Method and device for estimating road slope

Abstract

The application discloses a road slope estimation method and device, and belongs to the technical field of vehicle control. The method comprises the following steps: determining a ramp resistance acceleration initial value based on a first acceleration corresponding to an inertial measurement unit and a second acceleration corresponding to a vehicle speed, wherein the vehicle speed is determined based on a motor speed; determining a zero-crossing gap compensation value based on the vehicle speed and the second acceleration; determining a steering yaw compensation value based on the vehicle speed and a front axle angle; compensating the ramp resistance acceleration initial value based on the zero-crossing gap compensation value and the steering yaw compensation value to obtain a ramp resistance acceleration target value; and determining a road slope target value based on the ramp resistance acceleration target value. According to the scheme, the road slope is estimated based on the acceleration corresponding to the inertial measurement unit and the acceleration corresponding to the vehicle speed, the dependence on the acceleration sensor is reduced, the influence of vehicle torque zero-crossing and steering yaw on the estimation of the road slope is reduced, and the estimation accuracy of the road slope is improved.

Description

Technical Field

[0001] This application belongs to the field of vehicle control technology, and in particular relates to a method and device for estimating road slope. Background Technology

[0002] With the development of new energy electric vehicle technology, the control precision requirements of vehicle power systems in scenarios such as hill crawling, hill start, and hill coasting are constantly increasing. Road slope estimation, as the basis for correcting the control parameters of the above functions, directly affects the driving safety and user driving experience when the vehicle is driving on a slope.

[0003] Currently, the calculation method for road slope mainly relies on the signals collected by acceleration sensors. This method is highly dependent on the signals collected by acceleration sensors. Due to the significant noise in the signals collected by acceleration sensors, the accuracy of the calculated road slope is relatively low. Summary of the Invention

[0004] The embodiments of this application provide a method and apparatus for estimating road slope, which can at least improve the accuracy of road slope estimation to a certain extent.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to a first aspect of the embodiments of this application, a method for estimating road slope is provided, comprising: Based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed, the initial value of the slope resistance acceleration is determined, wherein the vehicle speed is determined based on the motor speed; The zero-crossing gap compensation value is determined based on vehicle speed and second acceleration; Determine the steering yaw compensation value based on vehicle speed and front axle angle; The initial value of the slope resistance acceleration is compensated based on the zero-crossing gap compensation value and the steering yaw compensation value to obtain the target value of the slope resistance acceleration. The target value of road slope is determined based on the target value of slope resistance acceleration.

[0007] In some embodiments, determining the zero-crossing clearance compensation value based on vehicle speed and second acceleration includes: The zero-crossing time of the motor is obtained by looking up the first preset mapping table based on the vehicle speed and the second acceleration. During the zero-crossing time of the motor, the preset compensation value is reduced to zero based on the preset gradient, and the reduced compensation value is used as the zero-crossing gap compensation value for the corresponding time. Outside of the motor's zero-crossing time, zero is defined as the zero-crossing gap compensation value.

[0008] In some embodiments, determining the steering yaw compensation value based on vehicle speed and front axle steering angle includes: The steering yaw compensation value is obtained by looking up the second preset mapping table based on the vehicle speed and front axle angle.

[0009] In some embodiments, determining the initial value of the ramp resistance acceleration based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed includes: The third acceleration is obtained by filtering the first acceleration corresponding to the inertial measurement unit. If the vehicle is moving in the forward direction, the difference between the third acceleration and the second acceleration is determined as the initial value of the slope resistance acceleration. If the direction of travel is backward, the sum of the third acceleration and the second acceleration is determined as the initial value of the ramp resistance acceleration.

[0010] In some embodiments, determining a target road slope value based on a target value for ramp resistance acceleration includes: The initial value of the road slope is determined based on the target value of the slope resistance acceleration and the gravitational acceleration. The difference between the initial value of the road slope and the target value of the vehicle pitch angle is determined as the candidate value of the road slope. If the rate of change of the candidate road slope value relative to the historical road slope value is greater than the preset slope change rate, then the target road slope value is determined based on the historical road slope value and the preset slope change rate. If the rate of change of the candidate road slope value relative to the historical road slope value is less than or equal to the preset slope change rate, then the candidate road slope value will be used as the target road slope value.

[0011] In some embodiments, the method for estimating road slope further includes: The initial value of the vehicle pitch angle is corrected based on the second acceleration to obtain the first pitch angle; The second pitch angle is estimated based on Kalman filtering; The first weight corresponding to the first pitch angle and the second weight corresponding to the second pitch angle are determined based on the vehicle's driving state. The target vehicle pitch angle is obtained by multiplying the first pitch angle by the first weight and adding the product of the second pitch angle by the second weight.

[0012] In some embodiments, the initial value of the vehicle pitch angle is corrected based on the second acceleration to obtain the first pitch angle, including: If the vehicle is in acceleration mode, the acceleration pitch gradient coefficient is determined based on the vehicle's driving torque and speed. The second acceleration is multiplied by the acceleration pitch gradient coefficient and then summed with the initial value of the vehicle pitch angle to obtain the first pitch angle. If the vehicle is in braking condition, the braking pitch gradient coefficient is determined based on the vehicle's braking torque and speed. The second acceleration is multiplied by the braking pitch gradient coefficient and then summed with the initial value of the vehicle's pitch angle to obtain the first pitch angle.

[0013] In some embodiments, estimating the second pitch angle based on Kalman filtering includes: A state vector is constructed based on pitch angle, pitch velocity, pitch acceleration, and longitudinal disturbance acceleration. Based on the vehicle pitch frequency, pitch damping ratio, coupling coefficient of longitudinal disturbance to pitch angular acceleration, and longitudinal disturbance attenuation time constant, a state equation matrix is ​​constructed. The input matrix is ​​constructed based on the transmission coefficient from driving torque to pitch angle acceleration; Based on the state vector, state equation matrix, and input matrix, the state equation of the Kalman filter is obtained; Based on the first acceleration, the second acceleration, and the target road slope value at the previous moment, the measurement equation of the Kalman filter is obtained; Using the state equation and measurement equation, time and measurement updates are performed through Kalman filtering to obtain the updated state vector; Extract the pitch angle from the updated state vector and use it as the second pitch angle.

[0014] In some embodiments, determining a first weight corresponding to a first pitch angle and a second weight corresponding to a second pitch angle based on the vehicle's driving state includes: If the vehicle's driving state represents the vehicle starting, driving at low speed, four-wheel slippage, or being in a steady state, then the first weight is set to be less than the second weight. If the vehicle's driving state is in a transient condition, then the first weight is set to be greater than the second weight.

[0015] According to a second aspect of the embodiments of this application, a road slope estimation device is provided, including a processor and a memory, wherein the memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, it implements the steps of the method as described in any of the first aspects above.

[0016] In this application, the initial value of the slope resistance acceleration is determined based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed. Considering that the vehicle speed is determined based on the motor speed, and that the motor's backlash control introduces calculation errors, zero-crossing clearance compensation is applied to the initial value of the slope resistance acceleration. Considering that vehicle steering yaw introduces calculation errors, steering yaw compensation is applied to the initial value of the slope resistance acceleration. Then, the target value of the road slope is determined based on the compensated target value of the slope resistance acceleration. This scheme reduces reliance on acceleration sensors, reduces the impact of vehicle torque zero-crossing and steering yaw on the estimation of road slope, and improves the accuracy of road slope estimation.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings: Figure 1 A flowchart illustrating a method for estimating road slope according to some embodiments of this application is shown; Figure 2 A schematic diagram illustrating the control principle of a road slope estimation method according to some embodiments of this application is shown; Figure 3 A block diagram of a road slope estimation device according to some embodiments of this application is shown; Figure 4 A schematic diagram of a road slope estimation device according to some embodiments of this application is shown. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0021] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0022] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0023] To enable those skilled in the art to better understand this application, the application scenarios involved in this application will be briefly described first.

[0024] To estimate road slope, two methods are commonly used in related technologies. One is the dynamic method, where the accuracy of parameters such as drag coefficient, rolling resistance coefficient, acceleration sensor signals, and vehicle mass directly determines the reliability of the estimation results when using dynamic equations to calculate road slope. However, because the drag model is affected by multiple factors such as road surface conditions, tire specifications, tire pressure, and ambient temperature, the parameters under actual operating conditions often deviate from the preset values. This estimation deviation of input terms leads to a decrease in the accuracy of slope calculation. The other method is the kinematic method, which mainly determines the slope based on signals collected by acceleration sensors. This calculation method is highly dependent on the signals collected by acceleration sensors, and because the signals collected by acceleration sensors are subject to significant noise, the accuracy of the calculated road slope is relatively low.

[0025] Based on this, the inventors provide a method for estimating road slope based on kinematic formulas. The method determines the initial value of the slope resistance acceleration based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed. Considering that the vehicle speed is determined based on the motor speed, and that motor backlash control introduces calculation errors, zero-crossing clearance compensation is applied to the initial value of the slope resistance acceleration. Considering that vehicle steering yaw introduces calculation errors, steering yaw compensation is applied to the initial value of the slope resistance acceleration. Finally, the target value of the road slope is determined based on the compensated target value of the slope resistance acceleration. This scheme reduces reliance on acceleration sensors, reduces the impact of vehicle torque zero-crossing and steering yaw on road slope estimation, and improves the accuracy of road slope estimation.

[0026] Figure 1 A flowchart illustrating a method for estimating road slope according to some embodiments of this application is shown. Figure 1 As shown, the method may include the following steps: Step 101: Determine the initial value of the ramp resistance acceleration based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed, wherein the vehicle speed is determined based on the motor speed; Step 102: Determine the zero-crossing gap compensation value based on vehicle speed and second acceleration; Step 103: Determine the steering yaw compensation value based on vehicle speed and front axle angle; Step 104: Compensate the initial value of the ramp resistance acceleration based on the zero-crossing clearance compensation value and the steering yaw compensation value to obtain the target value of the ramp resistance acceleration; Step 105: Determine the target value of road slope based on the target value of slope resistance acceleration.

[0027] In step 101, the inertial measurement unit (IMU) typically includes an accelerometer and a gyroscope. The first acceleration corresponding to the inertial measurement unit refers to the acceleration measurement value obtained after the acceleration measurement value detected by the accelerometer is transformed from the IMU coordinate system to the vehicle coordinate system.

[0028] Understandably, when there is a mounting offset between the IMU coordinate system and the vehicle coordinate system, the measurements from the accelerometer and gyroscope can be transformed to the vehicle coordinate system using a direction cosine matrix (DCM). The direction cosine matrix is ​​defined by the following formula: Formula 1; The single-axis rotation matrices are defined as follows: The mounting offset rotation matrix about the x-axis is: ; The mounting offset rotation matrix about the y-axis is: ; The mounting offset rotation matrix about the z-axis is: ; The installation offset angle is defined as: The mounting offset angle of the IMU relative to the vehicle coordinate system about the x-axis is denoted as . 1 represents the installation offset angle of the IMU relative to the vehicle coordinate system about the y-axis. 1 represents the installation offset angle of the IMU relative to the vehicle coordinate system around the z-axis.

[0029] The acceleration measurement value of the accelerometer in the vehicle coordinate system can be obtained by performing a coordinate transformation on the acceleration measurement value of the accelerometer in the IMU coordinate system using the direction cosine matrix (DCM). The calculation relationship is shown in Formula 2 below: Formula 2; in, The acceleration measurement values ​​are in the IMU coordinate system. This refers to the acceleration measurement in the vehicle coordinate system.

[0030] By converting the acceleration measurements in the IMU coordinate system to the acceleration measurements in the vehicle coordinate system, the error caused by sensor installation deviation is eliminated.

[0031] Considering that the vehicle speed obtained by the vehicle controller from the Electronic Stability Control (ESC) system is often not accurate enough and has filtering lag, the vehicle speed in this embodiment is determined based on the motor speed to improve the accuracy of road gradient calculation based on kinematic formula. In the implementation process, if the motor speed fails, the vehicle speed calculated by ESC can be used instead.

[0032] For a specific formula to convert motor speed into vehicle speed, please refer to Formula 3 below: ; in, For vehicle speed, This refers to the motor speed. The speed ratio from the motor end to the wheel is . This is the conversion relationship between rpm and m / s, where R is the wheel radius.

[0033] The second acceleration corresponding to the vehicle speed refers to the acceleration calculated based on the vehicle speed. Specifically, the second acceleration can be obtained by differentiating the vehicle speed.

[0034] In the implementation process, the initial value of the ramp resistance acceleration can be calculated directly using the first acceleration and the second acceleration, or the first acceleration can be filtered and then combined with the second acceleration to calculate the initial value of the ramp resistance acceleration.

[0035] In some embodiments, determining the initial value of the ramp resistance acceleration based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed includes: filtering the first acceleration corresponding to the inertial measurement unit to obtain a third acceleration; if the vehicle's running direction is forward, then the difference between the third acceleration and the second acceleration is determined as the initial value of the ramp resistance acceleration; if the running direction is backward, then the sum of the third acceleration and the second acceleration is determined as the initial value of the ramp resistance acceleration.

[0036] Specifically, if the vehicle is traveling in the forward direction, the initial value of the slope resistance acceleration can be calculated using the following formula: ; in, This is the initial value of the acceleration due to slope resistance, with the direction of the vehicle heading uphill being positive, and the unit is m / s². 2 ,

[0037] If the running direction is backward, the initial value of the ramp resistance acceleration can be calculated using the following formula:

[0038] Understandably, the raw IMU signal contains a large number of high-frequency spikes caused by road bumps and engine vibrations. By filtering the first acceleration, these noises can be effectively removed, making the processed third acceleration signal smoother and effectively avoiding the interference of noise peaks at a single moment on the calculation results.

[0039] In step 102, zero-crossing gap compensation is considered because the vehicle speed in this embodiment is obtained based on the motor speed. The motor transmission system has a gear system. When the motor crosses zero, the speed jumps at this moment due to the gear system, which leads to errors in the road slope estimation.

[0040] In some embodiments, determining the zero-crossing gap compensation value based on vehicle speed and second acceleration includes: looking up a first preset mapping table based on vehicle speed and second acceleration to obtain the motor zero-crossing time; during the motor zero-crossing time, reducing the preset compensation value to zero based on a preset gradient, and using the reduced compensation value as the zero-crossing gap compensation value for the corresponding time; outside the motor zero-crossing time, determining zero as the zero-crossing gap compensation value.

[0041] It is understandable that the transmission gear system is fixed, and the motor's zero-crossing time can be determined by the motor speed / vehicle speed and the second acceleration. Therefore, the motor's zero-crossing time can be determined using the vehicle speed and the second acceleration. In the implementation process, the first preset mapping table MAP1 can be calibrated in advance through actual vehicle testing. This table is used to characterize the correspondence between vehicle speed, the second acceleration, and the motor's zero-crossing time.

[0042] When the vehicle is detected to be in a torque zero-crossing condition, such as when switching from coasting to drive or vice versa, the parameters of the low-pass filter can be set to the motor zero-crossing time Ta. Ta is obtained by looking up table MAP1 using the vehicle speed and the second acceleration. Within Ta, the preset compensation value a0 is gradually reduced to zero according to a certain gradient. The reduced compensation value is the zero-crossing gap compensation value a1 for the corresponding time. If the vehicle is not in a torque zero-crossing condition, no zero-crossing gap compensation is required, and the zero-crossing gap compensation value a1 is zero.

[0043] In step 103, lateral interference can be eliminated by steering yaw compensation, thereby improving the accuracy of road slope estimation.

[0044] In some embodiments, determining the steering yaw compensation value based on vehicle speed and front axle angle includes: looking up a second preset mapping table based on vehicle speed and front axle angle to obtain the steering yaw compensation value.

[0045] The front axle steering angle can be obtained by multiplying the steering wheel angle by the steering wheel-to-front wheel steering angle transmission ratio. The second preset mapping table MAP2 can be obtained in advance through actual vehicle testing and calibration. This table is used to characterize the correspondence between vehicle speed, front axle steering angle, and steering yaw compensation value.

[0046] It should be noted that, considering that the front axle steering angle precedes the vehicle yaw, the steering yaw compensation value is obtained by using the front axle steering angle instead of the yaw rate in this embodiment of the application, which can improve the responsiveness of the calculation.

[0047] In step 104, the target value of the ramp resistance acceleration can be calculated using the following formula: Formula Six; in, The target value for ramp resistance acceleration. This is the initial value of the ramp resistance acceleration. This is the zero-crossing gap compensation value. This is the steering yaw compensation value.

[0048] In step 105, the initial value of the road slope can be calculated directly based on the target value of the slope resistance acceleration. Then, the initial value of the road slope is subtracted from the vehicle pitch angle, and the resulting road slope is directly used as the target value of the road slope. Alternatively, the obtained road slope can be filtered, and the processed road slope can be used as the target value of the road slope.

[0049] In some embodiments, an initial road slope value can be determined based on a target value of ramp resistance acceleration and gravitational acceleration; the difference between the initial road slope value and a target value of vehicle pitch angle is determined as a candidate road slope value; if the rate of change of the candidate road slope value relative to historical road slope values ​​is greater than a preset slope change rate, a target road slope value is determined based on historical road slope values ​​and the preset slope change rate; if the rate of change of the candidate road slope value relative to historical road slope values ​​is less than or equal to the preset slope change rate, the candidate road slope value is used as the target road slope value.

[0050] Specifically, the initial value of the road slope can be calculated using the following formula: *100% Formula Seven; in, This is the initial value of the road slope. This is the acceleration due to gravity.

[0051] The influence of vehicle pitch needs to be removed from the initial value of road slope. Therefore, the candidate value of road slope can be calculated using the following formula: Formula 8; in, Candidate values ​​for road slope. This represents the target value for the vehicle's pitch angle.

[0052] It is understandable that road slope changes are generally slow variables, so a low-pass filter can be used to filter the calculated road slope candidate values. The filter limit takes into account the slope change rate of the conventional road surface (i.e., the preset slope change rate) and can be set to 0.005% / S (i.e., the slope change per second does not exceed 0.005%).

[0053] If the rate of change of the candidate road slope value relative to the historical road slope value is greater than the preset slope change rate, the historical road slope value can be multiplied by the preset slope change rate to obtain the road slope change value. Then, the target road slope value can be calculated using the historical road slope value and the road slope change value.

[0054] By filtering the candidate road slope values, the estimation error of the target road slope value caused by changes in road potholes is eliminated, thus improving the reliability of the target road slope value.

[0055] After calculating the target road slope value, the update of the target road slope value can be stopped and the previous target road slope value can be maintained if any of the following conditions are met: 1. The derivative of acceleration is greater than the set calibrable threshold; 2. All four wheels slip; 3. The second derivative of the wheel speed of any wheel is greater than the set calibrable threshold; 4. The steering wheel angle and the vehicle yaw rate simultaneously exceed their respective calibration thresholds; 5. The vehicle is decelerating and the wheel speed is lower than the set threshold. The above thresholds are calibration values, specifically obtained through calibration under actual vehicle conditions. Their purpose is to maintain the previous target road slope value when the vehicle becomes unstable. A separate slope change slope filter is performed during the process of switching from the maintained value to the updated value.

[0056] It should be noted that the accuracy of the vehicle pitch angle calculation directly affects the accuracy of the road slope target value estimation. This application's embodiments estimate the vehicle pitch angle using two methods: vehicle pitch dynamics correction and Kalman filtering. The two methods are then weighted and fused according to different operating conditions to eliminate the influence of vehicle pitch changes caused by the vehicle suspension during acceleration and deceleration on the estimation of the road slope target value.

[0057] In some embodiments, the target value of the vehicle pitch angle can be obtained through the following steps: correcting the initial value of the vehicle pitch angle based on the second acceleration to obtain a first pitch angle; estimating the second pitch angle based on Kalman filtering; determining the first weight corresponding to the first pitch angle and the second weight corresponding to the second pitch angle based on the vehicle's driving state; and adding the product of the first pitch angle and the first weight to the product of the second pitch angle and the second weight to obtain the target value of the vehicle pitch angle.

[0058] The initial value of the vehicle pitch angle is the vehicle pitch angle obtained from a calibration test on a 0° slope.

[0059] The first pitch angle can be obtained by linearly estimating the vehicle pitch angle based on the initial value of the vehicle pitch angle and the pitch gradient characteristics of the vehicle under longitudinal acceleration and braking conditions. When the vehicle is in acceleration condition, the initial value of the vehicle pitch angle is corrected using the acceleration pitch gradient coefficient; when the vehicle is in braking condition, the initial value of the vehicle pitch angle is corrected using the braking pitch gradient coefficient.

[0060] In some embodiments, if the vehicle is in an acceleration condition, the acceleration pitch gradient coefficient is determined based on the vehicle's driving torque and speed. The second acceleration is multiplied by the acceleration pitch gradient coefficient and then summed with the initial value of the vehicle's pitch angle to obtain the first pitch angle. If the vehicle is in a braking condition, the braking pitch gradient coefficient is determined based on the vehicle's braking torque and speed. The second acceleration is multiplied by the braking pitch gradient coefficient and then summed with the initial value of the vehicle's pitch angle to obtain the first pitch angle.

[0061] Specifically, for acceleration conditions, the first pitch angle can be calculated using the following formula: Formula Nine; in, The first pitch angle, This is the initial value of the vehicle's pitch angle. To accelerate the pitch gradient coefficient, This is the second acceleration.

[0062] For braking conditions, the first pitch angle can be calculated using the following formula: Formula 10; in, This is the braking pitch gradient coefficient.

[0063] The acceleration pitch gradient coefficient is directly related to the driving conditions and can be obtained by looking up the MAP3 table using the driving torque and vehicle speed. This parameter supports adaptive suspension adjustment; for example, if the suspension is adjusted through the in-vehicle infotainment (IVI) system, there is an independent MAP3 table to support parameter calculation.

[0064] The braking pitch gradient coefficient is directly related to the braking condition and can be obtained by looking up the braking torque (the sum of electric braking and hydraulic braking torque) and vehicle speed in MAP4. This parameter supports adjustable suspension.

[0065] Considering that vehicle acceleration and deceleration cause load transfer between the front and rear axles, resulting in different displacement deviations in the suspension, which manifests as the vehicle pitch angle, the second pitch angle can be estimated by using the Kalman filter algorithm, which treats the suspension system as an equivalent second-order spring-damped system.

[0066] In some embodiments, estimating the second pitch angle based on Kalman filtering includes: constructing a state vector based on pitch angle, pitch angular velocity, pitch acceleration, and longitudinal disturbance acceleration; constructing a state equation matrix based on vehicle pitch frequency, pitch damping ratio, coupling coefficient of longitudinal disturbance to pitch acceleration, and longitudinal disturbance decay time constant; constructing an input matrix based on the transmission coefficient from driving torque to pitch acceleration; obtaining the state equation of Kalman filtering based on the state vector, state equation matrix, and input matrix; obtaining the measurement equation of Kalman filtering based on the first acceleration, second acceleration, and the target road slope value at the previous moment; using the state equation and measurement equation, performing time update and measurement update through Kalman filtering to obtain the updated state vector; and extracting the pitch angle from the updated state vector as the second pitch angle.

[0067] Specifically, based on the vehicle pitch rigid body dynamics and longitudinal kinematics, a linear state equation is constructed, and higher-order nonlinear terms are ignored, resulting in the following state equation: Formula 11; Where X is the state vector, A is the state equation matrix, and B is the input matrix. This refers to the motor drive torque. The process noise can be quantified using the covariance matrix Q, which can be calibrated using real vehicle data.

[0068] The state vector X can be defined as: ; in, The pitch angle, The pitch angular velocity, For pitch acceleration, This represents longitudinal disturbance acceleration.

[0069] The state equation matrix A can be defined as: ; in, The vehicle's pitch frequency. For pitch damping ratio, The coupling coefficient between longitudinal disturbance and pitch acceleration. This is the longitudinal interference attenuation time constant.

[0070] The vehicle pitch frequency can be a pre-calibrated natural frequency, such as 0.5~1Hz; the pitch damping ratio can be a pre-calibrated value, such as 0.1~0.3; the coupling coefficient of longitudinal disturbance to pitch angular acceleration can also be a calibrated value; the longitudinal disturbance decay time constant can also be a calibrated value, such as 50~100ms.

[0071] The input matrix B can be defined as: ; in, The transmission coefficient from drive torque to pitch acceleration can be obtained through actual vehicle calibration.

[0072] In defining the measurement equation, the following relationship exists between the first acceleration and the second acceleration: ; in, The target value for road gradient at the previous moment. This is interference acceleration.

[0073] Transforming the above formula, we obtain the following formula thirteen: .

[0074] When the slope and pitch angle are small, Using Taylor series expansion, and considering a certain level of precision while retaining the third-order terms, we obtain the following formula fourteen: = Formula Fourteen; Considering the relatively small pitch angle caused by acceleration and deceleration, we ignore the higher-order terms in Equation 14 above and retain only the first-order terms. Equation 14 can be expressed as: Formula 15; Substituting into Formula 13, we obtain Formula 16 as shown below: *( ) Formula Sixteen; By transforming Formula 16, we obtain Formula 17 as shown below: )= Formula 17; make = Formula 17 can then be transformed into Formula 18 as follows: *( Formula 18; The filter measurement equation is described as follows: Formula 19; Where H is the measurement matrix, To measure covariance.

[0075] In this measurement equation, the measurement matrix H can be defined as: ; , *( () is a single-valued quantity.

[0076] In the Kalman filter estimation process, the vehicle pitch behavior is treated as a second-order oscillatory system, which can effectively suppress noise and the second pitch angle calculated in steady state is stable, reducing the impact of changes in vehicle pitch angle caused by the vehicle suspension during acceleration and deceleration.

[0077] In some embodiments, determining the first weight corresponding to the first pitch angle and the second weight corresponding to the second pitch angle based on the vehicle's driving state includes: if the vehicle's driving state indicates that the vehicle is starting, driving at low speed, experiencing four-wheel slippage, or is in a steady-state condition, then the first weight is set to be less than the second weight; if the vehicle's driving state indicates that it is in a transient condition, then the first weight is set to be greater than the second weight.

[0078] It is understandable that the first pitch angle is calculated based on the vehicle body pitch dynamics correction. Because it is calculated using acceleration, the transient response is fast, but it is susceptible to interference. The second pitch angle, however, is calculated using Kalman filtering. It has the characteristic of being stable in steady state. Therefore, in the embodiments of this application, the two pitch angles are weighted and calculated to obtain the target value of the vehicle pitch angle.

[0079] Specifically, the target value of the vehicle pitch angle can be expressed by the following formula: ; in, The target value for the vehicle's pitch angle. As the first weight, The first pitch angle, As the second weight, This is the second pitch angle.

[0080] During implementation, when the vehicle is crawling and starting, or traveling at low speeds (such as below 10 km / h), the overall driving torque and acceleration are relatively small, and the initial gradient estimate is accurate, allowing for greater confidence in the second pitch angle. Second weight It can be set to 0.8.

[0081] In transient situations, the weights tend to favor the first pitch angle. At this point, the adjustment range of the second weight can be [0.2-0.5], while in steady state, the weight tends to favor the second pitch angle. At this point, the adjustment range of the second weight is [0.5 0.8].

[0082] The transient and steady-state determination methods can be achieved by comparing the rate of change of acceleration with a steady-state threshold. This steady-state threshold can be calibrated using a real vehicle. In some examples, the steady-state threshold... If the rate of change of acceleration is less than the steady-state threshold If the condition is met, the vehicle is determined to be in a steady-state condition; otherwise, the vehicle is determined to be in a transient condition.

[0083] If four wheels slip or lock up, the weighting is more biased towards the second pitch angle. Second weight It can be set to 0.9 because the second acceleration calculated from the vehicle speed is inaccurate at this point, and the first pitch angle is then calculated based on the second acceleration. That's not accurate either.

[0084] This application embodiment estimates the vehicle pitch angle using Kalman filtering and integrates it into the vehicle pitch dynamics correction strategy. This allows for the accurate acquisition of the target vehicle pitch angle value, which in turn eliminates the estimation bias introduced by vehicle pitch in subsequent road slope estimation, thereby improving the accuracy of road slope estimation.

[0085] Figure 2 A schematic diagram illustrating the control principle of a road slope estimation method according to some embodiments of this application is shown. Figure 2 As shown, the acceleration measurements detected by the IMU are transformed from the IMU coordinate system to the vehicle coordinate system to obtain the first acceleration; the second acceleration is calculated based on the vehicle speed; and the initial value of the slope resistance acceleration is obtained based on the first and second accelerations. Zero-crossing clearance compensation and steering yaw compensation are applied to the initial value of the slope resistance acceleration to obtain the target value of the slope resistance acceleration. The initial value of the road slope is calculated based on the target value of the slope resistance acceleration. The first pitch angle is obtained based on vehicle pitch dynamics correction, and the second pitch angle is estimated based on Kalman filtering. The first and second pitch angles are weighted according to different operating conditions to obtain the target value of the pitch angle. The target value of the pitch angle is then used to dynamically compensate the initial value of the road slope to obtain candidate values ​​of the road slope. These candidate values ​​are then filtered and limited, and combined with a slope update strategy, the target value of the road slope is obtained.

[0086] This embodiment determines the initial value of the slope resistance acceleration based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed. Considering that the vehicle speed is determined based on the motor speed, and the motor's backlash control introduces calculation errors, zero-crossing clearance compensation is applied to the initial value of the slope resistance acceleration. Considering that vehicle steering yaw introduces calculation errors, steering yaw compensation is applied to the initial value of the slope resistance acceleration. Then, the target value of the road slope is determined based on the compensated target value of the slope resistance acceleration. This scheme reduces the dependence on acceleration sensors and reduces the impact of vehicle torque zero-crossing and yaw on the estimation of road slope. In addition, this scheme estimates the vehicle pitch angle using two methods: Kalman filtering and vehicle pitch dynamics correction. It then performs weighted fusion of the two methods according to different operating conditions to accurately obtain the target value of the pitch angle, which helps to reduce the impact of vehicle pitch on the estimation of road slope and improves the estimation accuracy of road slope.

[0087] The following describes an embodiment of the apparatus of this application, which can be used to execute the road slope estimation method described in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the road slope estimation method described in the above applications.

[0088] See Figure 3 The diagram shows a block diagram of a road slope estimation device according to an embodiment of this application.

[0089] like Figure 3 As shown, the road slope estimation device of this application embodiment includes: an acceleration calculation module 301, a zero-crossing compensation value calculation module 302, a yaw compensation value calculation module 303, a compensation module 304, and a road slope calculation module 305. The acceleration calculation module 301 determines the initial value of the slope resistance acceleration based on a first acceleration corresponding to the inertial measurement unit and a second acceleration corresponding to the vehicle speed, wherein the vehicle speed is determined based on the motor rotation speed. The zero-crossing compensation value calculation module 302 determines the zero-crossing clearance compensation value based on the vehicle speed and the second acceleration. The yaw compensation value calculation module 303 determines the steering yaw compensation value based on the vehicle speed and the front axle angle. The compensation module 304 compensates the initial value of the slope resistance acceleration based on the zero-crossing clearance compensation value and the steering yaw compensation value to obtain a target value of the slope resistance acceleration. The road slope calculation module 305 determines the target value of the road slope based on the target value of the slope resistance acceleration.

[0090] Based on the same inventive concept, embodiments of this application also provide a road slope estimation device, with reference to... Figure 4 The diagram shows a schematic of the structure of a road slope estimation device according to an embodiment of this application. The road slope estimation device includes one or more memories 404, one or more processors 402, and at least one computer program (computer program instructions) stored in the memory 404 and executable on the processor 402. When the processor 402 executes the computer program, it implements the method described above.

[0091] Among them, Figure 4 In this document, a bus architecture (represented by bus 400) is used. Bus 400 may include any number of interconnected buses and bridges, linking various circuits including one or more processors represented by processor 402 and memory represented by memory 404. Bus 400 may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 405 provides an interface between bus 400 and receiver 401 and transmitter 403. Receiver 401 and transmitter 403 may be the same element, i.e., a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 402 is responsible for managing bus 400 and general processing, while memory 404 can be used to store data used by processor 402 during operation.

[0092] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, cause the processor to perform the steps of the method described above.

[0093] Based on the same inventive concept, embodiments of this application provide a computer program product, including a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0094] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and embodiments are within the scope and spirit of this application and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Furthermore, the functional units may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0096] The units described as separate components may or may not be physically separate. Similarly, the components of the control device may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0097] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing computer program instructions, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0098] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for estimating road slope, characterized in that, include: The initial value of the ramp resistance acceleration is determined based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed, wherein the vehicle speed is determined based on the motor speed. Based on the vehicle speed and the second acceleration, the zero-crossing gap compensation value is determined; Based on the vehicle speed and front axle angle, determine the steering yaw compensation value; The initial value of the slope resistance acceleration is compensated based on the zero-crossing gap compensation value and the steering yaw compensation value to obtain the target value of the slope resistance acceleration. Based on the target value of the slope resistance acceleration, the target value of the road slope is determined.

2. The method for estimating road slope according to claim 1, characterized in that, The determination of the zero-crossing gap compensation value based on the vehicle speed and the second acceleration includes: Based on the vehicle speed and the second acceleration, the first preset mapping table is consulted to obtain the zero-crossing time of the motor; During the zero-crossing time of the motor, the preset compensation value is reduced to zero based on the preset gradient, and the reduced compensation value is used as the zero-crossing gap compensation value for the corresponding time. Outside of the motor's zero-crossing time, zero is defined as the zero-crossing gap compensation value.

3. The method for estimating road slope according to claim 1, characterized in that, The determination of the steering yaw compensation value based on the vehicle speed and front axle angle includes: The steering yaw compensation value is obtained by looking up the second preset mapping table based on the vehicle speed and the front axle angle.

4. The method for estimating road slope according to claim 1, characterized in that, The determination of the initial value of the ramp resistance acceleration based on the first acceleration corresponding to the inertial measurement unit and the second acceleration corresponding to the vehicle speed includes: The first acceleration corresponding to the inertial measurement unit is filtered to obtain the third acceleration; If the vehicle is moving in the forward direction, the difference between the third acceleration and the second acceleration is determined as the initial value of the ramp resistance acceleration. If the running direction is backward, the sum of the third acceleration and the second acceleration is determined as the initial value of the ramp resistance acceleration.

5. The method for estimating road slope according to claim 1, characterized in that, Determining the target road slope value based on the target value of the slope resistance acceleration includes: Based on the target value of the slope resistance acceleration and the gravitational acceleration, the initial value of the road slope is determined; The difference between the initial value of the road slope and the target value of the vehicle pitch angle is determined as the candidate value of the road slope. If the rate of change of the candidate road slope value relative to the historical road slope value is greater than the preset slope change rate, then the target road slope value is determined based on the historical road slope value and the preset slope change rate. If the rate of change of the candidate road slope value relative to the historical road slope value is less than or equal to the preset slope change rate, then the candidate road slope value is used as the target road slope value.

6. The method for estimating road slope according to claim 5, characterized in that, Also includes: The initial value of the vehicle pitch angle is corrected based on the second acceleration to obtain the first pitch angle; The second pitch angle is estimated based on Kalman filtering; The first weight corresponding to the first pitch angle and the second weight corresponding to the second pitch angle are determined based on the vehicle's driving state. The target value of the vehicle pitch angle is obtained by multiplying the first pitch angle by the first weight and adding the product of the second pitch angle by the second weight.

7. The method for estimating road slope according to claim 6, characterized in that, The step of correcting the initial value of the vehicle pitch angle based on the second acceleration to obtain the first pitch angle includes: If the vehicle is in an acceleration condition, the acceleration pitch gradient coefficient is determined based on the vehicle's driving torque and the vehicle speed. The second acceleration is multiplied by the acceleration pitch gradient coefficient and then summed with the initial value of the vehicle pitch angle to obtain the first pitch angle. If the vehicle is in braking condition, the braking pitch gradient coefficient is determined based on the vehicle's braking torque and the vehicle speed. The second acceleration is multiplied by the braking pitch gradient coefficient and then summed with the initial value of the vehicle's pitch angle to obtain the first pitch angle.

8. The method for estimating road slope according to claim 6, characterized in that, The estimation of the second pitch angle based on Kalman filtering includes: A state vector is constructed based on pitch angle, pitch velocity, pitch acceleration, and longitudinal disturbance acceleration. Based on the vehicle pitch frequency, pitch damping ratio, coupling coefficient of longitudinal disturbance to pitch angular acceleration, and longitudinal disturbance attenuation time constant, a state equation matrix is ​​constructed. The input matrix is ​​constructed based on the transmission coefficient from driving torque to pitch angle acceleration; Based on the state vector, the state equation matrix, and the input matrix, the state equation of the Kalman filter is obtained; Based on the first acceleration, the second acceleration, and the target road slope value at the previous moment, the measurement equation of the Kalman filter is obtained; Using the state equation and the measurement equation, time and measurement updates are performed through Kalman filtering to obtain the updated state vector; Extract the pitch angle from the updated state vector and use it as the second pitch angle.

9. The method for estimating road slope according to claim 6, characterized in that, Determining the first weight corresponding to the first pitch angle and the second weight corresponding to the second pitch angle based on the vehicle's driving state includes: If the vehicle's driving state represents the vehicle starting, driving at low speed, four-wheel slippage, or being in a steady state, then the first weight is set to be less than the second weight. If the vehicle's driving state is in a transient condition, then the first weight is set to be greater than the second weight.

10. A road slope estimation device, comprising a processor and a memory, characterized in that, The memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, it implements the steps of the method as described in any one of claims 1 to 9.

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