, This refers to the wheel speed of the left front wheel. This refers to the wheel speed of the right front wheel. The speed is the vehicle speed.

[0081] If the vehicle's drive wheels are the front wheels, then the average wheel speed of the two rear wheels is taken as the vehicle speed. The vehicle speed calculation formula is as follows:

[0082] ;

[0083] in, This refers to the wheel speed of the left rear wheel. This is the wheel speed of the right rear wheel.

[0084] When a vehicle is accelerating, using the average wheel speed of the non-driving wheels as the vehicle speed can avoid interference from the slippage of the driving wheels and improve the accuracy of vehicle speed calculation.

[0085] Step 1120: Under braking conditions, take the maximum value between the average value of the front wheel speed and the average value of the rear wheel speed as the vehicle speed.

[0086] The formula for calculating vehicle speed when the vehicle is braking is as follows:

[0087] ;

[0088] Calculate the average speed of the front wheels and the average speed of the rear wheels separately, and then compare their values. If the average speed of the front wheels is greater than the average speed of the rear wheels, then the average speed of the front wheels is taken as the vehicle speed. If the average speed of the front wheels is less than the average speed of the rear wheels, then the average speed of the rear wheels is taken as the vehicle speed.

[0089] Step 1130: Under other operating conditions, take the average wheel speed of all wheels as the vehicle speed.

[0090] When the vehicle is under other operating conditions, such as constant speed, the formula for calculating the vehicle speed is as follows:

[0091] ;

[0092] The vehicle in this invention is a four-wheeled vehicle, so under other operating conditions, the vehicle speed is the average of the wheel speeds of the four wheels.

[0093] In this embodiment, the method further includes: performing low-pass filtering on the vehicle speed signal using a second-order Butterworth filter, wherein the second-order Butterworth filter is represented as follows:

[0094] ;

[0095] in, Let be the transfer function of the filter. The cutoff frequency, These are variables in the complex frequency domain.

[0096] like Figure 3 As shown, in the vehicle speed calculation process, the vehicle state is first determined to ascertain the vehicle's actual operating conditions. Then, based on these conditions, an appropriate method is selected to calculate the vehicle speed, followed by low-pass filtering using a second-order Butterworth filter. In practical applications, the cutoff frequency is selected based on the vehicle's dynamic characteristics. For example, the cutoff frequency... It can be 2Hz, used to suppress high-frequency noise.

[0097] This invention significantly reduces signal coupling errors by using wheel speed processing under different operating conditions and Kalman filtering. A five-point differential method is employed to improve acceleration calculation accuracy and adapt to dynamic operating conditions. Simultaneously, low-pass filtering and delay compensation are incorporated to effectively suppress noise and improve real-time performance.

[0098] This embodiment introduces an electronic device, including a processor and a memory, wherein the memory stores programs or instructions that can run on the processor, and when the programs or instructions are executed by the processor, they implement the steps of a vehicle acceleration and gradient signal separation method as described in any embodiment of the present invention.

[0099] This embodiment describes a vehicle that includes an electronic device as described in the above embodiments of the present invention.

[0100] While specific embodiments of the present invention have been described in detail by way of examples, those skilled in the art should understand that the above examples are for illustrative purposes only and are not intended to limit the scope of the invention. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of the invention.

[0101] Those skilled in the art will recognize that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0102] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described apparatus and equipment can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0103] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0104] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of the embodiments of the present invention, depending on actual needs.

[0105] In addition, the functional modules in the embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0106] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a 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, server, or network device, etc.) to execute all or part of the steps of the methods of 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, ROM, RAM, magnetic disks, or optical disks.

[0107] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

[0108] It should be understood that the sequence numbers of the steps in the invention's content and embodiments do not absolutely imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention. The foregoing description of embodiments of this disclosure has been provided for illustrative and descriptive purposes. The foregoing description is not exhaustive and is not intended to limit this disclosure to the exact form disclosed. Various modifications and variations may exist based on the foregoing teachings, or various modifications and variations may be derived from the practice of this disclosure. These embodiments were chosen and described to illustrate the principles of this disclosure and its practical application, so that those skilled in the art can utilize this disclosure in various implementations and modifications suitable for the specific purpose of the concept.

Claims

1. A method for separating vehicle acceleration and gradient signals, characterized in that, include: Calculate the vehicle speed based on the vehicle's actual operating conditions and wheel speed signals; The wheel acceleration is calculated using the five-point difference method based on the vehicle speed. Based on the vehicle's motion state and the wheel acceleration, the acceleration signal detected by the acceleration sensor is separated to obtain the vehicle's actual acceleration and gradient. The step of separating the acceleration signal detected by the acceleration sensor based on the vehicle's motion state and the wheel acceleration to obtain the vehicle's actual acceleration and gradient includes: When the vehicle is in motion, the state equation and observation equation of the vehicle are constructed based on the wheel acceleration. Based on the vehicle's state equation and the observation equation, the acceleration signal detected by the acceleration sensor is separated by Kalman filtering to obtain the vehicle's actual acceleration and gradient. When the vehicle is stationary, the actual acceleration of the vehicle is determined to be zero, and the slope is calculated based on the acceleration signal detected by the acceleration sensor; The observation equation is: ； in, For the observation vector, The acceleration detected by the accelerometer. For wheel acceleration, This is the actual acceleration of the vehicle. It is the acceleration due to gravity. The slope angle, To observe noise; A first-order delay model is introduced into the observation equation to correct the delay of the accelerometer signal. ； in, For the observation vector, The delayed observation vector, To delay time, These are variables in the complex frequency domain.

2. The method according to claim 1, characterized in that, The calculation of wheel acceleration based on the vehicle speed using the five-point difference method includes: Calculate wheel acceleration using the following formula: ； in, For wheel acceleration, For time step, Indicates the current moment. For vehicle speed, for The speed of the car at any given moment for The speed of the car at any given moment for The speed of the car at any given moment for The speed of the vehicle at any given moment.

3. The method according to claim 1, characterized in that, The state equation of the vehicle is: ； in, This is the actual acceleration of the vehicle. For wheel acceleration, It is the acceleration due to gravity. The slope angle, for The slope angle at any given moment for The slope angle at any given moment and This is process noise.

4. The method according to claim 1, characterized in that, The calculation of vehicle speed based on the vehicle's actual operating conditions and wheel speed signals includes: Under acceleration conditions, the average wheel speed of the non-driving wheels is taken as the vehicle speed; Under braking conditions, the maximum value between the average value of the front wheel speed and the average value of the rear wheel speed is taken as the vehicle speed; Under other operating conditions, the average wheel speed of all wheels is taken as the vehicle speed.

5. The method according to claim 4, characterized in that, The method further includes: applying a second-order Butterworth filter to perform low-pass filtering on the vehicle speed signal, wherein the second-order Butterworth filter is represented as follows: ； in, Let be the transfer function of the filter. The cutoff frequency, These are variables in the complex frequency domain.

6. An electronic device, characterized in that, It includes a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions being executed by the processor to implement the steps of a vehicle acceleration and gradient signal separation method as described in any one of claims 1 to 5.

7. A vehicle, characterized in that, Includes an electronic device as described in claim 6.

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