Vehicle state parameter calculation method and device

Abstract

The embodiment of the invention relates to the technical field of vehicle state parameter estimation, and discloses a vehicle state parameter calculation method and device, and the state parameters comprise a longitudinal vehicle speed value of a vehicle; the method comprises the steps that the working condition of the vehicle is determined; the working conditions comprise a stable working condition and an unstable working condition; calculating a first estimated vehicle speed value of the vehicle under a stable working condition; calculating a second estimated vehicle speed value of the vehicle under an unstable working condition; and fusing the first estimated vehicle speed value and the second estimated vehicle speed value to obtain a longitudinal vehicle speed value of the vehicle. Calculation is carried out in the mode, the actual running state of the vehicle can be fit, the deviation and error of calculation can be reduced, the calculation precision is improved, and the calculation requirement of an existing vehicle is met.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of vehicle state detection, and in particular to a method and device for calculating vehicle state parameters. Background Art

[0002] With the acceleration of the industrialization and modernization of human society and the rapid development of the economy, cars have become a necessity in life. People's demand for cars has gradually changed from traditional simple means of transportation to smarter, more comfortable and easier to control, which has put forward higher requirements for the performance of cars.

[0003] In order to meet the application needs of users, it is necessary to determine the real-time state parameters of the vehicle, and then make different adjustments based on the real-time state parameters of the vehicle. The commonly used state parameter calculation method is: install sensors on each wheel of the vehicle, directly use the sensors to detect the real-time parameters of each wheel of the vehicle in real time, and use each real-time parameter as the state parameter of the vehicle.

[0004] However, the currently commonly used state parameter calculation method has the following technical problems: different road conditions, different road materials and different modes have different effects on the wheels, resulting in deviations between the real-time parameters of different wheels and the real-time parameters of the vehicle. For example, the real-time speed of the wheel is different from the real-time speed of the vehicle. The error between the calculation result and the actual situation is large and the accuracy is low, which makes it difficult to meet the calculation needs of existing vehicles. Summary of the invention

[0005] In view of the above problems, embodiments of the present invention provide a method, device, equipment and medium for calculating vehicle state parameters, which are used to solve one or more technical problems existing in the prior art.

[0006] According to one aspect of an embodiment of the present invention, a method for calculating a vehicle state parameter is provided, wherein the state parameter includes: a longitudinal speed value of the vehicle; the method includes:

[0007] Determining the operating condition of the vehicle; the operating condition includes: a stable operating condition and an unstable operating condition;

[0008] Calculating a first estimated vehicle speed value when the vehicle is in a stable operating condition;

[0009] calculating a second estimated vehicle speed value when the vehicle is in an unstable operating condition;

[0010] The first estimated vehicle speed value and the second estimated vehicle speed value are integrated to obtain a longitudinal vehicle speed value of the vehicle.

[0011] In an optional manner, determining the driving speed value of each wheel of the vehicle includes:

[0012] If the signal of the wheel angular velocity sensor of the vehicle is valid, the wheel angular velocity value is collected by the wheel angular velocity sensor, and the driving speed value is calculated using the wheel angular velocity value;

[0013] If the signal of the wheel angular velocity sensor of the vehicle is invalid, the motor speed value of the distributed motor of the vehicle is collected, and the driving speed value is calculated using the motor speed value.

[0014] According to another aspect of an embodiment of the present invention, a device for calculating vehicle state parameters is provided, wherein the state parameters include: a longitudinal speed value of the vehicle; and

[0015] A working condition determination module, used to determine the working condition of the vehicle; the working condition includes: a stable working condition and an unstable working condition;

[0016] A first estimated vehicle speed module, used for calculating a first estimated vehicle speed value when the vehicle is in a stable working condition;

[0017] A second estimated vehicle speed module, used for calculating a second estimated vehicle speed value when the vehicle is in an unstable working condition;

[0018] The longitudinal vehicle speed module is used to fuse the first estimated vehicle speed value and the second estimated vehicle speed value to obtain the longitudinal vehicle speed value of the vehicle.

[0019] In a specific implementation, the present invention can adapt to the actual operating state of the vehicle, thereby reducing calculation deviations and errors to improve calculation accuracy and meet the calculation requirements of existing vehicles.

[0020] In an optional manner, determining the driving speed value of each wheel of the vehicle includes:

[0021] If the signal of the wheel angular velocity sensor of the vehicle is valid, the wheel angular velocity value is collected by the wheel angular velocity sensor, and the driving speed value is calculated using the wheel angular velocity value;

[0022] If the signal of the wheel angular velocity sensor of the vehicle is invalid, the motor speed value of the distributed motor of the vehicle is collected, and the driving speed value is calculated using the motor speed value.

[0023] According to another aspect of an embodiment of the present invention, there is provided an electronic device, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0024] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute the steps of the method for calculating the vehicle state parameters provided by the above embodiment.

[0025] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores at least one executable instruction, and the executable instruction enables an electronic device / apparatus to execute the steps of the method for calculating vehicle status parameters provided in the above embodiment.

[0026] In an optional manner, the method for calculating the vehicle state parameter may include the following operations:

[0027] Determining the operating condition of the vehicle; the operating condition includes: a stable operating condition and an unstable operating condition;

[0028] Calculating a first estimated vehicle speed value when the vehicle is in a stable operating condition;

[0029] calculating a second estimated vehicle speed value when the vehicle is in an unstable operating condition;

[0030] The first estimated vehicle speed value and the second estimated vehicle speed value are integrated to obtain a longitudinal vehicle speed value of the vehicle.

[0031] The embodiment of the present invention calculates an estimated vehicle speed value based on the vehicle's operating conditions, and then integrates the estimated vehicle speed values ​​of stable and unstable conditions to obtain the longitudinal vehicle speed value of the vehicle; the present invention calculates the longitudinal vehicle speed in combination with different vehicle operating conditions, which can fit the actual operating state of the vehicle, thereby reducing calculation deviations and errors, thereby improving calculation accuracy and meeting the calculation requirements of existing vehicles.

[0032] The above description is only an overview of the technical solution of the embodiment of the present invention. In order to more clearly understand the technical means of the embodiment of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0034] Figure 1 A schematic flow chart showing a first embodiment of a method for calculating vehicle state parameters provided by the present invention;

[0035] Figure 2 A schematic flow chart showing a second embodiment of a method for calculating vehicle state parameters provided by the present invention;

[0036] Figure 3 A flow chart of an embodiment of determining a vehicle driving condition provided by the present invention is shown;

[0037] Figure 4A flow chart showing an embodiment of the original slope value estimation provided by the present invention;

[0038] Figure 5 A schematic diagram showing the operation flow of the method for calculating vehicle state parameters provided by the present invention;

[0039] Figure 6 A schematic structural diagram of a first embodiment of a vehicle state parameter calculation device provided by the present invention is shown;

[0040] Figure 7 A schematic structural diagram of an embodiment of an electronic device provided by the present invention is shown. DETAILED DESCRIPTION

[0041] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0042] Figure 1 The flowchart of the first embodiment of the method for calculating vehicle state parameters of the present invention is shown, and the method is executed by an electronic device, which may be a vehicle-mounted terminal or a control terminal of the vehicle.

[0043] like Figure 1 As shown, the method comprises the following steps:

[0044] Step 110: Determine the operating condition of the vehicle; the operating condition includes: a stable operating condition and an unstable operating condition.

[0045] In one embodiment, the real-time operating condition of the vehicle may be determined first, and the operating condition may include: a stable operating condition and an unstable operating condition.

[0046] Among them, the stable operating condition may be the operating condition when the vehicle is driving stably; and the unstable operating condition may be the operating condition when the vehicle is driving unstably.

[0047] In one implementation, various parameters of the vehicle may be detected by sensors of the vehicle, and the operating condition of the vehicle may be determined based on the various parameters of the vehicle.

[0048] In one embodiment, the stable working condition includes: an absolute steady-state working condition, a straight-running working condition, and a turning working condition;

[0049] Wherein, as an example, determining the operating condition of the vehicle specifically includes the following steps:

[0050] Step 1101: If the vehicle meets the following conditions: each of the driving speed values ​​is in a stable state, the difference between the driving speed value with the largest value and the driving speed value with the smallest value is less than the wheel speed difference threshold, the difference between the wheel acceleration value with the largest value and the wheel acceleration value with the smallest value is less than the acceleration difference threshold, the vehicle is not in a turning state, and the absolute value of the difference between the vehicle speed change rate in the previous calculation cycle and the wheel acceleration value with the largest value and the wheel acceleration value with the smallest value in the current cycle is less than the acceleration change threshold, then it is determined that the operating condition of the vehicle is an absolute steady-state condition of a stable operating condition.

[0051] Specifically, the driving speed value is a speed value obtained by converting the wheel speed into the mass center position of the vehicle and in the driving direction of the vehicle.

[0052] When the vehicle meets the following conditions, the vehicle's operating condition can be determined to be an absolute steady-state condition. The specific conditions are as follows:

[0053] First, the driving speed value of each wheel is in a stable state; wherein the driving speed value being in a stable state may be that the absolute value of the wheel acceleration value of the wheel is less than the acceleration threshold. For example, the driving speed value of wheel A is v wii , the wheel acceleration value a can be calculated according to the driving speed value wii . And set the acceleration threshold a wth , judge a wii Is the absolute value of less than a wth , if a wii The absolute value of a is less than wth , then the wheel is determined to be in a stable state. Otherwise, if a wii The absolute value of a is greater than wth , it is determined that the wheel is in an unstable state.

[0054] Second, among the driving speed values ​​of the multiple wheels, the difference between the driving speed value with the largest value and the driving speed value with the smallest value is less than the wheel speed difference threshold (assuming 0.8 m / s).

[0055] Third, the difference between the maximum wheel acceleration value and the minimum wheel acceleration value is less than the acceleration difference threshold (assuming 1m / s 2 ). Specifically, each driving speed value may be used to calculate the wheel acceleration value of each wheel, and the wheel acceleration values ​​with the largest value and the smallest value may be selected therefrom for subsequent calculation.

[0056] Fourth, the vehicle is not in a turning state (not in a left turn state or a right turn state). For example, if the absolute value of the left turn angle of the vehicle steering wheel is less than the left turn angle threshold (assuming 0.1rad) or the body yaw rate is less than the preset left turn yaw rate threshold (assuming 0.1rad / s), it means that the vehicle is not in a left turn state. Similarly, if the absolute value of the right turn angle of the vehicle steering wheel is less than the right turn angle threshold (assuming 0.1rad) or the absolute value of the body yaw rate value is less than the yaw angle value (assuming 0.1rad / s), it means that the vehicle is not in a right turn state.

[0057] In specific operations, when the vehicle's steering wheel angle is greater than the preset left turn angle threshold (assuming 0.1rad), and the vehicle body yaw angular velocity is greater than the preset left turn yaw angular velocity threshold (assuming 0.1rad / s), the vehicle is determined to be in a left turn state (considering that the directions of the steering wheel angle and yaw angular velocity are both positive on the left and negative on the right / counterclockwise is positive).

[0058] When the vehicle steering wheel angle is less than the preset right turn angle threshold (assuming -0.1 rad), and the vehicle body yaw rate is less than the preset right turn yaw rate threshold (assuming -0.1 rad / s), the vehicle is determined to be in a right turn state. If not, it can be determined that the vehicle is not in a turning state.

[0059] Fifth, the absolute value of the difference between the vehicle speed change rate in the previous calculation cycle and the maximum wheel acceleration value and the minimum wheel acceleration value is less than the acceleration change threshold (assuming 1m / s 2 ).

[0060] The vehicle speed change rate may be the ratio of the estimated speed change value of the vehicle to time. Specifically, the estimated vehicle speed at the start time and the estimated vehicle speed at the end time of the previous calculation cycle may be determined, the difference between the two vehicle speeds may be calculated to obtain the vehicle speed difference, and then the ratio of the vehicle speed difference to the time of the previous calculation cycle may be calculated to obtain the vehicle speed change rate.

[0061] When the above conditions are met, it can be determined that the operating condition of the vehicle is a stable operating condition, and the stable operating condition is an absolute steady-state operating condition.

[0062] Step 1102: If the vehicle meets the following conditions: the vehicle is in a straight-moving state and each of the driving speed values ​​is in a stable state, then it is determined that the operating condition of the vehicle is a stable operating condition, and the stable operating condition is a straight-moving condition.

[0063] Specifically, the vehicle is in a straight-moving state, and the straight-moving state may be a state where the vehicle is accelerated and driven straight-moving, a state where the vehicle is steadily driven straight-moving, a state where the vehicle is decelerated and driven straight-moving, or a state where the vehicle is sliding straight-moving in neutral.

[0064] On this basis, the driving speed value of each wheel of the vehicle is in a stable state, specifically, the absolute value of the acceleration value of each wheel of the vehicle is less than the acceleration threshold, and it is determined that each wheel is in a stable state.

[0065] Step 1103: If the vehicle meets the following conditions: the vehicle is in a left turn state or a right turn state, it is determined that the operating condition of the vehicle is a stable operating condition, and the stable operating condition is a turning condition.

[0066] Specifically, when the vehicle's steering wheel angle is greater than the preset left turn angle threshold (assuming 0.1 rad), and the vehicle body yaw angular velocity is greater than the preset left turn yaw angular velocity threshold (assuming 0.1 rad / s), the vehicle is determined to be in a left turn state (considering that the directions of the steering wheel angle and yaw angular velocity are both positive on the left and negative on the right / counterclockwise is positive).

[0067] Similarly, when the vehicle steering wheel angle is less than the preset right turn angle threshold (assuming -0.1 rad), and the vehicle body yaw rate is less than the preset right turn yaw rate threshold (assuming -0.1 rad / s), it is determined that the vehicle is in a right turn state.

[0068] If the vehicle is in a left-turn state or the vehicle is in a right-turn state, it is determined that the vehicle is in a turning condition.

[0069] Step 1104: If the vehicle meets the following conditions: the vehicle is not in an absolutely steady-state condition, a straight-moving condition, or a turning condition, or each of the driving speed values ​​is in an unstable state, then the vehicle's operating condition is determined to be an unstable condition.

[0070] Specifically, when the vehicle's operating condition is not in any of the absolute steady-state condition, straight-driving condition and turning condition among the stable conditions, or each driving speed value is in an unstable state (that is, the absolute value of the wheel acceleration value corresponding to the driving speed value of each wheel of the vehicle is greater than the acceleration threshold), it can be determined that the vehicle's operating condition is an unstable condition.

[0071] A vehicle has multiple wheels. The speed of each wheel may be the same or different under different working conditions, and the wheel acceleration value corresponding to each wheel may also be the same or different. Therefore, after determining the stable working condition and unstable working condition of the vehicle, the speed of the vehicle under the stable working condition and the unstable working condition can be estimated respectively. Subsequently, the longitudinal speed value of the vehicle can be estimated based on the speed of the two different working conditions to improve the estimation accuracy.

[0072] Step 120: Calculate a first estimated vehicle speed value when the vehicle is in a stable operating condition.

[0073] In one embodiment, if the vehicle is in a stable operating condition, an estimated vehicle speed of the vehicle in the stable operating condition may be calculated to obtain a first estimated vehicle speed value.

[0074] In one operation mode, various parameters of the vehicle in a stable operating condition may be obtained, and then a first estimated vehicle speed value may be calculated based on the various parameters.

[0075] In one embodiment, the stable operating condition includes: an absolute steady-state operating condition, a straight-running operating condition, and a turning operating condition.

[0076] Wherein, as an example, the calculating of the first estimated vehicle speed value when the vehicle is in a stable working condition specifically includes the following steps:

[0077] Step 1201: Determine the driving speed value of each wheel of the vehicle, where the driving speed value is the speed value obtained by converting the wheel speed to the center of mass position of the vehicle and in the driving direction of the vehicle.

[0078] In one embodiment, the angular velocity of the vehicle may be detected by a sensor first, and then the wheel speed value may be calculated based on the angular velocity and the radius of the wheel, so as to convert the wheel speed value into a driving speed value, and then use the driving speed value for subsequent calculation processing.

[0079] In one embodiment, different road conditions, different road materials and different modes have different effects on wheels and may also affect sensors. Therefore, in order to avoid subsequent calculation errors caused by sensor failure, in one operation mode, it can be determined whether the sensor signal is valid, and calculation processing can be performed according to the state of the sensor signal.

[0080] Specifically, it can be determined whether the signal of the wheel angular velocity sensor is valid. If the signal of the wheel angular velocity sensor of the vehicle is valid, the wheel angular velocity information collected by the wheel angular velocity sensor can be obtained, and the wheel velocity value of each wheel can be calculated by combining the wheel angular velocity information and the wheel radius.

[0081] Specifically, the wheel speed value can be expressed as follows:

[0082]

[0083] In the above formula, Represents the wheel speed value of each wheel (m / s), ω ii Represents the vehicle angular velocity of each wheel (rad / s); ii represents wheels at different positions. For example, a vehicle has four wheels, namely the left front wheel FL, the right front wheel FR, the left rear wheel RL, and the right rear wheel RR; R represents the wheel radius (m).

[0084] Similarly, if the signal of the vehicle's wheel angular velocity sensor is invalid, the wheel speed is converted based on the speed of each motor of the distributed electric drive to obtain the wheel speed value of each wheel. Specifically, the wheel speed value can be shown as follows:

[0085]

[0086] In the above formula, Represents the wheel speed value of each wheel (m / s), n ii Represents the speed (rpm) of the motor corresponding to each wheel, θ ii Characterizes the corresponding motor speed ratio, i.e. the transmission ratio.

[0087] After the wheel speed value is calculated using the sensor, the wheel speed value may be converted to the center-of-mass vehicle speed to calculate the speed of the vehicle at the center of mass and in the direction of vehicle travel to obtain the travel speed value.

[0088] Specifically, it can be based on the calculated wheel speed value of each vehicle and based on the wheel angle (which can be calculated based on the steering wheel angle δ Steer Mapping is obtained, that is, δ ii =A i δ Steer , A i The vehicle speed is integrated with parameter information such as the distance from the center of mass to the front axle, the distance from the center of mass to the rear axle, the front wheel track, the rear wheel track, the yaw angular velocity, the sideslip angle of the center of mass, etc. to obtain the speed value at the center of mass of the wheel. Specifically, the rotation speed of each wheel is converted to the speed at the center of mass of the current vehicle and in the driving direction to obtain the driving speed value.

[0089] Specifically, the driving speed value at the wheel center of mass can be expressed as follows:

[0090]

[0091] In the above formula, represents the reference speed of each wheel at the center of mass, δ ii represents the steering angle at the four wheel positions, γ represents the yaw rate at the vehicle's center of mass, They represent the front and rear axle tracks, L represents the wheelbase, and L represents the a is the distance from the center of mass to the front axle, and β is the sideslip angle of the center of mass.

[0092] Step 1202: Determine the confidence coefficient of each wheel of the vehicle according to the stable operating condition of the vehicle.

[0093] After the stable operating condition of the vehicle is determined, a preset confidence coefficient of each wheel of the vehicle can be determined based on the stable operating condition of the vehicle. The confidence coefficient is a calculation reference value for estimating the vehicle speed.

[0094] Since there are many types of stable operating conditions for vehicles, different confidence coefficients can be set for different types to improve the accuracy of the calculation.

[0095] According to the analysis above, the stable operating conditions include: absolute steady-state operating conditions, straight-ahead operating conditions and turning operating conditions.

[0096] For the above-mentioned various working conditions and unstable working conditions, as an example, determining the confidence coefficient of each wheel of the vehicle according to the stable working condition of the vehicle specifically includes the following steps:

[0097] Step 12021: When the vehicle is in an absolutely steady-state condition, the confidence coefficient of each wheel of the vehicle is determined to be 1.

[0098] Step 12022: When the vehicle is in a straight-moving condition and in a driving state, the confidence coefficient of the wheel with the smallest driving speed value is determined to be 1, and the confidence coefficients of the remaining wheels are determined to be 0.

[0099] Step 12023: When the vehicle is in a straight-moving condition and is in an energy recovery or braking state, the confidence coefficient of the wheel with the largest driving speed value is determined to be 1, and the confidence coefficients of the remaining wheels are determined to be 0.

[0100] Step 12024: When the vehicle is in a turning condition, the confidence coefficient of the wheel whose driving speed value is in a stable state is set to 1, and the confidence coefficient of the wheel whose driving speed value is in an unstable state is set to 0 according to the specific turning condition and the set priority.

[0101] In actual operation, each wheel may have a corresponding confidence coefficient. If the vehicle is in an absolutely steady-state condition, the confidence coefficient of each wheel of the vehicle is determined to be 1.

[0102] If the vehicle is in a straight-ahead condition and the vehicle is in a driving state, the driving speed value with the smallest value is selected from the driving speed values ​​of each wheel, and then the confidence coefficient of the wheel corresponding to the driving speed value with the smallest value is determined to be 1, and the confidence coefficients of the remaining wheels are determined to be 0. Among them, the method of determining that the vehicle is in a driving state can be to determine that the gear state of the vehicle is valid and in a forward gear, when the sum of the actual torques of the motors is greater than the preset driving state motor torque threshold (assuming 5Nm), and the total torque requested by the whole vehicle is greater than the preset driving state request torque threshold (assuming 10Nm), determine that the vehicle is in a driving state. It can also be determined that when the gear state of the vehicle is valid and in a reverse gear, each torque threshold is taken as a negative value. For example, it can be determined that when the gear state of the vehicle is valid and in a reverse gear, when the sum of the actual torques of the motors is less than the preset driving state motor torque threshold (assuming -5Nm), and the total torque requested by the whole vehicle is less than the preset driving state request torque threshold (assuming -10Nm), it can also be determined that the vehicle is in a driving state.

[0103] If the vehicle is in a straight-moving condition and is in an energy recovery or braking state (for example, the vehicle is coasting, braking is switching to driving torque, or driving is switching to braking torque), the driving speed value with the largest value is selected from the driving speed values ​​of each wheel, and then the confidence coefficient of the wheel corresponding to the largest driving speed value is determined to be 1, and the confidence coefficients of the remaining wheels are determined to be 0.

[0104] The vehicle is in a coasting state, which can be coasting in neutral or in forward gear. For example, when the sum of the actual torque of the vehicle's D-gear motor is less than the preset coasting brake state motor torque threshold (assuming -5Nm), or the brake master cylinder pressure is greater than the preset threshold (assuming 5Bar), or the braking stroke is greater than the preset threshold (10mm), the vehicle is in energy recovery or braking state.

[0105] For torque reversal from braking to driving, it can be when starting or accelerating with a large throttle immediately after braking. The state is judged as follows: after the brake master cylinder pressure is greater than the preset threshold (assuming 5 Bar) or the braking stroke is greater than the preset threshold (assuming 10 mm), within the preset time threshold (assuming 200 ms), the accelerator pedal opening is greater than the preset threshold (assuming 30%), then the above operating state is determined to be established.

[0106] For the switching from driving to braking torque, it can be braking immediately after large throttle acceleration, and the state judgment method is as follows: after the accelerator pedal opening is greater than the preset threshold (assuming 30%), within the preset time threshold (assuming 0.2s), the brake master cylinder pressure is greater than the preset threshold (assuming 5Bar), or the braking stroke is greater than the preset threshold (assuming 10mm), then it is determined that the above working condition is established.

[0107] If the vehicle is in a turning condition, then according to the specific turning and the set priority, the confidence coefficient of the wheel whose driving speed value is in a stable state is set to 1, and the confidence coefficient of the wheel whose driving speed value is in an unstable state is set to 0.

[0108] In one embodiment, the pre-set priority may be based on whether the driving speed value of the currently turned wheel is stable.

[0109] For example, when the vehicle is moving forward, if the vehicle is in a left-turn operating state and its current direction is a left turn, the driving speed values ​​of the left rear wheel and the right rear wheel of the vehicle can be obtained.

[0110] We can first determine whether the driving speed value of the right rear wheel is stable (i.e., whether the absolute value of the wheel acceleration value corresponding to the driving speed value of the right rear wheel is less than the acceleration threshold). If the driving speed value of the right rear wheel is stable (i.e., the absolute value of the wheel acceleration value corresponding to the driving speed value of the right rear wheel is less than the acceleration threshold), it means that the wheel speed state of the right rear wheel is credible, and the confidence coefficient of the right rear wheel can be set to 1, and the confidence coefficients of the other wheels can be set to 0. On the contrary, if the absolute value of the wheel acceleration value corresponding to the driving speed value of the right rear wheel is greater than the acceleration threshold, the wheel speed state of the right rear wheel is unreliable, and the confidence coefficient of the left rear wheel can be set to 1, and the confidence coefficients of the other wheels can be set to 0.

[0111] Similarly, when the vehicle is in a right-turn working state, its current steering direction is right turn, and the driving speed values ​​of the left rear wheel and the right rear wheel of the vehicle can also be obtained.

[0112] It is possible to first determine whether the driving speed value of the left rear wheel is stable (i.e., determine whether the absolute value of the wheel acceleration value corresponding to the driving speed value of the left rear wheel is less than the acceleration threshold). If the driving speed value of the left rear wheel is stable (i.e., the absolute value of the wheel acceleration value corresponding to the driving speed value of the left rear wheel is less than the acceleration threshold), it means that the wheel speed state of the left rear wheel is credible, and the confidence coefficient of the left rear wheel can be set to 1, and the confidence coefficients of the remaining wheels can be set to 0. Conversely, if the driving speed value of the left rear wheel is unstable (i.e., the absolute value of the wheel acceleration value corresponding to the driving speed value of the left rear wheel is greater than the acceleration threshold), it means that the wheel speed state of the left rear wheel is unreliable, and the confidence coefficient of the right rear wheel can be set to 1, and the confidence coefficients of the remaining wheels can be set to 0.

[0113] For another example, when the vehicle is moving backward, if the vehicle is in a left-turn operating state and its current direction is a left turn, the driving speed values ​​of the left front wheel and the right front wheel of the vehicle can be obtained.

[0114] We can first determine whether the driving speed value of the right front wheel is stable (i.e., whether the absolute value of the wheel acceleration value corresponding to the driving speed value of the right front wheel is less than the acceleration threshold). If the driving speed value of the right front wheel is stable (i.e., the absolute value of the wheel acceleration value corresponding to the driving speed value of the right front wheel is less than the acceleration threshold), it means that the wheel speed state of the right front wheel is credible, and the confidence coefficient of the right front wheel can be set to 1, and the confidence coefficients of the other wheels can be set to 0. On the contrary, if the absolute value of the wheel acceleration value corresponding to the driving speed value of the right front wheel is greater than the acceleration threshold, the wheel speed state of the right front wheel is unreliable, and the confidence coefficient of the left front wheel can be set to 1, and the confidence coefficients of the other wheels can be set to 0.

[0115] Similarly, when the vehicle is in a right-turn working state, its current direction is right turn, and the driving speed values ​​of the left front wheel and the right front wheel of the vehicle can also be obtained.

[0116] It is possible to first determine whether the driving speed value of the left front wheel is stable (i.e., determine whether the absolute value of the wheel acceleration value corresponding to the driving speed value of the left front wheel is less than the acceleration threshold). If the driving speed value of the left front wheel is stable (i.e., the absolute value of the wheel acceleration value corresponding to the driving speed value of the left front wheel is less than the acceleration threshold), it means that the wheel speed state of the left front wheel is credible, and the confidence coefficient of the left front wheel can be set to 1, and the confidence coefficients of the remaining wheels can be set to 0. Conversely, if the driving speed value of the left front wheel is unstable (i.e., the absolute value of the wheel acceleration value corresponding to the driving speed value of the left front wheel is greater than the acceleration threshold), it means that the wheel speed state of the left front wheel is unreliable, and the confidence coefficient of the right front wheel can be set to 1, and the confidence coefficients of the remaining wheels can be set to 0.

[0117] Step 1203: Calculate a first estimated vehicle speed value using the driving speed value of each wheel and the confidence coefficient corresponding to each wheel.

[0118] In one embodiment, the first estimated vehicle speed value may be calculated using the travel speed value of each wheel and the confidence coefficient corresponding to each wheel according to the wheel speed method.

[0119] In an actual operation mode, the first estimated vehicle speed value can be expressed as follows:

[0120]

[0121] In the above formula, v est1 is the first estimated vehicle speed value, k n is the confidence factor of each wheel stability, which is determined based on the stability state and motion conditions of each wheel, and generally ranges from (0,1). are the driving speed values ​​of each wheel respectively.

[0122] It should be noted that each confidence coefficient can also be adjusted according to actual needs.

[0123] Step 130: Calculate a second estimated vehicle speed value when the vehicle is in an unstable operating condition.

[0124] If it is determined that the vehicle is in an unstable condition, the vehicle speed under the unstable condition can be estimated to obtain a second estimated vehicle speed value. In one operation mode, various parameters of the vehicle under the unstable condition can also be obtained, and then the second estimated vehicle speed value is calculated using the various parameters.

[0125] According to the above analysis, since the mass center speed values ​​of each wheel of the vehicle are unstable, it is determined that the vehicle is in an unstable working condition. At this time, if the mass center speed values ​​of each wheel of the vehicle are directly used to calculate the second estimated vehicle speed value under the unstable working condition, the calculation deviation is large.

[0126] In order to reduce calculation deviation and improve calculation accuracy, as an example, the calculation of the second estimated vehicle speed value when the vehicle is in an unstable working condition specifically includes the following steps:

[0127] Step 1301: Determine the historical estimated vehicle speed of the vehicle in the previous cycle.

[0128] Step 1302: Determine the longitudinal acceleration value of the vehicle.

[0129] Step 1303: Calculate the second estimated vehicle speed value according to the historical estimated vehicle speed and the vehicle body longitudinal acceleration value.

[0130] Specifically, the historical estimated vehicle speed of the vehicle in the previous cycle and the real-time longitudinal acceleration value of the vehicle body can be obtained respectively. The historical estimated vehicle speed of the previous cycle is the estimated vehicle speed value calculated last time. The historical estimated vehicle speed of the previous cycle may be the first estimated vehicle speed value when the vehicle is in a stable working condition during the previous cycle; or it may be the second estimated vehicle speed value when the vehicle is in an unstable working condition during the previous cycle.

[0131] The vehicle body longitudinal acceleration value may be a real-time longitudinal acceleration value of the vehicle, or a longitudinal acceleration value calculated in a previous cycle.

[0132] In a specific operation mode, the unstable state may be caused by the previous bad road conditions or potholes due to speed bumps. In order to further improve the calculation accuracy, the second estimated vehicle speed value may be calculated using the slope method using the historical estimated vehicle speed and the vehicle longitudinal acceleration value.

[0133] The second estimated vehicle speed value can be calculated as follows:

[0134] v est2 =v est-1 +∫a long dt.

[0135] In the above formula, v est2 is the estimated vehicle speed calculated using the slope method, v est-1 is the vehicle speed value of the previous cycle or the last calculation, a long is the longitudinal acceleration of the vehicle body.

[0136] The longitudinal acceleration value of the vehicle body may be directly acquired through a sensor. An estimated vehicle speed value (eg, a first estimated vehicle speed value) may be calculated first, and then the longitudinal acceleration value of the vehicle body may be calculated based on the estimated vehicle speed value.

[0137] Step 140: The first estimated vehicle speed value and the second estimated vehicle speed value are integrated to obtain a longitudinal vehicle speed value of the vehicle.

[0138] In one embodiment, the calculation of the longitudinal vehicle speed value may be as follows:

[0139]

[0140] In the above formula, v est is the longitudinal vehicle speed value, kn is the wheel speed method fusion weight coefficient, and ka is the slope method fusion weight coefficient.

[0141] In one embodiment, after the estimated vehicle speed value is calculated by the above-mentioned various methods, the estimated vehicle speed value may still have an error. In order to further reduce the error and improve the accuracy of subsequent calculations, as an example, after the step of fusing the first estimated vehicle speed value and the second estimated vehicle speed value to obtain the longitudinal vehicle speed value of the vehicle, the method further includes the following steps:

[0142] Step 150: Use a preset filter to correct the longitudinal vehicle speed value to obtain a correction parameter. The preset filter is obtained by calculating the covariance using a state prediction equation constructed using the vehicle's historical state, using the covariance and the optimal value of the real-time vehicle speed value to generate a gain matrix and using the gain matrix to construct the filter, wherein the correction parameter is the vehicle speed value obtained after correcting the estimation error of the longitudinal vehicle speed value.

[0143] Specifically, after the longitudinal speed value of the vehicle is preliminarily calculated, the Kalman filter can be used to correct the estimation error. Specifically, the longitudinal speed value can be input into the Kalman filter for filtering and correction, and the correction parameter is output, and the correction parameter is used for subsequent calculation.

[0144] The correction parameter may be a corrected longitudinal speed value. The present invention can significantly improve the accuracy of the longitudinal reference speed of the vehicle through the Kalman filter algorithm, thereby solving the problem that the wheel speed method in the traditional vehicle speed estimation technology is overly dependent on the wheel speed, which causes the vehicle to slip or lock at high speed due to acceleration or braking of the vehicle on low-adhesion roads such as icy and snowy roads and epoxy floor garages, resulting in a large error between the vehicle speed and the actual speed. At the same time, based on the vehicle's motion state, the forgetting factor value in the slope estimation is weightedly calculated, so that a relatively accurate slope parameter can be obtained in each scenario, which can effectively improve the accuracy of the calculation.

[0145] Moreover, by combining the advanced and reliable Kalman filter algorithm with the important interference noise of the longitudinal reference vehicle speed, the Kalman gain is adaptively adjusted based on the rules, thereby greatly improving the accuracy of the estimated vehicle speed in various scenarios and working conditions. At the same time, by estimating the slope based on the vehicle's motion state, the accuracy of the vehicle's slope parameter estimation in various scenarios can be further improved.

[0146] Furthermore, the present invention can effectively improve the scalability of calculations, because the Kalman filter rules can be expanded to deal with high-sensitivity noise interference conditions for various reference vehicle speed estimates, and the slope estimation based on the vehicle's motion state can significantly improve the prediction accuracy and performance. Therefore, it can be expanded and improved according to user needs and feedback to adapt to different application requirements.

[0147] Among them, the preset Kalman filter is constructed by calculating the covariance of the state prediction equation constructed using the vehicle's historical state, and then using the covariance and the optimal value of the real-time estimated vehicle speed value to generate a Kalman gain matrix, which is constructed using the Kalman gain matrix.

[0148] The state prediction equation can be expressed as follows:

[0149] X(k|k-1)=AX(k-1|k-1)+BU(k).

[0150] The state prediction equation may be a state prediction equation that predicts the current state based on the previous state.

[0151] The covariance can be expressed as follows:

[0152] P(k|k-1)=AP(k-1|k-1)A T +Q.

[0153] The optimal estimate of the state prediction equation can be expressed as follows:

[0154] X(k|k)=X(k|k-1)+K(k)[Z(k)-HX(k|k-1)].

[0155] The constructed Kalman gain matrix can be shown as follows:

[0156]

[0157] In one embodiment, the update of the error covariance may be expressed as follows:

[0158] P(k|k)=[1-K(k)H]P(k|k-1).

[0159] It should be noted that the parameter selection of the prior error noise Q and the sensor error noise R in the Kalman filter is very important for the selection of the optimal estimate. The larger the error noise, the lower the credibility of the corresponding state equation, and vice versa.

[0160] The present invention can adopt a sensor noise fusion control method based on credibility, determine the noise size according to the state of the vehicle, select the error coefficient based on the longitudinal acceleration of the vehicle and the slipping wheel state, and the relationship between the prior error noise and the sensor error noise can be expressed by parameter ρ, that is, ρ=Q / R.

[0161] Therefore, it is only necessary to confirm the size of the parameter ρ to confirm the noise error relationship in the Kalman filter. When the wheel speed method and the slope method are used to estimate the vehicle speed, due to the relationship of noise (mainly related to the longitudinal acceleration of the vehicle body and the stable state of the wheel), the basic expression of the parameter ρ can be obtained, which can be shown as follows:

[0162] ρ=f(a long , n slip ).

[0163] In the above formula, a long is the longitudinal acceleration of the vehicle body, n slip The slipping state can be obtained by counting the sum of the number of wheels whose absolute value of wheel acceleration is greater than the acceleration threshold. Whether the vehicle is slipping is determined based on the sum of the number of wheels in such an unstable state.

[0164] The basic trend is: when the absolute value of the longitudinal acceleration is larger, or the number of skidding wheels is larger, the ρ value is larger, that is, the proportion of the wheel speed method is smaller, and the proportion of the estimated value of the acceleration method is larger. Conversely, when the absolute value of the longitudinal acceleration is smaller, or the number of skidding wheels is smaller, the ρ value is smaller, that is, the proportion of the estimated value of the wheel speed method is larger, and the proportion of the estimated value of the acceleration method is smaller.

[0165] Based on this, the interference-noise relationship between the wheel speed method and the acceleration method for vehicle speed estimation under different working conditions can be obtained, so as to reasonably allocate weights to the estimation methods that are severely affected by noise interference under different working conditions to ensure the accuracy of the estimated vehicle speed value.

[0166] The embodiment of the present invention determines the working condition of the vehicle, calculates the estimated vehicle speed value according to the working condition of the vehicle, and then integrates the estimated vehicle speed values ​​of the stable working condition and the unstable working condition to obtain the longitudinal vehicle speed value of the vehicle; the present invention calculates the longitudinal vehicle speed in combination with different working conditions of the vehicle, which can fit the actual operating state of the vehicle, thereby reducing the deviation and error of the calculation, so as to improve the accuracy of the calculation and meet the calculation requirements of existing vehicles; in addition, by correcting the longitudinal vehicle speed value through a filter, the error of the calculation can be further reduced, and the estimation accuracy of the vehicle speed can be improved.

[0167] Figure 2 The flowchart of the second embodiment of the method for calculating vehicle state parameters of the present invention is shown, and the method is executed by an electronic device, which may be a vehicle-mounted terminal or a control terminal of the vehicle.

[0168] In one embodiment, the state parameter further includes: a target slope estimation value. The target slope estimation value may be the slope of the road on which the vehicle is currently traveling.

[0169] like Figure 2As shown, the method comprises the following steps:

[0170] Step 210: Determine the motion state of the vehicle.

[0171] Step 220: Determine a value of a slope estimation forgetting factor of the vehicle according to the motion state of the vehicle.

[0172] Step 230: According to the slope estimation forgetting factor value, low-pass filtering is performed on the original slope value of the vehicle to obtain a target slope estimation value.

[0173] Among them, the vehicle's motion state may include: the vehicle is in an accelerating state, the vehicle is in a sliding state, the vehicle is in a straight-moving condition or an absolutely steady-state condition, and the vehicle is driving on a speed bump or a pothole or on a bad road condition, etc.

[0174] The present invention covers various motion states of the vehicle to ensure the reliability of estimating state parameters such as vehicle speed and slope in various scenarios, and provides reliable state parameter information for the vehicle, which is beneficial to improving the controllability of the vehicle on bumpy roads, low-adhesion ice and snow roads and various extreme scenarios, while improving the safety of the vehicle, thereby ensuring the reliability of the vehicle in various usage scenarios.

[0175] After the motion state is determined, the slope of the vehicle can be determined to estimate the forgetting factor value according to the motion state of the vehicle.

[0176] Subsequently, the original slope of the vehicle can be low-pass filtered according to the slope estimation forgetting factor value to obtain the target slope estimation value. The original slope of the vehicle can be calculated by the longitudinal vehicle speed value of the above embodiment.

[0177] Specifically, the original slope value is optimized based on a low-pass filtering algorithm to obtain a target slope estimation value.

[0178] Specifically, the target slope estimation value can be calculated as follows:

[0179]

[0180] In the above formula, is the estimated target slope, is the average value of the driving slope value in the last n cycles, μ f Estimated forgetting factor for slope, its value range is (0,1).

[0181] In one embodiment, the motion state of the vehicle includes: an acceleration state, a sliding state, a driving state, and a road condition state.

[0182] The step of determining the value of the forgetting factor for estimating the slope of the vehicle according to the motion state of the vehicle comprises the following steps:

[0183] Step 2201: respectively determine the state factor value corresponding to each motion state.

[0184] Step 2202: Perform weighted average calculation on the multiple state factor values ​​to obtain a slope estimation forgetting factor value.

[0185] Specifically, the state factor value of the vehicle in the acceleration state, the state factor value of the vehicle in the sliding state, the state factor value of the vehicle in the driving state, and the state factor value of the vehicle in the road condition state can be determined.

[0186] Finally, the weighted average of the four state factor values ​​is calculated to obtain the slope estimation forgetting factor value.

[0187] Specifically, based on the vehicle motion state determined above, a weighted average calculation is performed on the state factor values, which can be specifically shown in the following formula:

[0188] μ f =τ1·τ2·τ3·τ4.

[0189] τ1 is the state factor value when the vehicle is in an accelerating state, τ2 is the state factor value when the vehicle is in a sliding state, τ3 is the state factor value when the vehicle is in a driving state, and τ4 is the state factor value when the vehicle is in a road condition state.

[0190] In order to set corresponding state factor values ​​for different motion states, as an example, respectively determining the state factor value corresponding to each motion state includes the following steps:

[0191] Step 22011: If the motion state is an acceleration state, the motion acceleration value of the vehicle is obtained, and a negative correlation calculation is performed on the absolute value of the motion acceleration value to obtain a state factor value.

[0192] Step 22012: If the motion state is a sliding state, after calculating the slip rate of each wheel, a negative correlation calculation is performed on the average values ​​of multiple slip rates to obtain a state factor value.

[0193] Step 22013: If the motion state is a driving state, then when the driving state of the vehicle is a driving state of a straight-ahead condition or a driving state of an absolute steady-state condition, the state factor value is set to 1; when the driving state of the vehicle is a driving state of a turning condition or the vehicle is in a driving or braking condition, the state factor value is set to 0.5; when the driving state of the vehicle is a driving state from driving to braking or from braking to driving, the state factor value is set to 0, and the low-pass filtering of the original slope of the vehicle is suspended.

[0194] Step 22014: If the motion state is a road condition state, then when it is determined that the vehicle's road condition state is neither a bad road condition state nor a speed bump road condition state, the state factor value is set to 1; when it is determined that the vehicle's road condition state is a speed bump road condition state, the state factor value is set to 0.2; when it is determined that the vehicle's road condition state is a bad road condition state, the state factor value is set to 0, and the low-pass filtering of the original slope of the vehicle is suspended.

[0195] Specifically, τ1 is a state factor value when the vehicle is in an accelerating state, and the motion acceleration value of the vehicle can be obtained, and the state factor value is obtained by performing a negative correlation calculation on the absolute value of the motion acceleration value.

[0196] The calculation of the state factor value when the vehicle is in the accelerating state is as follows:

[0197] τ1=f(|a|);

[0198] Among them, τ1 is negatively correlated with the absolute value of the vehicle acceleration a, that is, the larger the absolute value of a is, the smaller the acceleration forgetting factor τ1 is, and its value range is (0,1).

[0199] In actual operation, the longitudinal acceleration of the vehicle body measured by the vehicle sensor can be used as the motion acceleration value, such as the a analyzed in the previous article long The motion acceleration value can also be calculated from the longitudinal vehicle speed value.

[0200] τ2 is the state factor value when the vehicle is in a sliding state. The slip rate of each wheel can be calculated, and then the average value of multiple slip rates can be negatively correlated to obtain the state factor value.

[0201] Among them, τ2 is negatively correlated with the sum of the absolute values ​​of the slip rates s of each wheel of the vehicle. The slip rates of each wheel can be expressed as follows:

[0202]

[0203] The state factor value τ2 when the vehicle is in a sliding state can be expressed as follows:

[0204]

[0205] Right now The larger the absolute value of , the smaller the acceleration forgetting factor τ2, and the value range of τ2 is (0,1).

[0206] τ3 is the state factor value when the vehicle is in a driving state, which can determine the working condition and state of the vehicle. The corresponding state factor value can be determined for different working conditions or states.

[0207] For example, when the vehicle is in a straight-moving condition or an absolutely steady-state condition, τ3 takes a maximum value of 1, which ensures that the current estimated slope value is updated quickly; when the vehicle is in a turning condition or the vehicle is driving or braking (for example, turning left or right, driving, or braking), τ3 takes a median value of 0.5, and maintains a medium-speed update; when the vehicle is in a state of reversing from braking to driving torque or from driving to braking torque, τ3 takes a minimum value of 0, and the update of the current estimated slope value is prohibited, that is, the low-pass filtering of the original slope of the vehicle is suspended, and the value range of τ3 is (0,1).

[0208] τ4 is the state factor value of the vehicle in the road condition state, which is the state factor value of the vehicle in the state of driving on a speed bump and pothole road condition or the vehicle in the bad road condition.

[0209] Specifically, when the road condition on which the vehicle is traveling is identified as a speed bump, that is, the vehicle's motion state is in a state of traveling on a speed bump, τ4 takes the minimum value of 0, and the current estimated slope value is prohibited from being updated, that is, the low-pass filtering of the original slope of the vehicle is suspended.

[0210] When the road condition on which the vehicle is traveling is identified as a bad road condition, that is, the vehicle's motion state is in a state of traveling on a bad road condition, τ4 takes a smaller value of 0.2 and is updated at a low speed.

[0211] Otherwise, if the road condition is not bad or there is a speed bump, τ4 maintains its maximum value of 1, and the value range of τ4 is (0,1).

[0212] The embodiment of the present invention can obtain the original slope value of the vehicle by calculating the longitudinal acceleration of the vehicle body, but there is interference noise when the wheel speed method and the acceleration method are used to estimate the vehicle speed under different scene conditions, resulting in noise in the calculated original slope value. By determining the motion state of the vehicle; and performing low-pass filtering on the original slope value of the vehicle according to the slope estimation forgetting factor value of the motion state of the vehicle, the influence of noise can be eliminated and the estimation accuracy of the target slope can be improved.

[0213] Referring to the analysis content of the above embodiment, it can be known that one of the motion states of the vehicle is the road condition state, and the road condition state is the corresponding state of the road condition on which the vehicle is traveling. In order to accurately determine the road condition on which the vehicle is traveling, in one embodiment, after calculating the driving speed value, the road surface characteristics of the road surface on which the vehicle is currently traveling can be identified, and then the vehicle's driving road condition can be determined based on its road surface characteristics, and different applications and functional processing can be performed according to different road conditions. The vehicle's driving road condition can be determined later; based on the driving road condition, the motion state of the vehicle is determined.

[0214] Figure 3 The flowchart of an embodiment of determining the driving condition of a vehicle provided by the present invention is shown, and the method is executed by an electronic device, which may be an onboard terminal or a control terminal of the vehicle.

[0215] like Figure 3 As shown, in one embodiment, determining the vehicle driving condition may include the following steps:

[0216] Step 310: Calculate the wheel acceleration value of each wheel using the driving speed value, and calculate the acceleration change rate of each wheel using the wheel acceleration value. The driving speed value is the speed value obtained by converting the wheel speed to the center of mass position of the vehicle and in the driving direction of the vehicle.

[0217] After the driving speed value is calculated, the wheel acceleration value of each wheel can be calculated using the driving speed value. Specifically, the wheel acceleration value can be expressed as follows:

[0218]

[0219] In the above formula, Represents the wheel acceleration value of each wheel. t is time. The real-time working condition and motion state of the vehicle can be determined by the wheel acceleration value, and then the parameters can be estimated according to different working conditions and motion states, so as to improve the estimation accuracy by combining the actual driving state of the vehicle.

[0220] Specifically, the acceleration change rate of each wheel can be calculated using the wheel acceleration value of each wheel. Specifically, the ratio of the wheel acceleration value of each wheel to time can be calculated to obtain the acceleration change rate of each wheel.

[0221] Step 320: If the number of wheels whose acceleration change rate is greater than the wheel acceleration change rate threshold meets the preset number value, the difference between the maximum acceleration change rate and the minimum acceleration change rate is greater than the change difference threshold, and the duration meets the preset bad road cycle duration, then the motion state of the vehicle is determined to be a bad road condition state, wherein the duration is the duration during which the difference between the maximum acceleration change rate and the minimum acceleration change rate is greater than the change difference threshold.

[0222] Then, it is determined whether the acceleration change rate of each wheel is greater than the preset wheel change threshold. Then, the number of wheels whose acceleration change rate is greater than the wheel change threshold is counted, and it is determined that the number of wheels whose acceleration change rate is greater than the wheel change threshold satisfies the preset number value. Then, the acceleration change rate with the largest value and the acceleration change rate with the smallest value are extracted from the multiple acceleration change rates, and the difference between the acceleration change rate with the largest value and the acceleration change rate with the smallest value is calculated, and it is determined whether the difference is greater than the change difference threshold.

[0223] If the number of wheels whose acceleration change rate is greater than the wheel change threshold meets the preset number value, the difference between the acceleration change rate with the largest value and the acceleration change rate with the smallest value is greater than the change difference threshold, and the duration of satisfying the above conditions meets the preset bad road cycle duration, then it can be determined that the current driving condition of the vehicle is a bad road condition, and the vehicle's movement state is in a state of driving on a bad road condition.

[0224] For example, if there are four wheels, the statistical acceleration change rate is greater than the wheel change threshold (assuming 10m / s 2 ) has three or more wheels, and the preset number is 3, then the number of wheels meets the preset number. Maximum wheel acceleration change rate and minimum wheel acceleration rate of change The difference is greater than the change difference threshold (10m / s 3 ), and the above conditions are met for a duration of 1 minute, which exceeds the preset bad road cycle duration (30 seconds), then the current road condition of the vehicle is identified as a bad road condition.

[0225] Step 330: If the number of direction changes of the vehicle counted by using the acceleration change rate within the preset speed bump duration is greater than a preset number, then the movement state of the vehicle is determined to be a speed bump road condition state, wherein the number of direction changes is the number of times the state of the wheel acceleration change rate being greater than a preset positive threshold value becomes the number of times the wheel acceleration change rate is less than a preset negative threshold value, or the number of times the state of the wheel acceleration change rate being less than a preset positive threshold value becomes the number of times the wheel acceleration change rate is greater than a preset negative threshold value.

[0226] In another type of road condition recognition, the user can pre-set the period of the preset speed bump duration (assuming 200ms).

[0227] Then set the acceleration change rate of each wheel to be greater than the preset positive threshold (assuming 15m / s 3 ), the forward calculation is performed once; the acceleration change rate of each wheel is less than the preset negative threshold (assuming -15m / s 2 ), the negative direction is counted as 1; otherwise, it is not counted. If the direction changes from positive to negative, it is counted as one change of direction, and if the direction changes from negative to positive, it can also be counted as one change of direction.

[0228] If the number of direction changes within the preset speed bump period is greater than the preset number (assuming 2 times), it is determined that the current road condition of the vehicle is a speed bump road condition, and the vehicle's motion state is in a state of driving on a speed bump road condition.

[0229] In an actual operation mode, when it is determined that the current road condition of the vehicle is a speed bump road condition, a speed bump sign may be issued to prompt the user; otherwise, no sign is issued.

[0230] In another actual operation mode, when it is determined that the current road condition of the vehicle is a speed bump condition, the vehicle's brake master cylinder pressure or brake pedal stroke can be obtained. When the brake master cylinder pressure is greater than the deceleration brake master cylinder pressure threshold (for example, the brake master cylinder pressure is 20 Bar), or the brake pedal stroke exceeds the preset heavy braking threshold (for example, the brake pedal stroke is 15 mm), the speed bump flag may not be issued, and the speed bump flag may be reset.

[0231] Optionally, in actual operation, after determining the driving speed value of each wheel of the vehicle, the driving road condition of the vehicle may be determined.

[0232] The present invention can identify common road conditions such as bad roads, speed bumps, potholes, etc. by mining the wheel speed characteristics and their movement change trends. This can not only improve the recognition accuracy, but also adjust the confidence coefficient for different road conditions to further improve the calculation accuracy.

[0233] Figure 4 The flowchart of an embodiment of the original slope value estimation provided by the present invention is shown, and the method is executed by an electronic device. The electronic device may be a vehicle-mounted terminal or a control terminal of a vehicle.

[0234] like Figure 4 As shown, in one embodiment, the estimation of the original slope value includes the following steps:

[0235] Step 410: Obtain the longitudinal acceleration of the vehicle.

[0236] Step 420: Estimate the original slope value of the vehicle according to the longitudinal vehicle speed value and the longitudinal acceleration of the vehicle body.

[0237] After calculating the longitudinal vehicle speed value, the longitudinal vehicle speed value can be used to calculate the vehicle's body longitudinal acceleration, and finally, the body longitudinal acceleration is used to calculate the original slope value.

[0238] The longitudinal acceleration of the vehicle body can be calculated by using the above analytical method when confirming the noise error relationship in the Kalman filter.

[0239] The original slope value can be expressed as follows:

[0240] a long =v′ est +gsinθ0;

[0241]

[0242] In the above formula, θ0 can be the original slope value calculated, a long is the longitudinal acceleration of the vehicle body measured by the vehicle sensor, g is the acceleration due to gravity, and v′ est It is the rate of change of vehicle speed, that is, the vehicle's motion acceleration. Specifically, the longitudinal acceleration of the vehicle body can be calculated through the longitudinal vehicle speed value.

[0243] The embodiment of the present invention can calculate the original slope value of the vehicle by combining the longitudinal acceleration and longitudinal speed value of the vehicle body, so as to accurately determine the current driving state of the vehicle according to the original slope value of the vehicle, so as to evaluate different vehicle states and parameters according to the driving state of the vehicle.

[0244] Figure 5 FIG. 1 is a flow chart showing another embodiment of a method for calculating vehicle state parameters of the present invention, wherein the method is executed by an electronic device. Figure 5 As shown, the method comprises the following steps:

[0245] The first step is to use the wheel angular velocity sensor to collect the wheel angular velocity value.

[0246] The second step is to determine whether the signal from the wheel angular velocity sensor is valid.

[0247] In the third step, if the signal of the wheel angular velocity sensor is valid, the wheel speed is calculated using the wheel angular velocity value collected by the wheel angular velocity sensor.

[0248] The fourth step is to convert the wheel speed into the driving speed value at the center of mass position of the vehicle and in the driving direction of the vehicle.

[0249] The fifth step is to identify the vehicle's operating conditions, including stable conditions and unstable conditions.

[0250] The sixth step is to identify the vehicle's driving conditions.

[0251] The seventh step is to calculate the estimated vehicle speed values ​​under different vehicle operating conditions.

[0252] Step 8: The estimated vehicle speed values ​​under different working conditions are integrated to obtain the longitudinal vehicle speed value.

[0253] The ninth step is to correct the longitudinal vehicle speed value based on Kalman filtering.

[0254] Step 10. Calculate the original slope value using the longitudinal vehicle speed value.

[0255] In the eleventh step, the original slope value is low-pass filtered using the slope estimation forgetting factor values ​​corresponding to different vehicle motion states and driving conditions to obtain the target slope estimation value.

[0256] The present invention can solve the practical problem of inaccurate estimation of actual vehicle state parameters such as longitudinal reference speed and slope by identifying the vehicle's operating conditions and using Kalman filtering for correction processing. It can not only provide more accurate information input for vehicle control, thereby improving the vehicle's handling stability, comfort, safety and other performance, but also provide the vehicle driver with a more accurate reference to the vehicle's actual motion state under extreme abnormal conditions.

[0257] Moreover, the operation mode of the above embodiment can be applied to the longitudinal reference vehicle speed and slope estimation in different scenarios and working conditions, and has wide applicability and flexibility. For example, it can be applied to driving conditions on high-adhesion coefficient roads such as conventional urban areas, highways, and national highways, and is also applicable to acceleration, braking, steering and other working conditions on low-adhesion roads such as snow, mud, epoxy floors or intermittent potholes, as well as rapid acceleration, rapid deceleration, rapid steering and other working conditions in special scenarios, and can achieve good estimation results.

[0258] Figure 6 FIG. 2 is a schematic diagram showing the structure of an embodiment of a device for calculating vehicle state parameters of the present invention. Figure 6 As shown, the state parameters include: the longitudinal speed value of the vehicle; the device 600 includes: a working condition determination module 610, a first vehicle speed estimation module 620, a second vehicle speed estimation module 630 and a longitudinal vehicle speed module 640.

[0259] A working condition determination module, used to determine the working condition of the vehicle; the working condition includes: a stable working condition and an unstable working condition;

[0260] A first estimated vehicle speed module, used for calculating a first estimated vehicle speed value when the vehicle is in a stable working condition;

[0261] A second estimated vehicle speed module, used for calculating a second estimated vehicle speed value when the vehicle is in an unstable working condition;

[0262] The longitudinal vehicle speed module is used to fuse the first estimated vehicle speed value and the second estimated vehicle speed value to obtain the longitudinal vehicle speed value of the vehicle.

[0263] In an optional manner, the calculating the first estimated vehicle speed value when the vehicle is in a stable working condition specifically includes:

[0264] Determine a driving speed value of each wheel of the vehicle, wherein the driving speed value is a speed value obtained by converting the wheel speed to the center of mass position of the vehicle and in the driving direction of the vehicle;

[0265] Determining a confidence factor of each wheel of the vehicle according to a stable operating condition of the vehicle;

[0266] The first estimated vehicle speed value is calculated using the driving speed value of each wheel and the confidence coefficient corresponding to each wheel.

[0267] The stable working condition includes: an absolute steady-state working condition, a straight-ahead working condition, and a turning working condition; the confidence coefficient of each wheel of the vehicle is determined according to the stable working condition of the vehicle, specifically including:

[0268] When the vehicle is in an absolutely steady-state condition, the confidence coefficient of each wheel of the vehicle is determined to be 1;

[0269] When the vehicle is in a straight-moving condition and in a driving state, the confidence coefficient of the wheel with the smallest driving speed value is determined to be 1, and the confidence coefficients of the remaining wheels are determined to be 0;

[0270] When the vehicle is in a straight-moving condition and in an energy recovery or braking state, the confidence coefficient of the wheel with the largest driving speed value is determined to be 1, and the confidence coefficients of the remaining wheels are determined to be 0;

[0271] When the vehicle is in a turning condition, the confidence coefficient of the wheel whose driving speed value is in a stable state is set to 1, and the confidence coefficient of the wheel whose driving speed value is in an unstable state is set to 0 according to the specific turning and the set priority.

[0272] In an optional manner, the calculating the first estimated vehicle speed value by using the driving speed value of each wheel and the confidence coefficient corresponding to each wheel specifically includes:

[0273] The first estimated vehicle speed value of the vehicle is calculated using the following formula;

[0274]

[0275] Among them, v est1 is the first estimated vehicle speed value; k1, k2, k3, k4 are the confidence coefficients of each wheel respectively, are the driving speed values ​​of each wheel respectively.

[0276] In an optional manner, the calculating the second estimated vehicle speed value when the vehicle is in an unstable operating condition specifically includes:

[0277] determining a historical estimated speed of the vehicle for a previous cycle;

[0278] Determining a longitudinal acceleration value of the vehicle body;

[0279] The second estimated vehicle speed value is calculated according to the historical estimated vehicle speed and the vehicle body longitudinal acceleration value.

[0280] In an optional manner, the calculating the second estimated vehicle speed value according to the historical estimated vehicle speed and the vehicle body longitudinal acceleration value specifically includes:

[0281] v est2 =v est-1 +∫a long dt;

[0282] v est2 is the second estimated vehicle speed value, v est-1 is the estimated vehicle speed in the previous cycle, a long is the longitudinal acceleration of the vehicle body.

[0283] In an optional manner, the stable operating condition includes: an absolute steady-state operating condition, a straight-ahead operating condition, and a turning operating condition; and determining the operating condition of the vehicle specifically includes:

[0284] If the vehicle meets the following conditions: each of the driving speed values ​​is in a stable state, the difference between the driving speed value with the largest value and the driving speed value with the smallest value is less than the wheel speed difference threshold, the difference between the wheel acceleration value with the largest value and the wheel acceleration value with the smallest value is less than the acceleration difference threshold, the vehicle is not in a turning state, and the absolute value of the difference between the vehicle speed change rate in the previous calculation cycle and the wheel acceleration value with the largest value and the wheel acceleration value with the smallest value in the current cycle is less than the acceleration change threshold, then it is determined that the vehicle is in an absolute steady-state operating condition;

[0285] If the vehicle meets the following conditions: the vehicle is in a straight-moving state and each of the driving speed values ​​is in a stable state, it is determined that the vehicle is in a straight-moving condition;

[0286] If the vehicle meets the following conditions: the vehicle is in a left turn state or a right turn state, then it is determined that the vehicle is in a turning condition;

[0287] If the vehicle meets the following conditions: the vehicle is not in an absolutely steady-state condition, a straight-moving condition, or a turning condition, or each of the driving speed values ​​is in an unstable state, it is determined that the vehicle is in an unstable condition.

[0288] In an optional manner, the device further includes:

[0289] A correction processing module is used to, after the step of fusing the first estimated vehicle speed value and the second estimated vehicle speed value to obtain the longitudinal vehicle speed value of the vehicle, perform correction processing on the longitudinal vehicle speed value using a preset filter to obtain a correction parameter, wherein the preset filter is obtained by calculating the covariance using a state prediction equation constructed using a historical state of the vehicle, using the covariance and the optimal value of the real-time vehicle speed value to generate a gain matrix and using the gain matrix to construct the obtained result, wherein the correction parameter is the vehicle speed value obtained after correcting the estimation error of the longitudinal vehicle speed value.

[0290] In an optional manner, the device further includes:

[0291] An acceleration acquisition module, used for acquiring the longitudinal acceleration of the vehicle after the step of acquiring the longitudinal speed value of the vehicle;

[0292] The original slope estimation module is used to estimate the original slope value of the vehicle according to the longitudinal vehicle speed value and the longitudinal acceleration of the vehicle body.

[0293] In an optional manner, the device further includes:

[0294] a state determination module, configured to determine a motion state of the vehicle after the step of estimating an original slope value of the vehicle;

[0295] A factor value determination module, used to determine a forgetting factor value of a slope estimation of the vehicle according to a motion state of the vehicle;

[0296] The filtering processing module is used to estimate the forgetting factor value according to the slope, perform low-pass filtering on the original slope of the vehicle, and obtain a target slope estimation value.

[0297] In an optional manner, the motion state includes: an acceleration state, a sliding state, a driving state and a road condition state;

[0298] The step of determining a value of a forgetting factor for estimating a slope of the vehicle according to a motion state of the vehicle includes:

[0299] Respectively determine the state factor value corresponding to each motion state;

[0300] A weighted average calculation is performed on the multiple state factor values ​​to obtain a slope estimation forgetting factor value.

[0301] In an optional manner, the road condition includes a bad road condition and a speed bump condition, and determining the motion state of the vehicle includes:

[0302] Calculating the wheel acceleration value of each wheel using the driving speed value, and calculating the acceleration change rate of each wheel using the wheel acceleration value, wherein the driving speed value is a speed value obtained by converting the wheel speed to the center of mass position of the vehicle and in the driving direction of the vehicle;

[0303] If the number of wheels whose acceleration change rate is greater than the wheel acceleration change rate threshold satisfies a preset number value, the difference between the maximum acceleration change rate and the minimum acceleration change rate is greater than the change difference threshold, and the duration meets the preset bad road cycle duration, then the motion state of the vehicle is determined to be a bad road condition state, wherein the duration is the duration during which the difference between the maximum acceleration change rate and the minimum acceleration change rate is greater than the change difference threshold;

[0304] If the number of direction changes of the vehicle counted by using the acceleration change rate within the preset speed bump duration is greater than a preset number, then the movement state of the vehicle is determined to be a speed bump road condition state, wherein the number of direction changes is the number of times the state of the wheel acceleration change rate being greater than a preset positive threshold value becomes the number of times the wheel acceleration change rate is less than a preset negative threshold value, or the number of times the state of the wheel acceleration change rate being less than a preset positive threshold value becomes the number of times the wheel acceleration change rate is greater than a preset negative threshold value.

[0305] In an optional manner, the respectively determining the state factor value corresponding to each of the motion states includes:

[0306] If the motion state is an acceleration state, the motion acceleration value of the vehicle is obtained, and a state factor value is obtained by performing a negative correlation calculation on the absolute value of the motion acceleration value;

[0307] If the motion state is a sliding state, after calculating the sliding rate of each wheel, a negative correlation calculation is performed on the average values ​​of a plurality of the sliding rates to obtain a state factor value;

[0308] If the motion state is a driving state, when the driving state of the vehicle is a driving state of a straight-ahead condition or a driving state of an absolute steady-state condition, the state factor value is set to 1; when the driving state of the vehicle is a driving state of a turning condition or a driving state of the vehicle in driving or braking, the state factor value is set to 0.5; when the driving state of the vehicle is a driving state of switching from driving to braking or from braking to driving, the state factor value is set to 0, and the low-pass filtering of the original slope of the vehicle is suspended;

[0309] If the motion state is a road condition state, then when it is determined that the road condition state of the vehicle is not a bad road condition state or a non-speed belt road condition state, the state factor value is set to 1; when it is determined that the road condition state of the vehicle is a speed belt road condition state, the state factor value is set to 0.2; when it is determined that the road condition state of the vehicle is a bad road condition state, the state factor value is set to 0, and the low-pass filtering of the original slope of the vehicle is suspended.

[0310] Figure 7 The schematic diagram of the structure of an embodiment of the electronic device of the present invention is shown, and the specific embodiment of the present invention does not limit the specific implementation of the electronic device.

[0311] like Figure 7 As shown, the electronic device may include: a processor (processor) 402 , a communication interface (Communications Interface) 404 , a memory (memory) 406 , and a communication bus 408 .

[0312] The processor 402, the communication interface 404, and the memory 406 communicate with each other via the communication bus 408. The communication interface 404 is used to communicate with other devices such as a client or other server network elements. The processor 402 is used to execute the program 410, which can specifically execute the relevant steps in the above-mentioned embodiment of the method for calculating the vehicle state parameters.

[0313] Specifically, the program 410 may include program code including computer executable instructions.

[0314] The processor 402 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the electronic device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0315] The memory 406 is used to store the program 410. The memory 406 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0316] Program 410 can be specifically called by processor 402 to enable the electronic device to execute the method for calculating the vehicle state parameters provided in the above embodiment.

[0317] The method may include the following operations:

[0318] Determining the operating condition of the vehicle; the operating condition includes: a stable operating condition and an unstable operating condition;

[0319] Calculating a first estimated vehicle speed value when the vehicle is in a stable operating condition;

[0320] calculating a second estimated vehicle speed value when the vehicle is in an unstable operating condition;

[0321] The first estimated vehicle speed value and the second estimated vehicle speed value are integrated to obtain a longitudinal vehicle speed value of the vehicle.

[0322] In an optional manner, the program 410 is called by the processor 402 to enable the electronic device to execute the method for calculating the vehicle status parameters provided in the above embodiment.

[0323] The method may include the following operations:

[0324] Determining the operating condition of the vehicle; the operating condition includes: a stable operating condition and an unstable operating condition;

[0325] Calculating a first estimated vehicle speed value when the vehicle is in a stable operating condition;

[0326] calculating a second estimated vehicle speed value when the vehicle is in an unstable operating condition;

[0327] The first estimated vehicle speed value and the second estimated vehicle speed value are integrated to obtain a longitudinal vehicle speed value of the vehicle.

[0328] An embodiment of the present invention provides a computer-readable storage medium, which stores at least one executable instruction. When the executable instruction is executed on an electronic device / apparatus, the electronic device / apparatus executes the method for calculating the vehicle state parameters in any of the above method embodiments.

[0329] The executable instructions can be specifically used to enable the electronic device / apparatus to execute the method for calculating the vehicle status parameters provided in the above embodiment.

[0330] The method may include the following operations:

[0331] Determining the operating condition of the vehicle; the operating condition includes: a stable operating condition and an unstable operating condition;

[0332] Calculating a first estimated vehicle speed value when the vehicle is in a stable operating condition;

[0333] calculating a second estimated vehicle speed value when the vehicle is in an unstable operating condition;

[0334] The first estimated vehicle speed value and the second estimated vehicle speed value are integrated to obtain a longitudinal vehicle speed value of the vehicle.

[0335] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system or other device. In addition, the embodiments of the present invention are not directed to any particular programming language.

[0336] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. Similarly, in order to simplify the present invention and help understand one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, the various features of the embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. Wherein, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself is a separate embodiment of the present invention.

[0337] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and further may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive.

[0338] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A method for calculating vehicle state parameters, characterized in that: The state parameter includes: the longitudinal speed value of the vehicle; the method includes: Determining the operating condition of the vehicle; the operating condition includes: a stable operating condition and an unstable operating condition; Calculating a first estimated vehicle speed value when the vehicle is in a stable operating condition; calculating a second estimated vehicle speed value when the vehicle is in an unstable operating condition; The first estimated vehicle speed value and the second estimated vehicle speed value are integrated to obtain a longitudinal vehicle speed value of the vehicle.

2. The method according to claim 1, characterized in that The calculating a first estimated vehicle speed value when the vehicle is in a stable working condition specifically includes: Determine a driving speed value of each wheel of the vehicle, wherein the driving speed value is a speed value obtained by converting the wheel speed to the center of mass position of the vehicle and in the driving direction of the vehicle; Determining a confidence factor of each wheel of the vehicle according to a stable operating condition of the vehicle; The first estimated vehicle speed value is calculated using the driving speed value of each wheel and the confidence coefficient corresponding to each wheel.

3. The method according to claim 2, characterized in that The stable working condition includes: an absolute steady-state working condition, a straight-ahead working condition, and a turning working condition; the confidence coefficient of each wheel of the vehicle is determined according to the stable working condition of the vehicle, specifically including: When the vehicle is in an absolutely steady-state condition, the confidence coefficient of each wheel of the vehicle is determined to be 1; When the vehicle is in a straight-moving condition and in a driving state, the confidence coefficient of the wheel with the smallest driving speed value is determined to be 1, and the confidence coefficients of the remaining wheels are determined to be 0; When the vehicle is in a straight-moving condition and in an energy recovery or braking state, the confidence coefficient of the wheel with the largest driving speed value is determined to be 1, and the confidence coefficients of the remaining wheels are determined to be 0; When the vehicle is in a turning condition, the confidence coefficient of the wheel whose driving speed value is in a stable state is set to 1, and the confidence coefficient of the wheel whose driving speed value is in an unstable state is set to 0 according to the specific turning and the set priority.

4. The method according to claim 2, characterized in that: The calculating the first estimated vehicle speed value by using the driving speed value of each wheel and the confidence coefficient corresponding to each wheel specifically includes: The first estimated vehicle speed value of the vehicle is calculated using the following formula; Among them, v est1 is the first estimated vehicle speed value; k1, k2, k3, k4 are the confidence coefficients of each wheel respectively, are the driving speed values ​​of each wheel respectively.

5. The method according to claim 1, characterized in that The calculating a second estimated vehicle speed value when the vehicle is in an unstable working condition specifically includes: determining a historical estimated speed of the vehicle for a previous cycle; Determining a longitudinal acceleration value of the vehicle body; The second estimated vehicle speed value is calculated according to the historical estimated vehicle speed and the vehicle body longitudinal acceleration value.

6. The method according to claim 5, characterized in that The calculating the second estimated vehicle speed value according to the historical estimated vehicle speed and the vehicle body longitudinal acceleration value specifically includes: v est2 =v est-1 +∫a long dt; v est2 is the second estimated vehicle speed value, v est-1 is the estimated speed of the vehicle in the previous cycle, a long is the longitudinal acceleration value of the vehicle.

7. The method according to claim 2, characterized in that The stable working condition includes: an absolute steady-state working condition, a straight-ahead working condition, and a turning working condition; the working condition of the vehicle is determined, specifically including: If the vehicle meets the following conditions: each of the driving speed values ​​is in a stable state, the difference between the driving speed value with the largest value and the driving speed value with the smallest value is less than the wheel speed difference threshold, the difference between the wheel acceleration value with the largest value and the wheel acceleration value with the smallest value is less than the acceleration difference threshold, the vehicle is not in a turning state, and the absolute value of the difference between the vehicle speed change rate in the previous calculation cycle and the wheel acceleration value with the largest value and the wheel acceleration value with the smallest value in the current cycle is less than the acceleration change threshold, then it is determined that the vehicle is in an absolute steady-state operating condition; If the vehicle meets the following conditions: the vehicle is in a straight-moving state and each of the driving speed values ​​is in a stable state, it is determined that the vehicle is in a straight-moving condition; If the vehicle meets the following conditions: the vehicle is in a left turn state or a right turn state, then it is determined that the vehicle is in a turning condition; If the vehicle meets the following conditions: the vehicle is not in an absolutely steady-state condition, a straight-moving condition, or a turning condition, or each of the driving speed values ​​is in an unstable state, it is determined that the vehicle is in an unstable condition.

8. The method according to any one of claims 1 to 7, characterized in that: After the step of fusing the first estimated vehicle speed value and the second estimated vehicle speed value to obtain the longitudinal vehicle speed value of the vehicle, the method further includes: The longitudinal vehicle speed value is corrected by using a preset filter to obtain a correction parameter, wherein the preset filter is obtained by calculating the covariance using a state prediction equation constructed using a historical state of the vehicle, using the optimal value of the covariance and the real-time vehicle speed value to generate a gain matrix and using the gain matrix to construct the filter, wherein the correction parameter is the vehicle speed value obtained after correcting the estimation error of the longitudinal vehicle speed value.

9. The method according to claim 1, characterized in that: The state parameter also includes: a target slope estimation value; the method also includes: determining a motion state of the vehicle; Determining a value of a slope estimation forgetting factor of the vehicle according to a motion state of the vehicle; According to the slope estimation forgetting factor value, the original slope value of the vehicle is subjected to low-pass filtering to obtain a target slope estimation value.

10. The method according to claim 9, characterized in that The calculation operation of the original slope value includes: Obtaining the longitudinal acceleration of the vehicle; An original slope value of the vehicle is estimated according to the longitudinal vehicle speed value and the vehicle body longitudinal acceleration.

11. The method according to claim 9, characterized in that The motion state includes: acceleration state, sliding state, driving state and road condition state; The step of determining a value of a forgetting factor for estimating a slope of the vehicle according to a motion state of the vehicle includes: Respectively determine the state factor value corresponding to each motion state; A weighted average calculation is performed on the multiple state factor values ​​to obtain a slope estimation forgetting factor value.

12. The method according to claim 11, characterized in that The road condition includes a bad road condition and a speed bump condition. The determining the motion state of the vehicle includes: Calculating the wheel acceleration value of each wheel using the driving speed value, and calculating the acceleration change rate of each wheel using the wheel acceleration value, wherein the driving speed value is a speed value obtained by converting the wheel speed to the center of mass position of the vehicle and in the driving direction of the vehicle; If the number of wheels whose acceleration change rate is greater than the acceleration change rate threshold satisfies a preset number value, the difference between the maximum acceleration change rate and the minimum acceleration change rate is greater than the change difference threshold, and the duration meets the preset bad road cycle duration, then the motion state of the vehicle is determined to be a bad road condition state, wherein the duration is the duration during which the difference between the maximum acceleration change rate and the minimum acceleration change rate is greater than the change difference threshold; If the number of direction changes of the vehicle counted by using the acceleration change rate within the preset speed bump duration is greater than a preset number, then the movement state of the vehicle is determined to be a speed bump road condition state, wherein the number of direction changes is the number of times the state of the wheel acceleration change rate being greater than a preset positive threshold value becomes the number of times the wheel acceleration change rate is less than a preset negative threshold value, or the number of times the state of the wheel acceleration change rate being less than a preset positive threshold value becomes the number of times the wheel acceleration change rate is greater than a preset negative threshold value.

13. The method according to claim 11, characterized in that The step of respectively determining the state factor value corresponding to each motion state comprises: If the motion state is an acceleration state, the motion acceleration value of the vehicle is obtained, and a state factor value is obtained by performing a negative correlation calculation on the absolute value of the motion acceleration value; If the motion state is a sliding state, after calculating the sliding rate of each wheel, a negative correlation calculation is performed on the average values ​​of a plurality of the sliding rates to obtain a state factor value; If the motion state is a driving state, when the driving state of the vehicle is a driving state of a straight-ahead condition or a driving state of an absolute steady-state condition, the state factor value is set to 1; when the driving state of the vehicle is a driving state of a turning condition or a driving state of the vehicle in driving or braking, the state factor value is set to 0.5; when the driving state of the vehicle is a driving state of switching from driving to braking or from braking to driving, the state factor value is set to 0, and the low-pass filtering of the original slope of the vehicle is suspended; If the motion state is a road condition state, then when it is determined that the road condition state of the vehicle is not a bad road condition state or a non-speed belt road condition state, the state factor value is set to 1; when it is determined that the road condition state of the vehicle is a speed belt road condition state, the state factor value is set to 0.2; when it is determined that the road condition state of the vehicle is a bad road condition state, the state factor value is set to 0, and the low-pass filtering of the original slope of the vehicle is suspended.

14. A vehicle state parameter calculation device, characterized in that: The state parameter includes: the longitudinal speed value of the vehicle; the device includes: A working condition determination module, used to determine the working condition of the vehicle; the working condition includes: a stable working condition and an unstable working condition; A first estimated vehicle speed module, used for calculating a first estimated vehicle speed value when the vehicle is in a stable working condition; A second estimated vehicle speed module, used for calculating a second estimated vehicle speed value when the vehicle is in an unstable working condition; The longitudinal vehicle speed module is used to fuse the first estimated vehicle speed value and the second estimated vehicle speed value to obtain the longitudinal vehicle speed value of the vehicle.

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