METHOD FOR CALIBRINGING AN INERTITAL SENSOR OF A VEHICLE

Description

[0001] The invention relates to a method for calibrating an inertial measurement sensor of a vehicle according to the preamble of claim 1.

[0002] The invention further relates to a method for adjusting the headlight range of at least one headlight of a vehicle.

[0003] It is known that vehicles are equipped with inertial measurement sensors based on MEMS (Micro Electro Mechanical Systems), which measure the vehicle's rotation rate as yaw rate sensors and its acceleration in up to three spatial directions as accelerometers or acceleration sensors. These inertial measurement sensors are used for various vehicle systems, such as vehicle dynamics control, modern augmented reality applications, and assisted or automated driving.

[0004] However, measurements from such inertial measurement sensors can be prone to errors, which can limit usability or reduce achievable system accuracy in many applications that utilize these sensors. Examples of such sensor errors include incorrect alignment of the inertial measurement sensor with the vehicle and offset errors of individual measurement axes. These offset errors represent an intrinsic error of the inertial measurement sensor, manifesting as follows: The measured value xmeas is not only the current acceleration or rotation rate, but also exhibits a constant, slowly changing offset xoffset(t) relative to the actual value xreal. x meas = x real + x offset t exhibits.

[0005] It is known that such offset errors are determined internally in vehicles through a long-term comparison of measured values. This assumes that over a relatively long time horizon, the sums of the accelerations (since the vehicle starts and stops at 0 km / h) and the rotation rates (since the vehicle does not roll over or become upside down) are equal to zero. Therefore, any deviation in the measured values ​​must largely originate from offset components multiplied by the offset estimate of the inertial measurement sensors, which are thus also estimated and adjusted for future measured values ​​according to... x meas = x real + x offset t − x offsetsch ä tzung ≈ x real can be subtracted.

[0006] However, external influences, such as changes in the vehicle's position, for example due to changing pitch or roll angles, can invalidate these assumptions. Furthermore, it is not possible to reliably determine a yaw rate offset value using this method, as the vehicle could theoretically be in an infinite, stationary circular motion. Therefore, information from additional sensors, such as wheel speed sensors, must be used to obtain a reference value for the current yaw situation.

[0007] Due to the offset effect of gravity caused by the misalignment of the inertial measurement sensors relative to the vehicle's coordinate system, the offset error estimation already attempts to compensate for the effect of the sensor's installation position. Since the magnitude of gravity is known from the vehicle's position on Earth, excess acceleration components in a stationary situation are offset-related. However, because the offset can vary significantly for each sensor axis, a completely accurate gravity compensation, and therefore a precise offset determination, is not possible.

[0008] For more precise and comprehensive calibration of the respective inertial measurement sensors, a special measurement setup is required. This setup applies predefined accelerations and rotation rates to the inertial measurement sensors for offset calibration and provides a tared, horizontal surface for alignment calibration, where the acceleration directions of both gravity and the vehicle are defined within the vehicle coordinate system. This allows the inertial measurement sensors to be virtually rotated accordingly, but this process is very time-consuming and expensive.

[0009] From DE 10 2005 033 237 A1, a method for determining sensor misorientations of a vehicle sensor cluster is known. The sensor cluster comprises either three linear acceleration sensors or three yaw rate sensors. Desired installation directions of the sensors with respect to the coordinate axes of a vehicle-fixed Cartesian coordinate system are specified, whereby the actual installation directions of the sensors may deviate from the desired installation directions due to misorientations. By comparing values ​​measured by the sensors under different conditions with known values ​​in the vehicle-fixed Cartesian coordinate system for these different conditions, the actual installation directions of the sensors are determined.

[0010] From DE 10 2015 115 282 A1, a method for determining the orientation of an inertial measurement sensor of a vehicle with respect to a vehicle coordinate system is known, in which a first sensor signal of the inertial measurement sensor is acquired in a state of zero acceleration of the vehicle, in which a second sensor signal of the inertial measurement sensor is acquired in a linearly accelerated state of the vehicle, and in which the orientation is determined based on the first and second sensor signals. The first sensor signal is used to find a vertical orientation of the inertial measurement sensor based on the gravitational acceleration, and the second sensor signal is used to determine a rotation of the inertial measurement sensor about a vertical axis of the vehicle.

[0011] From DE 10 2004 045 890 A1, a method for calibrating an inertial measurement sensor of a vehicle is known, wherein the inertial measurement sensor is designed as a simple accelerometer for measuring the vertical acceleration of the vehicle. The method provides for determining the suspension state of the vehicle when the vehicle is stationary and storing it as a reference value. The suspension state of the vehicle is continuously determined during operation, and as soon as the measured suspension state corresponds to the suspension state stored as a reference value, the resting value of the simple accelerometer is set to a predetermined value.

[0012] A method for adjusting the low beam headlights of a vehicle is known from CN 1 08 819 831 A, wherein a headlight adjustment unit is provided which receives acceleration and angular velocity data from an inertial measurement sensor and receives vehicle information via a data bus. The headlight adjustment unit determines the vehicle's pitch angle from the received information and adjusts the illumination distance of the low beam headlights as a function of the pitch angle.

[0013] From WO 2017 / 129 199 A1 a method for determining a vehicle's tilting state with respect to a road surface is known, wherein the determination is carried out using a tilting model based on measured values ​​and wherein the measured values ​​are determined using inertial measurement sensors.

[0014] From US 2013 / 0 166 099 A1, a method for monitoring the condition of a vehicle is known, in which measured values ​​are recorded during driving operation of the vehicle using inertial measurement sensors and sampled over a period of time, and in which a rotation matrix is ​​determined on the basis of the measured values, which represents an offset between an orientation of the inertial measurement sensors and an actual orientation of the vehicle.

[0015] From EP 3 171 134 A1, a method for calibrating an inertial measurement sensor of a vehicle is known, wherein sensor data of the inertial measurement sensor are recorded at two stationary positions of the vehicle with different vehicle orientations, and wherein furthermore sensor data of the inertial measurement sensor are recorded during straight-line driving at constant speed, during a right-hand turn and during a left-hand turn, and wherein misalignments and offsets with respect to a vehicle coordinate system are determined on the basis of the recorded sensor data.

[0016] German patent DE 102017005019 A1 describes a lighting device for vehicles comprising at least one headlight, a position or acceleration sensor, and a control unit. The sensor detects pitching movements of the vehicle, and the control unit then compensates for the changes in the headlight's light-dark boundary caused by these movements.

[0017] Document US 20180154902 A1 describes vehicles, vehicle control systems, and methods for controlling a vehicle function. This involves measuring the vehicle's acceleration component. Additionally, the road gradient (slope / gradient) and / or the camber angle (i.e., the superelevation of the road) are determined. The vehicle function is then controlled based on the measured acceleration component and the road gradient or camber angle.

[0018] From US 2004 / 099044 A1 a method for determining the offset value of a longitudinal acceleration sensor installed in a vehicle is known.

[0019] The invention is based on the objective of providing a novel method for calibrating an inertial measurement sensor of a vehicle and a novel method for adjusting the headlight range of at least one headlight of a vehicle. This objective is achieved according to the invention by a method for calibrating an inertial measurement sensor of a vehicle, which has the features specified in claim 1, and by a method for adjusting the headlight range of at least one headlight of a vehicle, which has the features specified in claim 9.

[0020] Advantageous embodiments of the invention are the subject of the dependent claims.

[0021] In the inventive method for calibrating an inertial measurement sensor of a vehicle, the calibration is carried out during vehicle operation. The calibration is based on the determination of a misalignment of a sensor coordinate system of the inertial measurement sensor with respect to a vehicle coordinate system, wherein the determination of the misalignment is interrupted in situations in which a level deviation exceeding a predetermined threshold value compared to a reference level is detected by means of at least one vehicle-integrated level sensor.

[0022] In order for inertial measurement sensors based on acceleration sensors to provide a correct angle between the vehicle and a driving surface, such as a road surface, information about the installed inertial measurement sensor is required. Depending on the sensor package, its installation position on a circuit board, and the orientation of the corresponding control unit in the vehicle, different accelerations, such as rotational ones, are measured. These measurements must be internally rotated back to the orientation of the vehicle body, i.e., the vehicle coordinate system, using information from a previous calibration. Since the present method can differentiate between vehicle pitch angles and sensor installation rotations, both of which have an identical effect on measurements, it is possible to automate and perform the calibration of the inertial measurement sensor automatically.This eliminates the need for costly and time-consuming calibrations under controlled conditions, which require knowledge of either the vehicle pitch angles or sensor installation rotations and therefore cannot be performed in the field. This is particularly advantageous in the case of vehicle construction in a factory or sensor replacement, as such costly and time-consuming calibrations under controlled conditions are no longer necessary.

[0023] The present method significantly simplifies the calibration process by using the vehicle's own level sensor, which is installed, for example, on the rear axle, to control the calibration. Thus, after vehicle assembly or sensor replacement, a self-calibration procedure can be initiated. This procedure attempts to determine the installation position of the inertial measurement sensor relative to a body plane, i.e., relative to the vehicle coordinate system, during subsequent driving situations. A static rotation between the vehicle coordinate system, specifically a plane defined by a transverse and longitudinal axis of the vehicle, and the sensor coordinate system, specifically a plane defined by a transverse and longitudinal axis of the sensor, can then be calculated iteratively.

[0024] This method enables automated online calibration of inertial measurement sensors in a vehicle based on tangible and understandable criteria, preventing undefined scenarios, such as static pitch and / or roll angle changes, from influencing the calibration result. Depending on the configuration of the respective inertial measurement sensor system, for example, characterized by a number of measurement axes of an accelerometer and yaw rate sensor, various error components—that is, misorientations and offsets of the sensor coordinate system—can be calibrated. No additional hardware components are required, thus reducing material and cost expenditure as well as installation space requirements.

[0025] According to the procedure, map data from a digital road map is used to check whether there is a change in the slope of the road surface in a given section. Optical environmental sensors are used to verify that changes in the road surface profile do not exceed a predefined threshold in a given section. Inertial measurement sensors determine the vehicle's rotation in space, and a level sensor determines the vehicle's relative rotation to the road surface. If there is no change in the slope of the road surface and changes in the road surface profile do not exceed the predefined threshold, an offset of the inertial measurement sensor's yaw rate sensor is determined by comparing the rotation determined by the inertial measurement sensors with the relative rotation determined by the level sensor.This enables a particularly reliable and accurate determination of the offset of the rotation rate sensor of the inertial measurement sensor.

[0026] In one possible embodiment of the procedure, the calibration is carried out within a specified period during the vehicle's operation.

[0027] In one possible embodiment of the method, the misalignment of the sensor coordinate system relative to the vehicle coordinate system is determined using a static pitch angle calculated from the alignment of a longitudinal axis of the sensor coordinate system to a longitudinal axis of the vehicle coordinate system. Based on this static pitch angle, vehicle situations that significantly influence calibration errors can be identified simply and reliably, thus enabling their reliable elimination during calibration.

[0028] In another possible embodiment of the method, the vehicle coordinate system is defined such that a plane spanned by a transverse axis and a longitudinal axis of the vehicle runs parallel to a road surface plane under given normal conditions.

[0029] In another possible embodiment of the method, an acting gravitational acceleration is estimated based on a determined orientation of the sensor coordinate system, map data from a digital road map (in particular, geographical altitude and road gradient), and the vehicle's inclination relative to the road surface. During vehicle operation, a comparison is made between the acceleration measured by the inertial measurement sensor and the estimated gravitational acceleration at intervals without further acceleration. Based on the results of this comparison, an offset of the inertial measurement sensor relative to the acceleration measurement is determined. This enables a particularly reliable and precise determination of the inertial measurement sensor's offset relative to the acceleration measurement.

[0030] In another possible embodiment of the procedure, the calibration is based on the recording and evaluation of a large number of values ​​of longitudinal and lateral acceleration of the vehicle over a specified period and can therefore be carried out particularly easily and reliably.

[0031] In another possible embodiment of the procedure, long-term average values ​​are calculated from the recorded longitudinal and lateral acceleration values ​​of the vehicle, and the calibration is performed using these long-term average values. This represents a further simplification of the procedure.

[0032] In another possible embodiment of the procedure, the calibration is based on at least one learning algorithm and can therefore be automatically adapted to different situations of the vehicle and thus optimized.

[0033] In the inventive method for headlight range control of at least one headlight of a vehicle, an inertial measurement sensor is calibrated according to a previously described method, wherein the calibrated inertial measurement sensor determines the orientation of the vehicle relative to a road surface and regulates the headlight range depending on the determined orientation. The calibration of the inertial measurement sensor and its use in the headlight range control method enables compensation for changes in headlight range caused by vehicle acceleration.

[0034] Exemplary embodiments of the invention are explained in more detail below with reference to drawings.

[0035] This shows: Fig. 1 schematically shows a vehicle, a vehicle coordinate system, a sensor coordinate system and a driving surface with a surface coordinate system, and Fig. 2 schematically shows a learning process of a sensor installation angle.

[0036] Corresponding parts are marked with the same reference symbols in all figures.

[0037] In Figure 1 are represented as a vehicle 1, in particular a land vehicle, a Cartesian vehicle coordinate system, a Cartesian sensor coordinate system and a driving surface, in particular a driving surface plane E, with a Cartesian subsurface coordinate system.

[0038] The vehicle coordinate system is fixed to the body of vehicle 1 and has a transverse axis yv, a longitudinal axis xv, and a vertical axis zv. The origin of the vehicle coordinate system is located, in particular, at the center of gravity of vehicle 1. The vertical axis zv points upwards parallel to the normal vector of a cabin floor and cabin roof, the longitudinal axis xv points parallel to a longitudinal axis of the vehicle and perpendicular to the aforementioned normal vector, and the transverse axis yv points parallel to a transverse axis of the vehicle, also perpendicular to the aforementioned normal vector.

[0039] The subsurface coordinate system also has a transverse axis y E , a longitudinal axis x E and a vertical axis z E .

[0040] The sensor coordinate system is assigned to an inertial measurement sensor 2 of the vehicle 1 and also has a transverse axis y, a longitudinal axis x and a vertical axis z.

[0041] The misalignment of the inertial measurement sensor 2, which is used, for example, to operate an anti-lock braking system, a vehicle dynamics control system, and / or for other applications, results from a rotation of the sensor coordinate system relative to the vehicle coordinate system. The reasons for this include, for example, incorrect orientation of sensor axes within the sensor package of the inertial measurement sensor 2 by a sensor manufacturer, incorrect alignment on a control unit circuit board of the inertial measurement sensor 2, incorrect mounting in the control unit housing, or incorrect mounting of the inertial measurement sensor 2 housing to the vehicle body. In reality, all these components simultaneously contribute to the misalignment of the inertial measurement sensor 2 relative to the vehicle coordinate system.

[0042] The misalignment described by the rotation of the inertial measurement sensor 2 can be described by a sequence of three rotations Θ, Φ, Ψ, which can be considered as roll, pitch, and yaw angles. However, for various vehicle dynamics control systems and tasks, such as vehicle dynamics control, accelerations in the vehicle coordinate system are required to perform a correct calculation.

[0043] For reliable and accurate operation of the inertial measurement sensor 2, calibration is required. Error sources of the inertial measurement sensor 2 to be identified during calibration include, among others, misalignment of the sensor coordinate system relative to the vehicle coordinate system due to packaging, installation, and assembly; an offset of an accelerometer in the inertial measurement sensor 2; and an offset of a gyroscope in the inertial measurement sensor 2. This calibration makes it possible to rotate the inertial measurement sensor 2 back to the orientation of the vehicle 1, i.e., the orientation of the vehicle coordinate system.

[0044] It is assumed that all respective sensor axes of the inertial measurement sensor system 2 (transverse axis y, longitudinal axis x, vertical axis z) are perpendicular to each other and that the coordinate systems of a rotation rate sensor of the inertial measurement sensor system 2 and an acceleration sensor of the inertial measurement sensor system 2 are identical.

[0045] The present calibration concept involves, for example, an evaluation of acceleration directions occurring at vehicle 1. For a basic calibration, a baseline state of vehicle 1 is defined, which is to be used for the calibration. Specifically, this baseline state is characterized by an adult driver being present in vehicle 1 and a half-full fuel tank. Other situations involving heavy loads and passengers are detected by at least one level sensor installed on axle A1, A2 of vehicle 1 and, for example, by seat occupancy mats, and are excluded from the calibration.

[0046] This means that in the automated calibration of the inertial measurement sensor 2, rotational states of the vehicle 1 are detected with the aid of at least one level sensor (not shown in detail). In this process, misorientations and offsets of the sensor coordinate system of the inertial measurement sensor 2 are determined, and the calibration is performed during vehicle 1 operation for a predetermined period. During the calibration, misalignment of the sensor coordinate system relative to the vehicle coordinate system is detected. This misalignment detection is interrupted in situations during operation where the vehicle's own level sensor detects a level deviation exceeding a predetermined threshold relative to a reference level.

[0047] The misalignment of the sensor coordinate system with respect to the vehicle coordinate system is determined by means of an alignment of the longitudinal axis x of the sensor coordinate system to the longitudinal axis xv of the vehicle coordinate system and in Figure 2The static pitch angle α, as described in more detail, is determined. As previously explained, the vehicle coordinate system is defined such that its spanned plane, defined by the longitudinal axis xv and transverse axis yv, runs parallel to the road surface E under normal conditions, i.e., with a normal vehicle load. An actual static pitch angle α is therefore zero. The pitch angle α is measured in the sensor coordinate system. If the measured static pitch angle α is not zero, then the sensor coordinate system is rotated relative to the vehicle coordinate system. The measured static pitch angle α indicates by how many degrees the sensor coordinate system is rotated around the pitch axis relative to the vehicle coordinate system. The pitch angle α thus corresponds to the misalignment of the longitudinal axis x of the sensor coordinate system with respect to the longitudinal axis xv of the vehicle coordinate system.

[0048] Furthermore, the aforementioned information can be combined with highly accurate map data to obtain an estimate of the acting gravitational acceleration using the current geographic altitude, the gradient of the road surface, and the vehicle's inclination relative to this surface. This allows a comparison to be made, during periods without further acceleration, between the acceleration measured by the inertial measurement sensor 2 and the estimated gravitational acceleration, in order to determine the offset of the acceleration sensor of the inertial measurement sensor 2 according to: Measured acceleration = Gravitation + Vehicle acceleration + Inertial forces + Offset.

[0049] The time periods without further acceleration can be detected, for example, by wheel speed sensors and a wheel steering angle, assuming that at constant wheel speed there is no vehicle acceleration and then, if no wheel steering angle and no change in rotation are detected via level sensors, there are no inertial forces.

[0050] Furthermore, it is possible to compare a measured rotation of the vehicle body between the yaw rate sensor and the level sensor. It must be noted that the systems measure different types of rotation. The yaw rate sensor measures a complete rotation of the vehicle 1 in space, whereas the level sensor measures only a relative rotation to the road surface E.

[0051] Therefore, for calibration purposes, it must be ensured that the inclination of the road surface E remains constant and that the surface of the road surface E does not exhibit any significant profile changes, for example, due to speed bumps and / or potholes. Movements that meet these criteria are purely acceleration-induced, including braking-induced, pitch and roll movements of the vehicle 1. Using the high-precision map data, it can then be verified whether the inclination of the road surface E was constant in a given section. The flatness of the surface of the road surface E is checked using data from an optical environmental sensing sensor, such as a camera and / or lidar. Only when these conditions are met are the measured values ​​used for an offset calibration of the yaw rate sensor of the inertial measurement sensor 2.

[0052] Depending on the existing inertial measurement sensors 2, which are already present in the vehicle 1 for vehicle dynamics control and other driver assistance systems, costs can be minimized and a suitable combination can be selected depending on the desired accuracy and redundancy of the system.

[0053] In Figure 2 The figure shows the learning curve of a learned sensor installation angle, in particular a learned pitch angle α, as a function of a driving time t. Furthermore, areas B1 to Bn are shown, in which the values ​​of the level sensor are used according to the above description to interrupt the calibration and thus the learning process of the pitch angle α during the operation of vehicle 1.

[0054] This means that the calibration process is paused in situations with a changed chassis situation of vehicle 1, for example in the case of a large load and thus a static constant pitch angle α, which would otherwise be included in the calibration.

[0055] Other sources of error include, for example, vehicle tension during braking situations with the brakes applied or on steep inclines, which also lead to static pitch angles α. These situations can also be efficiently detected using information from the level sensor.

Claims

1. Method for calibrating an inertial measurement sensor system (2) of a vehicle (1), the calibration being carried out during a driving operation of the vehicle (2) and being based on determining a misalignment of a sensor coordinate system of the inertial measurement sensor system (2) with respect to a vehicle coordinate system, characterized in that determining misalignment is interrupted in situations in which, by means of at least one level sensor belonging to the vehicle, a level deviation exceeding a predetermined threshold is identified relative to a reference level, - a check being performed, based on map data from a digital road map, as to whether there is a change in the inclination of the driving surface plane (E) in a predetermined portion, and a check being performed as to whether using an optical environment-recording sensor system that profile changes of the driving surface plane (E) in a predetermined portion do not exceed a given threshold value, - a rotation of the vehicle (1) in space being determined by means of the inertial measurement sensor system (2), - a relative rotation of the vehicle (1) toward the driving surface plane (E) being determined by means of the level sensor and - an offset of a rotation rate sensor of the inertial measurement sensor system (2) then being determined, if there is no change in the inclination of the driving surface plane (E) and profile changes of the driving surface plane (E) do not exceed the predetermined threshold, by comparing the rotation determined by means of the inertial measurement sensor system (2) with the relative rotation determined by means of the level sensor.

2. Method according to claim 1, characterized in that the misalignment of the sensor coordinate system with respect to the vehicle coordinate system is determined based on a static pitch angle (α) determined from an alignment of a longitudinal axis (x) of the sensor coordinate system to a longitudinal axis (xv) of the vehicle coordinate system.

3. Method according to claim 1 or claim 2, characterized in that the vehicle coordinate system is defined such that a plane spanned by a lateral axis (yv) and a longitudinal axis (xv) of the vehicle (1) runs, under predetermined normal conditions, parallel to a driving surface plane (E).

4. Method according to any of the preceding claims, characterized in that - an acting gravitational acceleration is estimated based on a determined alignment of the sensor coordinate system, based on map data from a digital road map, in particular a geographical altitude and a road gradient, and based on an inclination of the vehicle (1) toward a driving surface plane (E), - during the driving operation of the vehicle (1) in time periods without further acceleration, a comparison is carried out between an acceleration measured by means of the inertial measurement sensor system (2) and the estimated gravitational acceleration, and - based on the results of the comparison, an offset of the inertial measurement sensor system (2) with respect to the acceleration measurement is determined.

5. Method according to any of the preceding claims, characterized in that the calibration is carried out during the driving operation of the vehicle (2) within a predetermined period of time.

6. Method according to claim 5, characterized in that the calibration is based on the recording and evaluation, carried out within a predetermined period of time, of a large number of values of longitudinal and lateral acceleration of the vehicle (1).

7. Method according to claim 6, characterized in that long-term mean values are formed from the recorded values of the longitudinal acceleration and lateral acceleration of the vehicle (1), and the calibration is carried out on the basis of these long-term mean values.

8. Method according to any of the preceding claims, characterized in that the calibration is based on at least one learning algorithm.

9. Method for adjusting the beam range of at least one headlight of a vehicle (1), wherein - an inertial measurement sensor system (2) is calibrated according to a method according to any of the preceding claims, - an alignment of the vehicle (1) relative to a driving surface plane (E) is determined by means of the calibrated inertial measurement sensor system (2), and - the beam range of the headlight is adjusted depending on the determined alignment.