Vehicle speed estimation method, device and equipment and readable storage medium

Abstract

The invention discloses a vehicle speed estimation method, device and equipment and a readable storage medium, which can be applied to the technical field of vehicles, and the method comprises the following steps: based on a four-wheel rotation angle, a four-wheel rotation speed and a yaw velocity, respectively determining predicted speeds corresponding to four wheels of a vehicle, a left front wheel corresponding to a first predicted speed and a right front wheel corresponding to a second predicted speed, the left rear wheel corresponds to a third predicted speed, and the right rear wheel corresponds to a fourth predicted speed; determining a first vehicle speed boundary and a second vehicle speed boundary of the vehicle according to the predicted speed based on the vehicle driving condition; estimating a coarse vehicle speed of the vehicle based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary, and the longitudinal acceleration; and performing Kalman filtering on the rough vehicle speed to obtain an estimated vehicle speed of the vehicle. Therefore, the concept of the vehicle speed boundary is introduced, the rough vehicle speed of the vehicle is estimated firstly, and then the rough vehicle speed is filtered through Kalman filtering, so that the rationalization and credibility of vehicle speed estimation are improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle speed estimation method, device, equipment and readable storage medium. Background Art

[0002] With the continuous improvement of vehicle stability control systems, the active safety capabilities of the entire vehicle have been greatly improved. Common stability control systems complete vehicle stability status identification through vehicle parameter fusion, and then prevent the vehicle from encountering dangerous conditions through slip rate control or engine torque control.

[0003] Common stability control systems, such as Bosch IPB and Continental MKCI, all collect parameters through sensors and then perform parameter fusion. In the identification of some dangerous working conditions, longitudinal vehicle speed is the core vehicle parameter. However, the existing longitudinal vehicle speed estimation methods are mostly based on working conditions, and wheel speed is preferred as the estimated vehicle speed. This method will reduce the accuracy when the vehicle loses handling stability, resulting in low credibility of vehicle speed estimation.

[0004] Therefore, how to improve the reliability of vehicle speed estimation is a problem that technical personnel in this field need to solve urgently. Summary of the invention

[0005] Based on the above problems, the present application provides a vehicle speed estimation method, device, equipment and readable storage medium. By introducing the concept of vehicle speed boundary, the rough speed of the vehicle is first estimated, and then the rough speed is filtered through Kalman filtering, thereby solving the problem of low credibility of vehicle speed estimation in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a vehicle speed estimation method, characterized in that the method comprises:

[0007] Based on the four-wheel turning angles, the four-wheel speeds and the yaw angular velocity, the predicted speeds corresponding to the four wheels of the vehicle are determined respectively, wherein the left front wheel corresponds to a first predicted speed, the right front wheel corresponds to a second predicted speed, the left rear wheel corresponds to a third predicted speed, and the right rear wheel corresponds to a fourth predicted speed;

[0008] Based on the vehicle driving condition, determining a first vehicle speed boundary and a second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed;

[0009] estimating a rough vehicle speed of the vehicle based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary, and the longitudinal acceleration;

[0010] Kalman filtering is performed on the rough vehicle speed to obtain an estimated vehicle speed.

[0011] Optionally, before determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition, the method further includes:

[0012] The driving torque, braking torque and longitudinal acceleration of the vehicle are acquired by using sensors, and the driving torque, braking torque and longitudinal acceleration are used as parameters corresponding to the vehicle driving condition.

[0013] Optionally, the determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition includes:

[0014] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0015] When the driving torque is less than the driving torque threshold and the braking torque is less than the braking torque threshold, or the longitudinal acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, if the vehicle is a front-wheel drive vehicle, the first maximum wheel speed is used as the first vehicle speed boundary and the third maximum wheel speed is used as the second vehicle speed boundary;

[0016] When the driving torque is less than the driving torque threshold and the braking torque is less than the braking torque threshold, or the longitudinal acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, if the vehicle is a four-wheel drive vehicle, the first maximum wheel speed is used as the first vehicle speed boundary, and the fourth maximum wheel speed is used as the second vehicle speed boundary.

[0017] Optionally, the determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition includes:

[0018] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0019] When the driving torque is greater than the driving torque threshold, or the longitudinal acceleration is greater than the driving acceleration threshold, if the vehicle is a front-wheel drive vehicle, the second largest wheel speed is used as the first vehicle speed boundary, and the third largest wheel speed is used as the second vehicle speed boundary;

[0020] When the driving torque is greater than the driving torque threshold, or the longitudinal acceleration is greater than the driving acceleration threshold, if the vehicle is a four-wheel drive vehicle, the fourth largest wheel speed is used as the first vehicle speed boundary, and the first vehicle speed collected when the driving torque is greater than the driving torque threshold is used as the second vehicle speed boundary.

[0021] Optionally, the determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition includes:

[0022] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0023] When the braking torque is greater than a braking torque threshold, or the longitudinal acceleration is less than a braking acceleration threshold, the second vehicle speed acquired when the braking torque is greater than the braking torque threshold is used as the first vehicle speed boundary, and the first maximum wheel speed is used as the second vehicle speed boundary.

[0024] Optionally, before estimating the rough vehicle speed of the vehicle based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary and the longitudinal acceleration, the method further includes:

[0025] The lateral speed of the vehicle is calculated based on the nominal value of the vehicle travel.

[0026] Optionally, estimating a rough vehicle speed based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary, and the longitudinal acceleration includes:

[0027] Using the first vehicle speed boundary and the second vehicle speed boundary as the upper limit and the lower limit of the integral respectively, performing an integral operation on the vehicle speed estimation formula to obtain a rough vehicle speed;

[0028] The vehicle speed estimation formula is:

[0029] Said is the real-time longitudinal speed, the a x is the longitudinal acceleration, the w r is the yaw angular velocity, the v y is the lateral vehicle speed.

[0030] In a second aspect, an embodiment of the present application provides a vehicle speed estimation device, comprising:

[0031] A longitudinal vehicle speed prediction module is used to determine the predicted speeds corresponding to the four wheels of the vehicle based on the four-wheel turning angles, the four-wheel speeds and the yaw angular velocity, wherein the left front wheel corresponds to a first predicted speed, the right front wheel corresponds to a second predicted speed, the left rear wheel corresponds to a third predicted speed, and the right rear wheel corresponds to a fourth predicted speed;

[0032] a vehicle speed boundary determination module, configured to determine a first vehicle speed boundary and a second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition;

[0033] A vehicle speed estimation module, configured to estimate a rough vehicle speed of the vehicle based on a lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary, and a longitudinal acceleration;

[0034] The state observer is used to perform Kalman filtering on the rough vehicle speed to obtain an estimated vehicle speed.

[0035] In a third aspect, an embodiment of the present application provides a vehicle speed estimation device, including:

[0036] Memory for storing computer programs;

[0037] The processor is used to implement the steps of the vehicle speed estimation method as described above when executing the computer program.

[0038] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the vehicle speed estimation method as described above are implemented.

[0039] It can be seen from the above technical solutions that compared with the prior art, the present application has the following advantages:

[0040] The present application first determines the predicted speeds corresponding to the four wheels of the vehicle based on the four-wheel turning angles, the four-wheel speeds and the yaw angular velocity, wherein the left front wheel corresponds to the first predicted speed, the right front wheel corresponds to the second predicted speed, the left rear wheel corresponds to the third predicted speed, and the right rear wheel corresponds to the fourth predicted speed. Then, based on the vehicle's driving conditions, the first speed boundary and the second speed boundary of the vehicle are determined according to the predicted speeds. Finally, the rough speed of the vehicle is estimated based on the lateral speed, the first speed boundary, the second speed boundary and the longitudinal acceleration, and the rough speed is Kalman filtered to obtain the estimated speed of the vehicle. In this way, the concept of speed boundary is introduced, the rough speed of the vehicle is estimated first, and then the rough speed is filtered by Kalman filtering, thereby improving the rationality and credibility of the speed estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a vehicle speed estimation method provided in an embodiment of the present application;

[0042] Figure 2 A schematic diagram of a vehicle reference system provided in an embodiment of the present application;

[0043] Figure 3 A schematic diagram of a system composition provided in an embodiment of the present application;

[0044] Figure 4 A schematic diagram of the structure of a vehicle speed estimation device provided in an embodiment of the present application;

[0045] Figure 5 A specific architecture diagram of a longitudinal vehicle speed estimation module provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] As mentioned above, the existing longitudinal speed estimation method has the problem of low reliability of speed estimation. Specifically, during vehicle driving, the chassis controller estimates the vehicle speed based on the working conditions of the vehicle. For example, when a two-wheel drive vehicle is accelerating, the actual vehicle speed is close to the speed of the non-driving wheels; when the vehicle is under ABS control, the four wheels take turns to maintain pressure, release pressure and increase pressure, and the vehicle speed can be the maximum wheel speed of the four wheels, etc. This method has a certain accuracy when the vehicle is driving normally, but when the vehicle loses handling stability, it affects the correlation between the wheel speed and the longitudinal vehicle speed, resulting in the problem of low reliability of the vehicle speed estimation.

[0047] In order to solve the above problems, the present application provides a vehicle speed estimation method, including: first, based on the four-wheel turning angle, the four-wheel speed and the yaw angular velocity, respectively determine the predicted speeds corresponding to the four wheels of the vehicle, wherein the left front wheel corresponds to the first predicted speed, the right front wheel corresponds to the second predicted speed, the left rear wheel corresponds to the third predicted speed, and the right rear wheel corresponds to the fourth predicted speed. Then, based on the vehicle driving conditions, the first speed boundary and the second speed boundary of the vehicle are determined according to the predicted speed. Finally, the rough speed of the vehicle is estimated based on the lateral speed, the first speed boundary, the second speed boundary and the longitudinal acceleration, and the rough speed is subjected to Kalman filtering to obtain the estimated speed of the vehicle.

[0048] In this way, the concept of vehicle speed boundary is introduced. The rough speed of the vehicle is first estimated, and then the rough speed is filtered through Kalman filtering, thereby improving the rationality and credibility of the vehicle speed estimation.

[0049] It should be noted that the vehicle speed estimation method, device, equipment and readable storage medium provided by the present application can be applied to the field of vehicle technology. The above is only an example and does not limit the application field of the vehicle speed estimation method, device, equipment and readable storage medium provided by the present application.

[0050] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0051] Figure 1 A flow chart of a vehicle speed estimation method provided in an embodiment of the present application. Figure 1 As shown, a vehicle speed estimation method provided by the present application may include:

[0052] S101: Based on the four-wheel turning angles, four-wheel rotation speeds and yaw angular velocity, respectively determine the predicted speeds corresponding to the four wheels of the vehicle, wherein the left front wheel corresponds to a first predicted speed, the right front wheel corresponds to a second predicted speed, the left rear wheel corresponds to a third predicted speed, and the right rear wheel corresponds to a fourth predicted speed.

[0053] In practical applications, common longitudinal speed estimation methods are mostly based on working conditions, and wheel speed is preferred as the estimated speed. This estimation will reduce accuracy when the vehicle loses handling stability, resulting in low reliability of speed estimation. To this end, the present application provides a speed estimation method that introduces the concept of speed boundary, first estimates the rough speed of the vehicle, and then filters the rough speed through Kalman filtering, thereby improving the rationality and reliability of speed estimation. First, determine the predicted speed of the four wheels of the vehicle. Specifically, Figure 2 A schematic diagram of a vehicle reference system provided in an embodiment of the present application. Figure 2 As shown, based on the rigid body motion relationship, there is the following relationship describing the longitudinal velocity of the wheel center and the velocity of the vehicle's center of mass:

[0054]

[0055] Among them, V FL , V FR , V RL and V RR are the wheel center speeds of the left front wheel, right front wheel, left rear wheel and right rear wheel respectively; v x and v y are the longitudinal speed and lateral speed of the vehicle respectively; w r is the yaw rate; a and b are the distances from the front axle to the center of mass and the distances from the rear axle to the center of mass, respectively; c1 and c2 are the front axle semi-wheelbase and the rear axle semi-wheelbase, respectively. During vehicle driving, assuming that the vehicle is driving smoothly (the lateral speed is credible), then all wheel center longitudinal speeds are equal to the product of the effective wheel radius and the wheel speed, and the wheel speed is the measured output of the wheel speed sensor. Then there is the following expression:

[0056]

[0057] Among them, w FL is the angular velocity of the left front wheel; R FL is the effective radius of the left front wheel; δ FL is the left front wheel turning angle. In this way, the first to fourth predicted speeds are obtained, corresponding to the left front wheel, right front wheel, left rear wheel and right rear wheel respectively. If the lateral speed credibility is low, it is considered that when the vehicle is driving, the tire slip angle is very small, and the wheel center speed and can be equivalent to the wheel center lateral speed. Adding the assumption, the following expression is obtained:

[0058] v xFL =w FL R FL cosδ FL +w r c1

[0059] v xFR =w FR R FR cosδ FR -w r c1

[0060] v xRL =w RL R RL cosδ RL +w r c2

[0061] v xRR =w RR R RR cosδ RR -w r c2

[0062] Thus, according to the above formula, when the lateral speed is unreliable, the left front wheel corresponds to the first predicted speed, the right front wheel corresponds to the second predicted speed, the left rear wheel corresponds to the third predicted speed, and the right rear wheel corresponds to the fourth predicted speed. Among them, the four-wheel steering angle can be obtained through the chassis CAN message using an algorithm, the four-wheel speed is obtained using a wheel speed sensor, and the yaw angular velocity is obtained using an inertial measurement unit (IMU).

[0063] S102: Based on the vehicle driving condition, determine a first vehicle speed boundary and a second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed.

[0064] In practical applications, existing longitudinal vehicle speed estimation methods are mostly based on working conditions, and wheel speed is preferred as the estimated vehicle speed. The accuracy of this method will decrease when the vehicle loses handling stability, resulting in the problem of low credibility of vehicle speed estimation. In the embodiment of the present application, an extended discussion is conducted to prevent this situation. Specifically, there are the following possibilities: regardless of whether the lateral speed is credible, the first predicted speed corresponding to the left front wheel, the second predicted speed corresponding to the right front wheel, the third predicted speed corresponding to the left rear wheel, and the fourth predicted speed corresponding to the right rear wheel calculated above are not necessarily valid, because the vehicle may be in certain driving conditions where the tires are unstable. For this reason, the embodiment of the present application needs to be processed by driving condition determination to convert the first to fourth predicted speeds into the first vehicle speed boundary and the second vehicle speed boundary.

[0065] In addition, since the methods for judging driving conditions are not the same, the embodiment of the present application can illustrate a possible judgment method.

[0066] In one case, before determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition, the method further includes:

[0067] The driving torque, braking torque and longitudinal acceleration of the vehicle are acquired by using sensors, and the driving torque, braking torque and longitudinal acceleration are used as parameters corresponding to the vehicle driving condition.

[0068] In actual applications, active control is activated, and the vehicle's four-wheel drive torque, braking torque, longitudinal acceleration after excluding slope, and road adhesion estimation are obtained through vehicle sensors as parameters corresponding to the vehicle's driving conditions, which are then integrated and combined with the four-wheel steering angle to judge the driving conditions.

[0069] In addition, since there are different ways to determine the vehicle speed boundary, the embodiment of the present application can illustrate a possible determination method.

[0070] In one case, determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle based on the vehicle driving condition and according to the first predicted speed, the second predicted speed, the third predicted speed, and the fourth predicted speed includes:

[0071] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0072] When the driving torque is less than the driving torque threshold and the braking torque is less than the braking torque threshold, or the longitudinal acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, if the vehicle is a front-wheel drive vehicle, the first maximum wheel speed is used as the first vehicle speed boundary and the third maximum wheel speed is used as the second vehicle speed boundary;

[0073] When the driving torque is less than the driving torque threshold and the braking torque is less than the braking torque threshold, or the longitudinal acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, if the vehicle is a four-wheel drive vehicle, the first maximum wheel speed is used as the first vehicle speed boundary, and the fourth maximum wheel speed is used as the second vehicle speed boundary.

[0074] In practical applications, the vehicle speed boundary is determined from the first to fourth predicted speeds according to the vehicle driving conditions. Specifically, the first to fourth predicted speeds are first sorted to obtain the first maximum wheel speed, the second maximum wheel speed, the third maximum wheel speed and the fourth maximum wheel speed. When the driving torque is less than the driving torque threshold, and the braking torque is less than the braking torque threshold; or the acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, the following definitions are made according to the different vehicle driving forms: for front-wheel drive vehicles, the first wheel boundary is the first maximum wheel speed, and the second vehicle speed boundary is the third maximum wheel speed; for four-wheel drive vehicles, the first vehicle speed boundary is the first maximum wheel speed, and the second vehicle speed boundary is the third maximum wheel speed; wherein, if a certain wheel is in an active control state, the boundary is extended accordingly. For example, when the driving torque of a vehicle is less than the driving torque threshold, and the braking torque is less than the braking torque threshold, and the maximum wheel speed of the vehicle is in the TCS control state, the first vehicle speed boundary is the second maximum wheel speed, and the second vehicle speed boundary is the fourth maximum wheel speed. In addition, the braking torque threshold, driving torque threshold and acceleration threshold can all be obtained by looking up the table of the road adhesion coefficient estimation module. In other words, the vehicle defines and pre-stores the corresponding braking torque threshold, driving torque threshold and acceleration threshold according to different road adhesion coefficients. When the vehicle sensor determines the road adhesion coefficient at this time, the current braking torque threshold, driving torque threshold and acceleration threshold can be determined by looking up the table. The torque threshold (brake torque threshold / drive torque threshold) is defined in a physical sense as 85% of the drive / brake torque when the vehicle is close to longitudinal instability. For example, the adhesion value obtained by the road adhesion estimation is 0.5. According to the design of the vehicle braking system, it can be known that the braking torque when the braking intensity is 0.5, and its value multiplied by the coefficient of 0.85 is the braking torque threshold at this time. The acceleration threshold directly corresponds to 85% of the acceleration / braking intensity that the current road surface can provide. This design is applicable to both EHB and EMB systems.

[0075] In addition, since there are different ways to determine the vehicle speed boundary, the embodiment of the present application may illustrate another possible determination method.

[0076] In another case, the determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition includes:

[0077] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0078] When the driving torque is greater than the driving torque threshold, or the longitudinal acceleration is greater than the driving acceleration threshold, if the vehicle is a front-wheel drive vehicle, the second largest wheel speed is used as the first vehicle speed boundary, and the third largest wheel speed is used as the second vehicle speed boundary;

[0079] When the driving torque is greater than the driving torque threshold, or the longitudinal acceleration is greater than the driving acceleration threshold, if the vehicle is a four-wheel drive vehicle, the fourth largest wheel speed is used as the first vehicle speed boundary, and the first vehicle speed collected when the driving torque is greater than the driving torque threshold is used as the second vehicle speed boundary.

[0080] In practical applications, the vehicle speed boundary is determined from the first to fourth predicted speeds according to the vehicle driving conditions. Specifically, the first to fourth predicted speeds are first sorted to obtain the first maximum wheel speed, the second maximum wheel speed, the third maximum wheel speed and the fourth maximum wheel speed. When the driving torque is greater than the driving torque threshold, or the acceleration is greater than the acceleration threshold, the following definitions are made according to the different vehicle drive forms: for front-wheel drive vehicles, the first speed boundary is the second maximum wheel speed, and the second speed boundary is the third maximum wheel speed; for four-wheel drive vehicles, the first speed boundary is the fourth maximum wheel speed, and the second speed boundary is the vehicle speed collected instantaneously when the driving torque is greater than the driving torque threshold.

[0081] In addition, since there are different ways to determine the vehicle speed boundary, the embodiment of the present application can illustrate another possible determination method.

[0082] In yet another embodiment, determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed, and the fourth predicted speed based on the vehicle driving condition includes:

[0083] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0084] When the braking torque is greater than a braking torque threshold, or the longitudinal acceleration is less than a braking acceleration threshold, the second vehicle speed acquired when the braking torque is greater than the braking torque threshold is used as the first vehicle speed boundary, and the first maximum wheel speed is used as the second vehicle speed boundary.

[0085] In practical applications, the vehicle speed boundary is determined from the first to fourth predicted speeds according to the vehicle driving conditions. Specifically, the first to fourth predicted speeds are first sorted to obtain the first maximum wheel speed, the second maximum wheel speed, the third maximum wheel speed and the fourth maximum wheel speed. When the braking torque is greater than the braking torque threshold, or the acceleration is less than the braking acceleration threshold, the following definition is given: the first speed boundary is the vehicle speed collected instantly when the braking torque is greater than the braking torque threshold, and the second speed boundary is the first maximum wheel speed. It should be noted that due to the characteristics of the vehicle, this state lasts for a maximum of two seconds, and returns to state 1 after two seconds for one cycle. It should be noted that the braking torque and driving torque here are calculated as absolute values, while the acceleration less than the braking acceleration threshold is calculated as positive and negative acceleration. For example, the current acceleration is -0.7g, the acceleration threshold is -0.55g, -0.7g<-0.55g, but the absolute value of -0.7g is greater than the absolute value of 0.55g.

[0086] S103: Estimate a rough vehicle speed of the vehicle based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary, and the longitudinal acceleration.

[0087] In practical applications, vehicle speed estimation requires the introduction of lateral vehicle speed and longitudinal acceleration, and an integral calculation is performed based on the vehicle speed boundary obtained by the above calculation to determine the rough vehicle speed of the estimated vehicle.

[0088] In addition, since there are different ways to obtain the lateral speed of the vehicle, the embodiment of the present application can illustrate a possible acquisition method.

[0089] In one embodiment, before estimating the rough vehicle speed of the vehicle based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary and the longitudinal acceleration, the method further includes:

[0090] The lateral speed of the vehicle is calculated based on the nominal value of the vehicle travel.

[0091] In practical applications, when the lateral vehicle speed signal is credible, the lateral vehicle speed is directly output to the vehicle speed estimation module; if the lateral vehicle speed signal is unreliable, the lateral vehicle speed is calculated based on the nominal value of the vehicle using an algorithm:

[0092]

[0093] Where b is the distance from the vehicle's center of mass to the rear axle, a is the distance from the vehicle's center of mass to the front axle, K is the stability factor, K2 is the rear axle lateral stiffness, is the nominal value of the yaw rate of steady-state steering, L is the distance from the center of the front axle to the center of the rear axle, u is the longitudinal speed of the vehicle, and v x is also the longitudinal velocity of the vehicle. In order to avoid algebraic loops, the present invention uses the nominal value of the lateral velocity in the previous cycle as input, vynom It is the nominal value of the vehicle's lateral speed.

[0094] In addition, since there are different ways to estimate the rough speed of the vehicle, the embodiment of the present application can illustrate a possible estimation method.

[0095] In one embodiment, estimating a rough speed of the vehicle based on the lateral speed, the first speed boundary, the second speed boundary, and the longitudinal acceleration includes:

[0096] Using the first vehicle speed boundary and the second vehicle speed boundary as the upper limit and the lower limit of the integral respectively, performing an integral operation on the vehicle speed estimation formula to obtain a rough vehicle speed;

[0097] The vehicle speed estimation formula is:

[0098] Said is the real-time longitudinal speed, the a x is the longitudinal acceleration, the w r is the yaw angular velocity, the v y is the lateral vehicle speed.

[0099] In practical applications, the vehicle speed estimation module is one of the core modules. During vehicle driving, the vehicle speed satisfies the following expression: where a x is the longitudinal acceleration of the vehicle, which is equal to the acceleration compensation obtained by excluding the slope estimation from the IMU acceleration value. The vehicle speed estimation module performs integral calculation according to the above formula, takes the first vehicle speed boundary and the second vehicle speed boundary as the upper and lower limits of the integral, and outputs the rough vehicle speed in real time.

[0100] S104: Perform Kalman filtering on the rough vehicle speed to obtain an estimated vehicle speed.

[0101] In practical applications, the Kalman filter can be regarded as a state observer, through which the dynamic method is introduced to estimate the longitudinal speed, thereby improving the credibility of the vehicle speed estimation. When the vehicle is moving longitudinally, the sum of the longitudinal forces of the tires provides the vehicle with the following expression:

[0102]

[0103] Among them, F Z is the vertical force, which is obtained by calculating the load transfer from the vehicle acceleration. The adhesion coefficient μ is given by the road adhesion coefficient estimation module, the tire slip angle is given by the lateral speed estimation module, and the slip rate can be converted into the relationship between the vehicle speed and the wheel speed. Then, a linear tire model is used to establish an observer for the driving process. The linear tire model has the following expression:

[0104]

[0105] After sorting, we get the following expression:

[0106]

[0107] Linearizing the above equation gives the following expression:

[0108]

[0109] That is Kalman's state transfer equation, and then introduce the kinematic longitudinal velocity and the IMU acceleration corrected by the slope estimate As an observation, it has the following expression:

[0110]

[0111] In the formula, w ri Corresponding to the rotation speed of the four wheels, i is 1-4 mapped to the four wheels, R i Corresponding to the effective rolling radius of wheel i, v x is the longitudinal velocity measurement in the Kalman filter state space, For rough longitudinal speed measurement, is the correction value of the acceleration measured by IMU after excluding the slope, μi is the road adhesion at wheel i, and F Zi is the vertical force of wheel i, Clambda is the proportional coefficient, which is a constant in the tire linear segment. In this way, the vehicle speed output by the Kalman filter in the above formula is the longitudinal speed estimation value, that is, the estimated vehicle speed.

[0112] Figure 3 A schematic diagram of a system composition provided in an embodiment of the present application. Figure 3 As shown in the figure, the algorithm is used to obtain the real-time four-wheel steering angle of the vehicle through the chassis CAN message; the longitudinal, lateral acceleration and yaw rate of the vehicle are obtained through the inertial measurement unit (IMU); the four-wheel speed is obtained through the wheel speed sensor; the lateral speed and its reliability are obtained through the lateral vehicle speed estimation algorithm. A series of vehicle sensors are used to obtain road adhesion estimation, drive / brake torque, active control activation signal and slope estimation. With these signals, the driving state of the vehicle can be judged in real time, and then the longitudinal speed estimation is realized based on the current driving state and various sensor fusion.

[0113] In summary, the present application first determines the predicted speeds corresponding to the four wheels of the vehicle based on the four-wheel turning angles, the four-wheel speeds and the yaw angular velocity, wherein the left front wheel corresponds to the first predicted speed, the right front wheel corresponds to the second predicted speed, the left rear wheel corresponds to the third predicted speed, and the right rear wheel corresponds to the fourth predicted speed. Then, based on the vehicle's driving conditions, the first speed boundary and the second speed boundary of the vehicle are determined according to the predicted speeds. Finally, the rough speed of the vehicle is estimated based on the lateral speed, the first speed boundary, the second speed boundary and the longitudinal acceleration, and the rough speed is Kalman filtered to obtain the estimated speed of the vehicle. In this way, the concept of speed boundary is introduced, the rough speed of the vehicle is estimated first, and then the rough speed is filtered by Kalman filtering, thereby improving the rationality and credibility of the speed estimation.

[0114] Based on the vehicle speed estimation method provided in the above embodiment, the present application further provides a vehicle speed estimation device. The vehicle speed estimation device is described below in conjunction with the embodiments and drawings.

[0115] Figure 4 A schematic diagram of the structure of a vehicle speed estimation device provided in an embodiment of the present application. Figure 4 As shown, the vehicle speed estimation device 200 provided in the embodiment of the present application includes:

[0116] The longitudinal vehicle speed prediction module 201 is used to determine the predicted speeds corresponding to the four wheels of the vehicle based on the four-wheel turning angles, the four-wheel speeds and the yaw angular velocity, wherein the left front wheel corresponds to the first predicted speed, the right front wheel corresponds to the second predicted speed, the left rear wheel corresponds to the third predicted speed, and the right rear wheel corresponds to the fourth predicted speed;

[0117] A vehicle speed boundary determination module 202, configured to determine a first vehicle speed boundary and a second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition;

[0118] A vehicle speed estimation module 203, configured to estimate a rough vehicle speed of the vehicle based on a lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary, and a longitudinal acceleration;

[0119] The state observer 204 is used to perform Kalman filtering on the rough vehicle speed to obtain an estimated vehicle speed.

[0120] As an implementation method, the vehicle speed estimation device 200 further includes: an acquisition module;

[0121] The acquisition module is used to acquire the driving torque, braking torque and longitudinal acceleration of the vehicle by using sensors, and use the driving torque, braking torque and longitudinal acceleration as parameters corresponding to the vehicle driving condition.

[0122] As an implementation manner, the vehicle speed boundary determination module 202 is specifically used for:

[0123] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0124] When the driving torque is less than the driving torque threshold and the braking torque is less than the braking torque threshold, or the longitudinal acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, if the vehicle is a front-wheel drive vehicle, the first maximum wheel speed is used as the first vehicle speed boundary and the third maximum wheel speed is used as the second vehicle speed boundary;

[0125] When the driving torque is less than the driving torque threshold and the braking torque is less than the braking torque threshold, or the longitudinal acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, if the vehicle is a four-wheel drive vehicle, the first maximum wheel speed is used as the first vehicle speed boundary, and the fourth maximum wheel speed is used as the second vehicle speed boundary.

[0126] As another implementation, the vehicle speed boundary determination module 202 is further configured to:

[0127] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0128] When the driving torque is greater than the driving torque threshold, or the longitudinal acceleration is greater than the driving acceleration threshold, if the vehicle is a front-wheel drive vehicle, the second largest wheel speed is used as the first vehicle speed boundary, and the third largest wheel speed is used as the second vehicle speed boundary;

[0129] When the driving torque is greater than the driving torque threshold, or the longitudinal acceleration is greater than the driving acceleration threshold, if the vehicle is a four-wheel drive vehicle, the fourth largest wheel speed is used as the first vehicle speed boundary, and the first vehicle speed collected when the driving torque is greater than the driving torque threshold is used as the second vehicle speed boundary.

[0130] As another implementation manner, the vehicle speed boundary determination module 202 is further configured to:

[0131] sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed;

[0132] When the braking torque is greater than a braking torque threshold, or the longitudinal acceleration is less than a braking acceleration threshold, the second vehicle speed acquired when the braking torque is greater than the braking torque threshold is used as the first vehicle speed boundary, and the first maximum wheel speed is used as the second vehicle speed boundary.

[0133] As an implementation mode, the vehicle speed estimation device 200 further includes: a lateral vehicle speed determination module;

[0134] The lateral vehicle speed determination module is used to calculate the lateral vehicle speed of the vehicle according to the nominal value of the vehicle travel.

[0135] As an implementation manner, the vehicle speed estimation module 203 is specifically used for:

[0136] Using the first vehicle speed boundary and the second vehicle speed boundary as an upper limit of integration and a lower limit of integration respectively, performing an integration operation on the vehicle speed estimation formula to obtain a rough vehicle speed;

[0137] The vehicle speed estimation formula is:

[0138] Said is the real-time longitudinal speed, the a x is the longitudinal acceleration, the w r is the yaw angular velocity, the v y is the lateral vehicle speed.

[0139] Figure 5 This is a specific architecture diagram of a longitudinal vehicle speed estimation module provided in an embodiment of the present application. Figure 5 As shown, the longitudinal speed prediction module can obtain the first to fourth predicted speeds through the four-wheel steering angle, the four-wheel speed and the yaw rate; the driving condition judgment module assists in the driving condition judgment through the four-wheel steering angle, the longitudinal acceleration, the road adhesion estimation, the four-wheel drive / braking torque and the lateral acceleration; the vehicle speed boundary determination module determines the first vehicle speed boundary and the second vehicle speed boundary according to the current driving condition; the lateral vehicle speed determination module determines the current lateral vehicle speed through the lateral vehicle speed estimation algorithm and the lateral vehicle speed state, assisted by the four-wheel steering angle and the yaw rate; the vehicle speed estimation module determines the first vehicle speed boundary, the second vehicle speed boundary, the longitudinal acceleration and the lateral vehicle speed according to the first vehicle speed boundary, the second vehicle speed boundary Driving speed estimation; the first speed boundary, the second speed boundary, the longitudinal acceleration and the lateral speed, and the yaw angular velocity jointly determine the current driving state. The fusion weight is obtained through the driving state judgment module (the role of the fusion weight is to achieve the transition between the two methods. The dynamic method is only applicable to small sideslip angles, and the kinematic method must be applicable to large sideslip angles after correcting the sensor offset. The two methods are combined by weight to make it applicable to all working conditions). For example, the preliminary estimation of the vehicle speed can be completed; then, using the vehicle dynamics relationship, the vehicle speed estimated based on the working condition judgment and kinematics can be Kalman filtered using the KF filter to further improve the accuracy of the vehicle speed estimation.

[0140] In summary, the present application first determines the predicted speeds corresponding to the four wheels of the vehicle based on the four-wheel turning angles, the four-wheel speeds and the yaw angular velocity, wherein the left front wheel corresponds to the first predicted speed, the right front wheel corresponds to the second predicted speed, the left rear wheel corresponds to the third predicted speed, and the right rear wheel corresponds to the fourth predicted speed. Then, based on the vehicle's driving conditions, the first speed boundary and the second speed boundary of the vehicle are determined according to the predicted speeds. Finally, the rough speed of the vehicle is estimated based on the lateral speed, the first speed boundary, the second speed boundary and the longitudinal acceleration, and the rough speed is Kalman filtered to obtain the estimated speed of the vehicle. In this way, the concept of speed boundary is introduced, the rough speed of the vehicle is estimated first, and then the rough speed is filtered by Kalman filtering, thereby improving the rationality and credibility of the speed estimation.

[0141] In addition, the present application also provides a vehicle speed estimation device, including: a memory for storing a computer program; and a processor for implementing the steps of the vehicle speed estimation method described above when executing the computer program.

[0142] In addition, the present application also provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the vehicle speed estimation method described above are implemented.

[0143] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A vehicle speed estimation method, characterized in that: The method comprises: Based on the four-wheel turning angles, the four-wheel speeds and the yaw angular velocity, the predicted speeds corresponding to the four wheels of the vehicle are determined respectively, wherein the left front wheel corresponds to a first predicted speed, the right front wheel corresponds to a second predicted speed, the left rear wheel corresponds to a third predicted speed, and the right rear wheel corresponds to a fourth predicted speed; Based on the vehicle driving condition, determining a first vehicle speed boundary and a second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed; estimating a rough vehicle speed of the vehicle based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary, and the longitudinal acceleration; Kalman filtering is performed on the rough vehicle speed to obtain an estimated vehicle speed.

2. The method according to claim 1, characterized in that Before determining the first vehicle speed boundary and the second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition, the method further includes: The driving torque, braking torque and longitudinal acceleration of the vehicle are acquired by using sensors, and the driving torque, braking torque and longitudinal acceleration are used as parameters corresponding to the vehicle driving condition.

3. The method according to claim 2, characterized in that The determining, based on the vehicle driving condition and according to the first predicted speed, the second predicted speed, the third predicted speed, and the fourth predicted speed, a first vehicle speed boundary and a second vehicle speed boundary of the vehicle comprises: sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed; When the driving torque is less than the driving torque threshold and the braking torque is less than the braking torque threshold, or the longitudinal acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, if the vehicle is a front-wheel drive vehicle, the first maximum wheel speed is used as the first vehicle speed boundary and the third maximum wheel speed is used as the second vehicle speed boundary; When the driving torque is less than the driving torque threshold and the braking torque is less than the braking torque threshold, or the longitudinal acceleration is less than the driving acceleration threshold and greater than the braking acceleration threshold, if the vehicle is a four-wheel drive vehicle, the first maximum wheel speed is used as the first vehicle speed boundary, and the fourth maximum wheel speed is used as the second vehicle speed boundary.

4. The method according to claim 2, characterized in that: The determining, based on the vehicle driving condition and according to the first predicted speed, the second predicted speed, the third predicted speed, and the fourth predicted speed, a first vehicle speed boundary and a second vehicle speed boundary of the vehicle comprises: sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed; When the driving torque is greater than the driving torque threshold, or the longitudinal acceleration is greater than the driving acceleration threshold, if the vehicle is a front-wheel drive vehicle, the second largest wheel speed is used as the first vehicle speed boundary, and the third largest wheel speed is used as the second vehicle speed boundary; When the driving torque is greater than the driving torque threshold, or the longitudinal acceleration is greater than the driving acceleration threshold, if the vehicle is a four-wheel drive vehicle, the fourth largest wheel speed is used as the first vehicle speed boundary, and the first vehicle speed collected when the driving torque is greater than the driving torque threshold is used as the second vehicle speed boundary.

5. The method according to claim 2, characterized in that: The determining, based on the vehicle driving condition and according to the first predicted speed, the second predicted speed, the third predicted speed, and the fourth predicted speed, a first vehicle speed boundary and a second vehicle speed boundary of the vehicle comprises: sorting the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed according to wheel speed; When the braking torque is greater than a braking torque threshold, or the longitudinal acceleration is less than a braking acceleration threshold, the second vehicle speed acquired when the braking torque is greater than the braking torque threshold is used as the first vehicle speed boundary, and the first maximum wheel speed is used as the second vehicle speed boundary.

6. The method according to claim 1, characterized in that Before estimating the rough vehicle speed of the vehicle based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary and the longitudinal acceleration, the method further includes: The lateral speed of the vehicle is calculated based on the nominal value of the vehicle travel.

7. The method according to claim 1, characterized in that The estimating the rough vehicle speed of the vehicle based on the lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary and the longitudinal acceleration includes: Using the first vehicle speed boundary and the second vehicle speed boundary as an upper limit of integration and a lower limit of integration respectively, performing an integration operation on the vehicle speed estimation formula to obtain a rough vehicle speed; The vehicle speed estimation formula is: · x =a x -w r v y ; The v · x is the real-time longitudinal speed, the a x is the longitudinal acceleration, the w r is the yaw angular velocity, the v y is the lateral vehicle speed.

8. A vehicle speed estimation device, characterized in that: include: A longitudinal vehicle speed prediction module is used to determine the predicted speeds corresponding to the four wheels of the vehicle based on the four-wheel turning angles, the four-wheel speeds and the yaw angular velocity, wherein the left front wheel corresponds to a first predicted speed, the right front wheel corresponds to a second predicted speed, the left rear wheel corresponds to a third predicted speed, and the right rear wheel corresponds to a fourth predicted speed; a vehicle speed boundary determination module, configured to determine a first vehicle speed boundary and a second vehicle speed boundary of the vehicle according to the first predicted speed, the second predicted speed, the third predicted speed and the fourth predicted speed based on the vehicle driving condition; A vehicle speed estimation module, configured to estimate a rough vehicle speed of the vehicle based on a lateral vehicle speed, the first vehicle speed boundary, the second vehicle speed boundary, and a longitudinal acceleration; The state observer is used to perform Kalman filtering on the rough vehicle speed to obtain an estimated vehicle speed.

9. A vehicle speed estimation device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the vehicle speed estimation method as claimed in any one of claims 1 to 7 when executing the computer program.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the vehicle speed estimation method according to any one of claims 1 to 7 are implemented.

Images