Patent Application
20140371990
This application claims priority to German Patent Application Nos. 10 2011 082 534.7, filed Sep. 12, 2011, 10 2011 082 535.5, filed Sep. 12, 2011, 10 2011 082 539.8, filed Sep. 12, 2011, 10 2011 082 548.7, filed Sep. 12, 2011, 10 2011 082 549.5, filed Sep. 12, 2011, 10 2011 082 551.7, filed Sep. 12, 2011, 10 2011 082 552.5, 10 2011 086 710.4, filed Nov. 21, 2011, 10 2012 207 297.7, filed May 2, 2012 and International Patent Application No. PCT/EP2012/067878, filed Sep. 12, 2012.
The invention relates to a sensor system in accordance with the preamble of claim 1 and to the use thereof in motor vehicles, in particular in automobiles.
Laid-open specification DE 10 2010 063 984 A1 describes a sensor system, comprising a plurality of sensor elements and a signal processing device, wherein the signal processing device is configured in such a way that the output signals from the sensor elements are evaluated jointly.
The invention is based on the object of proposing a sensor system which provides or enables a relatively high degree of accuracy with respect to its signal processing.
This object is achieved by the sensor system described herein.
Expediently, the sensor system is arranged in a vehicle, in particular a motor vehicle, particularly preferably an automobile.
It is preferable for the first, the second and the third defined axes to form a generating system, and in the process to be in particular oriented perpendicular to one another.
Preferably, the vehicle model unit is designed in such a way that it uses a least-squared-error method for solving an overdetermined system of equations for the calculation.
It is preferable for in each case one of the wheel rotation speed sensor elements to be assigned to each wheel of the vehicle, wherein the vehicle model unit is designed in such a way that, from the sensor signals of the wheel rotation speed sensor elements and the steering angle, provided by the steering angle sensor unit, and/or the steering angle of each wheel, in particular detected by the at least one steering angle sensor element for one or in each case for the plurality of steered/steerable axles and/or by at least one model assumption for one or more unsteered/unsteerable axles, it calculates, directly or indirectly, the velocity components and/or the velocity of each wheel along/with respect to the first and second defined axes, wherein, from these velocity components, in relation to the respective wheels and/or the velocities in each case with respect to the first and second defined axes of the associated wheels, the speed along a first defined axis, the speed along a second defined axis and the rotation rate about a third defined axis are calculated.
It is expedient for the sensor system to have four wheel rotation speed sensor elements, wherein in each case one of the wheel rotation speed sensor elements is assigned to each wheel of the vehicle, wherein the vehicle model unit is designed in such a way that, from the sensor signals of the wheel rotation speed sensor elements and the steering angle, provided by the steering angle sensor unit, and/or the steering angle of each wheel, in particular detected by the steering angle sensor element for the front wheels and from a model assumption or at least by means of a further steering angle sensor element for the rear wheels, it calculates, directly or indirectly, the velocity components and/or the velocity of each wheel along/with respect to the first and second defined axes, wherein, from these eight velocity components and/or the four velocities, in each case with respect to the first and second defined axes, the velocity along a first defined axis, the velocity along a second defined axis and the rotation rate about a third defined axis are calculated.
It is preferable for the steering angle of each wheel to be determined or calculated from a steering wheel angle sensor element, i.e. a sensor element which detects the steering angle desired by the driver, and from information relating to the steering ratio characteristic, which is in particular stored in the vehicle model unit or in another part of the signal processing device.
It is expedient for the vehicle model unit to be designed in such a way that, in its calculation, it takes into consideration at least the following physical variables and/or parameters
a) the steering angle of each wheel, in particular detected by the steering angle sensor for the two front wheels, wherein the model assumption is applied whereby the steering angle of the rear wheels is known, in particular the steering angle of the rear wheels is equal to zero or the steering angle of the rear wheels is additionally detected,
b) the wheel rotation speed or a variable dependent thereon of each wheel,
c) the direction of rotation of each wheel,
d) the dynamic radius and/or wheel diameter of each wheel or a variable derived therefrom as parameter, which is in particular taken into consideration or estimated and/or calculated as the constant value which is known to the model, and
e) the track width of each axle of the vehicle and/or the wheelbase between the axles of the vehicle.
Particularly preferably, the vehicle model unit is designed in such a way that, in its calculation, it takes into consideration at least one of the following physical variables and/or parameters
f) the slip angle of each wheel, in particular calculated from the transverse acceleration, i.e. the acceleration in the direction of the second defined axis, and/or
g) the wheel slip, in particular calculated from wheel forces and/or accelerations of each wheel.
It is preferable for the signal processing device to comprise a tire parameter estimation unit, which is designed in such a way that it calculates and/or estimates at least the radius, in particular the dynamic radius, of each wheel or a variable dependent thereon or derived therefrom and provides this to the vehicle model unit as additional input variable.
Particularly preferably, the tire parameter estimation unit is designed in such a way that it additionally calculates and/or estimates the cornering stiffness, and the slip stiffness or longitudinal slip stiffness of each wheel or a variable dependent thereon or derived therefrom and provides it to the vehicle model unit as additional input variable, wherein the tire parameter estimation unit is designed in such a way that it uses in particular a substantially linear tire model for the calculation of the wheel/tire variables.
Expediently, the tire parameter estimation unit is designed in such a way that it receives the wheel rotation speeds and the steering angle as input variables, at least partially or completely the output variables or values of the strapdown algorithm unit, in particular the variances provided thereby in addition to the values of the physical variables, and the variances of the fusion filter, with respect to the physical variables which are the input variables of the tire parameter estimation unit.
It is preferable for the vehicle model unit to be designed in such a way that, for each of its three calculated variables, namely the velocity along a first defined axis, the velocity along a second defined axis, and the rotation rate about a third defined axis, it calculates information relating to the data quality and provides this as additional output variable, in particular in each case a variance.
It is expedient for the vehicle model unit is designed in such a way that it evaluates the validity of its own output variables on the basis of the calculated variances and in the process in particular takes into consideration the respective variance of the velocity along the first and along the second defined axis and of the rotation rate about the third defined axis in the evaluation of the validity of its own output variables.
Particularly preferably, the vehicle model unit is designed in such a way that it checks the respective variance of its three output variables with respect to a or in each case one defined limit value being overshot, wherein, in the event of one or more of the variances being overshot, no validity of the present output variables of the vehicle model unit is provided.
It is preferable for the vehicle model unit and/or the tire parameter estimation unit to be designed in such a way that they comprise at least one linearization. This linearization is in particular only carried out or has the boundary parameter that the total acceleration of the vehicle, that is to say the acceleration relative to all three defined axes, is less than 5 m/s2 in terms of magnitude.
It is expedient for the first, second and third defined axes to be defined in relation to a coordinate system of the vehicle in which the sensor system is implemented, as follows:
the first defined axis corresponds to the longitudinal axis of the vehicle,
the second defined axis corresponds to the transverse axis of the vehicle, and
the third defined axis corresponds to the vertical axis of the vehicle. These three axes form in particular a Cartesian coordinate system, in particular a vehicle coordinate system.
It is preferable for the vehicle model unit to be designed in such a way that it carries out or supports a direct or indirect measurement of the wheel loads and/or wheel contact forces and at least provides this variable as output variable.
It is expedient for the vehicle model unit to be designed in such a way that it comprises the modeling of a wheel suspension, with regard to a kinematic and/or dynamic model, as a result of which, taking into consideration this modeling, a steering angle is or can be calculated with increased accuracy. Said steering angle relates, in particular, to the steering angle of each wheel, which is used in each case for the further calculation of the output variables of the vehicle model unit.
The steering angle of the rear wheels is expediently detected by means of at least one additional rear wheel steering angle sensor element. In particular additionally or alternatively preferably the actuator system of a rear axle steering system provides the steering angle of the wheels of the rear axle.
The signal processing device of the sensor system additionally preferably comprises a fusion filter. The fusion filter provides a defined fusion data set in the course of the joint evaluation of at least the sensor signals and/or signals derived therefrom of the sensor elements, that is to say of the odometry, and in particular additionally of the output signals of a satellite navigation system and/or signals derived therefrom. Said fusion data set has in each case data with respect to defined physical variables, wherein the fusion data set comprises, with respect to at least one physical variable, a value of said physical variable and information about the data quality thereof, wherein this information about the data quality is expressed as variance in accordance with the example.
Preferably, the fusion data set comprises, as the value of the at least one physical variable, a relative value, for example a correction value, also referred to as offset value or change value or error value.
The relative values of the respective physical variables of the fusion data set are therefore expediently correction values and variances.
The values of the physical variables of the fusion data set are preferably calculated on a direct or indirect basis of the sensor signals of the sensor elements and the satellite navigation system, wherein at least some variables, for example the velocity and the position of the vehicle in relation to the vehicle coordinates, are detected and computed with redundancy.
The fusion filter is expediently designed as an error state space extended sequential Kalman filter, that is to say as a Kalman filter which comprises, in particular a linearization, and in which the correction values are calculated and/or estimated and which operates sequentially and in this case uses/takes into consideration the input data available in the respective function step of the sequence.
The vehicle model unit provides its output variables or output data, that is to say at least the velocity along a first defined axis, the velocity along a second defined axis and the rate of rotation about a third defined axis, preferably to the fusion filter, which takes into consideration or uses said output variables or output data of the vehicle model unit in its calculations, that is to say the calculations of the fusion filter.
The dynamic radius of each wheel or the dynamic tire radius rdyn is preferably defined as follows: effectively covered distance during a tire revolution. The latter does not correspond to the radius of the tire, since the radius of the tire effectively decreases as a result of spring deflection under load. Influencing variables that can alter the tire radius including during a journey are, for example, traveling velocity, air pressure and temperature.
The variable referred to as longitudinal slip λ is expediently defined as follows: under the influence of longitudinal force, a slip movement arises as a result of the deformation of the tread elements of the tire, without taking into consideration the tire sliding on the road. Said slip movement has the consequence that the tire, depending on the longitudinal force, rotates faster or more slowly than would be expected over the tire radius. The extent to which this effect is manifested is influenced principally by the rubber mix and the type of tire and is characterized by the longitudinal slip stiffness:
Skew running or the slip angle α is preferably defined as follows: in a manner similar to that in the case of longitudinal slip, lateral forces, perpendicular to the rolling direction, cause a sideways movement of the tire as a result of the rubber elasticity. This relationship is characterized by the cornering stiffness:
In order to compensate for these disturbance variables, the vehicle model unit preferably makes recourse to a linear tire model of the tire parameter estimation unit or includes it in the calculations. Said model is restricted in particular to accelerations or total accelerations of the vehicle
In this range, it is particularly preferably assumed, in particular as a model assumption for the calculation, that the relationship between longitudinal slip and skew running and the associated forces is linear, and that the forces that can be transmitted rise linearly with the contact force FR or normal force on the tire. By canceling the vehicle mass, this allows a normalization of the variables to accelerations. In this case, the vehicle masses and accelerations are expediently related to individual wheels, but assumed to be randomly distributed:
In this case, the following preferably hold true:
Δφwheel: Angle of rotation of the wheel measured from wheel ticks
Sx,absolute,tire: Distance actually covered over the road
g: Acceleration due to gravity
The following preferably ensue therefrom for the distances covered:
In this case, the following preferably hold true:
λa: Drive slip during acceleration
λa: Braking slip during deceleration
According to the example, therefore, it is the case that the slip variable that is respectively not applicable in the traveling situation=0.
Since the accelerations used are known from the navigation calculation, the actual planar movement of the vehicle over the roadway can be estimated in a model-based manner preferably given a known tire radius and known cornering and longitudinal slip stiffness. A possible skew of tire coordinates relative to the vehicle coordinates is expediently taken into consideration by means of the measured steering wheel angle and the known steering ratio. The distances and velocities of the individual wheels are preferably calculated as follows in the vehicle model unit:
calculation of accelerations and rates of rotation at the center of gravity of the vehicle
transformation to tire coordinates
calculation of the velocities/distances using the tire model and the wheel angular momenta or wheel rotation speeds
inverse transformation into vehicle coordinates.
Preferably, two measured variables (ΔXwheel, γYwheel in vehicle coordinates) per wheel, that is to say a total of eight measurement values, are available after the conclusion of these steps.
It is preferable for the tire parameter estimation unit to be designed in such a way that it carries out a method for estimating tire parameters for a vehicle, comprising the following steps:
measuring a reference movement of the vehicle;
modeling a model movement of the vehicle on the basis of a model freed of the tire parameters to be estimated; and
estimating the tire parameters of the vehicle on the basis of a comparison of the reference movement and the model movement.
The method comprises in particular additionally the following step:
detecting the real velocity of the vehicle at wheel contact points of the vehicle.
It is preferred for the method to comprise the following step:
establishing the model freed of the tire parameters to be estimated on the basis of approximated tire parameters, and in particular the following further step:
using the estimated tire parameters as approximated tire parameters in the model, for estimating new tire parameters.
The method expediently comprises the following steps:
detecting a variance of the reference movement, and
estimating the tire parameters of the vehicle on the basis of the detected variance.
The method is preferably developed by the estimated tire parameters of the vehicle being regarded as valid if the reference movement and/or the model movement exceed(s) a specific value.
The method expediently comprises the following step:
comparing the reference movement and the model movement on the basis of an observer.
With regard to the method in the tire parameter estimation unit the observer preferably a Kalman filter.
It is preferable for the signal processing device to have a fusion filter, which provides a defined fusion data set in the course of the joint evaluation of at least the sensor signals and/or signals derived therefrom of the sensor elements, wherein said fusion data set has in each case data with respect to defined physical variables, wherein the fusion data set comprises, with respect to at least one physical variable, a value of said physical variable and information about the data quality thereof.
The fusion filter is preferably in the form of a Kalman filter, alternatively preferably a particle filter or alternatively an information filter or alternatively in the form of an “unscented” Kalman filter.
It is preferable for the fusion filter to be designed in such a way that the fusion data set comprises, as value of the at least one physical variable, a relative value, in particular an offset value and/or change value and/or correction value and/or error value.
It is expedient for the relative values of the respective physical variables of the fusion data set to be correction values, to each of which scattering information or scattering or scattering degree, in particular a variance, is assigned as information relating to the data quality of said correction values.
It is preferable for the fusion filter to be designed in such a way that the value of at least one physical variable of the fusion data set is calculated on a direct or indirect basis from sensor signals from a plurality of sensor elements, wherein these sensor elements detect this at least one physical variable in a direct or indirect manner, with redundancy. This redundant detection is particularly preferably implemented as direct or parallel redundancy and/or as analytical redundancy, from computationally derived or deduced variables/values and/or model assumptions.
The fusion filter is preferably in the form of a Kalman filter which iteratively implements at least prediction steps and correction steps and at least partially provides the fusion data set. In particular, the fusion filter is in the form of an error state space extended sequential Kalman filter, i.e. in the form of a Kalman filter which particularly preferably comprises linearization and in which error state information is calculated and/or estimated and/or which operates sequentially and in the process uses/takes into consideration the input data available in the respective function step of the sequence.
It is expedient for the sensor system to have an inertial sensor arrangement, comprising at least one acceleration sensor element and at least one rotation rate sensor element, and for the sensor system to comprise a strapdown algorithm unit, in which a strapdown algorithm is implemented, with which at least the sensor signals of the inertial sensor arrangement relating to in particular corrected navigation data and/or driving dynamics data are processed, on the basis of the vehicle in which the sensor system is arranged.
It is particularly preferable for the strapdown algorithm unit to provide its calculated navigation data and/or driving dynamics data to the fusion filter directly or indirectly.
The sensor system preferably has an inertial sensor arrangement, which is designed in such a way that it can detect at least the acceleration along a second defined axis, in particular the transverse axis of the vehicle, and at least the rotation rate about a third defined axis, in particular the vertical axis of the vehicle, wherein the first and third defined axes form a generating system, and in the process are in particular oriented perpendicular to one another, wherein the sensor system also has at least one wheel rotation speed sensor element, in particular at least or precisely four wheel rotation speed sensor elements, which detect the wheel rotation speed of a wheel or the wheel rotation speeds of in each case one of the wheels of the vehicle and in particular additionally detect the direction of rotation of the assigned wheel of the vehicle in which the sensor system is arranged,
wherein the sensor system additionally comprises at least one steering angle sensor element, which detects the steering angle of the vehicle, and
wherein the sensor system furthermore comprises a satellite navigation system, which is designed in particular in such a way that it detects and/or provides the distance data in each case between the assigned satellite and the vehicle or a variable dependent thereon and velocity information data in each case between the assigned satellite and the vehicle or a variable dependent thereon.
Particularly preferably, the inertial sensor arrangement is designed in such a way that it can detect at least the accelerations along a first, a second and a third defined axis and at least the rotation rates about these first, second and third defined axes, wherein these first, second and third defined axes form a generating system, and in the process are in particular in each case oriented perpendicular to one another.
It is preferable for the inertial sensor arrangement to provide its sensor signals to the strapdown algorithm unit and for the strapdown algorithm unit to be designed in such a way that it at least calculates and/or provides
at least corrected accelerations along the first, the second and the third defined axes,
at least corrected rotation rates about these three defined axes,
at least a velocity with respect to these three defined axes,
and at least one position variable,
as measured variables and/or navigation data and/or driving dynamics data
from the sensor signals of the inertial sensor arrangement and in particular at least fault state information and/or variance and/or information on the data quality which is assigned to a sensor signal or a physical variable and is provided by the fusion filter.
It is expedient for the sensor system to be designed in such a way that in each case at least one sensor signal and/or a physical variable, as direct or derived variable
of the inertial sensor arrangement and/or the strapdown algorithm unit,
of the wheel rotation speed sensor elements and the steering angle sensor element, in particular indirectly via a vehicle model unit,
and of the satellite navigation system, in this case in particular distance data in each case between the assigned satellite and the vehicle or a variable dependent thereon and velocity information data in each case between the assigned satellite and the vehicle or a variable dependent thereon,
are provided to the fusion filter and taken into consideration by the fusion filter in the calculations it performs.
It is particularly preferable for the vehicle model unit to be designed in such a way that
the speed along the first defined axis,
the speed along the second defined axis
and the rotation rate about the third defined axis
are calculated from the sensor signals of the wheel rotation speed sensor elements and the steering angle sensor element.
It is very particularly preferable for the vehicle model unit to be designed in such a way that, for the calculation, a least-squared-error method is used for solving an overdetermined system of equations.
It is expedient for the vehicle model unit to be designed in such a way that, in its calculation, it takes into consideration at least the following physical variables and/or parameters
a) the steering angle of each wheel, in particular detected by the steering angle sensor for the two front wheels, wherein the model assumption whereby the steering angle of the rear wheels is equal to zero or the steering angle of the rear wheels is additionally detected is used,
b) the wheel rotation speed or a variable dependent thereon for each wheel,
c) the rotation direction of each wheel,
d) the dynamic radius and/or wheel diameter of each wheel, and
e) the track width of each axle of the vehicle and/or the wheelbase between the axles of the vehicle.
The signal processing device is preferably designed in such a way that the fusion filter calculates and/or provides and/or outputs the fusion data set at defined times.
The fusion filter is preferably designed in such a way that it calculates and/or provides and/or outputs the fusion data set independently of the sampling rates and/or sensor signal output times of the sensor elements, in particular the wheel rotation speed sensor elements and the steering angle sensor element, and independently of temporal signal or measured variable or information output times of the satellite navigation system.
It is expedient for the signal processing device to be designed in such a way that, over the course of a function step of the fusion filter, the newest information and/or signals and/or data available to the fusion filter
of the sensor elements, in particular of the wheel rotation speed sensor elements and the steering angle sensor element, are always updated, in particular asynchronously, directly or indirectly, in particular by means of the vehicle model unit and the satellite navigation system directly or indirectly, sequentially and/or are recorded by the fusion filter and taken into consideration in the calculation of the assigned function step of the fusion filter.
It is preferable for the sensor system to have a standstill identification unit, which is designed in such a way that it can identify a standstill of the vehicle and, in the event of an identified standstill of the vehicle, provides information from a standstill model at least to the fusion filter, in this case in particular the information that the rotation rates about all of the three axes have the value zero and at least one position change variable likewise has the value zero and in particular the velocities along all three axes have the value zero.
It is preferable for the signal processing device to calculate and/or use a first group of data of physical variables, whose values relate to a vehicle coordinate system, and wherein the signal processing device additionally calculates and/or uses a second group of data of physical variables, whose values relate to a world coordinate system, wherein this world coordinate system is suitable in particular at least for describing the orientation and/or dynamic variables of the vehicle in the world, wherein
the sensor system has an orientation model unit,
with which the orientation angle between the vehicle coordinate system and the world coordinate system is calculated, wherein
the orientation angle between the vehicle coordinate system and the world coordinate system is calculated in the orientation model unit at least on the basis of the following variables:
the velocity with respect to the vehicle coordinate system,
the velocity with respect to the world coordinate system and in particular the steering angles.
It is expedient for the following terms to be used synonymously, i.e. have the same meaning when implemented technically: offset value, change value, correction value and error value.
Error state information is preferably understood to mean error information and/or error correction information and/or scattering information and/or variance information and/or accuracy information.
The term variance is preferably understood to mean scatter, wherein in particular in the case of a general fusion filter, said filter in each case assigns scatter or a scatter value to each value of a physical variable of the fusion filter, and in the case of a Kalman filter as the fusion filter, in each case a variance is assigned to each value of a physical variable of the fusion filter.
It is expedient for the first, second and third defined axes on the basis of a coordinate system of the vehicle in which the sensor system is implemented to be defined as follows: the first defined axis corresponds to the longitudinal axis of the vehicle, the second defined axis corresponds to the transverse axis of the vehicle, and the third defined axis corresponds to the vertical axis of the vehicle. These three axes in particular form a Cartesian coordinate system.
It is preferable for the fusion filter to be designed in such a way that its data, in particular the physical variables or the data of the physical variables of the fusion data set, are divided into blocks which always have a constant size and which are processed iteratively in any desired order in the fusion filter, i.e. the fusion filter implements a sequential update with respect to its input data. In this case, the fusion filter is particularly preferably designed in such a way that the filter equations are matched, with the result that the computational result of the sequential update in each step of the fusion filter is an update, i.e. a data update, for all measured variables of the input data of the fusion filter.
The sensor system is expediently arranged in a vehicle, in particular in a motor vehicle, particularly preferably in an automobile.
The sensor system is preferably designed in such a way that data of the satellite navigation system, in particular position data, are assigned timestamp information, which substantially describes the measurement time of these data. The timestamp information of the respective datum of the satellite navigation system is provided together with this respective datum to the fusion filter and taken into consideration in the internal calculation in the fusion filter.
Preferably, in addition such timestamp information is likewise assigned to the data of further or all of the sensor elements and/or the inertial sensor arrangement, which timestamp information is likewise provided with the respective datum to the fusion filter and is taken into consideration in the internal calculation in the fusion filter. Expediently, the respective timestamp information is generated by the satellite navigation system itself with respect to the data of the satellite navigation system.
It is preferable for the respective timestamp information to be generated by the signal processing device in the case of the additional timestamp information of the further sensor elements and/or the inertial sensor arrangement, in particular depending on the time measurement of the satellite navigation system.
Preferably, a function step of the fusion filter comprises at least one prediction step and a correction step. The fusion filter is in this case formed iteratively and performs iteratively, one after the other, function steps. In particular, data or values or signals are input within each function step of the fusion filter, i.e. input data are taken into consideration, i.e. data or values or signals are also output, i.e. provided as output data.
The fusion filter is preferably designed in such a way that the fusion filter implements a plurality of update steps within a function step, wherein these update steps relate to loading or use or updating of input data or signals. The fusion filter runs in particular sequentially through all of the input variables or input signals and checks in each case whether new information/data are present. If this is the case, this information or data is transferred into the filter or the information/data are updated in the filter, and if this is not the case the present value is maintained and the filter checks the next input or the next input variable or the next input signal.
The strapdown algorithm unit preferably provides at least absolute values of physical variables, in particular absolute values for the acceleration, the rotation rate, the velocity, in this case in each case in relation to the three axes, to the vehicle and/or world coordinate system, and a position and the orientation angle. The values with respect to these variables are in this case particularly preferably all provided by the strapdown algorithm unit as corrected values/variables.
It is expedient for the inertial sensor arrangement to clock and/or trigger the fusion filter, in particular each fusion step which is implemented by the fusion filter is triggered by the inertial sensor arrangement or at least one output signal or output datum.
It is preferable for the strapdown algorithm unit to be designed in such a way that it has a start vector of physical variables and/or a start value of the position, in particular with respect to the start of the sensor system, particularly preferably after each time the sensor system is switched on. The strapdown algorithm unit particularly preferably receives this start vector and/or this start position via the fusion filter from the satellite navigation system.
It is expedient for the data of the fusion filter, in particular the fusion data set thereof, to image a virtual sensor or correspond to such a virtual sensor.
The term sensor elements is preferably understood to mean the wheel rotation speed sensor elements, the at least one steering angle sensor element, the sensor elements of the inertial sensor arrangement and in particular additionally also the satellite navigation system.
If, in general, a variable and/or value is specified in respect of the three defined axes, it is preferable for this to be intended with respect to the vehicle coordinate system and/or the world coordinate system.
It is expedient for the fusion data set, which comprises values of the physical variables, to comprise a relative value, for example a correction value, also referred to as offset value, and in particular to be provided to the strapdown algorithm unit. In accordance with the example, this respective correction value results in each case from the accumulated error values or change values which are provided by the fusion filter.
In addition, the invention relates to the use of the sensor system in vehicles, in particular motor vehicles, particularly preferably in automobiles.
Further preferred embodiments result from the description below relating to an exemplary embodiment with reference to
The sensor system comprises an inertial sensor arrangement 1, IMU, “inertial measurement unit”, which is designed in such a way that it can detect at least the accelerations along a first, a second and a third defined axis and at least the rotation rates about these first, second and third defined axes, wherein the first defined axis corresponds to the longitudinal axis of the vehicle, the second defined axis corresponds to the transverse axis of the vehicle, and the third defined axis corresponds to the vertical axis of the vehicle. These three axes form a Cartesian coordinate system, the vehicle coordinate system.
The sensor system has a strapdown algorithm unit 2, in which a strapdown algorithm is implemented, with which at least the sensor signals of the inertial sensor arrangement 1 are processed to give corrected navigation data and/or driving dynamics data. These output data of the strapdown algorithm unit 2 include the data of the following physical variables:
the velocity, the acceleration and the rotation rate in each case of the vehicle, by way of example with respect to the three axes of the vehicle coordinate system and, in accordance with the example, additionally in each case in relation to a world coordinate system, which is suitable for describing the orientation and/or dynamic variables of the vehicle in the world. In addition, the output data of the strapdown algorithm unit 2 comprise the position with respect to the vehicle coordinate system and the orientation with respect to the world coordinate system. In addition, the output data of the strapdown algorithm unit have the variances as information on the data quality of the abovementioned physical variables, at least some of said variables. These variances, in accordance with the example, are not calculated in the strapdown algorithm unit, but are only used and passed on by said strapdown algorithm unit.
The output data of the strapdown algorithm unit are additionally, by way of example, the output data or signals 12 of the entire sensor system.
The sensor system additionally comprises wheel rotation speed sensor elements 3 for each wheel of the vehicle, in accordance with example four, which detect the wheel rotation speeds of in each case one of the wheels of the vehicle and in each case additionally detect the direction of rotation, and additionally a steering angle sensor element 3, which detects the steering angle of the vehicle. The wheel rotation speed sensor element and the steering angle sensor element form a sensor arrangement 3 for odometry detection.
Furthermore, the sensor system has a satellite navigation system 4, which is designed in such a way that it detects and/or provides the distance data in each case between the assigned satellite and the vehicle or a variable dependent thereon and velocity information data in each case between the assigned satellite and the vehicle or a variable dependent thereon. In addition, the satellite navigation system 4, in accordance with the example, provides a start position or start position information, at least for starting or switching on the sensor system, to the fusion filter.
The signal processing device of the sensor system also comprises a fusion filter 5. The fusion filter 5 provides a defined fusion data set 6 over the course of the joint evaluation of at least the sensor signals and/or signals derived therefrom of the sensor elements 3, i.e. the odometry, and the output signals of the satellite navigation system 4 and/or signals derived therefrom. This fusion data set has in each case data with respect to defined physical variables, wherein the fusion data set 6 with respect to at least one physical variable comprises a value of this physical variable and information on its data quality, wherein this information on the data quality is expressed as variance, in accordance with the example.
The fusion data set 6 comprises, as value of the at least one physical variable, a relative value, for example a correction value, also referred to as offset value. In accordance with the example, the correction value results in each case from the accumulated error values or change values which are provided by the fusion filter 5.
The relative values of the respective physical variables of the fusion data set 6 are therefore correction values and variances, in accordance with the example. In other words, the fusion data set 6, in accordance with the example, calculates an error budget, which is provided as input variable or input data set to the strapdown algorithm unit and is taken into consideration at least partially by said strapdown algorithm unit in its calculations. This error budget comprises, as data set or output data, at least correction values or error values of physical variables and in each case a variance, as information on the data quality, with respect to each value. In this case, at least the correction values and variances with respect to the physical variables velocity, acceleration and rotation rate, in each case in relation to the vehicle coordinate system, i.e. in each case the three components of these variables with respect to this coordinate system, and IMU orientation or the IMU orientation angle between the vehicle coordinate system and the coordinate system or the installation orientation of the inertial sensor arrangement 1 and the position in relation to the world coordinate system are transmitted by the fusion filter to the strapdown algorithm unit.
The values of the physical variables of the fusion data set are calculated on a direct or indirect basis of the sensor signals of the sensor elements 3 and the satellite navigation system 4, wherein at least some variables, for example the velocity and the position of the vehicle with respect to the vehicle coordinates, are detected and used with redundancy with respect to the data of the strapdown algorithm unit 2.
The fusion filter 5 is, in accordance with the example, in the form of an error state space extended sequential Kalman filter, i.e. in the form of a Kalman filter which comprises in particular linearization and in which the correction values are calculated and/or estimated and which operates sequentially and in the process uses/takes into consideration the input data available in the respective function step of the sequence.
The fusion filter 5 is designed in such a way that, over the course of a function step of the fusion filter, the newest information and/or signals and/or data available to the fusion filter
of the sensor elements 3, i.e. the wheel rotation speed sensor elements and the steering angle sensor element indirectly by means of a vehicle model unit 7 and
of the satellite navigation system 4 directly or indirectly
are always sequentially updated, asynchronously, and/or recorded in the fusion filter and taken into consideration in the calculation of the assigned function step of the fusion filter 5.
The vehicle model unit 7 is designed in such a way that it calculates, from the sensor signals of the wheel rotation speed sensor elements 3 and the steering angle sensor element 3, at least
the velocity along a first defined axis,
the velocity along a second defined axis, and
the rotation rate about a third defined axis
and provides these to the fusion filter 5.
The sensor system has, in accordance with the example, four wheel rotation speed sensor elements 3, wherein in each case one of the wheel rotation speed sensor elements is assigned to each wheel of the vehicle, wherein the vehicle model unit 7 is designed in such a way that it calculates, from the sensor signals of the wheel rotation speed sensor elements and the steering angle, provided by the steering angle sensor unit, and/or the steering angle of each wheel, in particular detected by the steering angle sensor element for the front wheels and by means of at least one further steering angle sensor element for the rear wheels or at least from a model assumption for the rear wheels,
the velocity components and/or the velocity of each wheel, along/with respect to the first and second defined axes directly or indirectly,
wherein, from these eight velocity components and/or the four velocities, in each case with respect to the first and second defined axes,
the velocity along a first defined axis,
the velocity along a second defined axis, and
the rotation rate about a third defined axis
are calculated.
The sensor system or the signal processing device of said sensor system also comprises a tire parameter estimation unit 10, which is designed in such a way that it calculates at least the radius, in accordance with the example the dynamic radius, of each wheel and additionally calculates the cornering stiffness and the slip stiffness of each wheel and provides these to the vehicle model unit 7 as additional input variables, wherein the tire parameter estimation unit 10 is designed in such a way that it uses a substantially linear tire model for calculating the wheel/tire variables. The input variables of the tire parameter estimation unit in accordance with the example are in this case the wheel rotation speeds 3 and the steering angle 3, at least partially or completely the output variables or values of the strapdown algorithm unit 2, in particular the variances provided thereby in addition to the values of the physical variables, and the variances of the fusion filter 5, with respect to the physical variables which are the input variables of the tire parameter estimation unit 10.
The sensor system or its signal processing device also comprises a GPS error identification and plausibilization unit 11, which is designed in such a way that, in accordance with the example, it receives, as input data, the output data or output signals of the satellite navigation system 4 and at least partially the output data or output signals of the strapdown algorithm unit 2 and takes these into consideration in its calculations.
In this case, the GPS error identification and plausibilization unit 11 is additionally connected to the fusion filter 5 and exchanges data therewith.
The GPS error identification and plausibilization unit 11 is designed, by way of example, in such a way that it implements the following method:
measuring measurement position data of the vehicle with respect to the satellite on the basis of the GNSS signal, i.e. the global navigation satellite system signal, the output signal or the output data of the satellite navigation system 4,
determining reference position data of the vehicle which are redundant with respect to the measurement position data determined on the basis of the GNSS signal; and
selecting the satellite when a comparison of the measurement position data and the reference position data satisfies a predetermined condition,
wherein, in order to compare the measurement position data and the reference position data, a difference between the measurement position data and the reference position data is formed,
wherein the predetermined condition is a maximum permissible error between the measurement position data and the reference position data,
wherein the maximum permissible error is dependent on a standard deviation, which is calculated on the basis of a sum of a reference variance for the reference position data and a measurement variance for the measurement position data,
wherein the maximum permissible error corresponds to a multiple of the standard deviation such that a probability that the measurement position data fall below a predetermined threshold value in a scatter interval which is dependent on the standard deviation.
The sensor system or its signal processing device also has a standstill identification unit 8, which is designed in such a way that it can identify a standstill of the vehicle and, in the event of an identified standstill of the vehicle, provides information from a standstill model at least to the fusion filter 5, in this case in particular the information that the rotation rates about all three axes have the value zero and at least one position change variable likewise has the value zero and in particular the velocities along all three axes have the value zero. The standstill identification unit 8 is in this case designed, in accordance with the example, in such a way that it uses the wheel rotation speeds or wheel rotation speed signals as input data and the “raw” or direct output signals of the inertial sensor arrangement 1.
The signal processing device calculates and/or uses, in accordance with the example, a first group of data of physical variables, whose values relate to a vehicle coordinate system and in addition calculates and/or uses a second group of data of physical variables, whose values relate to a world coordinate system, wherein this world coordinate system is suitable in particular at least for describing the orientation and/or dynamic variables of the vehicle in the world, wherein the sensor system has an orientation model unit 9, with which the orientation angle between the vehicle coordinate system and the world coordinate system is calculated.
The orientation angle between the vehicle coordinate system and the world coordinate system in the orientation model unit 9 is calculated at least on the basis of the following variables:
the velocity with respect to the vehicle coordinate system, the velocity with respect to the world coordinate system and the steering angle.
The orientation angle between the vehicle coordinate system and the world coordinate system is calculated, in accordance with the example, in the orientation model unit 9 additionally at least on the basis of one or more of the following variables:
orientation information of the vehicle based on the world coordinate system,
same or all of the correction values and/or variances of the fusion filter and/or
the acceleration of the vehicle in relation to the vehicle coordinate system and/or the world coordinate system.
The orientation model unit 9 uses some or all of the output data and/or output signals of the strapdown algorithm unit 2 for the calculation.
The orientation model unit 9 is designed, in accordance with the example, in such a way that it calculates and provides, in addition to the orientation angle, also information on the data quality of this variable, in particular the variance of the orientation angle, wherein the orientation model unit 9 provides the orientation angle between the vehicle coordinate system and the world coordinate system and the information on the data quality of this variable to the fusion filter 5, and the fusion filter uses this orientation angle in its calculations and particularly preferably passes on the information on the data quality of this variable, in particular the variance of the orientation angle, to the strapdown algorithm unit 2.
While the above description constitutes the preferred embodiment of the present invention, it will be appreciated that the invention is susceptible to modification, variation, and change without departing from the proper scope and fair meaning of the accompanying claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 102011082535.5 | Sep 2011 | DE | national |
| 102011082539.8 | Sep 2011 | DE | national |
| 102011082548.7 | Sep 2011 | DE | national |
| 102011082549.5 | Sep 2011 | DE | national |
| 102011082551.7 | Sep 2011 | DE | national |
| 102011082552.5 | Sep 2011 | DE | national |
| 102011082534.7 | Nov 2011 | DE | national |
| 102011086710.4 | Nov 2011 | DE | national |
| 102012207297.7 | May 2012 | DE | national |
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/EP2012/067878 | 9/12/2012 | WO | 00 | 8/15/2014 |
