DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11 November 2025 has been entered.
Status of Claims
This Office Action is in response to the application filed on 11 December 2025 and 11 November 2025. Claims 1-10 are presently pending and are presented for examination.
Priority
Acknowledgement is made of applicant’s claim for foreign priority based on an application DE10 2021 213 542.0 filed in Federal Republic of Germany on 30 November 2021.
Applicant cannot rely upon the certified copy of the foreign priority application to overcome potential future rejections made using references falling between the filing date and the foreign priority date, because a translation of said application has not been made of record in accordance with 37 CFR 1.55. When an English language translation of a non-English language foreign application is required, the translation must be that of the certified copy (of the foreign application as filed) submitted together with a statement that the translation of the certified copy is accurate. See MPEP §§ 215 and 216. No action is required by Applicant at this time.
Response to Arguments
Applicant’s arguments, see Remarks, pg. 5, filed 11 November 2025, with respect to claims 1 and 10 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
The remaining arguments are essentially the same as those addressed above and/or below and are moot for at least the same reasons. Therefore, examiner is unpersuaded and maintains the corresponding rejections.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 7, and 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over US-20130110335-A1, hereinafter “Durdevic” (previously of record), in view of US-20140195080-A1, “Lehmen” (newly of record).
Regarding claim 1, Durdevic discloses a method for operating an electric bicycle (Durdevic, para. 0007: “The example embodiment of the present invention provides a method for automatically controlling the gear of a gearshift of an electric bicycle.”), comprising the following steps:
detecting a mechanical load of a component of the bicycle in a load parameter set caused by a drive of the electric bicycle (Durdevic, para. 0009: “According to an example embodiment of the present invention, at least one actual operating parameter of a drive component of the electric bicycle is recorded. As the actual operating parameter one should understand an operating variable of the drive component. The actual operating parameter or the operating variable is a physical quantity which reflects the current operation of the drive component [i.e., a load parameter set caused by a drive of the electric bicycle], and which is able to be recorded by (at least) one sensor, for instance, a rotational speed sensor or a torque sensor [i.e., detecting a mechanical load of a component of the bicycle], the operating variable also being able to be derived from sensor data or actuation information (such as for controlling the rotational speed, the power, the torque or the motor current).”);
ascertaining a resultant mechanical load, which results from the mechanical load of the component caused by the drive since a start of the detection of the mechanical load, based on the load parameter set (Durdevic, para. 0010: “An operating variable of the drive component is recorded [i.e., ascertaining a resultant mechanical load]. The associated, at least one actual operating parameter is compared to a setpoint default, which reflects a more optimal operating point of the electric drive, i.e., a drive component driven by the electric drive, that is linked to a higher efficiency, greater reliability or greater durability of components of the electric or other drive.”; para. 0013: “The dependence between efficiency and actual operating parameters (such as rotational speed) of the motor is continuous and is stored in the device which provides the controller [i.e., results from the mechanical load of the component caused by the drive since a start of the detection of the mechanical load], for example, as a characteristics curve or individual characteristics curve points.”)…
Durdevic does not appear to disclose the following:
…wherein the resultant mechanical load represents a cumulative load to which the component was exposed over a course of time, wherein the resultant mechanical load reflects an aging of the component and/or a fatigue of a material of the component; and limiting a torque provided by the drive when the resultant mechanical load exceeds a limiting value, wherein the limiting value is a predefined limiting value which corresponds to the resultant mechanical load for which the electric bicycle was designed to withstand over time, wherein the torque provided by the drive is adjusted during operation based on the resultant mechanical load derived from accumulated historical operational data, the adjustment based on torque measurements over time as recorded in the load parameter set describing frequency distributions and time periods during which torque values lay within defined intervals.
However, in the same field of endeavor, Lehman teaches:
…wherein the resultant mechanical load represents a cumulative load to which the component was exposed over a course of time, wherein the resultant mechanical load reflects an aging of the component and/or a fatigue of a material of the component (Lehman, Table 2; FIG. 2A and 2B; para. 0076: “As illustrated in the chart 250 and Table 2 [i.e., the resultant mechanical load represents a cumulative load to which the component was exposed over a course of time], the first fatigue peak 280 may increase the event count in the 300-350 range, the second fatigue peak 282 may increase the event count in the 250-300 range, and the third fatigue peak 283 may increase the event count in the 350-400 range.”; para. 0048: “A minimum threshold 212 represents raw input torque that may result in minor or major impairment of one or more components due to fatigue conditions. When the input torque signal 202 crosses the minimum threshold 212 many times, the cumulative effects may result in long-term component or system failure resulting from repeated alternating or cyclic stresses [i.e., the resultant mechanical load represents a cumulative load to which the component was exposed over a course of time, wherein the resultant mechanical load reflects an aging of the component and/or a fatigue of a material of the component].”); and
limiting a torque provided by the drive when the resultant mechanical load exceeds a limiting value, wherein the limiting value is a predefined limiting value which corresponds to the resultant mechanical load for which the electric bicycle was designed to withstand over time (Lehman, Table 2; para. 0037: “A fatigue limitation module 148 is configured to prevent operation of the powertrain 110 at levels that exceed fatigue design limitations [i.e., mechanical load for which the electric bicycle was designed to withstand over time].”; para. 0079: “The fatigue event counts may be compared against maximum fatigue levels or counts [i.e., a limiting value, wherein the limiting value is a predefined limiting value which corresponds to the resultant mechanical load for which the electric bicycle was designed to withstand over time]. For example, there may be a maximum number of event counts that can occur in any range, such as the Maximum Fatigue column in Table 2. When the fatigue event count in any range reaches its maximum [i.e., when the resultant mechanical load exceeds a limiting value], the control system 140 predicts that fatigue failure may be imminent and remediation [i.e., limiting a torque provided by the drive when the resultant mechanical load exceeds a limiting value] may be needed to prevent failure due to, at least, that range.”; para. 0087: “One technique for remediation involves placing the vehicle into a reduced performance mode, including shutting down the vehicle. Other techniques for remediation involve altering specific characteristics, such as speed or torque requests for individual components [i.e., limiting a torque provided by the drive when the resultant mechanical load exceeds a limiting value], of the powertrain 110 to move away from the banned critical vehicle characteristics while still satisfying the overall output request.”),
wherein the torque provided by the drive is adjusted during operation based on the resultant mechanical load derived from accumulated historical operational data, the adjustment based on torque measurements over time as recorded in the load parameter set describing frequency distributions and time periods during which torque values lay within defined intervals (Lehman, Table 2 [i.e., torque values lay within defined intervals]; para. 0079: “The fatigue event counts may be compared against maximum fatigue levels or counts. For example, there may be a maximum number of event counts that can occur in any range, such as the Maximum Fatigue column in Table 2. When the fatigue event count in any range reaches its maximum, the control system 140 predicts that fatigue failure may be imminent and remediation may be needed to prevent failure due to, at least, that range.”; para. 0087: “One technique for remediation involves placing the vehicle into a reduced performance mode, including shutting down the vehicle. Other techniques for remediation involve altering specific characteristics, such as speed or torque requests for individual components [i.e., wherein the torque provided by the drive is adjusted during operation based on the resultant mechanical load], of the powertrain 110 to move away from the banned critical vehicle characteristics while still satisfying the overall output request.”; para. 0092: “The method 300 may begin at a start or initialization step [i.e., derived from accumulated historical operational data], during which time the method 300 is made active and is monitoring operating conditions of the vehicle, the powertrain 110 and, particularly, the engine 112 and the transmission 114. Initiation may occur, for example, in response to the vehicle operator inserting the ignition key or in response to specific conditions being met. The method 300 may be running constantly or looping constantly whenever the vehicle is in use.”; para. 0098: “However, when the control system 140 recognizes that input torque exceeds the minimum threshold, the method 300 identifies that a critical event, such as a first critical event, is occurring. Generally, critical events last for the duration of time in which the monitored input torque exceeds the minimum threshold [i.e., load parameter set describing frequency distributions and time periods during which torque values lay within defined intervals]. Once the critical event is identified, the method 300 may then determine whether to intervene in operation of the powertrain 110 [i.e., the adjustment based on torque measurements over time as recorded in the load parameter set].”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Durdevic, with the concept of measuring and storing data on the cumulative load of a mechanical component over time and controlling loads experienced by the mechanical component when the loads exceed a fatigue limit of the mechanical component, taught by Lehman, in order to limit the exposure of the mechanical component to high fatigue-causing scenarios and therefore increase the safety and usable life of the mechanical component (Lehman, para. 0037: “A fatigue limitation module 148 is configured to prevent operation of the powertrain 110 at levels that exceed fatigue design limitations. The fatigue limitation module 148 is configured to prevent input torque that may result in minor or major impairment of one or more components, over time as fatigue conditions build. Therefore, the fatigue limitation module 148 prevents input torque that may result in component or system failure resulting from repeated alternating or cyclic stresses.”).
Regarding claim 2, Durdevic and Lehman teach the method as recited in claim 1, and Durdevic further discloses the following:
wherein the mechanical load is caused using a torque provided by the drive (Durdevic, para. 0018: “…a pedal crank torque is recorded as the variable of driven electric bicycle components as the at least one actual operating parameter [i.e., the mechanical load]. The pedal crank torque is equivalent to the drive torque of the pedal crank [i.e., caused using a torque provided by the drive].”), and
a behavior of the torque is described by the load parameter set (Durdevic, para. 0016: ” Furthermore, an operating parameter [i.e., the load parameter set] may be averaged over a time window (e.g., 1-10 sec), in order to record usually frequently occurring phases of weaker pedal crank operation (i.e., lower pedal crank torque), and in response to the falling below the torque boundary [i.e., a behavior of the torque is described], to trigger the temporarily stored shifting process.”).
Regarding claim 7, Durdevic and Lehman teach the method as recited in claim 1,
wherein the load parameter set includes a temperature parameter, which describes at which temperature a particular torque has been provided by the drive (Durdevic, para. 0016: “The durability depends particularly on the torque at which the pedal crank drive is being operated or which the motor gives off, but also on the rotational speed of the motor or the temperature of the motor or of the battery or of the power control which supplies the motor, according to the design-conditioned properties of these components. The dependence of durability (i.e., a value that reflects the wear of the components) and the actual operating parameter [i.e., the load parameter set], i.e., torque acting upon the gearshift, or torque, rotational speed or power of the motor, or the temperature of the motor [i.e., temperature parameter, which describes at which temperature a particular torque has been provided by the drive], of the associated power control, or of the battery, is stored in the device which provides the controller.”).
Regarding claim 9, Durdevic and Lehman teach the method as recited in claim 1,
wherein the ascertainment of the resultant mechanical load takes place based on a same calculation criteria that have been utilized when designing the electric bicycle (Durdevic, para. 0016: “The durability depends particularly on the torque at which the pedal crank drive is being operated or which the motor gives off, but also on the rotational speed of the motor or the temperature of the motor or of the battery or of the power control which supplies the motor, according to the design-conditioned properties of these components [i.e., based on a same calculation criteria that have been utilized when designing the electric bicycle]. The dependence of durability (i.e., a value that reflects the wear of the components) and the actual operating parameter, i.e., torque acting upon the gearshift, or torque, rotational speed or power of the motor, or the temperature of the motor, of the associated power control, or of the battery, is stored in the device which provides the controller [i.e., ascertainment of the resultant mechanical load].”).
Regarding claim 10, Durdevic discloses a device for operating an electric bicycle (Durdevic, para. 0025: “The present invention further provides an example device for automatically controlling the gear of a gearshift of an electric bicycle.”), comprising:
a control unit (Durdevic, para. 0026: “The device also provides a controller [i.e., a control unit] which is connected to the comparative device to receive the difference between actual operating parameters and the setpoint default.”) configured to:
detect a mechanical load of a component of the electric bicycle in a load parameter set caused by a drive of the electric bicycle (Durdevic, para. 0025: “The example device includes: a sensor device configured to record at least one actual operating parameter of a drive component of the electric bicycle [i.e., detect a mechanical load of a component of the electric bicycle], the sensor device being connected to the drive component in order to record an operating variable of the drive component [i.e., a load parameter set caused by a drive of the electric bicycle].”),
ascertain a resultant mechanical load, which results from the mechanical load of the component caused by the drive since a start of the detection of the mechanical load, based on the load parameter set (Durdevic, para. 0010: “An operating variable of the drive component is recorded [i.e., ascertaining a resultant mechanical load]. The associated, at least one actual operating parameter is compared to a setpoint default, which reflects a more optimal operating point of the electric drive, i.e., a drive component driven by the electric drive, that is linked to a higher efficiency, greater reliability or greater durability of components of the electric or other drive.”; para. 0013: “The dependence between efficiency and actual operating parameters (such as rotational speed) of the motor is continuous and is stored in the device which provides the controller [i.e., results from the mechanical load of the component caused by the drive since a start of the detection of the mechanical load], for example, as a characteristics curve or individual characteristics curve points.”),
Durdevic does not appear to disclose the following:
wherein the resultant mechanical load represents a cumulative load to which the component was exposed over a course of time, wherein the resultant mechanical load reflects an aging of the component and/or a fatigue of a material of the component, and limit a torque provided by the drive when the resultant mechanical load exceeds a limiting value, wherein the limiting value is a predefined limiting value which corresponds to the resultant mechanical load for which the electric bicycle was designed to withstand over time, wherein the torque provided by the drive is adjusted during operation based on the resultant mechanical load derived from accumulated historical operational data, the adjustment based on torque measurements over time as recorded in the load parameter set describing frequency distributions and time periods during which torque values lay within defined intervals.
However, in the same field of endeavor, Lehman teaches:
wherein the resultant mechanical load represents a cumulative load to which the component was exposed over a course of time, wherein the resultant mechanical load reflects an aging of the component and/or a fatigue of a material of the component (Lehman, Table 2; FIG. 2A and 2B; para. 0076: “As illustrated in the chart 250 and Table 2 [i.e., the resultant mechanical load represents a cumulative load to which the component was exposed over a course of time], the first fatigue peak 280 may increase the event count in the 300-350 range, the second fatigue peak 282 may increase the event count in the 250-300 range, and the third fatigue peak 283 may increase the event count in the 350-400 range.”; para. 0048: “A minimum threshold 212 represents raw input torque that may result in minor or major impairment of one or more components due to fatigue conditions. When the input torque signal 202 crosses the minimum threshold 212 many times, the cumulative effects may result in long-term component or system failure resulting from repeated alternating or cyclic stresses [i.e., the resultant mechanical load represents a cumulative load to which the component was exposed over a course of time, wherein the resultant mechanical load reflects an aging of the component and/or a fatigue of a material of the component].”), and
limit a torque provided by the drive when the resultant mechanical load exceeds a limiting value, wherein the limiting value is a predefined limiting value which corresponds to the resultant mechanical load for which the electric bicycle was designed to withstand over time (Lehman, Table 2; para. 0037: “A fatigue limitation module 148 is configured to prevent operation of the powertrain 110 at levels that exceed fatigue design limitations [i.e., mechanical load for which the electric bicycle was designed to withstand over time].”; para. 0079: “The fatigue event counts may be compared against maximum fatigue levels or counts [i.e., a limiting value, wherein the limiting value is a predefined limiting value which corresponds to the resultant mechanical load for which the electric bicycle was designed to withstand over time]. For example, there may be a maximum number of event counts that can occur in any range, such as the Maximum Fatigue column in Table 2. When the fatigue event count in any range reaches its maximum [i.e., when the resultant mechanical load exceeds a limiting value], the control system 140 predicts that fatigue failure may be imminent and remediation [i.e., limit a torque provided by the drive when the resultant mechanical load exceeds a limiting value] may be needed to prevent failure due to, at least, that range.”; para. 0087: “One technique for remediation involves placing the vehicle into a reduced performance mode, including shutting down the vehicle. Other techniques for remediation involve altering specific characteristics, such as speed or torque requests for individual components [i.e., limiting a torque provided by the drive when the resultant mechanical load exceeds a limiting value], of the powertrain 110 to move away from the banned critical vehicle characteristics while still satisfying the overall output request.”),
wherein the torque provided by the drive is adjusted during operation based on the resultant mechanical load derived from accumulated historical operational data, the adjustment based on torque measurements over time as recorded in the load parameter set describing frequency distributions and time periods during which torque values lay within defined intervals (Lehman, Table 2 [i.e., torque values lay within defined intervals]; para. 0079: “The fatigue event counts may be compared against maximum fatigue levels or counts. For example, there may be a maximum number of event counts that can occur in any range, such as the Maximum Fatigue column in Table 2. When the fatigue event count in any range reaches its maximum, the control system 140 predicts that fatigue failure may be imminent and remediation may be needed to prevent failure due to, at least, that range.”; para. 0087: “One technique for remediation involves placing the vehicle into a reduced performance mode, including shutting down the vehicle. Other techniques for remediation involve altering specific characteristics, such as speed or torque requests for individual components [i.e., wherein the torque provided by the drive is adjusted during operation based on the resultant mechanical load], of the powertrain 110 to move away from the banned critical vehicle characteristics while still satisfying the overall output request.”; para. 0092: “The method 300 may begin at a start or initialization step, during which time the method 300 is made active and is monitoring operating conditions of the vehicle, the powertrain 110 and, particularly, the engine 112 and the transmission 114. Initiation may occur, for example, in response to the vehicle operator inserting the ignition key or in response to specific conditions being met. The method 300 may be running constantly or looping constantly whenever the vehicle is in use [i.e., derived from accumulated historical operational data].”; para. 0098: “However, when the control system 140 recognizes that input torque exceeds the minimum threshold, the method 300 identifies that a critical event, such as a first critical event, is occurring. Generally, critical events last for the duration of time in which the monitored input torque exceeds the minimum threshold [i.e., load parameter set describing frequency distributions and time periods during which torque values lay within defined intervals]. Once the critical event is identified, the method 300 may then determine whether to intervene in operation of the powertrain 110 [i.e., the adjustment based on torque measurements over time as recorded in the load parameter set].”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Durdevic, with the concept of measuring and storing data on the cumulative load of a mechanical component over time and controlling loads experienced by the mechanical component when the loads exceed a fatigue limit of the mechanical component, taught by Lehman, in order to limit the exposure of the mechanical component to high fatigue-causing scenarios and therefore increase the safety and usable life of the mechanical component (Lehman, para. 0037: “A fatigue limitation module 148 is configured to prevent operation of the powertrain 110 at levels that exceed fatigue design limitations. The fatigue limitation module 148 is configured to prevent input torque that may result in minor or major impairment of one or more components, over time as fatigue conditions build. Therefore, the fatigue limitation module 148 prevents input torque that may result in component or system failure resulting from repeated alternating or cyclic stresses.”).
Claim(s) 3 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Durdevic, in view of Lehman, as applied to claim 1 above, and further in view of US-20220281345-A1, hereinafter “Kim” (previously of record).
Regarding claim 3, Durdevic and Lehman teach the method as recited in claim 1, but do not appear to explicitly teach the following:
wherein a torque range covered by the drive is subdivided into multiple torque intervals, and the time period, which describes how long the torque lying within the respective torque interval has been provided by the drive, are stored in the load parameter set for each of the multiple torque intervals.
However, in the same field of endeavor, Kim teaches:
wherein a torque range covered by the drive is subdivided into multiple torque intervals, and the time period, which describes how long the torque lying within the respective torque interval has been provided by the drive, are stored in the load parameter set for each of the multiple torque intervals (Kim, Fig. 5: see figure, below [i.e., wherein a torque range covered by the drive is subdivided into multiple torque intervals, and the time period, which describes how long the torque lying within the respective torque interval has been provided by the drive]; para. 0052: ” The control system 15 may record driving characteristic information of the electric vehicle EVn in the storage means 15 a [i.e., stored in the load parameter set]. The driving characteristic information includes at least one selected from the group consisting of speed of the electric vehicle EVn, driving area of the electric vehicle EVn, and humidity thereof.”; para. 0057: “Preferably, the driving characteristic accumulative information of the electric vehicle EVn may include at least one selected from the group consisting of accumulative driving time of each speed section [i.e., a torque range covered by the drive is subdivided into multiple torque intervals, and the time period, which describes how long the torque lying within the respective torque interval has been provided by the drive; Note: It would be obvious to one of ordinary skill in the art, at the time of the application, that torque and speed are obvious variants due to their commonly-known mathematical relationship.], accumulative driving time of each driving area, and accumulative driving time of each humidity section.”).
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Kim, Fig. 5
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Durdevic, as modified by Lehman, with the concept of recording a frequency distribution of a vehicle parameter, like speed or torque, taught by Kim, in order to track and utilize system data to better predict and/or detect system conditions that lead to reduced operational life and/or operational failure (in other words, component failure analysis) (Kim, para. 0004: “In case of a battery of an electric vehicle, the speed of performance degradation changes depending on driving habits of a driver or driving environments. For example, if the electric vehicle is used with frequent rapid acceleration or operated in a mountainous area, a desert area or a cold area, the battery of the electric vehicle has a relatively fast degradation speed.”).
Regarding claim 4, Durdevic, Lehman and Kim teach the method as recited in claim 3, and Kim further teaches the following:
wherein the multiple torque intervals are identical in size, the covered torque range being subdivided in multiple torque intervals of 5% or 10% or 20% (Kim, FIG. 5: see figure, above; Multiple speed intervals [i.e., torque intervals] are identical in size: 20 [“50-70, 70-90, 90-110…”]. The covered speed range [i.e., torque range] is subdivided in multiple speed intervals [i.e., multiple torque intervals] of a substantially identical interval range of 10%. The displayed range is 0-190 and multiple intervals are 20:
20
190
≈
10.5
%
).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Durdevic, as modified by Lehman and Kim, with the concept of driving characteristic accumulative information defined with identical intervals and intervals of about 10%, taught by Kim, in order to organize the accumulative information in the most usable format for analysis (Kim , para. 0108: “Meanwhile, if the frequency distribution data (see FIG. 6) generated from the driving accumulative time information of each driving area in the driving characteristic accumulative information of the electric vehicle EVn has too many variables, the artificial neural network 100 may be trained separately for each wide area that groups a plurality of areas.”).
Alternatively, the specification states that the “torque intervals are preferably of identical size” (pg. 6, lines 12-13) and not that the identical size intervals are critical. Additionally, the torque range being subdivided in multiple torque intervals of “5% or 10% or 20%” also does not represent a critical subdivision interval due to the mathematically significant difference amongst 5%, 10%, and 20%, nor does the specification state that the subdivision intervals are critically defined. It would have been obvious to one of ordinary skill in the art, at the time of the application, to choose torque intervals that best fit the torque data or a use case of the torque data, in order to yield the most usable results, given available resources. The driving characteristic accumulative information shown in Kim’s FIG. 5 (see Kim, para. 0070) is input assigned to the nodes of the input layer of a neural network (see Kim, para. 0088), where the number of speed (i.e., torque) intervals becomes the number of input layer nodes. Therefore, the chosen intervals affect aspects of the neural network considered for optimization, like accurate performance and computational complexity, and Kim teaches neural network optimization (see Kim, paragraphs 0099-0101). Since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art. In re Aller, 105 USPQ 233.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Durdevic, in view of Lehmen, as applied to claim 1 above, and further in view of US-20130144473-A1, hereinafter “Jeong” (previously of record).
Regarding claim 5, Durdevic and Lehman teach the method as recited in claim 1, but does not appear to explicitly disclose the following:
wherein the load parameter set describes a frequency, which indicates how often a torque provided by the drive lay continuously above a predefined torque threshold for longer than a predefined time interval.
However, in the same field of endeavor, Jeong teaches:
wherein the load parameter set describes a frequency, which indicates how often a torque provided by the drive lay continuously above a predefined torque threshold for longer than a predefined time interval (Jeong, para. 0011: ” A method for determining whether an engine stop in a hybrid electric vehicle is abnormal according to an exemplary embodiment of the present invention may include: a) determining, by a control unit…c) increasing, by the control unit, a stall count when the engine stalls [i.e., load parameter set describes a frequency, which indicates how often]…”; para. 0012: “The engine may be determined to stall when the speed of the engine is less than a predetermined threshold speed [i.e., torque provided by the drive lay continuously above a predefined torque threshold; Note: The Broadest Reasonable Interpretation (BRI) of “above” relative to a threshold encompasses the concept of “below” relative to the same threshold based on relative position or approach (e.g., higher/lower, better/worse). The mathematical concept of a value being compared to a threshold and a counter that stores data on the duration of when threshold violations occur represents the BRI of the limitation.] and a staying time when the speed of the engine is less than the predetermined threshold speed is greater than a predetermined threshold time [i.e., for longer than a predefined time interval] under predetermined environmental conditions in step b).”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Durdevic, as modified by Lehman, with the concept of recording the frequency of a parameter exceeding or at least not meeting a threshold, for a predefined time interval, taught by Jeong, in order to track and utilize system data to better predict and/or detect system conditions that lead to reduced operational life and/or operational failure (Jeong, para. 0006: “On the other hand, in a hybrid electric vehicle the engine is frequently stopped and restarted even in a normal state based upon whether the vehicle is in an idle stop mode, an electric vehicle (EV) driving mode, or a passive run mode. These various modes help to improve the fuel efficiency of the vehicle. As a result, hybrid electric vehicles need to have an additional algorithm for distinguishing between when the engine has been stopped normally and when the engine has been stopped abnormally.”).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Durdevic, in view of Lehmen, as applied to claim 1 above, and further in view of US-20140166385-A1, hereinafter “Arimune” (previously of record).
Regarding claim 6, Durdevic and Lehman teach the method as recited in claim 1, but does not appear to explicitly disclose the following:
wherein the load parameter set describes a load time, which indicates how long a torque provided by the drive lay above a predefined torque threshold.
However, in the same field of endeavor, Arimune teaches:
wherein the load parameter set describes a load time, which indicates how long a torque provided by the drive lay above a predefined torque threshold (Arimune, para. 0140: “If it is determined in step SE2 that the motor rotation speed is equal to or more than the rotation speed threshold (YES) [i.e., above a predefined torque threshold], the control proceeds to step SE3 and the duration of the determination (detection duration A) is counted by the timer 121 [i.e., load time].”; Note: It would be obvious to one of ordinary skill in the art, at the time of the application, that torque and speed have a commonly-known mathematical relationship.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Durdevic, as modified by Lehman, with the concept of recording a load parameter for the frequency of a torque provided by the drive of an electric bicycle being greater than or equal to a torque threshold, taught by Arimune, in order to collect data to support the prediction of lifetime wear on the drive components and/or collect data to support the determination of the ideal threshold for providing assistance torque to the rider (Arimune, para. 0007-0008: “Therefore, if starting/stopping of assist control is determined using a torque generated at the crankshaft as disclosed in Japanese Patent No. 4129084, a battery-assisted bicycle with a high assist ratio ends up repeatedly starting and stopping assist control in response to slight changes of a small torque value. More specifically, in the structure disclosed above, the assist control starts or stops in response to a slight change in the torque value, and the rider may feel uncomfortable.”).
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Durdevic, in view of Lehmen, as applied to claim 1 above, and further in view of US-5971090-A, hereinafter “Tanaka” (previously of record).
Regarding claim 8, Durdevic and Lehman teach the method as recited in claim 1, but does not appear to disclose the following:
wherein the limitation of the torque provided by the drive takes place via a reduction of an assistance factor.
However, in the same field of endeavor, Tanaka teaches:
wherein the limitation of the torque provided by the drive takes place via a reduction of an assistance factor (Tanaka, col. 1, line 57: “For that purpose, the electrically assisted bicycle includes a torque sensor for detecting the torque of the human driving power, a speed sensor for detecting the running speed, and a microcomputer for performing calculations to determine the motor driving power [i.e., limitation of the torque], whereby the torque of the human driving power obtained by the torque sensor and the running speed obtained by the speed sensor are inputted to change the assist ratio [i.e., a reduction of an assistance factor] on the basis of the table data stored in the microcomputer.”; col. 1, line 66: “For example, supposing that a torque of 100 kg·cm based on the human driving power is applied, the torque based on the motor driving power is set to be 100 kg·cm when the running speed is 10 km/h, whereas an output of 44 kg·cm based on the motor driving power is calculated in the microcomputer and outputted when the running speed is 20 km/h because the assist ratio must be reduced to about 0.44.”).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable likelihood of success to modify the invention disclosed by Durdevic, as modified by Lehman, with the concept of reducing an assistance factor for torque limiting in an electric bicycle, taught by Tanaka, in order to limit an electric bicycle torque that is a combination of electric motor torque and torque provided by the rider, because only the electric motor torque can be controlled by a control system and therefore must be responsive to the rider-provided torque, so as to not exceed system torque limits (Tanaka, col. 1, line 13: “More particularly, the present invention relates to a torque limiting device which is suitable for limiting the torque so that the motor as a driving power source may not rotate at a speed exceeding a predetermined value…”; col. 1, line 33: ” Namely, it is generally known in the art that a vehicle speed signal detected by a vehicle speed detection means such as a speed sensor provided in a wheel and a pedalling signal which is a human driving power detected by a pedalling power detection means are inputted into a controller whereby the assist ratio, namely the ratio of the motor driving power to the human driving power, are varied in accordance with the vehicle speed on the basis of predetermined table data.”).
Additional Relevant Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
"Frequency Domain Fatigue Assessment of Vehicle Component under Random Load Spectrum" (2011) | “This research is focused on the application of frequency domain based fatigue life predict methods on vehicle component” (Abstract). “It is very difficult to assessment fatigue damage of vehicle components in time-domain, but more convenient to analysis based on the signal in the frequency domain. Therefore, it is fit to assess fatigue damage of vehicle components in frequency domain.” (Introduction). “(3) PSD average methods, frequency ranges and intervals have great influence on frequency domain based methods. It should be careful to select proper parameters for the assessment of fatigue damage for vehicle components. Appropriate validation with experiment data or simulative time history data is recommended before the application of suitable frequency domain based methods method.” (Conclusions).
“Using Balanced Random Forests on Load Spectrum Data for Classifying Component Failures of a Hybrid Electric Vehicle Fleet” (2014) | “Components, not only in an automotive context, usually contain some elements or parts that are exposed to different types and amounts of loads, like static or alternating stress. For being able to design reliable components it is therefore necessary to analyze the effects of static and dynamic stress on the strengths of the components. Fatigue Analysis thereby especially focuses on analyzing the effects of cyclic stresses that often result in failures by fatigue [5]. As the fatigue life of mechanical and electrical components depends on the magnitude and frequency of occurrences of the amplitudes of the alternating stress, many counting methods have been proposed to transform stress-time functions to frequency distributions. These methods can be divided into one-parameter and two-parameter counting methods [5]. The result of counting is a load spectrum. Load spectra resulting from one-parameter counting methods can be visualized as barplots or as histograms, whereas the outcomes of two-parameter counting methods are usually stored in matrices [5] that can be presented as three-dimensional barplots or as heatmaps.” (Section II – Methods, A. Load Spectrum Data).
Conclusion
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/L.N.M./Examiner, Art Unit 3663
/ABBY J FLYNN/Supervisory Patent Examiner, Art Unit 3663