METHOD AND DRIVE SYSTEM FOR ADAPTING A DRIVE ASSIST BY AN ELECTRIC DRIVE MOTOR OF AN ELECTRICALLY DRIVABLE BICYCLE

Abstract

A method and a drive system for adapting a drive assist by an electric drive motor of an electrically drivable bicycle. The method includes: ascertaining an instantaneous rider torque exerted by a rider of the bicycle on a drive train of the bicycle, ascertaining rider torque statistics based on a plurality of rider torques ascertained over time, ascertaining an assignment rule between the rider torque statistics and a predefined target load spectrum for the bicycle, the assignment rule approximating the rider torque statistics to the target load spectrum, establishing a motor torque corresponding to the instantaneous rider torque, based on the assignment rule, and operating the electric drive by specifying the ascertained motor torque.

Claims

1. A method for adapting a drive assist by an electric drive motor of an electrically drivable bicycle, comprising the following steps: ascertaining an instantaneous rider torque exerted by a rider of the bicycle on a drive train of the bicycle; ascertaining rider torque statistics based on a plurality of rider torques ascertained over time; ascertaining an assignment rule between the rider torque statistics and a predefined target load spectrum for the bicycle, the assignment rule approximating the rider torque statistics to the target load spectrum; ascertaining a motor torque corresponding to the instantaneous rider torque, based on the assignment rule; and operating the electric drive motor by specifying the ascertained motor torque.

2. The method as recited in claim 1, wherein: the rider torque statistics are ascertained only when the instantaneous rider torque exceeds a first predefined rider torque threshold value; and/or standard rider torque statistics or rider torque statistics ascertained from a usage history of the bicycle are used as rider torque statistics, provided that in a present utilization period of the bicycle: a minimum number of rider torques necessary for ascertaining the rider torque statistics is not yet present, and/or an idle period of the bicycle exceeds a predefined first time period, and/or a change of riders has been ascertained.

3. The method as recited in claim 1, wherein: the rider torque statistics are computed as an arithmetic average value or as a sliding average value over a number of ascertained rider torques; and the number of rider torques included in the computation is established as a function of: a presently ascertained rider torque, and/or a position of the bicycle, and/or a route, and/or a minimum speed, and/or a distance covered, and/or a second predefined time period.

4. The method as recited in claim 1, wherein: at least the step of operating the electric drive motor is carried out by specifying the ascertained motor torque only when the instantaneous rider torque exceeds the first rider torque threshold value; and/or using the assignment rule, it is ensured that the target load spectrum is not exceeded.

5. The method as recited in claim 1, wherein the target load spectrum and/or the assignment rule between the rider torque statistics and the target load spectrum is adapted as a function of: a rider cadence and/or a rider cadence profile, and/or an ambient temperature, and/or a temperature of one or multiple component(s) of the drive train of the bicycle, and/or a rider identification, and/or a position of the bicycle, and/or a route and/or a route plan, and/or an age and/or a cumulative operating period of the bicycle, and/or a selected riding mode for the bicycle.

6. The method as recited in claim 1, wherein the ascertaining of the assignment rule between the rider torque statistics and the target load spectrum takes place based on the following steps: ascertaining a first histogram that represents the rider torque statistics in the form of a distribution density of rider torques that have been ascertained over time; and assigning an unassigned class or multiple neighboring unassigned classes of a second histogram, which represents the target load spectrum in the form of a distribution density of maximum motor torques that are to be used, to an unassigned class or multiple unassigned neighboring classes of the first histogram until all classes of the first histogram are assigned.

7. The method as recited in claim 6, wherein: the assignment of particular classes of the second histogram with particular classes of the first histogram takes place in sequence, starting with those classes of the first and second histograms that represent highest torques in each case, to those classes of the first and second histograms that represent lowest torques in each case, and/or the first and second histograms each have a uniform normalization.

8. The method as recited in claim 6, wherein: for each assignment within the assignment rule, a) a sum of values of classes of the first histogram involved in the assignment does not exceed a sum of values of classes of the second histogram involved in the assignment, b) a number of classes of the second histogram involved in the assignment corresponds to a minimum number of classes necessary to fulfill a), c) a number of classes of the first histogram involved in the assignment corresponds to the maximum possible number for fulfilling a); and for a case in which two or more classes of the second histogram are assigned to an individual class of the first histogram, a value of that class from the second histogram that represents a lowest torque is selected as the motor torque that corresponds to the instantaneous rider torque.

9. The method as recited in claim 1, wherein: the assignment rule is formed by a function that is defined in segments, and that includes a first segment in which rider torques that do not exceed an average rider torque are mapped onto corresponding motor torques, the average rider torque being mapped onto an average motor torque, includes a second segment in which rider torques that exceed the average rider torque are mapped onto corresponding motor torques, a maximum rider torque being mapped onto a maximum motor torque, the average motor torque and the maximum motor torque are ascertained based on the target load spectrum of the bicycle, the maximum rider torque is a highest rider torque that is ascertained within a third predefined time period or within a predefined distance, a first segment of the function and/or a second segment of the function is formed in each case by a linear term and/or a nonlinear term, and the function includes a continuous transition between the first segment and the second segment.

10. The method as recited in claim 9, wherein the motor torque is additionally ascertained as a function of: an assistance factor that is established based on a rider preference and that is in a value range of 0<u≤4, and/or a first correction factor that influences the first segment of the function and that is used to adapt riding dynamics, and/or a second correction factor that influences the second segment of the function and that is used to adhere to the target load spectrum.

11. A drive system for an electrically drivable bicycle, comprising: an electric drive motor; a torque sensor; and an evaluation unit configured to: ascertain, using the torque sensor, an instantaneous rider torque exerted by a rider of the bicycle on a drive train of the bicycle, ascertain rider torque statistics based on a plurality of rider torques ascertained over time, ascertain an assignment rule between the rider torque statistics and a predefined target load spectrum for the bicycle, the assignment rule approximating the rider torque statistics to the target load spectrum, ascertain a motor torque, corresponding to the instantaneous rider torque, based on the assignment rule, and operate the electric drive motor by specifying the ascertained motor torque.

12. The drive system as recited in claim 11, wherein: the rider torque statistics are ascertained only when the instantaneous rider torque exceeds a first predefined rider torque threshold value; and/or standard rider torque statistics or rider torque statistics ascertained from a usage history of the bicycle are used as rider torque statistics, provided that in a present utilization period of the bicycle: a minimum number of rider torques necessary for ascertaining the rider torque statistics is not yet present, and/or an idle period of the bicycle exceeds a predefined first time period, and/or a change of riders has been ascertained.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

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

[0025] FIG. 1 shows a flowchart that illustrates steps of a method according to an example embodiment of the present invention.

[0026] FIG. 2 shows an example of a distribution density of rider torques and motor torques, and an example of an assignment of their respective classes.

[0027] FIG. 3 shows examples of assignment functions between rider torques and corresponding motor torques for riders with different performance capabilities.

[0028] FIG. 4 shows a schematic overview of components of a drive system according to an example embodiment of the present invention for an electrically drivable bicycle.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

[0029] FIG. 1 shows a flowchart that illustrates steps of a method according to the present invention for adapting a drive assist by an electric drive motor 10 of an electrically drivable bicycle.

[0030] In step 100 of the method according to the present invention, with the aid of a torque sensor 20 an instantaneous rider torque M.sub.rider exerted by a rider of the bicycle on a drive train of the bicycle is ascertained by an evaluation unit 30, which in the present case is a microcontroller of the drive train of the bicycle. The ascertaining takes place cyclically at a predefined frequency of 10 Hz. For subsequent processing, rider torques M.sub.rider cyclically ascertained in this way are stored as data, which represent these torques, in a memory unit that is connected to evaluation unit 30, using information technology.

[0031] Rider torque statistics are ascertained in step 200 based on the plurality of rider torques M.sub.rider ascertained over time. The rider torque statistics are cyclically ascertained here at a frequency of 10 Hz, and represent an arithmetic average value over all stored rider torques that have been ascertained within a present utilization period of the bicycle and that are above a first predefined rider torque threshold value of 1 Nm. A new utilization period begins here, for example, after an idle period of the bicycle of 2 h or when a change of riders is recognized, the change of riders being automatically ascertained based on distinguishable rider cadence profiles.

[0032] An assignment rule between the rider torque statistics and a predefined target load spectrum is ascertained for the bicycle in step 300, the assignment rule approximating the rider torque statistics to the target load spectrum. The assignment rule is ascertained according to the described steps. In addition, the assignment rule is cyclically ascertained at a frequency of 10 Hz.

[0033] A motor torque M.sub.motor corresponding to instantaneous rider torque M.sub.rider is established in step 400, based on the assignment rule, if instantaneous rider torque M.sub.rider exceeds the first rider torque threshold value. For the case in which the first rider torque threshold value is not exceeded by instantaneous rider torque M.sub.rider, motor torque M.sub.motor is ascertained based on a predefined fixed assistance factor of 2 by multiplying this assistance factor by instantaneous rider torque M.sub.rider.

[0034] In step 500, by specifying ascertained motor torque M.sub.motor, electric drive motor 10 is operated in such a way that a control unit for electric drive motor 10 makes an adjustment to predefined motor torque M.sub.motor.

[0035] FIG. 2 shows an example of a distribution density of rider torques M.sub.rider and motor torques M.sub.motor, and an example of the assignment of their respective classes KF, KM. The top histogram in FIG. 2 represents the distribution density of rider torques ρ.sub.rider over a certain time period. Particular classes KF of this histogram are only partly provided with reference symbols for reasons of clarity. The bottom histogram in FIG. 2 represents the distribution density of motor torques ρ.sub.motor, which represents a previously ascertained maximum allowable load spectrum for the drive train of the bicycle. Particular classes KM of this histogram are likewise only partly provided with reference symbols for reasons of clarity. As an example, three assignments 40, 42, 44 between the two histograms, which result according to the steps described herein, are illustrated.

[0036] FIG. 3 shows an example of assignment functions 70, 72, 74, defined in segments, between rider torques M.sub.rider and corresponding motor torques M.sub.motor for riders with different performance capabilities. First assignment function 70 represents a rider of below-average performance, second assignment function 72 represents a rider of average performance, and third assignment function 74 represents a rider of above-average performance. The particular straight line segments leading out from the origin represent respective first segments f1 of assignment functions 70, 72, 74, and are established in such a way that in each case they connect the origin to the particular intersection point of a rider-specific average rider torque M.sub.rider_Ø, which in each case has been multiplied by a rider-specific first correction factor k1, and predefined allowable average motor torque M.sub.motor_Ø.

[0037] Proceeding from these particular intersection points of average torques M.sub.rider_Ø, M.sub.motor_Ø, the continuing straight line segments of the particular assignment functions, which represent respective second segments f2 of assignment functions 70, 72, 74, are selected in such a way that they connect the particular intersection points from average torques M.sub.rider_Ø, M.sub.motor_Ø and an intersection point of particular corresponding maximum rider torque M.sub.rider_max, which in each case has been multiplied by a rider-specific second correction factor k2, and a predefined maximum allowable motor torque M.sub.motor_max. Particular average rider torques M.sub.rider_Ø are ascertained based on a sliding average value of detected rider torques M.sub.rider, the sliding average value being computed in each case over those rider torques M.sub.rider that have been detected within a previous time period of 300 s. Particular maximum rider torque M.sub.rider_max is ascertained in each case from those rider torques M.sub.rider that have been detected in a previous time period of 300 s.

[0038] First correction factor k1 is preferably used to increase or decrease riding dynamics, and second correction factor k2 is preferably used to reliably adhere to the target load spectrum.

[0039] FIG. 4 shows a schematic overview of components of a drive system according to the present invention for an electrically drivable bicycle. The drive system includes a torque sensor 20 that is configured to detect a rider torque M.sub.rider and transfer a piece of information concerning same to an evaluation unit 30 according to the present invention. Evaluation unit 30, which in the present case is a microcontroller, includes a plurality of processing sections, which are designed here in each case as computer program sections. With the aid of a torque processing section 50, evaluation unit 30 is configured to compute rider torque statistics, in the form of average rider torques M.sub.rider_Ø and maximum rider torques M.sub.rider_max, from rider torque values M.sub.rider that are received from torque sensor 20. With the aid of a motor torque ascertainment section 52, which is based on an assignment rule between the rider torque statistics and a predefined target load spectrum for the bicycle, evaluation unit 30 is configured to assign a corresponding motor torque M.sub.motor to each rider torque M.sub.rider present at the time, and to operate an electric drive motor 10 of the bicycle by specifying this motor torque M.sub.motor. With the aid of an ascertainment section for instantaneous load profile 54, evaluation unit 30 is configured to ascertain an actually present load profile for the drive train of the bicycle. In conjunction with a target load profile ascertainment section 58, in which a target load profile or target load spectrum for the bicycle is stored, a control and/or regulation section 60 of evaluation unit 30 is configured to address motor torque ascertainment section 52 in such a way that a control with regard to the target load profile takes place. This may occur based on previous and/or predicted rider torques M.sub.rider. With the aid of an observation horizon establishment section 56, evaluation unit 30 is also configured to establish, based on time and/or based on route, a particular number of rider torque values M.sub.rider to be considered, as a function of further boundary conditions such as an instantaneous route profile and/or an instantaneous position of the bicycle, etc. It is pointed out that this establishment for the particular components that use this observation horizon may be different.