Patent ID: 12202527

Parts corresponding to one another are provided in all figures with like reference signs.

DETAILED DESCRIPTION

FIG.1shows a schematic view of a steering column1with a steering wheel2for a vehicle3, in particular a motor vehicle.

In a method according to the invention, a steering column torque MMess_Lenkstangeat the steering column1is measured, for example by means of a torque sensor5. Furthermore, a steering wheel angle δLRis measured, for example by means of a rotary angle sensor6. A manual torque MHandacting on the steering wheel2is not measured. The method is used to determine the manual torque MHandfrom the steering column torque MMess_Lenkstange.

It is known to determine the manual torque MHandindirectly by measuring the steering column torque MMess_Lenkstangein the vehicle3. The steering column torque MMess_Lenkstangeis measured, for example, using a strain sensor, which is arranged in the vehicle3on the steering rod1directly above a steering system. The assumption that the manual torque MHandat the steering wheel2is equal to the steering column torque MMess_Lenkstangecan be considered to be valid during automated driving for slow steering movements, but not for rapid, automated steering movements, since these likewise introduce a torque.

In accordance with the invention, a method is proposed that determines the steering column torque MMess_Lenkstange, for example, by means of the strain sensor, and which also uses a rotary angle sensor6on the steering wheel2. The method is modelled by means of parameters, for example a frictional torque MRof the steering rod1and a moment of inertia ⊖LRof the steering wheel2, which can be obtained from measurement data of the vehicle3. The method, using two information sources, for example sensors, together with the knowledge of identified system parameters, for example the frictional torque MRand the moment of inertia ⊖LR, allows an estimation of torque introduced by rapid automated steering movements, in order to filter this torque out, so that the remaining torque is at least approximately equal to the manual torque actually applied at the steering wheel.

The following model equation of the steering system forms the basis of the calculation of the manual steering torque MHand(equation in the frequency range with the complex frequency s):

MMess⁢_⁢Lenkstange=e-s·Tt·1TMess·s+1·(MHand+ΘLR·δ¨LR+MR·sign⁡(δ.LR))(equation⁢1)

The parameters have the following meaning here:Ttdead time by CAN transfer of the measurement data

1TMess·s+1
measurement filter, low-pass effect by measurement arrangement⊖LRmoment of inertia of the steering wheel{umlaut over (δ)}LRsteering angle accelerationMRfrictional torque{dot over (δ)}LRsteering angle speed

The steering wheel angle δLRis a discrete-time variable determined in a clocked manner. The determination of the time derivatives of such variables by subtraction can lead to high noise contributions on account of the discretization. Therefore, the time derivatives are preferably calculated via a low-pass filtering with a third-order Bessel filter. The following is then true:

δ¨=s2N3⁢ter⁢_⁢O⁢_⁢Bessel⁢δLR(equation⁢2)δ.=sN3⁢ter⁢_⁢O⁢_⁢Bessel⁢δLR(equation⁢3)

The denominator N3ter_O_Besselin this case represents the third-order Bessel polynomial (N3ter_O_Bessel=s3+6s2+15s+15). The advantage of the Bessel filtering lies in a linear phase delay, that is to say a constant group delay in the passband, the Bessel filtering leads to a phase delay. In order to avoid errors as a result of this phase delay, all elements of the equation must be subjected to the same phase delay. All elements of the equation are therefore extended by the denominator N3ter_O_Bessel. The following equation is obtained:

MMess⁢_⁢LenkstangeN3⁢ter⁢_⁢O⁢_⁢Bessel=e-sTt·1TMess·s+1·(MHandN3⁢ter⁢_⁢O⁢_⁢Bessel+ΘLR·s2N3⁢ter⁢_⁢O⁢_⁢Bessel·δLR+MR·sign(sN3⁢ter⁢_⁢O⁢_⁢Bessel·δLR))(equation⁢4)

For the measurement, it is advantageous to determine the parameters of this equation. This parameter determination (parameterization) is performed as follows:

A transverse controller, which in automated driving operation, that is to say in the normal operating mode, performs steering interventions at the steering system via a steering actuator, is switched to a parameterization mode. In the parameterization mode, the driver must keep his hands off the steering wheel (hands-off operation), so that MHand=0. The driver is advantageously prompted to do this. In the parameterization mode, the steering column torque MMess_Lenkstangeand the steering wheel angle δLRare also measured, and the steering actuator is actuated by the transverse controller in such a way that it applies predefined pulses of a simulated steering torque MSimto the steering column. As a result of these steering torque pulses, a steering torque MSimis simulated, which is created when the vehicle3travels over potholes. The simulated steering torque MSimis compared with the measured steering column torque MMess_LenkstangeThe parameters constituted by moment of inertia ⊖LR, frictional torque MR, and dead time Ttare modelled in such a way that the simulated torque MSimmatches the measured steering column torque MMess_Lenkstange.

FIG.2shows a schematic graph with a time curve of the simulated steering torque MSimand of the measured steering column torque MMess_Lenkstange.

This parameterization is advantageously performed during the production of the vehicle3, that is to say prior to delivery of the vehicle3to the customer, or alternatively during a visit to a garage.

To determine the manual torque MHand, equation 4 is solved in terms of MHand. The following is then obtained:

MMessLenkstangeN3⁢ter⁢_⁢O⁢_⁢Bessel-e-sTt·1TMess·s+1·(ΘLR·s2N3⁢ter⁢_⁢O⁢_⁢Bessel·δLR+MR·sign(sN3⁢ter⁢_⁢O⁢_⁢Bessel·δLR))=e-sTt·1TMess·s+1·(1N3⁢ter⁢_⁢O⁢_⁢Bessel)·MHand=MHand*(equation⁢5)

The right side is equated to an estimated manual torque MHand:

MHand*=e-sTt·1TMess·s+1·(1N3⁢ter⁢_⁢O⁢_⁢Bessel)·MHand.(equation⁢6)

The estimated manual torque M*Handdeviates from the sought manual torque MHand, however, the deviation Δ=M*Hand−MHandis so small that M*Handis a good estimation for the sought manual torque MHand, and therefore can be used for the decision to terminate the automated driving operation.

In an extension of the method, the parameters can be updated over the operating time of the vehicle3. The update is based on equation 1. For an improved presentability of the method, the contributions of the dead time Ttand of the measurement filter

1TMess·s+1
can be ignored. A person skilled in the art, however, will readily be able to modify the following equations also to the extent that the contributions of the dead time Ttand of the measurement filter

1TMess·s+1
are also taken into consideration. Furthermore, in equation 1 an additional offset torque Moffis also introduced. Proceeding from equation 1, this then results in:
MMess_Lenkstange=MHand+⊖LR·{umlaut over (δ)}LR+MR{dot over (δ)}LR+Moff(equation 7)

Both sides of equation 7 are summed over a multiplicity n of measurement values (MMess_Lenkstange, δLR). The measurement values are temporarily stored for this purpose, for example in a ring buffer. The following is then obtained

∑nMMess⁢_⁢Lenkstange=∑n(MHand+ΘLR·δ¨LR+MR·δ.LR+Moff).(equation⁢8)

If the sum on the right side is solved in terms of the constant factors, the following is obtained:
ΣnMMess_Lenkstange=ΣnMHand+⊖LR·Σn{umlaut over (δ)}LR+MR·Σn{dot over (δ)}LR+n·Moff(equation 9)

The offset torque Moffis determined for example as follows: From the multiple stored measurements, those measurements are identified for which the following is true:
Σn{umlaut over (δ)}LR=0,Σn{dot over (δ)}LR=0,ΣnMHand=0

With longer-lasting measurements, this will only ever be the case. The following is then obtained from equation 9
ΣnMMess_Lenkstange=n·Moff
and Moffcan be updated to

M^off=Moff=∑nMMess⁢_⁢Lenkstangen.

The moment of inertia ⊖LRof the steering wheel can be determined as follows: From the multiplicity of stored measurements, those measurements are identified for which the following is true:
Σn{umlaut over (δ)}LR≠0,Σn{dot over (δ)}LR=0,ΣnMHand=0

With longer-lasting measurements, this will only ever be the case. The following is then obtained from equation 9
ΣnMMess_Lenkstange=⊖LR·Σn{umlaut over (δ)}LR+n·{circumflex over (M)}off
and ⊖LRcan be updated to

Θ^LR=ΘLR=∑nMMessLenkstange-n·M^off∑nδ¨LR.

The frictional torque MRcan be determined as follows: From the multiplicity of stored measurements, those measurements are identified for which the following is true:
Σn{umlaut over (δ)}LR=0,Σn{dot over (δ)}LR≠0,ΣnMHand=0

With longer-lasting measurements, this will only ever be the case. The following is then obtained from equation 9
ΣnMMess_Lenkstange=MR·Σn{dot over (δ)}LR+n·{circumflex over (M)}off.
and MRcan be updated to

M^R=MR=∑nMMessLenkstange-n·M^off∑nδ.LR.

In this way, parameter changes that occur on account of signs of wear or signs of aging during operation with the customer can also be corrected during operation.

The termination criterion is satisfied when the manual torque MHandexceeds a predefinable deactivation threshold, wherein the deactivation threshold is predefined depending on the situation, in particular depending on whether the driver is holding the steering wheel by at least one hand or no hands (hands-on-/hands-off situation), whether or not the driver is monitoring the traffic situation ahead of the vehicle3, and/or whether there is a lateral collision risk in the effective direction of the manual torque.

In particular, the deactivation threshold is predefined in such a way that, to terminate the automated driving operation,a small manual torque (for example 3 Nm) is sufficient if a hands-on situation is present,a medium manual torque for example 6 Nm) is necessary if a hands-off situation is present,a high manual torque (for example 8 Nm) is necessary if the driver is not observing the traffic situation ahead of the vehicle3or if there is a lateral collision risk in the effective direction of the manual torque.

The detection of whether a hands-on or hands-off situation is present can be implemented by sensor, for example by means of a capacitive steering wheel. The detection of whether the driver is observing the traffic situation can be implemented using a camera that monitors the driver, for example by means of viewing direction recognition. The detection of the lateral collision risk can be implemented using conventional ambient sensors, for example radar, lidar, or camera.

The method can be implemented in a control unit4arranged in the vehicle3.

Although the invention has been illustrated and described in detail by way of preferred embodiments, the invention is not limited by the examples disclosed, and other variations can be derived from these by the person skilled in the art without leaving the scope of the invention. It is therefore clear that there is a plurality of possible variations. It is also clear that embodiments stated by way of example are only really examples that are not to be seen as limiting the scope, application possibilities or configuration of the invention in any way. In fact, the preceding description and the description of the figures enable the person skilled in the art to implement the exemplary embodiments in concrete manner, wherein, with the knowledge of the disclosed inventive concept, the person skilled in the art is able to undertake various changes, for example, with regard to the functioning or arrangement of individual elements stated in an exemplary embodiment without leaving the scope of the invention, which is defined by the claims and their legal equivalents, such as further explanations in the description.