DE102017007122A1 - Method for detecting the direction of travel of a vehicle - Google Patents

Abstract

The invention relates to a method for detecting the direction of travel of a vehicle (1). According to the invention, a respective direction of travel or a stoppage of the vehicle (1) is determined on the basis of a balance of forces acting on the vehicle (1).

Description

The invention relates to a method for detecting the direction of travel of a vehicle according to the preamble of claim 1.

From the EP 2 171 480 B1 is a method for detecting the direction of travel or for detecting a change in direction of a motor vehicle having at least two Raddrehzahlsensoranordnungen, each comprising an encoder with an incremental scale and scale scales and a wheel speed sensor and are connected to an electronic control unit, the wheel speed sensors upon detection of scale graduation each transmit a speed signal to the electronic control unit, wherein the direction of travel or a change of direction is determined at least from the order of occurrence of the speed signals with respect to the individual Raddrehzahlsensoranordnungen.

The invention is based on the object to provide a comparison with the prior art improved method for detecting the direction of travel of a vehicle.

The object is achieved with the features specified in claim 1.

Advantageous embodiments of the invention are the subject of the dependent claims.

In a method for detecting the direction of travel of a vehicle, according to the invention a respective direction of travel or a stoppage of the vehicle is determined on the basis of a balance of forces acting on the vehicle.

Advantageously, a slope of a currently traveled route is taken into account, which is determined or estimated.

Furthermore, a mass of the vehicle can be taken into account, which is estimated, for example.

By means of the method and the resulting force-based direction of travel and standstill detection, a change of direction of the vehicle, in particular after a standstill of the vehicle, can be detected early. A fast, d. H. early, and highly accurate knowledge of a current direction of travel or the stoppage of the vehicle allows a comparison with conventional methods more accurate determination of Odometriedaten and thus a more accurate position of the vehicle. Thus, a functionality of certain assistance devices, such as a parking assistant, over the prior art can be improved.

By means of the method according to the invention can be made very much a statement about whether the vehicle is at a standstill or has changed the direction of travel, since engine torques of a drive motor of the vehicle already present, before the vehicle has moved.

The method according to the invention is advantageously used in combination with one or more methods for detecting the direction of travel and / or odometry data by means of wheel speed sensors, for example for the plausibility of such methods. Such a method which can be combined with the method according to the invention is, for example, in the not yet published DE 10 2017 003 442.7 by the assignee, the entire contents of which are hereby incorporated by reference.

In such methods, the respective vehicle wheel is associated with an encoder which rotates with the vehicle wheel, and a wheel speed sensor fixedly arranged on the vehicle. The passage of the encoder on the wheel speed sensor causes rashes in a detected by the wheel speed sensor speed signal, also referred to as ticks or Radticks. In previously known methods, for example, four such detected ticks are required in order to be able to determine a respective direction of travel of the vehicle. By means of the method according to the invention, this direction detection is already possible much earlier, namely already when setting up the balance of forces. As a result, smaller zero phases of a travel direction signal are achieved, whereby the detected ticks can be used with correct reference for odometry.

By means of the method, for example by using a Kalman filter, for example, a signal indicating the respective direction of travel or the standstill of the vehicle is determined, which has the following structure:

Ie. This signal, called drive, may have the value of one, zero, and one minus one, and when the signal assumes the value of one, indicates that the vehicle is in the forward driving direction, assuming the value zero, indicating that the vehicle is in the forward direction Vehicle is at a standstill, and when it assumes the value minus one, indicates that the vehicle is in the direction of travel reverse.

Embodiments of the invention are explained in more detail below with reference to drawings.

Showing:

1 schematically a vehicle,

2 schematically the vehicle on a currently traveled route, which has a slope, and

3 schematically diagrams that illustrate a driving direction determination based on a balance of forces acting on the vehicle forces.

Corresponding parts are provided in all figures with the same reference numerals.

1 shows a schematically simplified view of a vehicle 1 , In a method for detecting the direction of travel of such a vehicle 1 becomes a respective direction of travel or a stoppage of the vehicle 1 based on a balance of forces on the vehicle 1 attacking forces. For this purpose, in one possible embodiment of the method, a Kalman filter is used.

This method is advantageously used in combination with a method for detecting the direction of travel and / or odometry data by means of wheel speed sensors, for example, to check the plausibility of such a method. Such a method which can be combined with the method described here is, for example, in the not yet published DE 10 2017 003 442.7 by the assignee, the entire contents of which are hereby incorporated by reference.

In the following, an approach based on the method for direction detection and standstill detection on the basis of forces and moments is described. A sign of a speed of the vehicle 1 in the longitudinal direction determines the direction of travel of the vehicle 1 , The speed is integrated via a sectionally linear Kalman filter from the forces and, if present, at a speed of wheels 2 of the vehicle 1 merged.

It is assumed that inertia of a drive train of the vehicle 1 comprising, in particular, a transmission, a motor, drive shafts and the wheels 2 of the vehicle 1 , against a mass m to be accelerated of the vehicle 1 are negligible. The approach is based on Newton's second law:

In this case, F _{x is} the force in the X direction of a vehicle coordinate system, ie in the longitudinal direction of the vehicle 1 , v _x the speed of the vehicle 1 in the X direction of the vehicle coordinate system, m the mass of the vehicle 1 , v. _x an acceleration of the vehicle 1 in the X direction of the vehicle coordinate system, F _to which the vehicle 1 driving force and _friction the vehicle 1 braking friction force.

• • Motormoment am Rad T_eng -> F_eng = T_eng/r_dyn
• • Motorschleppmoment am Rad T_schlepp -> F_schlepp = T_schlepp/r_dyn
• • Bremsmoment am Rad T_brk -> F_brk = T_brk/r_dyn
• • Rollreibungskraft F_roll = μ_roll·cosθ·m·g
• • Hangabtriebskraft F_steig = sinθ·m·g

The sum of all forces in the longitudinal direction is made up of variables with known sign F _on and off sizes with speed-dependent sign F _rub (v _x) together. In detail, these are composed of the following forces and moments:

• • Motor torque at wheel T _narrow -> F _narrow = T _narrow / r _dyn
• • Motor _drag torque on the wheel T _schlepp -> F _schlepp = T _schlepp / r _dyn
• • Braking torque on the wheel T _brk -> F _brk = T _brk / r _dyn
• Rolling friction force F _roll = μ _roll · cosθ · m · g
• • slope force F _sidewalk = sinθ · m · g

In this case, F _{eng is} an engine power of the engine of the vehicle 1 , r _dyn a dynamic radius of the wheel of the vehicle 1 , F _drag a motor _{drag force of} the engine of the vehicle 1 , F _brk a braking force of the vehicle 1 , μ _roll a rolling friction coefficient, θ a slope of a currently traveled route FS, m the mass of the vehicle 1 and g is the gravitational acceleration.

In the 2 shown slope θ of the currently traveled route FS can by comparing a measured acceleration with the acceleration of the vehicle 1 be determined. For this purpose, wheel speed sensors and an inertial sensor of the vehicle 1 is used, wherein for sensor results of Raddrehzahlsensoren a Kalman filter and sensor results of Inertialsensorik a low-pass filter is used.

The determined slope θ results from a difference between the inertial sensor and the actual vehicle acceleration.

In this case, a _{sx is} a measured value of an inertial sensor in the X direction of the vehicle coordinate system, ie in the vehicle longitudinal direction, a _x an acceleration determined in the X direction of the vehicle coordinate system by means of the wheel speed sensors, a _h- a downhill acceleration and a _{h +} a counter acceleration of the vehicle 1 ,

The downhill acceleration a _h- is determined as follows: a _h- = -gsin (θ) = -a _sx + a _x (5)

The counter-acceleration a _{h + of} the vehicle 1 is determined as follows: a _{h +} = gsin (θ) = a _sx - a _x (6)

It is advantageously carried out a post-processing of this slope determination by smoothing the signal and filtering out implausible values.

The frictional forces, which always lead to the reduction of the speed, consist of the amounts of braking force F _brk , rolling friction F _roll and possibly the engine _drag torque from the engine or the resulting motor _{drag force} F _schlepp , as shown by formula (7), where F _{friction, abs is} the absolute friction force. They are opposite to the instantaneous velocity direction at all times, as shown by formula (8). F _{friction, abs} = F _brk + F _roll + F _drag (7) F _rub = sgn (v _x) · F _{rub, abs} (8)

The sign function is denoted by sgn and is defined as:

The sign of the forces due to motor or slope θ is independent of the direction of the speed. It therefore applies: F _an = F _eng + F _asc (10)

The following linear discrete-time system model is obtained: x _k = A * x _k-1 + B * u _k (11) v * / f * = k (v _k-1) = v _k-1 + .DELTA.t / m · (F _{k to} - F _{k, rub} (v _k-1)) (12)

Applying the equation (12) alone can cause a problem because the speed can make a constant sign change between k-1 and k by a frictional force. The speed v * / k = 0 will probably never be hit. The following logic avoids this problem. L _k : = (F _{friction, abs} ≥ | F _an |) ∧ [(sgn (v * / k) ≠ sgn (v _k-1 )) ∨ (v _k-1 = 0)] (13)

Here, in the logical expression L _{k is} stored the information as to whether the frictional forces are sufficient to bring the speed to zero or to keep it at zero. An extended Kalman filter is used to estimate an optimal speed that exists even without the direction of the RIZ sensor, ie the wheel speed sensor.

The system equation f (x _k-1 ) with the system noise w _x and the measurement equation h (x _k ) with the measurement noise w _z are: x _k = f (x _k-1 ) + w _x with ε (w _x ) = 0; Q _k : = ε {w _x · w T / x) (15) z _k = h (x _k) + w _z = x _k + w _z, w ε _{z) = 0; R _k : = ε (w _z · w T / z) (16)

wodurch ein Extended-Kalman-Filter der allgemeinen Form erhalten wird: x ^_k|k-1 = f(x ^_k–1|k-1) (19) P ^_k|k-1 = P ^_k-1|k-1 + Q_k (20) S ^_k = H·P ^_k|k-1·H^T + R_k (21) K_k = P ^_k|k-1·H^T + S ^ –1 / k (22) x ^_k|k = x ^_k|k–1 + K_k·(z_k – h(x ^_k|k-1)) (23) wobei für den Fall, dass keine Messung zur Verfügung steht, nur die Prädiktion verwendet wird: x ^_k|k := x ^_k|k-1 (24) P ^_k|k := P ^_k|k-1 (25) The Jacobi matrices are defined as

whereby an extended Kalman filter of the general form is obtained: x ^ _{k | k-1} = f (x ^ _{k-1 | k-1} ) (19) P ^ _{k | k-1} = P ^ _{k-1 | k-1} + Q _k (20) S ^ _k = H · P _k · _k-1 · H ^T + R _k (21) K _k = P _k · _k-1 · H ^T + S ^ -1 / k (22) x ^ _{k | k} = x ^ _{k | k-1} + _Kk · ( _zk -h (x ^ _{k | k-1} )) (23) in the case where no measurement is available, only the prediction is used: x ^ _{k | k} : = x ^ _{k | k-1} (24) P ^ _{k | k} : = P ^ _{k | k-1} (25)

There is no measurement of the speed available if the direction signal of the RIZ sensors is undefined or 0. The algorithm has been tested for the following parameters in the plane:
Covariance ratio R _k / Q _k = 5

The mass m of the vehicle 1 is 2000 kg.

The rolling friction coefficient μ _roll is 0.02.

The dynamic radius r _{dyn of} the wheel 2 is 2.09 / 2 · π m.

The slope θ is 0 rad.

In a test drive the vehicle was 1 forward, backward and forward again.

In 3 one sees in the above graph a directional signal determined by means of the wheel speed sensors designed as Hall sensors, designated Dir_Veh_Stat, a by means of the pattern recognition according to that in the not yet published DE 10 2017 003 442.7 Applicant's method determines detected directional signal, denoted by dir_pattern, and the directional signal determined by the force approach described herein, denoted by dir_force. Below this is the raw signal in the form of the count differences of the wheel speed signals DWPC: 1 to DWPC: 4 of the wheel speed sensors of the four wheels 2 of the vehicle 1 shown. In the third graph is v detects the speed measurements, _a v as an input signal of the Kalman filter and the fused condition of the Kalman filter as the output signal _from the speed of the vehicle 1 , As a reminder: If no measurement is available, ie the directional signal Dir_Veh_Stat = 0 determined by the wheel speed sensors, the merged state of the Kalman filter is determined from the previous state and the momentary force. The lower graph shows the driving forces F _an and the positive and negative values of the maximum absolute frictional forces F _{friction, abs} , _respectively . In this case, provide the maximum friction force F _{friction, abs} represents threshold values, wherein the amount-exceeded by the driving force of F _at the vehicle 1 emotional.

It can be seen that the direction signal dir_force seems plausible on the basis of the forces and even while the direction signal Dir_Veh_Stat determined by the wheel speed sensors is undefined exists. Plausible, therefore, because it strives against the true value of the directional signal Dir_Veh_Stat determined by the wheel speed sensors when Dir_Veh_Stat ≠ 0, and is similar to the direction signal dir_pattern determined by the pattern-based direction detection. It has short phases in which the direction information is zero. So it is possible with this direction signal dir_force, the count differences, where no direction signal Dir_Veh_Stat of the wheel speed sensors exist, to use properly in a later filter. Between about 9.3 s and 10 s, the direction signal of the wheel speed sensors Dir_Veh_Stat = 0, but there are non-zero values in the count differences of the wheel speed signals DWPC: 1 to DWPC: 4. A similar scenario can be seen between about 15.5 s and 16.5 s.

On the abscissa axis of in 3 The diagrams shown in each case the time is removed in seconds. On the ordinate axis in the first and third diagram from above the direction is removed, with positive values for forward drive and negative values for reverse drive, in the second diagram is plotted on the ordinate axis the signal amplitude of the wheel speed sensors and in the fourth, ie lowest, diagram is on the Ordinatenachse the force in Newton removed.

Variablen Fhhrzeugsensorik

Simulationsmodell

Kalman-Filter

The symbols used in the formulas given above, in particular those which have not already been explained in the above text, have the following meaning: Nomenclature Mathematical notation

Variable vehicle sensors

simulation model

Kalman filter

LIST OF REFERENCE NUMBERS

1

vehicle

2

wheel

a _sx

Measured value of an inertial sensor in the X direction

a _x

By means of the wheel speed sensors determined acceleration in the X direction

a _h

Downhill acceleration

a _{h +}

Counter acceleration of the vehicle

FS

driving route

θ

pitch

Dir_Veh_Stat

Direction signal from wheel speed sensors

dir_pattern

Directional signal from pattern recognition

dir_force

Direction signal by means of force

DWPC: 1

wheel speed

DWPC: 2

wheel speed

DWPC: 3

wheel speed

DWPC: 4

wheel speed

v _a

input

v _out

output

F _on

driving force

F _{friction, abs}

absolute friction force

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• EP 2171480 B1 [0002]
• DE 102017003442 [0011, 0022, 0048]

Claims (3)

Method for detecting the direction of travel of a vehicle ( 1 ), characterized in that a respective direction of travel or a stoppage of the vehicle ( 1 ) based on a balance of forces on the vehicle ( 1 ) of attacking forces is determined. A method according to claim 1, characterized in that in determining the balance of forces a slope θ of a currently traveled route (FS) is taken into account. Method according to one of the preceding claims, characterized in that for determining the balance of forces a mass of the vehicle ( 1 ) is estimated.

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