METHOD FOR ADJUSTING A MOTOR TORQUE OF A MOTOR OF AN ELECTRIC BICYCLE AND ASSOCIATED DEVICE FOR ADJUSTING A MOTOR TORQUE

Abstract

A method for adjusting a motor torque of a motor of an electric bicycle. The method includes a detection of a speed signal, which describes a speed of the bicycle, a selection of a filter parameter for a filter unit based on a dynamics of the speed signal, a filtering of the speed signal by the filter unit by applying the selected filter parameter, and an ascertainment of a motor torque based on the filtered speed signal. An associated device is also described.

Claims

1. A method for adjusting a motor torque of a motor of an electric bicycle, comprising the following steps: detecting a speed signal, which describes a speed of the bicycle; selecting a filter parameter for a filter unit based on dynamics of the speed signal; filtering the speed signal by the filter unit by applying the selected filter parameter; and ascertaining a motor torque based on the filtered speed signal.

2. The method as recited in claim 1, wherein the dynamics of the speed signal are described by an acceleration of the bicycle.

3. The method as recited in claim 1, wherein the filter unit includes a low-pass filter.

4. The method as recited in claim 1, wherein the filter parameter is selected in such a way that the speed signal is filtered to a lesser degree in a case of a first dynamics than in a case of a second dynamics, the first dynamics being greater than the second dynamics.

5. The method as recited in claim 1, wherein, above a predefined first dynamics limit value, the filter parameter is set to a minimum value, at which, for the filter unit, a minimal filtering or no filtering of the speed signal occurs.

6. The method as recited in claim 1, wherein the filter parameter is selected as a function of an acceleration of the bicycle in such a way that a degree of filtering of the speed signal rises over time when the acceleration is below a second dynamics limit value; and a degree of filtering of the speed signal falls over time when the acceleration is above the second dynamics limit value.

7. The method as recited in claim 6, wherein the first dynamics limit value corresponds to a higher acceleration than the second dynamics limit value.

8. The method as recited in claim 1, wherein in the ascertainment of the motor torque based on the filtered speed signal, the motor torque is ascertained based on an assistance characteristic curve.

9. The method as recited in claim 8, wherein the assistance characteristic curve defines an assistance factor over a speed.

10. A device for adjusting a motor torque of a motor of an electric bicycle, the device configured to: detect a speed signal, which describes a speed of the bicycle; select a filter parameter for a filter unit based on a dynamics of the speed signal; filter the speed signal by the filter unit by applying the selected filter parameter; and ascertain a motor torque based on the filtered speed signal.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Exemplary embodiments of the present invention are described in detail below with reference to the figures.

[0025] FIG. 1 is an illustration of an electric bicycle including a device for adjusting a motor torque of a motor of the electric bicycle, in accordance with an example embodiment of the present invention.

[0026] FIG. 2 is a flow chart of a method according to an example embodiment of the present invention for adjusting a motor torque of a motor of an electric bicycle,

[0027] FIG. 3 shows a representation of an exemplary assistance characteristic curve, in accordance with an example embodiment of the present invention.

[0028] FIG. 4 shows a signal flow chart, which allows for an implementation of the method for adjusting a motor torque of a motor of a bicycle, in accordance with an example embodiment of the present invention.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

[0029] FIG. 1 shows a bicycle 1, which comprises a device 2 for adjusting a motor torque of a motor of the electric bicycle 1. The device 2 is an electronic control unit of a motor of the electric bicycle 1. Device 2 is configured to carry out the method 100 according to the present invention for adjusting a motor torque of a motor of an electric bicycle 1.

[0030] FIG. 2 shows a flow chart of the method 100 for adjusting a motor torque of a motor of the electric bicycle 1.

[0031] If method 100 is triggered, initially a first method step 101 is carried out. In the first method step 101, a speed signal 10 is detected that describes a speed of the bicycle 1. The speed signal 10 is here in particular an output signal of a speed sensor, for example of a reed sensor. Thus, speed signal 10 is for example an analog signal, which has an amplitude that describes the speed of bicycle 1. Thus, there is for example a linear relationship between the amplitude of speed signal 10 and the speed of electric bicycle 1. In alternative specific embodiments, speed signal 10 is a digital signal.

[0032] Following the performance of the first method step 101, a second method step 102 is carried out. In second method step 102, a filter parameter is selected for a filter unit 11, based on a dynamics of the speed signal. Thus, in second method step 102, at least one filter parameter T is selected or generated, which is supplied to filter unit 11. The filter unit 11 is in this specific embodiment a low-pass filter, through which the speed signal 10 is filtered. By way of filter parameter T, a filter characteristic of filter unit 11, here of the low-pass filter, is adjusted. In the process, in particular a damping value of the low-pass filter is adjusted by filter parameter T.

[0033] The dynamics of speed signal 10 are fundamentally a variability of the speed signal. In the specific embodiment described here, the dynamics of the speed signal are defined by an acceleration of the electric bicycle 1. Speed signal 10 thus rises sharply in the event of a sharp acceleration, which results in a sharp change of speed signal 10. There thus exists a high dynamics of the speed signal. It should be noted, however, that it is alternatively also possible to utilize other values describing a dynamics of the speed signal for the purpose of selecting the filter parameter. Thus, speed signals contain frequency components for example, which result from a cadence of a rider of bicycle 1. The dynamics could also be selected in such a way, for example, that they describe a variability of the frequencies of the speed signal 10.

[0034] Filter parameter T is selected in such a way that speed signal 10 is filtered to a lesser degree in the case of a first dynamics than in the case of a second dynamics, where the first dynamics is greater than the second dynamics. This has the result that speed signal 10 is filtered less in the case of a high dynamics, whereby, for example, a precise adherence to limit values in a subsequent ascertainment of a motor torque is ensured. In the specific embodiment described here, two dynamics limit values are defined, whereby a bandwidth of possible values describing the dynamics of the speed signal is subdivided into three ranges. Thus, a first dynamics limit value and a second dynamics limit value are defined. The first dynamics limit value corresponds to a higher acceleration than the second dynamics limit value.

[0035] Above the first dynamics limit value, that is, when the dynamics of the speed signal are greater than the first dynamics limit value, the filter parameter T is set to a minimum value, at which a, for the filter unit, minimal filtering or no filtering of the speed signal 10 occurs. Thus, for example, a damping of the damping range of the low-pass filter is set to zero. This corresponds to a state, in which the low-pass filter is deactivated. This ensures that at a very high dynamics of the speed signal, no change occurs in speed signal 10, before the latter is used for ascertaining the motor torque.

[0036] If the dynamics of the speed signal are between the first dynamics limit value and the second dynamics limit value, then the filter parameter T is set in such a way that it decreases over time. This ensures that a filtering of speed signal 10 is not ended abruptly, which could result in an uncomfortable sensation for the rider.

[0037] If the dynamics of speed signal 10 are below the second dynamics limit value, then a degree of the filtering of speed signal 10 rises over time. This means that over time a particularly strong filtering of speed signal 10 is achieved by the low-pass filter. It is thus ensured that especially in rides at continuous speed, a strong filtering of speed signal 10 occurs, which also entails a particularly continuous assistance of the rider, that is, a particularly continuous result in an ascertainment of the motor torque. Thus, as particularly comfortable riding experience is achieved in rides at continuous speeds.

[0038] In a third method step 103, which follows the selection of filter parameter T for filter unit 11 in the second method step 102, speed signal 10 is filtered by filter unit 11 by applying the selected filter parameter T. Speed signal 10 is thus first analyzed in order to determine a filter parameter T for filter unit 11 and is subsequently filtered accordingly by filter unit 11. In the process, the unwanted signal components are filtered out of speed signal 10. Speed signal 10 is thus provided at an input of filter unit 11. A filtered speed signal 12 is output at an output of filter unit 11.

[0039] Following the third method step 103, a fourth method step 104 is carried out. In fourth method step 104, a motor torque is ascertained on the basis of the filtered speed signal 12. For this purpose, the motor torque of the motor of the electric bicycle 1 is ascertained on the basis of an assistance characteristic curve. The assistance characteristic curve 20 defines an assistance factor S over a speed of bicycle 1.

[0040] An exemplary assistance characteristic curve 20 is shown in FIG. 3. The assistance characteristic curve 20 thus defines to what degree the motor torque of the motor should assist the bicycle torque. It can be seen, for example, that in a low speed range, for example below 23 km/h, an assistance factor S of “1” should be selected. This means that a rider torque applied by the rider is multiplied by the assistance factor S of the value “1” in order to calculate the motor assistance, in particular the motor torque, to be provided. Following the exemplary limit speed of 23 km/h, assistance factor S decreases in accordance with a ramp and at a speed of approx. 26 km/h drops to the value zero. In this range, the assistance factor S drops from a value of “1” to a value of “0”. This means that above the limit of 26 km/h, no assistance is provided to the driver by a motor torque of the motor. In an intermediary range, that is, in the range from 23 to 26 km/h, the assistance of the rider by the motor is reduced in linear fashion. Assistance characteristic curves 20 of this kind are described in the related art. According to the present invention, the motor torque and here therefore also the assistance factor are ascertained on the basis of the filtered speed signal 12, however, and not based on the speed signal, which was initially detected by the sensor. This has the effect that in a continuous propulsion of the electric bicycle 1, signal components are removed from speed signal 10 that would result in a selection of assistance factor S, which may be experienced as uncomfortable.

[0041] FIG. 4 shows a signal flow chart, by which method 100 may be implemented accordingly. Thus, FIG. 4 shows that the speed signal 10 is provided on the input side. Speed signal 10 was detected by a sensor, for example. The speed signal 10 is provided directly to filter unit 11, which is a low-pass filter. In parallel, a derivation of speed signal 10 is formed in order to ascertain the dynamics of speed signal 10. In this example, the speed v written by speed signal 10 is transformed into acceleration a. Based on the acceleration a, the filter parameter T is calculated in a calculation electronics system 13 from the acceleration a. In the process, filter parameter T is calculated dynamically. Filter parameter T may also be designated a filter constant. The filter parameter T is supplied to filter unit 11 and a filter characteristic of the filter unit 11 is adjusted. The speed signal 10 is filtered in accordance with the selected filter characteristic of filter unit 11 and is provided by filter unit 11 on the output side. The filtered speed signal 12 is used to calculate an assistance factor S.

[0042] Thus, for example, an ascertainment unit 14 reads out the assistance factor S from the assistance characteristic curve shown in FIG. 3. The motor torque of the motor of the electric bicycle 1 is adjusted in accordance with the read-out assistance factor S. The motor torque is calculated for example from the bicycle torque, the assistance factor F and the factor of a speed cut-off.

[0043] With the aid of method 100, a uniform assistance of the rider at the cut-off limit is thus achieved even in the event of slight fluctuations in the speed signal.

[0044] In some situations, a simple and non-dynamic low-pass filtering of the speed signal will also result in a uniform assistance of the rider at the cut-off limit. However, the associated phase delay of the signal results in a delayed suspension of the assistance. Adherence to the regulatory norms is therefore not possible. For this reason, a concept including a dynamic low-pass filtering of the speed signal is created by method 100.

[0045] For this purpose, filter constant T of the low-pass filter varies in accordance with the dynamics of speed signal 10. The following behavior is to be achieved:

[0046] a) In the case of high dynamics of the speed signal (intense acceleration or braking processes), no or little filtering of speed signal 10.

[0047] b) In the case of no or low dynamics of the speed signal 10 (constant travel), strong filtering of the speed signal 10.

[0048] The speed signal 10 is filtered using filter constant T. This is limited to Tmax (maximum filtering) and Tmin (no filtering). An acceleration level is calculated from the speed signal. Above a specific acceleration level a.sub.limit, it is always the case that T=Tmin. This ensures that the regulatory provisions are maintained for great accelerations at the cut-off limit and that in the event of intense braking above the cut-off limit, the assistance sets in again as quickly as possible.

[0049] Below a.sub.limit, the filter constant T is varied dynamically. At a low acceleration level, the filter constant rises over time, at a higher acceleration level, the filter constant falls over time. During uniform rides, this results in a smoother speed signal 10 and thus results in a more uniform assistance of the rider at the cut-off limit.

[0050] In addition to the above written disclosure, explicit reference is made to the disclosure of FIGS. 1 through 4.