Abstract
A method and a device for ascertaining a dynamic tire circumference of a transportation vehicle. The method includes: receiving a first signal representing a yaw rate of the transportation vehicle, a second signal representing a wheel rotation speed of a wheel of the transportation vehicle, a third signal representing a steering angle of the transportation vehicle, and a fourth signal representing a dynamic track width of the transportation vehicle; ascertaining a first output signal of a first Kalman filter that represents the dynamic tire circumference of the wheel, using the first signal, the second signal, the third signal, and the fourth signal as input signals for the first Kalman filter; and using the first output signal in a control unit of the transportation vehicle.
Claims
1-11. (canceled)
12. A method for ascertaining a dynamic tire circumference of a transportation vehicle, the method comprising the following steps: receiving a first signal representing a yaw rate of the transportation vehicle, a second signal representing a wheel speed of a wheel of the transportation vehicle, a third signal representing a steering angle of the transportation vehicle, and a fourth signal representing a dynamic track width of the transportation vehicle; ascertaining a first output signal of a first Kalman filter that represents the dynamic tire circumference of the wheel, using the first signal, the second signal, the third signal, and the fourth signal as input signals for the first Kalman filter; and using the first output signal in a control unit of the transportation vehicle.
13. The method as recited in claim 12, wherein the first Kalman filter is a filter that includes a state space model for computing the dynamic tire circumference.
14. The method as recited in claim 13, wherein the first Kalman filter is an extended Kalman (EKF) filter or an unscented Kalman (UKF) filter.
15. The method as recited in claim 12, wherein the dynamic track width is a predefined estimated value of the dynamic track width, or is computed using a second Kalman filter whose input signals include the first signal, the second signal, the third signal, and the first output signal of the first Kalman filter.
16. The method as recited in claim 15, wherein the second Kalman filter is a filter that includes a state space model for computing the dynamic track width.
17. The method as recited in claim 16, wherein the second Kalman filter is an extended Kalman (EKF) filter or an unscented Kalman (UKF) filter.
18. The method as recited in claim 12, wherein a fifth signal representing a piece of position information of a satellite-based locating system of the transportation vehicle is additionally fed as an input signal into the first Kalman filter and used in ascertaining the dynamic tire circumference.
19. The method as recited in claim 12, wherein the first output signal of the first Kalman filter (K1) is updated or not updated as a function of predefined criteria.
20. The method as recited in claim 12, wherein a second output signal representing a quality of the first output signal of the first Kalman filter is output by the first Kalman filter.
21. The method as recited in claim 12, wherein the ascertainment of the dynamic tire circumference and/or of the dynamic track width is carried out at a longitudinal speed of the transportation vehicle of 1 km/h to 200 km/h.
22. The method as recited in claim 12, wherein the ascertainment of the dynamic tire circumference and/or of the dynamic track width is carried out at a longitudinal speed of the transportation vehicle of 3 km/h to 150 km/h.
23. The method as recited in claim 12, wherein the ascertainment of the dynamic tire circumference and/or of the dynamic track width is carried out at a longitudinal speed of the transportation vehicle of 5 km/h to 130 km/h.
24. The method as recited in claim 12, wherein the first output signal of the first Kalman filter is used in a driver assistance system of the transportation vehicle.
25. The method as recited in claim 12, wherein the first output signal of the first Kalman filter is used in a driver assistance system of the transportation vehicle in a maneuvering system of the transportation vehicle.
26. The method as recited in claim 12, wherein the first output signal of the first Kalman filter is used in a driver assistance system of the transportation vehicle in a parking assistance system of the transportation vehicle.
27. The method as recited in claim 12, wherein a plurality of second signals representing a plurality of wheel speeds of a plurality of wheels of the transportation vehicle is incorporated into the first Kalman filter.
28. A device for ascertaining a dynamic tire circumference of a transportation vehicle, comprising: an evaluation unit; a data input; and a data output; wherein the evaluation unit is configured to: receive, in conjunction with the data input, a first signal representing a yaw rate of the transportation vehicle, a second signal representing a wheel speed of a wheel of the transportation vehicle, a third signal representing a steering angle of the transportation vehicle, and a fourth signal representing a dynamic track width of the transportation vehicle; ascertain a first output signal of a first Kalman filter that represents the dynamic tire circumference of the wheel, using the first signal, the second signal, the third signal, and the fourth signal, as input signals for the first Kalman filter; and use, in conjunction with the data output, the first output signal in a control unit of the transportation vehicle.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0025] Exemplary embodiments of the present invention are described in greater detail below with reference to the figures.
[0026] FIG. 1 shows a flowchart that illustrates steps of one exemplary embodiment of a method according to the present invention.
[0027] FIG. 2 shows a block diagram of a first Kalman filter according to the present invention for computing a dynamic tire circumference of a means of transportation.
[0028] FIG. 3 shows a block diagram of a second Kalman filter according to the present invention for computing a dynamic track width of a means of transportation.
[0029] FIG. 4 shows a schematic overview of components of a device according to the present invention in conjunction with a means of transportation.
[0030] FIG. 1 shows a flowchart that illustrates steps of one exemplary embodiment of a method according to the present invention for ascertaining a dynamic tire circumference of a means of transportation, which is a passenger automobile here. An evaluation unit according to the present invention, which is coupled via information technology to a vehicle electrical system of the means of transportation, in first step 100 receives a first signal representing a yaw rate of the means of transportation, a second signal representing a wheel speed of a wheel of the means of transportation, a third signal representing a steering angle of the means of transportation, and a fourth signal representing a dynamic track width of the means of transportation, and stores data represented by the signals in a memory unit that is connected via information technology to the evaluation unit. The evaluation unit ascertains a first output signal of a first Kalman filter representing the dynamic tire circumference of the wheel, using the first signal, the second signal, the third signal, and the fourth signal as input signals for the first Kalman filter in step 200. The first Kalman filter is a UKF filter here. The first output signal is ascertained based on a computer program that is executed by the evaluation unit and that maps a state space model for computing the dynamic tire circumference. The first output signal of the UKF filter is transferred to a parking assistance system of the means of transportation via the vehicle electrical system of the means of transportation in third step 300, and the parking assistance system carries out a fully automatic parking maneuver based on the first output signal.
[0031] FIG. 2 shows a block diagram of a first Kalman filter K1 according to the present invention for computing a dynamic tire circumference of a means of transportation. For this purpose, a first signal S1 representing a yaw rate of the means of transportation, a second signal S2 representing a wheel speed of a wheel of the means of transportation, a third signal S3 representing a steering angle of the means of transportation, and a fourth signal S4 representing a dynamic track width of the means of transportation are fed into the input of first Kalman filter K1. Fourth signal S4 representing the dynamic track width of the means of transportation corresponds here to a value of the dynamic track width that is actually computed and not estimated. Based on input signals S1, S2, S3, S4 and based on a suitable state space model, first Kalman filter K1 is configured to compute a first output signal A1 that represents the dynamic tire circumference of the means of transportation. In addition, first Kalman filter K1 generates a second output signal A2 that represents a measure for a quality of first output signal A1.
[0032] FIG. 3 shows a block diagram of a second Kalman filter K2 according to the present invention for computing a dynamic track width of a means of transportation. For this purpose, a first signal S1 representing a yaw rate of the means of transportation, a second signal S2 representing a wheel speed of a wheel of the means of transportation, a third signal S3 representing a steering angle of the means of transportation, and a first output signal A1 of first Kalman filter K1 representing a dynamic tire circumference of the means of transportation are fed into the input of second Kalman filter K2. First output signal A1 representing the dynamic tire circumference of the means of transportation corresponds here to a value of the dynamic tire circumference that is actually computed and not estimated. Second Kalman filter K2 is configured, based on input signals S1, S2, S3, A1 and based on a suitable state space model, to compute a fourth signal S4 that represents the dynamic track width of the means of transportation.
[0033] FIG. 4 shows a schematic overview of components of a device according to the present invention in conjunction with a means of transportation 80. The device according to the present invention includes an evaluation unit 10, which is a microcontroller here and which includes a data input 12 and a data output 14. In addition, an external memory unit 20 in which evaluation unit 10 may store received and/or computed data is connected via information technology to evaluation unit 10. Evaluation unit 10 is configured to carry out the above-described method steps according to the present invention, based on a computer program. A rotation rate sensor 50 of means of transportation 80 is connected via information technology to data input 12 of evaluation unit 10 via a CAN bus of a vehicle electrical system of means of transportation 80. In addition, a plurality of wheel speed sensors 60 of particular wheels 85 of means of transportation 80 is likewise connected to data input 12 of evaluation unit 10 via the CAN bus. Furthermore, a steering angle sensor 70 and a GPS receiver 40 of means of transportation 80 are likewise connected to data input 12 of evaluation unit 10 via the CAN bus. In this way, evaluation unit 10 is configured to receive a first signal representing a yaw rate of rotation rate sensor 50, second signals representing wheel speeds of a plurality of wheel speed sensors 60, a third signal representing a steering angle of steering angle sensor 70, and a fifth signal representing a piece of position information of GPS receiver 40 of means of transportation 80. In addition, evaluation unit 10 receives from memory unit 20 a predefined estimated value of a dynamic track width of means of transportation 80. All of the reception signals described above and the predefined estimated value of the dynamic track width of means of transportation 80 are supplied to a first Kalman filter in evaluation unit 10 as input signals in order to compute a dynamic tire circumference of means of transportation 80 based on these input signals. The first Kalman filter is implemented with the aid of the computer program that is executed by evaluation unit 10. A result of the computation of the dynamic tire circumference is transferred, with the aid of data output 14 of evaluation unit 10, to a parking assistance system 30 of means of transportation 80 via the CAN bus. Parking assistance system 30 subsequently uses the information concerning the dynamic tire circumference in carrying out a fully automatic parking operation of means of transportation 80.
