Method and apparatus for determining the filter output variables of a filter for filtering the torsion bar moment of a steer-by-wire steering system for a vehicle.

Abstract

An apparatus and method for determining a filter output variable of a filter, in particular a filter (100) for filtering a torsion bar moment of a steer-by-wire steering system of a vehicle, depending on a filter input variable to be filtered, characterized in that preset filter characteristics of the filter are selected from a plurality of preset filter characteristics depending on input signal characteristics of the filter input variables, the input signal characteristics being determined depending on the filter input variables at a current time point and at least one preceding time point, and the filter output variable is determined by the filter having the filter characteristics.

Description

[Technical Field]

[0001] Background technology The present invention relates, in particular, to a method and apparatus for determining the filter output variables of a filter for filtering the torsion bar moment of a steer-by-wire steering system for a vehicle. [Background technology]

[0002] In a steer-by-wire steering system, the driver's direction setting is received via the steering control unit, and the steering feel of the vehicle to the driver is generated by a manual moment adjuster. To generate the steering feel, the manual moment adjuster includes a motor, which outputs a corresponding moment to the rotor shaft, and this moment is transferred to the steering control unit via the transmission and steering column. The motor is located relatively close to the driver, which leads to acoustically and tactilely distinctive characteristics for the driver. This characteristic increases to an unacceptable level of interference if the motor is driven and controlled by a strong noise signal. A common procedure for handling noise signals is to use a filter with low-pass characteristics to compensate for high-frequency noise components, but this introduces an additional phase shift to the steer-by-wire steering system. Therefore, a compromise is needed regarding noise filtering and phase delay to avoid degrading the stability characteristics of the steer-by-wire steering system due to the additional phase delay. [Overview of the project] [Problems that the invention aims to solve]

[0003] Therefore, a filter is desired that reduces noise without introducing a long phase delay and suppresses filter error within a predetermined range. [Means for solving the problem]

[0004] Disclosure of the invention This is achieved by the method and apparatus according to the independent claim.

[0005] In this method, in order to determine the filter output variable of a filter, particularly a filter for filtering the torsion bar moment of a vehicle's steer-by-wire steering system, depending on the filter input variable to be filtered, it is assumed that the filter's preset filter characteristics are selected from a plurality of preset filter characteristics depending on the input signal characteristics of the filter input variable, the input signal characteristics are determined depending on the filter input variable at the current time and at least one preceding time, and the filter output variable is determined by the filter having the filter characteristics. Different filter characteristics of the filter affect the filter error. This makes it possible to limit the filter error to a maximum value. In addition, the filter is operated in an operating state suitable for the input signal, thereby reducing phase delay and improving the characteristics of the control loop of the steer-by-wire steering system.

[0006] Preferably, the filter characteristics include a first filter characteristic, a second filter characteristic, and a third filter characteristic, where the first filter characteristic places the filter output variable at the center point of the filter input variable, particularly the center point of the noise band; the second filter characteristic causes the filter to operate as a low-pass filter; and the third filter characteristic causes the filter to operate as a pass-through filter. These filter characteristics allow the filter to operate under different operating conditions. This makes it possible to compensate for noise in certain scenarios, such as a stationary steering wheel. This leads to improvements in the acoustic and tactile characteristics of steer-by-wire steering systems.

[0007] Preferably, the pre-set filter characteristics of the filter are assumed to be parameterized by at least one application parameter. According to the application parameter, for example, it is possible to limit the filter error to a predetermined value or to adapt individual filter characteristics. This allows the filter to be adapted to different operating conditions or to different types of steer-by-wire steering systems.

[0008] Preferably, at least one applied parameter for a predetermined filter characteristic is intended to characterize the low-pass filter coefficient and / or the maximum allowable filter error.

[0009] Preferably, the input signal characteristics are assumed to be determined by at least one applicable parameter. This makes it possible to adapt the operating conditions and the limits of their operating range, which improves the flexibility of the filter.

[0010] Preferably, at least one applicable parameter for the input signal characteristics of the filter input variable characterizes, in particular, the width of the noise bandwidth of the filter input variable in the form of quantization noise of the filter input variable, and / or the rate of change of the filter input variable.

[0011] Preferably, the filter input variables for the input signal characteristics are as follows: If the filter remains within the width of the noise band, a first operating state of the filter is determined, in which case a first filter characteristic is determined for the filter; if the filter tends to move away from the width of the noise band, a second operating state of the filter is determined, in which case a second filter characteristic is determined for the filter; if the filter tends to enter the width of the noise band, a third operating state of the filter is determined, in which case a second filter characteristic is determined for the filter; if the filter is outside the width of the noise band and continuously moving away from it, a fourth operating state of the filter is determined, in which case a third filter characteristic is determined for the filter; and if the filter is outside the width of the noise band and beginning to approach the noise band, a fifth operating state of the filter is determined, in which case a second filter characteristic is determined for the filter. Thus, the filter has these operating states and their defined operating ranges. This makes it possible to implement the filter in embedded software efficiently and resource-efficiently. This also has a positive effect on the propagation time of the filter.

[0012] In a vehicle, it can be assumed that the torsion bar moment is measured, the filter input variables to be filtered are determined depending on the measured torsion bar moment, and the motor moment for the steer-by-wire steering system is determined depending on the filter output variables and the target moment for the torsion bar moment. This allows the closed-loop control of the torsion bar moment in the steer-by-wire steering system to be dynamically adapted and improved overall.

[0013] An apparatus for determining the filter output variable of a filter, particularly a filter for filtering the torsion bar moment of a vehicle's steer-by-wire steering system, depending on the filter input variable to be filtered, is configured as follows: a preset filter characteristic of the filter is selected from a plurality of preset filter characteristics depending on the input signal characteristics of the filter input variable; the input signal characteristics are determined depending on the filter input variable at the current time and at least one preceding time; and the filter output variable is determined by a filter having the filter characteristics. Different filter characteristics of the filter can affect the filter error. This allows the filter error to be limited to a maximum value. It also allows the filter to operate in a suitable operating state for the input signal, thereby reducing phase delay and improving the characteristics of the control loop of the steer-by-wire steering system.

[0014] Preferably, the filter characteristics include a first filter characteristic, a second filter characteristic, and a third filter characteristic, where the device is configured as follows: the first filter characteristic of the filter is used to place the filter output variable at the center point of the filter input variable, particularly the center point of the noise band; the second filter characteristic of the filter is used to operate the filter as a low-pass filter; and the third filter characteristic is used to operate the filter as a pass-through element. These filter characteristics make it possible to operate the filter under different operating conditions. This makes it possible to compensate for noise in certain scenarios, such as a stationary steering wheel. This leads to improvements in the acoustic and tactile characteristics of steer-by-wire steering systems.

[0015] Preferably, the device is assumed to be configured to parameterize the pre-set filter characteristics of the filter depending on at least one applicable parameter. Depending on the applicable parameter, for example, it is possible to limit the filter error to a specific value or to adapt individual filter characteristics. This allows the filter to be appropriately adapted for different operating conditions or different types of steer-by-wire steering systems.

[0016] Preferably, at least one applied parameter for a predefined filter characteristic is intended to characterize the low-pass filter coefficient and / or maximum filter error.

[0017] Preferably, the device is assumed to be configured to determine the input signal characteristics depending on at least one applicable parameter. This makes it possible to adapt the limits of the operating state and its operating range, which improves the flexibility of the filter.

[0018] Preferably, at least one applicable parameter for the input signal characteristics of the filter input variable is intended to characterize, in particular, the width of the noise bandwidth of the filter input variable in the form of quantization noise of the filter input variable, and / or the rate of change of the filter input variable.

[0019] Preferably, the apparatus is configured as follows: namely, when the filter input variable for the input signal characteristics remains within the width of the noise band, determine the first operating state of the filter, determine the first filter characteristics for the filter, when there is a tendency to deviate from the width of the noise band, determine the second operating state of the filter, determine the second filter characteristics for the filter, when there is a tendency to enter the width of the noise band, determine the third operating state of the filter, determine the second filter characteristics for the filter, when it exists outside the width of the noise band and continuously moves away therefrom, determine the fourth operating state of the filter, determine the third filter characteristics for the filter, when it exists outside the width of the noise band and begins to approach the noise band, determine the fifth operating state of the filter, and determine the second filter characteristics for the filter. Thus, the filter has these operating states and their defined operating regions. This enables the filter to be implemented efficiently and resource-friendly in embedded software. This also has a positive impact on the propagation time of the filter.

[0020] The present apparatus can improve the steer-by-wire function in a vehicle. The vehicle, in this case, includes the apparatus, where the apparatus is configured as follows: namely, measure the torsion bar moment, determine a filter input variable to be filtered depending on the measured torsion bar moment, and determine a motor moment for a steer-by-wire steering system depending on the filter output variable and a target moment for the torsion bar moment.

[0021] Further preferred embodiments will become apparent from the following description and drawings.

Brief Description of the Drawings

[0022] [Figure 1] It is a schematic diagram showing a filter. [Figure 2] It is a schematic diagram showing a state graph of the filter. [Figure 3]It is a flowchart showing a method for determining a filter output variable of a filter. [Figure 4] It is a schematic diagram showing a vehicle. [Figure 5] It is a diagram showing a control loop.

Embodiments for Carrying Out the Invention

[0023] FIG. 1 schematically shows a filter 100. A filter input variable 102 is provided to the filter 100. The filter 100 determines a filter output variable 104 depending on the filter input variable 102. Also, the filter input variable 102 is supplied to an evaluation device 106. The filter 100 includes the evaluation device 106 in this example. The evaluation device 106 may be assumed to be arranged as a device external to the filter 100. The filter 100 further has a plurality of filter characteristics 108. These plurality of filter characteristics 108 include a first filter characteristic 110, a second filter characteristic 112, and a third filter characteristic 114. The plurality of filter characteristics 108 may be assumed to include a smaller number or a larger number of filter characteristics. The evaluation device 106 determines, depending on the input signal characteristics of the filter input variable 102, from the plurality of filter characteristics 108, the filter characteristics to be used for processing the filter input variable 102 by the filter 100. The filter output variable 104 is determined depending on the filter input variable 102 and the filter characteristics of the filter 100 specified by the filter 100. The input signal characteristics are determined by the evaluation device 106 depending on the filter input variable 102 at the current time point and at least one preceding time point.

[0024] Filter 100 is operated by the first filter characteristic 110 when the filter input variable 102 alternates between two quantization values ​​by only the mean value. The upper and lower quantization values ​​are limits for the noise band and define the width of the noise band. The first filter characteristic 110 causes the filter output variable 104 to be placed at the mean value of the noise band when the filter input variable 102 is within the noise band. Therefore, the first filter characteristic 110 causes the filter output variable 104 to remain at a gradually constant value and does not have the alternating characteristic of the filter input variable 102.

[0025] Filter 100 is operated by a second filter characteristic 112 when the filter input variable 102 has dynamic characteristics. The filter input variable 102 is further near the average value of the noise band, but tends to either leave the noise band or enter the noise band. In this case, the second filter characteristic 112 gives filter 100 a first-order low-pass characteristic.

[0026] Filter 100 is operated by a third filter characteristic 114 when the filter input variable 102 moves continuously away from the noise band and has very dynamic characteristics. In this case, the third filter characteristic 114 gives filter 100 the characteristics of a pass-through element. Filter 100 connects the filter input variable 102 directly to the filter input variable 102 by the third filter characteristic 114.

[0027] Furthermore, it is conceivable that the multiple filter characteristics 108 include further characteristics of the signal processing structure or function, such as bandpass characteristics, inverter characteristics, or differently configured filter characteristics of the same category.

[0028] Figure 2 shows a schematic diagram of the state graph 200 for filter 100. This state graph includes operating states 202, 204, 206, 208, and 210. These operating states 202 to 210 are mapped by filter 100 and a plurality of filter characteristics 108.

[0029] In the first operating state 202, the filter input signal 102 remains within the noise band, and the filter 100 is operated according to the first filter characteristic 110. Therefore, the filter output variable 104 is set to the average value of the noise band.

[0030] In the second operating state 204, the filter input signal 102 tends to move away from the noise band, and the filter 100 is operated by the second filter characteristic 112. Therefore, the filter output variable 104 is the low-pass filtered filter input variable 102.

[0031] In the third operating state 206, the filter input signal 102 tends to fall into the noise band, and the filter 100 is operated by the second filter characteristic 112. Therefore, the filter output variable 104 is the low-pass filtered filter input variable 102.

[0032] In the fourth operating state 208, the filter input variable 102 is located outside the noise band and moves continuously away from it, and the filter 100 is operated by the third filter characteristic 114. Therefore, the filter input signal 102 is directly connected to the filter output variable 104, and as a result, no filtering is performed.

[0033] In the fifth operating state 210, the filter input signal 102 no longer has the dynamic characteristics of the fourth operating state 206 and begins to approach the noise band, and the filter 100 is operated by the second filter characteristics 112. Therefore, the filter output variable 104 is the low-pass filtered filter input variable 102.

[0034] Depending on the operating state, the average value of the noise band is updated accordingly, and as a result, the noise band shifts in accordance with the signal progression of the filter input variable 102. This update occurs in operating states 206, 208, and 210. The state graph 200 shows the following characteristics of the filter 100. In the first operating state 202, the filter error e = |in - out| (which is calculated from the absolute value obtained by subtracting the filter output variable 104 from the filter input variable 102) shifts within the noise band. In the first operating state 202, the filter error e is defined by the width of the noise band. In this example, the first operating state 202 is only achievable starting from the third operating state 206 and the fifth operating state 210, in particular, when the average value of the noise band is updated to the current variable of the filter output variable 104, thereby allowing the input signal 102 to remain as close to the center of the noise band as possible in the first operating state 202. Here, it may be assumed that the width of the noise band is used as an application parameter of the filter 100. In the fourth operating state 208, the filter input variable 102 is placed in the filter output variable 104, and therefore the filter error e = 0. In the second operating state 204, the third operating state 206, and the fifth operating state 210, an additional check is performed on the deviation between the filter input variable 102 and the filter output variable 104. This deviation is the defined maximum filter error e. m If it is greater than, the filter output variable 104 is the defined maximum filter error e m It is adapted to the low-pass filter characteristics of the second filter characteristic 112 by appropriately selected coefficients, so that the filter error e is the maximum filter error e m It becomes possible to remain within the range. In this case, testing for deviation is unnecessary.

[0035] The structure and algorithm of filter 100 are illustrated below. This structure is based on the state graph and operating states 202 to 210 in Figure 2, and in particular, the transition conditions for each operating state 202 to 210 and the practice of filter characteristics 110 to 114 are shown. This structure can be implemented, for example, by embedded software.

[0036] Variables and parameters: -Filter input variable 102: 1. u(k), u(k-1): Current or preceding sampling value of the filter input variable 102 to be filtered. -Filter output variable 104: 1. y(k), y(k-1): Current or preceding sampling value of the filter output variable 104 -Internally determined application parameters: 1. ∈: width of the noise bandwidth 2. β∈(1,3): Applicable parameter for slowly changing filter input variable 102 3. α∈(0,1): coefficients of a first-order low-pass filter 4.e m : Maximum allowable filter error 5.d: Application parameter greater than the maximum difference of the filter input variables in the sampling step -Internal variables: 1. m(k), m(k-1): Current or preceding average value of the noise band. 2. D(k), D(k-1): The distance between the current or preceding sample value of the filter input variable 102 and the preceding mean value of the noise band. Therefore, D(k) = u(k) - m(k-1) or D(k-1) = u(k-1) - m(k-1) applies.

[0037] Conditions for transitioning to corresponding operation states 202 to 210 and the corresponding triggered events: -Operation status 202: 1. Conditions: |D(k-1)| < ∈ and |D(k)| < ∈ 2. Event: y(k)=y(k-1), followed by m(k)=m(k-1) -Operation status 204: 1. Conditions: (|D(k-1)|≦∈ and |D(k)|≧∈) or (|D(k)|>∈ and |D(k-1)|≦β*∈ and ||D(k)|-|D(k-1)||≦∈) 2. Event: y(k) = α * u(k) + (1 - α) * y(k - 1) + sgn(y(k - 1) - u(k)) * min(e m - (1 - α) * |y(k - 1) - u(k)|, 0), where sgn(.) is the sign function and min(.) takes the smaller value of the two expressions, and subsequently m(k) = m(k - 1). - Operating state 206: 1. Condition: |D(k - 1)| ≥ ∈ and |D(k)| < ∈ 2. Event: y(k) = α * u(k) + (1 - α) * y(k - 1) + sgn(y(k - 1) - u(k)) * min(e m - (1 - α) * |y(k - 1) - u(k)|, 0), and subsequently m(k) = y(k). - Operating state 208 1. Condition: (|D(k - 1)| ≤ |D(k)| and |D(k - 1)| > β * ∈) or (|D(k - 1)| > ∈ and |D(k)| - |D(k - 1)| > ∈) 2. Event: y(k) = u(k), and subsequently m(k) = u(k) - sgn(D(k)) * d - Operating state 210: 1. Condition: (|D(k - 1)| > |D(k)| and |D(k)| ≥ ∈ and |D(k - 1)| > β * ∈) or (|D(k - 1)| - |D(k)| > ∈ and |D(k)| ≥ ∈) 2. Event: y(k) = α * u(k) + (1 - α) * y(k - 1) + sgn(y(k - 1) - u(k)) * min(e m - (1 - α) * |y(k - 1) - u(k)|, 0), and subsequently m(k) = y(k).

[0038] Filter 100 is parameterized by the application parameters ∈, β, α, e m and d. The application parameter ∈ for the width of the noise band and the application parameter β are used as parameters for determining the input signal characteristics of the filter input variable 102. The application parameter α is used as the coefficient of the low-pass filter characteristic of the second filter characteristic 112, whereby this filter characteristic is parameterized. The application parameter e for the maximum filter error mSimilarly, the applied parameter d is used as an application parameter for the second filter characteristic 112. The applied parameter d is used as a parameter for the third filter characteristic 114 to update the average value of the noise band. The filter 100 is adapted to different scenarios and application fields using the applied parameters.

[0039] Figure 3 shows a flowchart 300 of a method for determining the filter output variable 104 of filter 100. In step 302, the filter input variable 102 is provided to filter 100 and the input signal characteristics are determined.

[0040] The input signal characteristics are determined depending on the filter input variable 102 at the current time and at least one preceding time.

[0041] The input signal characteristics may be assumed to be determined by at least one applied parameter, for example, the noise bandwidth ∈ and / or an applied parameter relating to the rate of change of the filter input variable 102.

[0042] In step 304, the preset filter characteristics of the filter 100 are selected from a plurality of preset filter characteristics 108, depending on the input signal characteristics of the filter input variable 102.

[0043] Preferably, the filter characteristics 108 include a first filter characteristic 110, a second filter characteristic 112, and a third filter characteristic 114, where the first filter characteristic 110 of the filter 100 places the filter output variable 104 at the center point of the filter input variable 102, particularly at the center point of the noise band. The second filter characteristic 112 causes the filter 100 to operate as a low-pass filter. The third filter characteristic 114 causes the filter 100 to operate as a pass-through element.

[0044] Preferably, the preset filter characteristics of the filter 100 are parameterized by at least one application parameter. The at least one application parameter may be assumed to be the low-pass filter coefficient and / or the maximum allowable filter error.

[0045] Here, if the filter input variable 102 for the input signal characteristics remains within the width of the noise bandwidth, a first operating state 202 of the filter 100 is determined, and in this case, it is assumed that the filter 100 is operated by the first filter characteristic 110. If the filter input variable 102 for the input signal characteristics tends to move away from the width of the noise bandwidth, a second operating state 204 of the filter 100 is determined, and in this case, the filter is operated by the second filter characteristic 112. If the filter input variable 102 for the input signal characteristics tends to enter the width of the noise bandwidth, a third operating state 206 of the filter 100 is determined, and in this case, the filter is operated by the second filter characteristic 112. If the filter input variable 102 for the input signal characteristics is outside the width of the noise bandwidth and moves continuously away from it, a fourth operating state 208 of the filter 100 is determined, and in this case, the filter is operated by the third filter characteristic 114. When the filter input variable 102 for the input signal characteristics lies outside the width of the noise band and begins to approach the noise band, a fifth operating state 210 of the filter 100 is determined, in which case the filter 100 is operated by the second filter characteristic 112.

[0046] In step 306, the filter output variable 104 is determined by a filter 100 having pre-set filter characteristics.

[0047] Filter 100 is used, for example, to filter out the torsion bar moment as a filter input variable 102 in a steer-by-wire steering system.

[0048] In this example, filter 100 is configured as a torsion bar moment filter in the context of manual moment closed-loop control of a steer-by-wire steering system. Filter 100 is used, for example, to smooth or filter out torsion bar moments containing quantization noise.

[0049] Figure 4 shows a vehicle 400 equipped with a steer-by-wire steering system including a steering unit 402 and a manual moment adjuster 404.

[0050] In this example, the vehicle 400 includes two rear wheels 406 and two front wheels 408. In this example, the rear wheels 406 are not steerable. In this example, the front wheels 408 are steerable by a steering unit 402.

[0051] Here, the rear wheels 406 may be steerable by the steering section of the rear axle, either in addition to or instead of the front wheels 408.

[0052] The manual moment adjuster 404 accepts the driver's direction setting and generates a steering feel for the driver. To generate the steering feel, the manual moment adjuster 404 includes a motor 410, which outputs a corresponding motor moment to the rotor shaft 412, and this motor moment is then transmitted to the steering control unit 418 via a gear 414 and a torsion bar 416. A steering wheel is shown as an example of the steering control unit 418.

[0053] Given that the motor 410 is located relatively close to the driver, this could result in acoustically and tactilely distinctive characteristics for the driver. In fact, if the motor 410 is driven and controlled by a strong noise signal, these characteristics could increase to an unacceptable level of disruption.

[0054] According to filter 100 and the filtering method, acoustic and tactile characteristics are significantly improved without significantly degrading residual control quality.

[0055] Figure 5 shows a control loop comprising a closed-loop controller 502 and a filter 100 for closed-loop control of a manual moment adjuster 404. Closed-loop control using the closed-loop controller 502 is based on the actual moment 504, in this example, the torsion bar moment at the torsion bar 416, and a set target moment 506, in this example, the desired torsion bar moment.

[0056] The closed-loop controller 502 determines an appropriate motor moment 508 to control the target moment 504 in a closed loop, even in the presence of an obstacle 510, such as an intervention operation by the driver or a model deviation. As shown in Figure 5, the filtered input signal 102 is based on the actual moment 504 and basically contains noise due to noise 512.

[0057] In this example, specific quantization noise is considered. Expensive measurement techniques may reduce the effects of noise, but they can never completely compensate for it. The closed-loop controller 502 itself can be configured to take into account the effects of noise 512. However, this typically means that the control characteristics will be negatively affected with respect to other criteria, such as performance, and thus a contradiction in objectives may arise.

[0058] A common procedure for processing noise signals is to use corresponding filters. Conventional filters have low-pass characteristics to compensate for high-frequency noise components, but they introduce an additional phase shift to the system. Therefore, further compromises are needed regarding noise filtering and phase delay to avoid significantly degrading the system's stability characteristics due to the additional phase.

[0059] In this process, a case-dependent filter 100 is used to significantly reduce quantization noise and limit filter errors to a defined range without introducing a large phase delay. The filter output variable 104 is, in this example, a feedback signal for a closed-loop controller 502. This closed-loop controller 502 uses this feedback signal and a target moment 506 to determine the motor moment 508.

[0060] Typically, when the steering wheel of a steer-by-wire steering system is stationary, i.e., when the torsion bar moment does not change significantly, the filter 100 is operated by the first filter characteristic 110, where the torsion bar moment, i.e., the filter input variable 102, alternates between two quantized values ​​by an average value. When the characteristics of the torsion bar moment change, the input characteristics in the filter 100 also change. As a result, the filter characteristics are switched based on the input signal characteristics as described above. The filter output variable 104 is thus dynamically adapted.

Claims

1. A method (300) for determining a filter output variable (104) of a filter (100) for filtering the torsion bar moment of a vehicle's steer-by-wire steering system, depending on a filter input variable (102) to be filtered, Step (304) of selecting a preset filter characteristic of the filter (100) from a plurality of preset filter characteristics (108) depending on the input signal characteristics of the filter input variable (102), Step (302) in which the input signal characteristics are determined depending on the current sampling value of the filter input variable (102) at the present time and the preceding sampling value of the filter input variable (102) at a preceding time, The filter output variable (104) is determined by the filter (100) having the filter characteristics (306), A method (300) characterized by including the following.

2. The plurality of preset filter characteristics (108) include a first filter characteristic (110), a second filter characteristic (112), and a third filter characteristic (114). Due to the first filter characteristic (110) of the filter (100), the filter output variable (104) is placed at the center point of the noise band. Due to the second filter characteristic (112) of the filter (100), the filter (100) is made to operate as a low-pass filter. The method according to claim 1 (300), wherein the filter (100) is made to operate as a pass-through element due to the third filter characteristic (114) of the filter (100).

3. The method according to claim 1 (300), wherein the preset filter characteristics of the filter (100) are parameterized depending on at least one application parameter.

4. The method according to claim 3 (300), wherein the at least one application parameter for the preset filter characteristics characterizes the low-pass filter coefficient and / or the maximum allowable filter error.

5. The method according to claim 1 (300), wherein the input signal characteristics are determined depending on at least one application parameter.

6. The method according to claim 5 (300), wherein the applied parameter for the input signal characteristics of the filter input variable (102) characterizes the width of the noise bandwidth of the filter input variable (102) and / or the rate of change of the filter input variable (102).

7. The filter input variable (102) for the input signal characteristics is, If the noise remains within the width of the noise bandwidth, the first operating state (202) of the filter (100) is determined, and the first filter characteristics (110) are determined for the filter (100). If a tendency to deviate from the width of the noise bandwidth is observed, a second operating state (204) of the filter (100) is determined, and the second filter characteristics (112) are determined for the filter (100). If a tendency to fall within the noise bandwidth is observed, a third operating state (206) of the filter (100) is determined, and the second filter characteristic (112) is determined for the filter (100). If the noise is located outside the width of the noise band and moves continuously away from it, a fourth operating state (208) of the filter (100) is determined, and the third filter characteristic (114) is determined for the filter (100). The method according to claim 2 (300), wherein a fifth operating state (210) of the filter (100) is determined when it is outside the width of the noise band and begins to approach the noise band, and the second filter characteristic (112) is determined for the filter (100).

8. The method according to claim 1, wherein the torsion bar moment (504) is measured, the filter input variable (102) to be filtered is determined depending on the measured torsion bar moment (504), and the motor moment (508) for the steer-by-wire steering system is determined depending on the filter output variable (104) and a target moment (506) for the torsion bar moment.

9. In a device for determining the filter output variable (104) of a filter (100) for filtering the torsion bar moment of a vehicle's steer-by-wire steering system, depending on the filter input variable (102) to be filtered, The aforementioned device is The preset filter characteristics of the filter are selected from a plurality of preset filter characteristics (108) depending on the input signal characteristics of the filter input variable (102). The input signal characteristics are determined depending on the current sampling value of the filter input variable (102) at the present time and the preceding sampling value of the filter input variable (102) at a preceding time. The filter output variable (104) is determined by the filter (100) having the filter characteristics. An apparatus characterized by being configured in such a way.

10. The plurality of preset filter characteristics (108) include a first filter characteristic (110), a second filter characteristic (112), and a third filter characteristic (114). The aforementioned device is Using the first filter characteristic (110) of the filter (100), the filter output variable (104) is placed at the center point of the noise band. Using the second filter characteristic (112) of the filter (100), the filter (100) is operated as a low-pass filter. Using the third filter characteristic (114), the filter (100) is operated as a pass-through element. The apparatus according to claim 9, configured as described above.

11. The apparatus according to claim 9, wherein the apparatus is configured to parameterize the preset filter characteristics of the filter (100) depending on at least one application parameter.

12. The apparatus according to claim 9, wherein at least one application parameter for the preset filter characteristics characterizes the low-pass filter coefficient and / or maximum filter error.

13. The apparatus according to claim 9, wherein the apparatus is configured to determine the input signal characteristics depending on at least one applicable parameter.

14. The apparatus according to claim 13, wherein the at least one application parameter for the input signal characteristics of the filter input variable (102) characterizes the width of the noise bandwidth of the filter input variable (102) and / or the rate of change of the filter input variable (102).

15. The aforementioned device is The filter input variable (102) for the input signal characteristics is, If the noise remains within the width of the noise bandwidth, the first operating state (202) of the filter (100) is determined, and the first filter characteristics (110) are determined for the filter (100). If a tendency to deviate from the width of the noise bandwidth is observed, a second operating state (204) of the filter (100) is determined, and the second filter characteristics (112) are determined for the filter (100). If a tendency to fall within the noise bandwidth is observed, a third operating state (206) of the filter (100) is determined, and the second filter characteristic (112) is determined for the filter (100). If the noise is located outside the width of the noise band and moves continuously away from it, a fourth operating state (208) of the filter (100) is determined, and the third filter characteristic (114) is determined for the filter (100). When the noise is outside the width of the noise band and begins to approach the noise band, a fifth operating state (210) of the filter (100) is determined, and the second filter characteristic (112) is determined for the filter (100). The apparatus according to claim 10, configured as described above.

16. In vehicles, The vehicle includes the device described in claim 9, The aforementioned device is The torsion bar moment (504) was measured, The filter input variable (102) to be filtered is determined depending on the measured torsion bar moment (504), The motor moment (508) for the steer-by-wire steering system is determined depending on the filter output variable (104) and the target moment (506) for the torsion bar moment (504). A vehicle characterized by being configured in such a way.

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