DETAILED ACTION
This is a response to the Amendment to Application # 18/342,256 filed on February 24, 2026 in which claims 4, 6, 11, and 12 were amended; claim 5 was cancelled, and claims 24 and 35 were added.
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 .
Status of Claims
Claims 4, 6-17, 19, 20, and 22-25 are pending, which are rejected under 35 U.S.C. § 103.
Claim Interpretation
Claim 4 includes the limitation “specifying the predicted power limit for at least one of the energy storage or the vehicle as part of the sequence of actions.” (Emphasis added). This appears to recite that the predicted power limit is specified as part of the sequence of actions and that the power limit is specified for at least one of the energy storage or the vehicle and not that the “sequence of actions” only applies to “the vehicle.”
Claim Rejections - 35 U.S.C. § 103
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 of this title, 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.
Claims 4, 8-15, 24, and 25 are rejected under 35 U.S.C. § 103 as being unpatentable over Loonen et al., US Publication 2017/0338667 (hereinafter Loonen) in view of Holme, US Patent 11,691,518 (hereinafter Holme), as cited on the Notice of References Cited dated August 12, 2025 and which incorporates Hettrich et al., US Publication 2016/0059733 (hereinafter Hettrich) at col. 5, ll. 15-22 and col. 4, ll. 21-31, as cited on the Notice of References Cited dated December 16, 2025.
Regarding claim 4, Loonen discloses a method … comprising “deriving a model for determining a power limit of an energy storage for the vehicle” (Loonen ¶ 32) where the model calculates the “highest possible, charging current at each moment in time and for each battery state.” Additionally, Loonen discloses “providing or obtaining at least one input value for the model, wherein the at least one input value comprises a planned power load for a first time point” (Loonen ¶ 38) where a certain input current for a time step is input into the model. Further, Loonen discloses “providing a plurality of different predetermined power limits, each predetermined power limit indicating a maximum power that can be handled by the energy storage for a predetermined period of time, including a first predetermined power limit indicative of a first maximum power to be handled for a first predetermined period of time and a second predetermined power limit indicative of a second maximum power to be handled for a second predetermined period of time different than the first predetermined period of time” (Loonen ¶ 35 and Fig. 3) by receiving the maximum allowed charger current Imax, which is shown in Fig. 3 to be for different time periods. Moreover, Loonen discloses “determining parameters of the model as a function of the plurality of different predetermined power limits” (Loonen ¶ 34) by giving an example of determining a surface concentration with the battery model as a function of the initial current. Likewise, Loonen discloses “determining an output value by means of the model, wherein the output value comprises a predicted power limit at a second time point subsequent to the first time point indicating a maximum amount of power to be handled by the energy storage” (Loonen ¶¶ 32, 38) where the model calculates the highest possible charging current (Loonen ¶ 32) for time unit “k+1” (i.e., a time point subsequent to k, Loonen ¶ 38). Finally, Loonen discloses “specifying the predicted power limit for at least one of the energy storage …” (Loonen ¶ 38) by calculating (i.e., specifying) the battery voltage calculated by the model.
Loonen does not appear to explicitly disclose “specifying the predicted power limit for at least one of the energy storage or the vehicle as part of the sequence of actions; and controlling a trajectory of the vehicle by at least one of drawing power from the energy storage or providing power by the vehicle according to the predicted power limit.”
However, Holme discloses a method for controlling a vehicle according to a sequence of actions for the vehicle, the method comprising “specifying the predicted power limit for at least one of the energy storage or the vehicle as part of the sequence of actions” (Holme col. 12, ll. 5-19) where the predicted battery state is provided to the BMS. Additionally, Holme discloses “controlling a trajectory of the vehicle by at least one of drawing power from the energy storage or providing power by the vehicle according to the predicted power limit” (Holme col. 2, l. 62-col. 3, l. 22) by detailing that alternate routes may be determined for the vehicle based on the predicted battery state data.
Further, Holme discloses “deriving a model for determining a power limit of an energy storage for the vehicle” (Holme col. 5, ll. 30-49) by training the battery model. Additionally, Holme discloses “providing or obtaining at least one input value for the model” (Holme col. 11, ll. 14-27) by receiving input values, such as those in TABLE 2 for the model. Moreover, Holme discloses “providing a plurality of different predetermined power limits … including a first predetermined power limit indicative of a first maximum power to be handled for a first predetermined period of time and a second predetermined power limit is indicative of a second maximum power to be handled for a second predetermined period of time different than the first predetermined period of time” (Hettrich ¶ 157, Fig. 6A) by disclosing a maximum power of the battery over various time intervals. Finally, Holme discloses “determining an output value by means of the model, wherein the output value comprises a predicted power limit at a second time point subsequent to the first time point indicating a maximum amount of power to be handled by the energy storage” (Holme col. 6, ll. 40-58, col. 13, ll. 6-20) where the “state of charge” (SOC) includes maximum charging capacity of battery (i.e., power limit), which is a battery state (Holme col. 2, ll. 20-23) and then predicting future battery states.
Loonen and Holme are analogous art because they are from the “same field of endeavor,” namely that of battery management processes.
Prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Loonen and Holme before him or her to modify the battery management method of Loonen to be implemented for a vehicle, as taught by Holme.
The motivation/rationale for doing so would have been that of applying a known technique to a known device. See KSR Int’l Co. v. Teleflex Inc., 550 US 398, 82 USPQ2d 1385, 1396 (U.S. 2007) and MPEP § 2143(I)(D). Loonen teaches the “base device” for predicting battery power limits. Further, Holme teaches the “known technique” controlling a vehicle based on predicted power limits that is applicable to the base device of Loonen. One of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system because such a modification would have merely required implementing the model of Loonen in the vehicle of Holme by replacing the existing power modeling system.
Regarding claim 11, Loonen discloses a non-transitory, computer-readable storage medium containing instructions that when executed on a computer cause the computer to “provide a plurality of different predetermined power limits, each predetermined power limit indicating a maximum power that can be handled by the energy storage for a predetermined period of time, including a first predetermined power limit indicative of a first maximum power to be handled for a first predetermined period of time and a second predetermined power limit indicative of a second maximum power to be handled for a second predetermined period of time different than the first predetermined period of time” (Loonen ¶ 35 and Fig. 3) by receiving the maximum allowed charger current Imax, which is shown in Fig. 3 to be for different time periods. Additionally, Loonen discloses “determine, based on the plurality of predetermined power limits, a model outputting an output value based on at least one input value, by determining parameters of the model as a function of the plurality of different predetermined power limits” (Loonen ¶ 34) by giving an example of determining a surface concentration with the battery model as a function of the initial current. Further, Loonen discloses “wherein the at least one input value comprises a planned power to be, at a first time point, by at least one selected from the group consisting of drawn from the energy storage and handled by a vehicle” (Loonen ¶ 38) where a certain input current for a time step is input into the model. Finally, Loonen discloses “wherein the output value comprises a predicted power limit at a time point subsequent to the first time point that indicates a maximum power which can be handled by the energy storage” (Loonen ¶¶ 32, 38) where the model calculates the highest possible charging current (Loonen ¶ 32) for time unit “k+1” (i.e., a time point subsequent to k, Loonen ¶ 38).
Loonen does not appear to explicitly disclose “use the model to determine a sequence of actions for the vehicle; and control the vehicle according to the sequence of actions.”
However, Holme discloses a non-transitory, computer-readable storage medium containing instructions that when executed on a computer cause the computer to “use the model to determine a sequence of actions for the vehicle; and control the vehicle according to the sequence of actions” (Holme col. 2, l. 62-col. 3, l. 22) by detailing that alternate routes may be determined for the vehicle based on the predicted battery state data.
Additionally, Holme discloses “provide a plurality of different predetermined power limits … including a first predetermined power limit indicative of a first maximum power to be handled for a first predetermined period of time and a second predetermined power limit indicative of a second maximum power to be handled for a second predetermined period of time different than the first predetermined period of time” (Hettrich ¶ 157, Fig. 6A) by disclosing that a maximum power of the battery over various time intervals. Further, Holme discloses “determine, based on the plurality of predetermined power limits, a model outputting an output value based on at least one input value, by determining parameters of the model as a function of the plurality of different predetermined power limits” (Holme col. 5, ll. 30-49) by training the battery model. Moreover, Holme discloses “wherein the at least one input value comprises a planned power to be, at a first point in time by at least one selected from the group consisting of drawn from the energy storage and handled by the vehicle” (Holme TABLE 2) where one input may be the load current and/or voltage at time histories of the battery (i.e., the energy storage). Finally, Holme discloses “wherein the output value comprises a predicted power limit at a time point subsequent to the time point that indicates a maximum power which can be handled by the energy storage” (Holme col. 6, ll. 40-58, col. 13, ll. 6-20) where the “state of charge” (SOC) includes maximum charging capacity of battery (i.e., power limit), which is a battery state (Holme col. 2, ll. 20-23) and then predicting future battery states.
Loonen and Holme are analogous art because they are from the “same field of endeavor,” namely that of battery management processes.
Prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Loonen and Holme before him or her to modify the battery management method of Loonen to be implemented for a vehicle, as taught by Holme.
The motivation/rationale for doing so would have been that of applying a known technique to a known device. See KSR Int’l Co. v. Teleflex Inc., 550 US 398, 82 USPQ2d 1385, 1396 (U.S. 2007) and MPEP § 2143(I)(D). Loonen teaches the “base device” for predicting battery power limits. Further, Holme teaches the “known technique” controlling a vehicle based on predicted power limits that is applicable to the base device of Loonen. One of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system because such a modification would have merely required implementing the model of Loonen in the vehicle of Holme by replacing the existing power modeling system.
Regarding claim 12, Loonen discloses a method … comprising “determining a plurality of different predetermined power limits for a battery management system … each predetermined power limit indicating a maximum power that can be handled by the energy storage for a predetermined period of time, including a first predetermined power limit indicative of a first maximum power to be handled for a first predetermined period of time and a second predetermined power limit is-indicative of a second maximum power to be handled for a second predetermined period of time different than the first predetermined period of time” (Loonen ¶ 35 and Fig. 3) by receiving the maximum allowed charger current Imax, which is shown in Fig. 3 to be for different time periods. Additionally, Loonen discloses “determining parameters as a function of the plurality of different predetermined power limits” (Loonen ¶ 34) by giving an example of determining a surface concentration with the battery model as a function of the initial current. Further, Loonen discloses “deriving a model for determining a current power limit of the energy storage based on the parameters” (Loonen ¶ 32) where the model calculates the “highest possible, charging current at each moment in time and for each battery state.” Moreover, Loonen discloses “determining at least one input value comprising a power to be handled by at least one of the energy storage or the vehicle and planned for a first time point” (Loonen ¶ 38) where a certain input current for a time step is input into the model. Finally, Loonen discloses “applying the model by receiving the at least one input value and outputting an output value comprising a power limit at a second time point subsequent to the first time point and indicating a maximum power that can be handled by the energy storage” (Loonen ¶¶ 32, 38) where the model calculates the highest possible charging current (Loonen ¶ 32) for time unit “k+1” (i.e., a time point subsequent to k, Loonen ¶ 38).
Loonen does not appear to explicitly disclose a vehicle and, therefore, does not appear to explicitly disclose “determining a plurality of different predetermined power limits for a battery management system of the vehicle, each predetermined power limit indicating a maximum power that can be handled by the energy storage for a predetermined period of time, including a first predetermined power limit indicative of a first maximum power to be handled for a first predetermined period of time and a second predetermined power limit is-indicative of a second maximum power to be handled for a second predetermined period of time different than the first predetermined period of time.” Loonen also does not appear to explicitly disclose “determining a sequence of actions for the vehicle based on the output value; and controlling a speed of the vehicle based on the sequence of actions.”
However, Holme discloses a method of controlling a vehicle using a predicted power value. (Holme Abstract). A person of ordinary skill in the art prior to the effective filing date of the present invention would have recognized that when Holme was combined with Loonen, the power prediction method of Loonen would be used with a vehicle, as taught by Holmes. Therefore, the combination of Loonen and Holme at least teaches and/or suggests the claimed limitation “determining a plurality of different predetermined power limits for a battery management system of the vehicle, each predetermined power limit indicating a maximum power that can be handled by the energy storage for a predetermined period of time, including a first predetermined power limit indicative of a first maximum power to be handled for a first predetermined period of time and a second predetermined power limit is-indicative of a second maximum power to be handled for a second predetermined period of time different than the first predetermined period of time,” rendering it obvious.
Additionally, Loonen discloses “determining a sequence of actions for the vehicle based on the output value; and controlling a speed of the vehicle based on the sequence of actions” (Holme col. 2, l. 62-col. 3, l. 22) by detailing that alternate routes may be determined for the vehicle based on the predicted battery state data.
Further, Holme discloses “determining a plurality of different predetermined power limits for a battery management system of the vehicle, … including a first predetermined power limit indicative of a first maximum power to be handled for a first predetermined period of time and a second predetermined power limit indicative of a second maximum power to be handled for a second predetermined period of time different than the first predetermined period of time” (Hettrich ¶ 157, Fig. 6A) by disclosing that a maximum power of the battery over various time intervals. Additionally, Holme discloses “determining parameters as a function of the plurality of different predetermined power limits” (Holme col. 20, ll. 42-56) where parameters are determined that correlate to each of those values, making them “a function of” those values. Further, Holme discloses “deriving a model for determining a current power limit of the energy storage based on the parameters” (Holme col. 5, ll. 30-49) by training the battery model. Moreover, Holme discloses “determining at least one input value comprising a power to be handled by at least one of the energy storage or the vehicle and planned for a first time point” (Holme TABLE 2) where one input may be the load current and/or voltage at time histories of the battery (i.e., the energy storage). Likewise, Holme discloses “applying the model by receiving the at least one input value and outputting an output value comprising a power limit at a second time point subsequent to the first time point and indicating a maximum power that can be handled by the energy storage” (Holme col. 6, ll. 40-58, col. 13, ll. 6-20) where the “state of charge” (SOC) includes maximum charging capacity of battery (i.e., power limit), which is a battery state (Holme col. 2, ll. 20-23) and then predicting future battery states.
Loonen and Holme are analogous art because they are from the “same field of endeavor,” namely that of battery management processes.
Prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Loonen and Holme before him or her to modify the battery management method of Loonen to be implemented for a vehicle, as taught by Holme.
The motivation/rationale for doing so would have been that of applying a known technique to a known device. See KSR Int’l Co. v. Teleflex Inc., 550 US 398, 82 USPQ2d 1385, 1396 (U.S. 2007) and MPEP § 2143(I)(D). Loonen teaches the “base device” for predicting battery power limits. Further, Holme teaches the “known technique” controlling a vehicle based on predicted power limits that is applicable to the base device of Loonen. One of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system because such a modification would have merely required implementing the model of Loonen in the vehicle of Holme by replacing the existing power modeling system.
Regarding claim 8, the combination of Loonen and Holme discloses the limitations contained in parent claim 12 for the reasons discussed above. In addition, the combination of Loonen and Holme discloses “wherein the sequence of actions is determined as a trajectory or as part of a trajectory, wherein the trajectory comprises commands for acceleration and speed of the vehicle. (Holme col. 17, l. 57-col. 18, l. 9) where the predictions are used to adjust the speed of the vehicle, which is both a command for acceleration and speed of the vehicle.
Regarding claim 9, the combination of Loonen and Holme discloses the limitations contained in parent claim 12 for the reasons discussed above. In addition, the combination of Loonen and Holme discloses “wherein the vehicle is a battery-electric vehicle.” (Holme col. 5, ll. 50-65).
Regarding claim 10, the combination of Loonen and Holme discloses the limitations contained in parent claim 12 for the reasons discussed above. In addition, the combination of Loonen and Holme discloses “[a] computing unit that is configured to perform all method steps of a method according to claim 12.” (Holme col. 5, ll. 50-65).
Regarding claim 13, the combination of Loonen and Holme discloses the limitations contained in parent claim 12 for the reasons discussed above. In addition, the combination of Loonen and Holme discloses “wherein the model is determined based on the plurality of predetermined power limits and at least one further power limit, wherein the at least one further power limit is determined on the basis of the plurality of predetermined power limits” (Holme col. 3, ll. 6-22) where the prediction (i.e., one future power limit) may be used to generate another prediction with a second model.
Regarding claim 14, the combination of Loonen and Holme discloses the limitations contained in parent claim 12 for the reasons discussed above. In addition, the combination of Loonen and Holme discloses “wherein the model is redetermined in the presence of one or more new predetermined power limits. (Holme col. 18, l. 64-col. 19, l. 5) by retraining the model based on updated data.
Regarding claim 15, the combination of Loonen and Holme discloses the limitations contained in parent claim 4 for the reasons discussed above. In addition, the combination of Loonen and Holme discloses “wherein the trajectory is a speed trajectory. (Holme col. 17, l. 57-col. 18, l. 9) where the predictions are used to adjust the speed of the vehicle, which is a speed trajectory.
Regarding claims 24 and 25, the combination of Loonen and Holme discloses the limitations contained in parent claims 4 and 12 for the reasons discussed above. In addition, the combination of Loonen and Holme discloses “wherein the maximum power is a voltage and amperage that can be provided by the energy storage for the predetermined period of time” (Loonen ¶ 34) where the voltage and current values, which a person of ordinary skill in the art would understand is measured in amperes, is calculated for periods of time.
Claims 6, 7, 22, and 23 are rejected under 35 U.S.C. § 103 as being unpatentable over Loonen in view of Holme, as applied to claims 4 and 8 above, in view of Jiang, US Publication 2022/0227397 (hereinafter Jiang).
Regarding claim 6, the combination of Loonen and Holme discloses the limitations contained in parent claim 4 for the reasons discussed above. In addition, the combination of Loonen and Holme discloses “wherein the at least one input value for the model comprises the output value at a previous time point” (Loonen ¶ 56) where the outputs are used as inputs.
The combination of Loonen and Holme does not appear to explicitly disclose “determining the sequence of actions for at evenly spaced time points, wherein the at least one input value for the model comprises the output value at a previous time point and a corresponding output value is determined for each of the evenly spaced time points by means of the model.”
However, Jiang discloses a route planning method including the step of “determining the sequence of actions for at evenly spaced time points” (Jiang ¶ 46) by giving examples of route planning with action intervals at every 100 milliseconds and 5 seconds. Additionally, Jiang discloses “wherein the at least one input value for the model comprises the output value at a previous time point and a corresponding output value is determined for each of the evenly spaced time points by means of the model” (Jiang ¶ 47) by dynamically updating the path based on the user’s driving, meaning that prior output points are input to the path generation algorithm.
Loonen, Holme, and Jiang are analogous art because they are from the “same field of endeavor,” namely that of route planning methods.
Prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Loonen, Holme, and Jiang before him or her to modify the route planner of Loonen and Holme to include the use of evenly spaced time points of Jiang.
The motivation/rationale for doing so would have been that of applying a known technique to a known device. See KSR Int’l Co. v. Teleflex Inc., 550 US 398, 82 USPQ2d 1385, 1396 (U.S. 2007) and MPEP § 2143(I)(D). The combination of Loonen and Holme teaches the “base device” for planning a route of a vehicle. Further, Jiang teaches the “known technique” of planning a route based on evenly spaced time points that is applicable to the base device of Loonen and Holme. One of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system because all routes contain actions at future time points and those time points must necessarily be spaced evenly or spaced unevenly, indicating that such a modification would likely be a success.
Regarding claim 7, the combination of Loonen, Holme, and Jiang discloses the limitations contained in parent claim 6 for the reasons discussed above. In addition, the combination of Loonen, Holme, and Jiang discloses “wherein the sequence of actions is further determined while taking at least one selected from the group consisting of static and dynamic characteristics of the vehicle into account” (Holme TABLE 2) where the input parameters are shown to include both static and dynamic characteristics of the vehicle.
Regarding claims 22 and 23, the combination of Loonen and Holme discloses the limitations contained in parent claims 4 and 8 for the reasons discussed above. In addition, the combination of Loonen and Holme does not appear to explicitly disclose “wherein the trajectory includes an overtaking maneuver.”
However, Jiang discloses a route determining method using a machine learning engine, “wherein the trajectory includes an overtaking maneuver” (Jiang ¶ 44) where the trajectory includes a pass action, which is an “overtaking maneuver” within the plain and ordinary meaning of the term.
Loonen, Holme, and Jiang are analogous art because they are from the “same field of endeavor,” namely that of route planning methods.
Prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Loonen, Holme, and Jiang before him or her to modify the route planner of Loonen and Holme to include the pass maneuvers of Jiang.
The motivation/rationale for doing so would have been that of applying a known technique to a known device. See KSR Int’l Co. v. Teleflex Inc., 550 US 398, 82 USPQ2d 1385, 1396 (U.S. 2007) and MPEP § 2143(I)(D). The combination of Loonen and Holme teaches the “base device” for planning a route of a vehicle. Further, Jiang teaches the “known technique” of planning a route including a pass maneuver that is applicable to the base device of Loonen and Holme. One of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system because passing maneuvers are a very common driving action, indicating that such a modification would likely be a success.
Claims 16, 17, 19, and 20 are rejected under 35 U.S.C. § 103 as being unpatentable over Holme in view of Brannan, US Patent 11,447,024 (hereinafter Brannan).
Regarding claims 16 and 19, the combination of Loonen and Holme discloses the limitations contained in parent claims 4 and 12 for the reasons discussed above. In addition, the combination of Loonen and Holme does not appear to explicitly disclose “determining a time schedule for charging the energy storage.”
However, Brannan discloses a route planning method and system including the step of “determining a time schedule for charging the energy storage” (Brannan col. 14, l. 45-col. 16, l. 4) by disclosing an exemplary method for scheduling a recharge including analysis of what times are available.
Loonen, Holme, and Brannan are analogous art because they are from the “same field of endeavor,” namely that of route planning algorithms.
Prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Loonen, Holme, and Brannan before him or her to modify the route planning of Loonen and Holme to include the recharge scheduling of Brannan.
The motivation for doing so would have been to reduce “range anxiety” that is often experienced by drivers of electric vehicles. (Brannan col. 12, ll. 7-20).
Regarding claims 17 and 20, the combination of Loonen, Holme, and Brannan discloses the limitations contained in parent claims 16 and 19 for the reasons discussed above. In addition, the combination of Loonen, Holme, and Brannan discloses “wherein charging occurs via external charging from a power grid or via recuperation” (Holme col. 19, ll. 53-59, col. 29, ll. 1-14) where the charging occurs via external charging (col. 19, ll. 53-59) or via regenerate braking, which is another name for recuperation (col. 29, ll. 1-14).
Response to Arguments
Applicant’s arguments filed February 24, 2026, with respect to the rejection of claims 4, 6-17, 19, 20, 22, and 23 under 35 U.S.C. §§ 102(a)(1) and 103, respectively, (Remarks 7-12) have been considered but are moot in view of the new grounds of rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure:
Desprez et al., US Publication 2016/0301219, System and method for predicting the maximum amperage and voltage of a battery.
Killic, US Publication 2018/0001777, System and method for predicting the maximum amperage and voltage of a vehicle battery.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 C.F.R. § 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 C.F.R. § 1.17(a)) pursuant to 37 C.F.R. § 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ANDREW R DYER/Primary Examiner, Art Unit 3662