Vehicle signal processing method, device and driving equipment

Abstract

The embodiment of the present invention discloses a vehicle signal processing method, device and driving equipment, the method comprising obtaining a bus signal of a vehicle to be tested; correcting the measured value of an acceleration sensor based on the bus signal to obtain a corrected value of the acceleration sensor; and determining the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested based on the corrected value of the acceleration sensor. The present application corrects the measured value of the acceleration sensor and uses the corrected value to estimate the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested, thereby solving the technical problem that the prior art uses a dynamic model to estimate the vehicle speed, driving slope and center of mass sideslip angle, which has low accuracy and requires additional sensors, and achieves the technical effect of improving the estimation accuracy of the current vehicle speed, driving slope and center of mass sideslip angle.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of signal processing technology, and in particular to a vehicle signal processing method, device and driving equipment. Background Art

[0002] As vehicles become increasingly intelligent, configurations such as intelligent driving and stability control are gradually being installed on cars. These functional configurations have higher requirements for the accuracy of vehicle status information.

[0003] The information about the vehicle's speed in the forward direction is very important. Currently, this information is mainly obtained by calculating the wheel speed sensor. When the wheel is in a slipping state, it cannot accurately represent the true vehicle speed. Another method is to observe the vehicle speed from the outside through devices such as GPS, but it is not widely used due to factors such as accuracy, real-time performance, and cost. There is also a method of calculating the vehicle speed using a vehicle dynamics model. The accurate model has high accuracy under good road adhesion conditions, but poor accuracy under low adhesion conditions.

[0004] The slope information of the road on which the vehicle is located is equally important. Obtaining the road slope information can be transmitted to the transmission controller to achieve changes in the shifting strategy to improve the vehicle's power and fuel economy. Road slope information also represents the safety level of the vehicle, especially suitable for off-road roads and intelligent driving scenarios. The existing method is to use the integral of the angular acceleration in the pitch direction of the vehicle body and the kinematic equation to jointly determine the longitudinal slope of the road surface, but the measurement of the vehicle body pitch angle requires an additional sensor, and the signal processing relies on a low-pass filter, which causes a large delay in the slope signal.

[0005] The center of mass slip angle can characterize the characteristics of the vehicle's lateral movement and is an important indicator for evaluating the vehicle's driving stability. The calculation of the center of mass slip angle requires the longitudinal and lateral speeds of the vehicle, and the above-mentioned speed estimation module can already estimate the longitudinal speed of the vehicle. The center of mass slip angle estimation module focuses on the estimation of the lateral speed. The existing method uses tire models and dynamic models for calculations and uses adaptive Kalman filtering for information fusion. However, the tire lateral force parameters cannot be directly sensed on mainstream models, and the accuracy of the model calculation is greatly affected by road conditions. In addition, this method requires high computing power for the controller. Summary of the invention

[0006] The embodiments of the present invention provide a vehicle signal processing method, device and driving equipment, which solve the technical problems that the prior art uses a dynamic model to estimate the vehicle speed, driving slope and center of mass sideslip angle, which has low accuracy and requires additional sensors.

[0007] An embodiment of the present invention provides a vehicle signal processing method, the vehicle signal processing method comprising:

[0008] Acquiring a bus signal of the vehicle to be tested, wherein the bus signal at least includes a yaw angular velocity value and a yaw angular acceleration value;

[0009] Correcting a measurement value of an acceleration sensor based on the bus signal to obtain a correction value of the acceleration sensor, wherein the acceleration sensor includes a longitudinal acceleration sensor and a lateral acceleration sensor;

[0010] The current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested are determined based on the correction value of the acceleration sensor.

[0011] Further, the step of correcting the measured value of the acceleration sensor based on the bus signal to obtain the corrected value of the acceleration sensor includes:

[0012] Correcting the longitudinal acceleration sensor based on the yaw angular velocity value to obtain a correction value of the longitudinal acceleration sensor;

[0013] The lateral acceleration sensor is corrected based on the yaw angular acceleration value to obtain a correction value of the lateral acceleration sensor.

[0014] Further, the determining the current speed of the vehicle to be tested based on the correction value of the acceleration sensor includes:

[0015] Calculating a true longitudinal acceleration value based on the correction value of the longitudinal acceleration sensor;

[0016] Determine the synchronous speed value at the current moment according to the true longitudinal acceleration value;

[0017] Determining whether the vehicle to be tested is in a slipping state;

[0018] If yes, determining a first speed estimate value based on the true longitudinal acceleration value and the synchronous speed at the current moment;

[0019] The first speed estimation value and the first fused speed value are fused through a second Kalman filter to obtain a second fused speed value, wherein the first fused speed value is obtained by fusing the front axle speed and the rear axle speed of the vehicle to be tested through the first Kalman filter, and the second fused speed value is the current vehicle speed of the vehicle to be tested.

[0020] Furthermore, if the vehicle to be tested is not in a slipping state, the vehicle signal processing method further includes:

[0021] A first speed estimate is determined based on the current synchronous speed.

[0022] Further, the driving slope includes a longitudinal slope and a lateral slope, and determining the driving slope of the vehicle to be tested based on the correction value of the acceleration sensor includes:

[0023] Determining whether the vehicle to be tested has slipped;

[0024] If not, the longitudinal slope is determined based on the correction value of the longitudinal acceleration sensor, the current vehicle speed at the current moment and the current vehicle speed k sampling periods ago, and the lateral slope is determined based on the correction value of the lateral acceleration sensor, the yaw angular velocity value and the longitudinal vehicle speed.

[0025] Further, if the vehicle to be tested does not slip, then determining the driving slope of the vehicle to be tested based on the correction value of the acceleration sensor includes:

[0026] Determine the longitudinal slope based on the correction value of the longitudinal acceleration sensor, the current vehicle speed at the current moment, the current vehicle speed k sampling periods ago, and a first turning angle value, wherein the first turning angle value is a turning angle value of the vehicle body relative to the ground due to different suspension heights of front and rear axles of the vehicle;

[0027] The lateral slope is determined based on the correction value of the lateral acceleration sensor, the yaw angular velocity value, the longitudinal vehicle speed and a second turning angle value, wherein the second turning angle value is a turning angle value of the vehicle body relative to the ground due to different suspension heights of left and right axles of the vehicle.

[0028] Furthermore, if the vehicle to be tested slips, the longitudinal slope and the lateral slope of the road surface on which the vehicle to be tested is currently located are converted into a longitudinal slope vector and a lateral slope vector respectively;

[0029] Establishing a current road surface plane based on the longitudinal slope vector and the lateral slope vector, and obtaining a normal vector of the current road surface plane;

[0030] and constructing a rotation matrix based on the normal vector of the current road surface plane;

[0031] Determining a rotated longitudinal slope vector and a lateral slope vector based on the rotation matrix;

[0032] The longitudinal slope and the lateral slope are determined based on the rotated longitudinal slope vector and the lateral slope vector, respectively.

[0033] Further, determining the center of mass sideslip angle of the vehicle to be tested based on the correction value of the acceleration sensor includes:

[0034] Determining whether the vehicle to be tested is in a steady-state driving state;

[0035] If yes, determining the center of mass sideslip angle based on the yaw rate value, the current vehicle speed and the tire sideslip coefficient;

[0036] If not, the center of mass sideslip angle is determined based on the correction value of the lateral acceleration sensor, the yaw angular velocity value, the current vehicle speed and the tire sideslip coefficient.

[0037] An embodiment of the present invention further provides a vehicle signal processing device, the vehicle signal processing device comprising:

[0038] A signal acquisition unit, used to acquire a bus signal of the vehicle to be tested, wherein the bus signal at least includes a yaw angular velocity value, a lateral translation acceleration value, a lateral slope value, and a yaw angular acceleration value;

[0039] a measurement value correction unit, configured to correct a measurement value of an acceleration sensor based on the bus signal to obtain a correction value of the acceleration sensor, wherein the acceleration sensor includes a longitudinal acceleration sensor and a lateral acceleration sensor;

[0040] A signal processing unit is used to determine the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested based on the correction value of the acceleration sensor.

[0041] An embodiment of the present invention further provides an electronic control unit, which executes the vehicle signal processing method described in any of the above embodiments.

[0042] An embodiment of the present invention further provides a driving device, which includes the electronic control unit described in any of the above embodiments.

[0043] The embodiment of the present invention discloses a vehicle signal processing method, device and driving equipment, the method includes obtaining a bus signal of a vehicle to be tested, wherein the bus signal includes at least a yaw angular velocity value and a yaw angular acceleration value; based on the bus signal, correcting the measured value of the acceleration sensor to obtain the corrected value of the acceleration sensor, wherein the acceleration sensor includes a longitudinal acceleration sensor and a lateral acceleration sensor; based on the corrected value of the acceleration sensor, determining the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested. The present application corrects the measured value of the acceleration sensor and estimates the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested using the corrected value, thereby solving the technical problem of low accuracy and the need to add additional sensors in the prior art of estimating the vehicle speed, driving slope and center of mass sideslip angle of the vehicle using a dynamic model, and achieves the technical effect of improving the estimation accuracy of the current vehicle speed, driving slope and center of mass sideslip angle. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1is a flow chart of a vehicle signal processing method provided by an embodiment of the present invention;

[0045] Figure 2 is a schematic diagram of an acceleration sensor provided by an embodiment of the present invention;

[0046] Figure 3 is a schematic diagram of the influence of vehicle body yaw on the longitudinal acceleration sensor provided by an embodiment of the present invention;

[0047] Figure 4 is a signal processing flow chart provided by an embodiment of the present invention;

[0048] Figure 5 is a flow chart of estimating the current vehicle speed provided by an embodiment of the present invention;

[0049] Figure 6 It is a principle diagram of the "delay / integration" link provided by an embodiment of the present invention;

[0050] Figure 7 is a structural diagram of the working principle of the first Kalman filter provided by an embodiment of the present invention;

[0051] Figure 8 It is a structural diagram of a vehicle signal processing device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0053] It should be noted that the terms "first", "second", etc. in the specification, claims and drawings of the present invention are used to distinguish different objects, rather than to limit a specific order. The following embodiments of the present invention can be implemented separately, or in combination with each other, and the embodiments of the present invention do not impose specific limitations on this.

[0054] Figure 1 The present invention provides a flow chart of a vehicle signal processing method.

[0055] like Figure 1 As shown, the vehicle signal processing method specifically includes the following steps:

[0056] S101, obtaining a bus signal of a vehicle to be tested, wherein the bus signal at least includes a yaw angular velocity value and a yaw angular acceleration value.

[0057] Specifically, after obtaining the yaw angular velocity value ω of the vehicle to be tested yawThen, by calculating dω yaw / dt to obtain the yaw angular acceleration value of the vehicle to be tested. In addition to the yaw angular velocity value and the yaw angular acceleration value, the bus signals of the vehicle to be tested also include four-wheel speed sensor signals, driving direction signals, ABS (Antilock Brake System, anti-lock braking system) / ESC (Electronic Stability Controller, electronic stability control system) / TCS (Traction Control System) trigger signals, vehicle body longitudinal and lateral acceleration signals, yaw angular velocity signals, steering wheel angle signals, engine speed signals, accelerator pedal position signals, brake pedal signals, brake master cylinder pressure signals, suspension height signals, and vehicle body height signals.

[0058] S102, correcting the measured value of the acceleration sensor based on the bus signal to obtain a corrected value of the acceleration sensor, wherein the acceleration sensor includes a longitudinal acceleration sensor and a lateral acceleration sensor.

[0059] Figure 2 4 is a schematic diagram of an acceleration sensor provided by an embodiment of the present invention. Figure 3 It is a schematic diagram of the influence of vehicle body yaw on the longitudinal acceleration sensor provided by an embodiment of the present invention.

[0060] Specifically, Figure 2 As shown in the figure, the acceleration sensor can be approximately regarded as a mass-stiffness system. The position of the mass block m relative to the vehicle body is the sensor output value. Therefore, the value of the longitudinal acceleration sensor is affected by the following factors: (1) the longitudinal acceleration of the vehicle body; (2) the longitudinal slope of the road surface; (3) the yaw angular velocity of the vehicle body; (4) the pitch angular velocity of the vehicle body. Among them, the yaw and pitch motion of the vehicle body will produce centripetal acceleration, which will throw the acceleration sensor toward the front of the vehicle and reduce the value of the acceleration sensor. Since the pitch range of the vehicle body is small, the impact on the acceleration sensor is small and is ignored here. The value of the longitudinal acceleration sensor can be expressed by the following formula:

[0061]

[0062] Among them: A x_sensor is the value of the longitudinal acceleration sensor, A x_hull is the real vehicle longitudinal acceleration, g is the local gravity acceleration, i x The longitudinal slope of the road surface at this time, ω yaw is the vehicle body yaw angular velocity, L ar is the distance from the acceleration sensor to the rear axle.

[0063] Optionally, S102, correcting the measured value of the acceleration sensor based on the bus signal to obtain the corrected value of the acceleration sensor includes: correcting the longitudinal acceleration sensor based on the yaw angular velocity value to obtain the corrected value of the longitudinal acceleration sensor.

[0064] Specifically, it can be seen from the above expression of the longitudinal acceleration sensor value that the actual vehicle body longitudinal acceleration A x_hull The longitudinal slope of the road surface at this time is i x is the calculated value for subsequent slope estimation and speed estimation, and the yaw angular velocity ω yaw The impact can be regarded as the error caused by the acceleration sensor structure, such as Figure 3 As shown in the figure, it is a schematic diagram of the influence of the vehicle body yaw on the longitudinal acceleration sensor. Therefore, it is necessary to correct it based on the yaw angular velocity value. The correction value A of the longitudinal acceleration sensor x_fixed for:

[0065]

[0066] The value of the lateral acceleration sensor is affected by the following factors: (1) lateral translation acceleration of the vehicle body; (2) lateral slope of the road surface; (3) centripetal acceleration caused by vehicle steering; (4) vehicle yaw angular acceleration; (5) vehicle roll angular velocity. Among them, the vehicle roll angular velocity is small and is ignored here. The value of the lateral acceleration sensor can be expressed by the following formula:

[0067] A y_sensor =A y_hull +g×sin(tan -1 i y / 100)-ω yaw ×u x -dω yaw / dt×L ar

[0068] Among them, A y_sensor is the value of the lateral acceleration sensor, A y_hull is the lateral translation acceleration of the vehicle body, g is the local gravity acceleration, i y This is the lateral slope of the road surface, ω yaw is the vehicle body yaw angular velocity, u x is the longitudinal speed, dω yaw / dt is the vehicle yaw angular acceleration, L ar is the distance from the acceleration sensor to the rear axle.

[0069] Optionally, S102, correcting the measured value of the acceleration sensor based on the bus signal to obtain the corrected value of the acceleration sensor includes: correcting the lateral acceleration sensor based on the yaw angular acceleration value to obtain the corrected value of the lateral acceleration sensor.

[0070] Specifically, it can be seen from the above expression of the lateral acceleration sensor value that the yaw angular acceleration dω yaw The effect of / dt can be regarded as the error caused by the acceleration sensor structure, so it needs to be corrected based on the yaw angular acceleration value. The correction value A of the lateral acceleration sensor is y_fixed for:

[0071] A y_fixed =A y_sensor +dω yaw / dt×L ar

[0072] S103, determining the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested based on the correction value of the acceleration sensor.

[0073] Figure 4 is a flowchart of a signal processing process provided by an embodiment of the present invention. Specifically, Figure 4 As shown, the bus signal enters the sensor compensation module, and is corrected by the sensor compensation module. After the longitudinal and lateral acceleration sensor values ​​are corrected, the correction values ​​are processed together with other bus signals to obtain the current vehicle speed, driving slope and center of mass slip angle of the vehicle to be tested. Among them, the current vehicle speed and the calculated value of the driving slope will be output at the same time, and the longitudinal slope signal from the driving slope calculation result will be used in the current vehicle speed estimation process, and the current vehicle speed from the current vehicle speed calculation will also be used in the driving slope estimation process; the center of mass slip angle will be calculated using the lateral slope in the current vehicle speed and driving slope calculation process, and other bus signals will also be used in the calculation process.

[0074] The present application corrects the measurement values ​​of the acceleration sensor and uses the corrected values ​​to estimate the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested, thereby solving the technical problems in the prior art of using dynamic models to estimate the vehicle speed, driving slope and center of mass sideslip angle of the vehicle, which has low accuracy and requires additional sensors, and achieves the technical effect of improving the estimation accuracy of the current vehicle speed, driving slope and center of mass sideslip angle.

[0075] Figure 5 The present invention provides a flowchart for estimating the current vehicle speed.

[0076] Alternatively, if Figure 5 As shown, S103, determining the current speed of the vehicle to be tested based on the correction value of the acceleration sensor includes:

[0077] S501, calculating a true longitudinal acceleration value based on a correction value of the longitudinal acceleration sensor.

[0078] Specifically, in the prior art, when the vehicle detects a trigger signal from a function such as ESC / ABS / TCS, the vehicle longitudinal acceleration is integrated. However, the problem with this method is that the trigger signal from the function such as ESC / ABS / TCS usually has a certain delay. When such a signal is received, the wheel has already slipped and caused a change in the vehicle speed. If the speed at this moment is used as the initial value for integration, the speed estimation will produce a large error. In addition, the real-time requirements of the vehicle speed signal are high, and the above problems cannot be avoided by delaying the output of the vehicle speed signal. Therefore, this application designs a "delay / integration" link to delay the speed fluctuation caused by wheel slip while ensuring the real-time performance of the vehicle speed signal, provide redundant time for the delay of the ESC / ABS / TCS trigger signal, and ensure the accuracy of the initial value of the speed integral.

[0079] Figure 6 is a schematic diagram of the "delay / integration" link provided by an embodiment of the present invention. Figure 6 As shown, is the first fusion speed at the current moment, is the first fusion speed n sampling steps ago, is the true longitudinal acceleration of the vehicle at the moment i sampling steps ago, is the synchronous speed at the current moment. Then the real longitudinal acceleration A is calculated based on the correction value of the longitudinal acceleration sensor. r The calculation method is:

[0080] A r =A x_fixed -g·sin(tan -1 (i x / 100))

[0081] Among them, i x is the longitudinal slope value of the current road surface output during the driving slope estimation process, A x_fixed It is the correction value obtained by the longitudinal acceleration sensor.

[0082] The "delay / integration" stage uses the first fusion speed n sampling steps ago The actual longitudinal acceleration A after n steps r Integration, that is, using A within these n steps r After accumulation, at synchronous speed Real-time output represents the real longitudinal speed of the vehicle. The characteristics of this method are that it is consistent with the input speed in phase, does not cause delay to the output speed, and delays the speed noise that only affects the wheel speed but not the vehicle body speed, that is, the speed fluctuation caused by tire slip by n sampling steps, which provides n steps of redundant time for the ESC / ABS / TCS trigger signal.

[0083] S502: Determine the synchronous speed value at the current moment according to the true longitudinal acceleration value.

[0084] Specifically, Figure 6 As shown, the current synchronization speed value is the first fusion speed before n sampling steps and the true longitudinal acceleration value A r The sum of the integrals within n steps is

[0085] S503, determining whether the vehicle to be tested is in a slipping state.

[0086] Figure 7 It is a structural diagram of the working principle of the first Kalman filter provided by an embodiment of the present invention.

[0087] Specifically, Figure 7 As shown, in order to achieve zero-delay filtering of the vehicle speed signal, and considering that there is usually a phase difference between the front and rear axle wheel speed noises, the four-wheel speed values ​​(i.e. Figure 7 The left front wheel and right front wheel speeds and the left rear wheel and right rear wheel speeds shown in are processed into the front axle speed and the rear axle speed, and input into the first Kalman filter to realize vehicle speed fusion, and obtain the first fusion speed value Calculate the first fusion speed value At the same time, the current state of the vehicle to be tested is judged according to bus signals such as the accelerator pedal position, brake pedal state, brake wheel cylinder pressure, steering wheel angle, etc., that is, whether the vehicle to be tested is in a slipping state is judged, so as to change the observation noise covariance S of the first Kalman filter based on different states, and then change the confidence level of the front and rear axle speeds, so as to realize speed fusion using different confidence levels and improve calculation accuracy.

[0088] Specifically, for vehicles under test with different driving modes, there are different methods for judging their current states:

[0089] (1) For rear-wheel drive or rear-driven four-wheel drive vehicles, an increase in the accelerator pedal position signal will increase the confidence in the front axle speed, and an increase in the brake pedal state, brake master cylinder pressure, and steering wheel angle will increase the confidence in the rear axle speed. When the vehicle is traveling in a straight line at a constant speed, the confidence in the front and rear axles should be equal;

[0090] (2) For front-wheel drive or front-dominant four-wheel drive vehicles, increases in accelerator pedal position, brake pedal status, brake master cylinder pressure, and steering wheel angle should increase the confidence in rear axle speed. When the vehicle is traveling in a straight line at a constant speed, the confidence in the front and rear axles should be equal.

[0091] By judging the slip state of the vehicle to be tested and changing the observation noise covariance S of the first Kalman filter according to the judgment result, and then changing the confidence of the front and rear axle speeds, it is possible to effectively reduce the fluctuation of the drive shaft wheel speed caused by gear shifting, and switch to the rear axle speed output when the vehicle turns, increasing the accuracy of vehicle speed calculation. In particular, the Kalman filter has a better effect on the phase difference of the front and rear axle speed fluctuations caused by road roughness.

[0092] S504: If yes, determine a first speed estimation value based on the true longitudinal acceleration value and the current synchronous speed.

[0093] Specifically, if the wheel slips, the calculation of the current speed is switched to the slip mode, so that the synchronous speed at the switching time is (i.e. the synchronous speed value calculated in step S502 above) is taken as the initial value, and the real acceleration A is taken as the r The integral output of the first estimated speed value u e ,Right now:

[0094] S505, the first speed estimation value and the first fused speed value are fused through a second Kalman filter to obtain a second fused speed value, wherein the first fused speed value is obtained by fusing the front axle speed and the rear axle speed of the vehicle to be tested through the first Kalman filter, and the second fused speed value is the current vehicle speed of the vehicle to be tested.

[0095] Specifically, obtain the first speed estimation value u e After that, in order to avoid the divergence of the accumulated error caused by sensor error, integration and slope estimation error, the first speed estimation value u e As the predicted value, the first fusion speed value u f Input the second Kalman filter into the observation value to obtain the second fusion speed value u n , to improve the accuracy and stability of the vehicle speed, wherein the second Kalman filter uses the second fusion speed value u n The current speed of the vehicle to be tested is output to the bus.

[0096] Alternatively, if Figure 5 As shown, if the vehicle to be tested is not in a slipping state, the vehicle signal processing method further includes:

[0097] S506: Determine a first speed estimation value based on the current synchronization speed.

[0098] When the vehicle under test is not in a slipping state, that is, when the vehicle under test is in a stable working condition, the calculation of the current speed is in normal mode. Since the n sampling steps are short, the accumulated acceleration error can be ignored. The first speed estimate u e with ui Value output, that is: u e =u i .

[0099] In the embodiment of the present invention, through the "delay / integration" link, the speed fluctuation caused by wheel slip is delayed under the premise of ensuring the real-time performance of the vehicle speed signal, and redundant time is provided for the delay of the ESC / ABS / TCS trigger signal, so as to achieve zero-delay output of the vehicle speed signal and better filtering effect, and have a higher precision effect when the wheel slips; compared with the existing method based on multi-sensor fusion calculation such as GPS, the present application only needs to use the bus signal, and the cost and installation difficulty are lower, and the real-time performance is better; compared with the existing method of using the vehicle dynamics model to calculate the speed, the present application does not need to have an accurate vehicle dynamics model, has better applicability across models and scenarios, and has lower requirements on the computing power of the controller; compared with the existing method of calculating through the bus signal and integrating the acceleration during slip, the present application can delay the fluctuation of the wheel speed caused by slip without delaying the vehicle speed signal, so that the initial value of the integral is more accurate, and the present application also realizes the road slope estimation at the same time, so that the accuracy of the speed estimation can be significantly improved.

[0100] Optionally, the driving slope includes a longitudinal slope and a lateral slope. S103, determining the driving slope of the vehicle to be tested based on the correction value of the acceleration sensor includes: judging whether the vehicle to be tested slips; if not, determining the longitudinal slope based on the correction value of the longitudinal acceleration sensor, the current vehicle speed at the current moment, and the current vehicle speed k sampling periods ago, and determining the lateral slope based on the correction value of the lateral acceleration sensor, the yaw angular velocity value, and the longitudinal vehicle speed.

[0101] Specifically, when calculating the driving slope, it is first necessary to determine whether the vehicle under test has slipped. If no slip has occurred, for the calculation of the longitudinal slope, the input speed signal is delayed by k sampling cycles to obtain That is, the second fusion speed value u is input with a delay of k sampling periods n and use the correction value A of the longitudinal acceleration sensor x_fixed Integrate k steps to get the integration speed at the current moment It is related to the current vehicle speed u n Keep the same phase. Due to the correction value A of the longitudinal acceleration sensor x_fixed A is the actual acceleration of the vehicle x_hull and the slope acceleration g×sin(tan -1 i x / 100), then the integral speed u s With the current vehicle speed u n The difference is the value of the slope acceleration after k-step integration, that is:

[0102] Ax_fixed =A x_hull +g×sin(tan -1 i x / 100)

[0103]

[0104]

[0105]

[0106] From this, the longitudinal slope value i can be obtained x for:

[0107] If no slip occurs, the lateral slope is calculated according to the following formula:

[0108] A y_fixed =A y_hull +g×sin(tan -1 i y / 100)-ω yaw ×u x

[0109] Among them, A y_fixed is the correction value of the lateral acceleration sensor, ω yaw is the vehicle body yaw angular velocity, u x is the longitudinal speed, A y_hull is the acceleration of the lateral translation of the vehicle body. When the vehicle is in a steady state, the vehicle should not slide sideways, that is, A y_hull If it is 0, the lateral slope value can be obtained. y for:

[0110] Optionally, if the vehicle to be tested does not slip, determining the driving slope of the vehicle to be tested based on the corrected value of the acceleration sensor includes: determining the longitudinal slope based on the corrected value of the longitudinal acceleration sensor, the current vehicle speed at the current moment, the current vehicle speed k sampling periods ago, and a first turning angle value, wherein the first turning angle value is the turning angle value of the vehicle body relative to the ground due to the different suspension heights of the front and rear axles of the vehicle; determining the lateral slope based on the corrected value of the lateral acceleration sensor, the yaw angular velocity value, the longitudinal vehicle speed, and a second turning angle value, wherein the second turning angle value is the turning angle value of the vehicle body relative to the ground due to the different suspension heights of the left and right axles of the vehicle.

[0111] Specifically, due to the different suspension heights of the front and rear axles of the vehicle, the vehicle body has a first rotation angle α relative to the ground. x Therefore, in order to calculate the longitudinal slope more accurately, α can be introduced x After correction, the longitudinal slope value ix for:

[0112]

[0113] Among them, the first rotation angle α x The value of can be obtained by the vehicle height sensor or suspension height sensor, i x is the average longitudinal slope in k sampling cycles. Since the actual road slope change rate is small and the k sampling cycles are short, i x It should be noted that the speed signal used in the calculation is the calculated current speed, that is, the second fused speed value u n , which is accurate, stable and has low noise, and can increase the accuracy of slope estimation; the measurement value of the longitudinal acceleration sensor used is the corrected value A after correction x_fixed , which increases the accuracy of the vehicle's longitudinal acceleration value under turning conditions, thereby improving the accuracy of driving slope estimation.

[0114] Specifically, due to the different suspension heights of the left and right wheels of the vehicle, the vehicle body has a second rotation angle α relative to the ground. y , so in order to calculate the lateral slope more accurately, α can be introduced y After correction, the longitudinal slope value i y for: Among them, the second rotation angle α y The value can be measured by the suspension height sensor.

[0115] Optionally, if the vehicle to be tested slips, the longitudinal slope and lateral slope of the road surface on which the vehicle to be tested is currently located are converted into a longitudinal slope vector and a lateral slope vector, respectively; a current road surface plane is established based on the longitudinal slope vector and the lateral slope vector, and a normal vector of the current road surface plane is obtained; and a rotation matrix is ​​constructed based on the normal vector of the current road surface plane; the rotated longitudinal slope vector and lateral slope vector are determined based on the rotation matrix; and the longitudinal slope and lateral slope are determined based on the rotated longitudinal slope vector and lateral slope vector, respectively.

[0116] Specifically, when the judgment result is that the vehicle to be tested has slipped, that is, the wheels have slipped, the calculation of the longitudinal and lateral slopes is suspended at this time because the wheel speed fluctuates greatly and the vehicle may slip. Since the slope change rate of the road surface in actual working conditions is not large, but the longitudinal and lateral slope changes caused by the change in the direction of the front of the vehicle in a short period of time are more obvious, the present invention sets a coordinate rotation transformation algorithm, establishes the current road surface plane based on the longitudinal and lateral slope values ​​at the time when the vehicle slips, and determines the rotation angle of the vehicle around the Z axis of the body coordinate system according to the yaw angular velocity integral, and realizes the continuous estimation of the slope under unstable working conditions through the coordinate transformation algorithm. The specific algorithm is as follows.

[0117] When the vehicle detects the moment of slip, that is, when the ABS / TCS / ESC function is triggered, the longitudinal slope of the road surface is The lateral slope is Convert them into longitudinal slope vectors and the lateral slope vector is Then use these two vectors to establish the current road surface plane, and the normal vector of the current road surface plane is Convert it to the unit normal vector of the road surface Then the unit normal vector for:

[0118]

[0119] Construct the rotation matrix R based on the normal vector of the current road surface:

[0120]

[0121] Where θ is the rotation angle, which is determined by the yaw rate ω yaw Integral obtains, that is: θ = ∫ω yaw , then the rotated longitudinal slope vector Should be: Rotated lateral slope vector Should be: Finally, based on the rotated longitudinal slope vector and the lateral slope vector Determine the longitudinal slope i of the vehicle under test when it is in a slipping state x and the lateral slope i y .

[0122] In an embodiment of the present invention, in terms of driving slope calculation, compared with the existing method of using a vehicle dynamics model to calculate the slope, the advantages are the same as the above-mentioned calculation of the current vehicle speed; compared with the existing method of using IMU (Inertial Measurement Unit) and other devices to calculate the velocity vector angle, the cost of the present application is lower and the accuracy is similar; compared with the method of using bus signal calculation, the existing method uses the differential value of the vehicle speed signal, and the vehicle speed signal itself has large noise and poor quality, and the fluctuation and error will be further amplified after differentiation. The present application uses an integral method and will not be affected by this. In addition, based on the sensor characteristics, the present application realizes compensation for the measurement values ​​of the longitudinal and lateral acceleration sensors, that is, the measurement values ​​of the longitudinal and lateral acceleration sensors are corrected, which can further improve the accuracy of the driving slope calculation.

[0123] Optionally, S103, determining the center of mass sideslip angle of the vehicle to be tested based on the correction value of the acceleration sensor includes: judging whether the vehicle to be tested is in a steady-state driving state; if so, determining the center of mass sideslip angle based on the yaw angular velocity value, the current vehicle speed and the tire sideslip coefficient; if not, determining the center of mass sideslip angle based on the correction value of the lateral acceleration sensor, the yaw angular velocity value, the current vehicle speed and the tire sideslip coefficient.

[0124] Specifically, the formula for the center of mass sideslip angle β is: Where v is the lateral velocity of the vehicle, u x is the longitudinal velocity of the vehicle.

[0125] When the judgment result is that the vehicle under test is in a normal steady-state driving state and the wheels do not slip, that is, the lateral velocity v of the vehicle is composed of the vehicle yaw and tire sideways. The lateral velocity v caused by the tire sideways under steady-state conditions is basically linearly related to the vehicle's centripetal acceleration. Use the current vehicle speed u n 、Yaw angular velocity-ω yaw With coefficient K w Calculate. At this time, the lateral velocity v of the vehicle's center of mass is: v = -ω yaw ×L ar +ω yaw ×u n 2 ×K w Among them, L ar is the distance from the acceleration sensor to the rear axle; ω yaw is the vehicle yaw angular velocity; K w is the tire slip coefficient, which is a standard quantity. Then the vehicle's center of mass slip angle is:

[0126]

[0127] When the vehicle is in an unsteady state and the wheels are slipping, the lateral speed of the vehicle also includes the lateral translation speed. The present invention uses the integral method to estimate the lateral speed at this time. The specific method is that after receiving the vehicle ESC trigger signal, according to the following formula:

[0128] A y_fixed =A y_hull +g×sin(tan -1 i y / 100)-ω yaw ×u x

[0129] At this time, the lateral slope i y The output value calculated by the slope rotation transformation algorithm is the same as A y_fixed Decoupling, the lateral translation acceleration of the vehicle body A y_hullThe value can be calculated. Since the triggering condition of ESC is based on the calculation result of wheel speed, the lateral speed of the vehicle is very small when it is triggered and is ignored here. The lateral speed of the vehicle body when slipping occurs is:

[0130]

[0131] The center of mass sideslip angle at this time is:

[0132]

[0133] In the embodiment of the present invention, in terms of the calculation of the center of mass slip angle, the existing center of mass slip angle estimation methods are mostly based on dynamic model calculations, and few methods realize the center of mass slip angle estimation based on bus signals. The present application is based on speed estimation, slope estimation, and acceleration sensor compensation, and uses more accurate speed and slope signals to achieve accurate calculation of the vehicle center of mass slip angle under steady-state and non-steady-state conditions.

[0134] Figure 8 It is a structural diagram of a vehicle signal processing device provided by an embodiment of the present invention.

[0135] like Figure 8 As shown, the vehicle signal processing device includes:

[0136] A signal acquisition unit 81 is used to acquire a bus signal of the vehicle to be tested, wherein the bus signal at least includes a yaw angular velocity value, a lateral translation acceleration value, a lateral slope value, and a yaw angular acceleration value;

[0137] A measurement value correction unit 82, used to correct the measurement value of the acceleration sensor based on the bus signal to obtain a correction value of the acceleration sensor, wherein the acceleration sensor includes a longitudinal acceleration sensor and a lateral acceleration sensor;

[0138] The signal processing unit 83 is used to determine the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested based on the correction value of the acceleration sensor.

[0139] Optionally, the measurement value correction unit 82 is specifically used for:

[0140] Correcting the longitudinal acceleration sensor based on the yaw angular velocity value to obtain a correction value of the longitudinal acceleration sensor;

[0141] The lateral acceleration sensor is corrected based on the yaw angular acceleration value to obtain a correction value of the lateral acceleration sensor.

[0142] Optionally, the signal processing unit 83 determines the current speed of the vehicle to be tested based on the correction value of the acceleration sensor, specifically including:

[0143] Calculating a true longitudinal acceleration value based on a correction value of the longitudinal acceleration sensor;

[0144] Determine the synchronous speed value at the current moment according to the real longitudinal acceleration value;

[0145] Determine whether the vehicle to be tested is in a slipping state;

[0146] If yes, determining a first speed estimate based on the true longitudinal acceleration value and the synchronous speed at the current moment;

[0147] The first speed estimation value and the first fused speed value are fused through a second Kalman filter to obtain a second fused speed value, wherein the first fused speed value is obtained by fusing the front axle speed and the rear axle speed of the vehicle to be tested through the first Kalman filter, and the second fused speed value is the current vehicle speed of the vehicle to be tested.

[0148] Optionally, if the vehicle to be tested is not in a slipping state, the measured value correction unit 82 is further used to:

[0149] A first speed estimate is determined based on the current synchronous speed.

[0150] Optionally, the driving slope includes a longitudinal slope and a lateral slope, and the measured value correction unit 82 determines the driving slope of the vehicle to be tested based on the correction value of the acceleration sensor, including:

[0151] Determine whether the vehicle to be tested has slipped;

[0152] If not, the longitudinal slope is determined based on the correction value of the longitudinal acceleration sensor, the current vehicle speed at the current moment and the current vehicle speed k sampling periods ago, and the lateral slope is determined based on the correction value of the lateral acceleration sensor, the yaw angular velocity value and the longitudinal vehicle speed.

[0153] Optionally, if the vehicle to be tested does not slip, the measurement value correction unit 82 determines the driving slope of the vehicle to be tested based on the correction value of the acceleration sensor, including:

[0154] Determine the longitudinal slope based on the correction value of the longitudinal acceleration sensor, the current vehicle speed at the current moment, the current vehicle speed k sampling periods ago, and the first turning angle value, wherein the first turning angle value is the turning angle value of the vehicle body relative to the ground due to the different suspension heights of the front and rear axles of the vehicle;

[0155] The lateral slope is determined based on the correction value of the lateral acceleration sensor, the yaw angular velocity value, the longitudinal vehicle speed and the second turning angle value, wherein the second turning angle value is the turning angle value of the vehicle body relative to the ground due to the different suspension heights of the left and right axles of the vehicle.

[0156] Optionally, if the vehicle to be tested slips, the measurement value correction unit 82 is further used to:

[0157] Convert the longitudinal slope and lateral slope of the road surface on which the vehicle to be tested is currently located into a longitudinal slope vector and a lateral slope vector respectively;

[0158] Establishing a current road surface plane based on the longitudinal slope vector and the lateral slope vector, and obtaining a normal vector of the current road surface plane;

[0159] And construct a rotation matrix based on the normal vector of the current road surface plane;

[0160] Determine a rotated longitudinal slope vector and a lateral slope vector based on the rotation matrix;

[0161] The longitudinal slope and the lateral slope are determined based on the rotated longitudinal slope vector and the lateral slope vector, respectively.

[0162] Optionally, the measurement value correction unit 82 determines the center of mass sideslip angle of the vehicle to be tested based on the correction value of the acceleration sensor, including:

[0163] Determine whether the vehicle to be tested is in a steady-state driving state;

[0164] If yes, determine the center of mass slip angle based on the yaw rate value, the current vehicle speed and the tire slip coefficient;

[0165] If not, the center of mass slip angle is determined based on the correction value of the lateral acceleration sensor, the yaw rate value, the current vehicle speed and the tire slip coefficient.

[0166] The device provided in the embodiment of the present invention has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0167] The vehicle signal processing method provided in the embodiment of the present invention has the same technical features as the vehicle signal processing device provided in the above embodiment, so it can also solve the same technical problems and achieve the same technical effects.

[0168] An embodiment of the present invention further provides an electronic control unit, which executes the vehicle signal processing method in any of the above embodiments.

[0169] The electronic control unit provided in the embodiment of the present invention uses the vehicle signal processing method in the above embodiment, so the electronic control unit provided in the embodiment of the present invention also has the beneficial effects described in the above embodiment, which will not be described again here.

[0170] An embodiment of the present invention further provides a driving device, which includes the electronic control unit in any of the above embodiments.

[0171] The driving device provided in the embodiment of the present invention includes the electronic control unit in the above embodiment, so the driving device provided in the embodiment of the present invention also has the beneficial effects described in the above embodiment, which will not be repeated here.

[0172] In the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0173] Finally, it should be noted that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A vehicle signal processing method, It is characterized in that The vehicle signal processing method comprises: Acquiring a bus signal of the vehicle to be tested, wherein the bus signal at least includes a yaw angular velocity value and a yaw angular acceleration value; Correcting a measurement value of an acceleration sensor based on the bus signal to obtain a correction value of the acceleration sensor, wherein the acceleration sensor includes a longitudinal acceleration sensor and a lateral acceleration sensor; Determining the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested based on the correction value of the acceleration sensor; Wherein, determining the current speed of the vehicle to be tested based on the correction value of the acceleration sensor includes: Calculating a true longitudinal acceleration value based on the correction value of the longitudinal acceleration sensor; Determine the synchronous speed value at the current moment according to the true longitudinal acceleration value; wherein the synchronous speed value at the current moment is the sum of the first fusion speed n sampling steps ago and the integral of the true longitudinal acceleration value within n steps; Determining whether the vehicle to be tested is in a slipping state; If yes, determining a first speed estimate value based on the true longitudinal acceleration value and the synchronous speed at the current moment; The first speed estimation value and the first fused speed value are fused through a second Kalman filter to obtain a second fused speed value, wherein the first fused speed value is obtained by fusing the front axle speed and the rear axle speed of the vehicle to be tested through the first Kalman filter, and the second fused speed value is the current vehicle speed of the vehicle to be tested.

2. The vehicle signal processing method according to claim 1, It is characterized in that The step of correcting the measured value of the acceleration sensor based on the bus signal to obtain the corrected value of the acceleration sensor comprises: Correcting the longitudinal acceleration sensor based on the yaw angular velocity value to obtain a correction value of the longitudinal acceleration sensor; The lateral acceleration sensor is corrected based on the yaw angular acceleration value to obtain a correction value of the lateral acceleration sensor.

3. The vehicle signal processing method according to claim 1, It is characterized in that If the vehicle to be tested is not in a slipping state, the vehicle signal processing method further includes: A first speed estimate is determined based on the current synchronous speed.

4. The vehicle signal processing method according to claim 2, It is characterized in that The driving slope includes a longitudinal slope and a lateral slope, and the determining the driving slope of the vehicle to be tested based on the correction value of the acceleration sensor includes: Determining whether the vehicle to be tested has slipped; If not, the longitudinal slope is determined based on the correction value of the longitudinal acceleration sensor, the current vehicle speed at the current moment and the current vehicle speed k sampling periods ago, and the lateral slope is determined based on the correction value of the lateral acceleration sensor, the yaw angular velocity value and the longitudinal vehicle speed.

5. The vehicle signal processing method according to claim 4, It is characterized in that If the vehicle to be tested does not slip, then determining the driving slope of the vehicle to be tested based on the correction value of the acceleration sensor includes: Determine the longitudinal slope based on the correction value of the longitudinal acceleration sensor, the current vehicle speed at the current moment, the current vehicle speed k sampling periods ago, and a first turning angle value, wherein the first turning angle value is a turning angle value of the vehicle body relative to the ground due to different suspension heights of front and rear axles of the vehicle; The lateral slope is determined based on the correction value of the lateral acceleration sensor, the yaw angular velocity value, the longitudinal vehicle speed and a second turning angle value, wherein the second turning angle value is a turning angle value of the vehicle body relative to the ground due to different suspension heights of left and right axles of the vehicle.

6. The vehicle signal processing method according to claim 4, It is characterized in that If the vehicle to be tested slips, the longitudinal slope and the lateral slope of the road surface on which the vehicle to be tested is currently located are converted into a longitudinal slope vector and a lateral slope vector respectively; Establishing a current road surface plane based on the longitudinal slope vector and the lateral slope vector, and obtaining a normal vector of the current road surface plane; and constructing a rotation matrix based on the normal vector of the current road surface plane; Determining a rotated longitudinal slope vector and a lateral slope vector based on the rotation matrix; The longitudinal slope and the lateral slope are determined based on the rotated longitudinal slope vector and the lateral slope vector, respectively.

7. The vehicle signal processing method according to claim 2, It is characterized in that Determining the sideslip angle of the center of mass of the vehicle to be tested based on the correction value of the acceleration sensor includes: Determining whether the vehicle to be tested is in a steady-state driving state; If yes, determining the center of mass sideslip angle based on the yaw rate value, the current vehicle speed and the tire sideslip coefficient; If not, the center of mass sideslip angle is determined based on the correction value of the lateral acceleration sensor, the yaw angular velocity value, the current vehicle speed and the tire sideslip coefficient.

8. A vehicle signal processing device, It is characterized in that The vehicle signal processing device comprises: A signal acquisition unit, used to acquire a bus signal of the vehicle to be tested, wherein the bus signal at least includes a yaw angular velocity value, a lateral translation acceleration value, a lateral slope value, and a yaw angular acceleration value; a measurement value correction unit, configured to correct a measurement value of an acceleration sensor based on the bus signal to obtain a correction value of the acceleration sensor, wherein the acceleration sensor includes a longitudinal acceleration sensor and a lateral acceleration sensor; A signal processing unit, used for determining the current vehicle speed, driving slope and center of mass sideslip angle of the vehicle to be tested based on the correction value of the acceleration sensor; Wherein, the signal processing unit comprises: The current vehicle speed determination subunit is used to calculate the true longitudinal acceleration value based on the correction value of the longitudinal acceleration sensor; determine the synchronous speed value at the current moment according to the true longitudinal acceleration value; wherein the synchronous speed value at the current moment is the sum of the first fused speed n sampling steps ago and the integral of the true longitudinal acceleration value within n steps; determine whether the vehicle to be tested is in a slip state; if so, determine a first speed estimate value based on the true longitudinal acceleration value and the synchronous speed at the current moment; fuse the first speed estimate value and the first fused speed value through a second Kalman filter to obtain a second fused speed value, wherein the first fused speed value is obtained by fusing the front axle speed and the rear axle speed of the vehicle to be tested through the first Kalman filter, and the second fused speed value is the current vehicle speed of the vehicle to be tested.

9. An electronic control unit, It is characterized in that The electronic control unit executes the vehicle signal processing method described in any one of claims 1-7.

10. A driving device, It is characterized in that The driving device comprises the electronic control unit as claimed in claim 9 above.

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