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 .
Response to Arguments
Applicant's arguments filed 10/22/2025 have been fully considered but they are not persuasive.
Regarding applicants argument that “claim 1 recites, "determining, by the control system, charging requirements for each of a first plurality of electric vehicles." Applicant submits that the Daniel reference fails to disclose this element of claim 1. Claim 1 further recites that allocating energy to charge the first plurality of electric vehicles may be allocated based on, "the charging requirements for each of the first plurality of electric vehicles." Applicant submits that the Daniel reference also fails to disclose this element of claim 1” the Examiner restfully disagrees.
Daniel discloses in para 0210 that;
For example a dedicated neural network may recognise that a change in load corresponds to the start of an electric vehicle charge event, and then use additional learnt behavior or data (e.g. size and type of vehicle) to make a prediction on the duration of charge and therefore aid informing the forecast load for the next few hours [emphasis added]. This then aids a utility on a supply and trade position, or a local network in forward knowledge of load demand on the network.
As seen the prior art clearly used the size and type of vehicle and thus the particular charging requirements for each type of vehicles of the plurality of vehicles. Therefore one of ordinary skill in the filed would clearly look at the prior art and arrive at applicants invention without an inventive step. In fact the system of Daniel clearly uses the charging requirements of each vehicle to generate a charging strategy that would be use renewable resources and maximize cost and profit, therefore Daniel clearly anticipates the currently drafted claims.
Further regarding applicant argument that claims 9, 10, 19 and 20 are not anticipated by Daniel. These claims were amended to include new limitations that are supported by the prior art. Lui in the same art clearly disclosed the cited limitation not disclosed by Daniel. Lui teaches that the limitations are not novel nor inventive in light of Daniel in view of Lui.
In conclusion the prior art teaches all of the limitations as currently presented any minor differences would flow naturally to one of ordinary skill within the filed. To expedite prosecution, the examiner recommends amending the claims to include structural components that distinguish the invention from the cited prior art.
Double Patenting
Claims 1-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of copending Application No. 18/506,397 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because the scope of the applications are not patentably distinct and considered obvious variances of each other. In other words
the claims in the applications are not considered a distinct invention from each other, but rather a variation or a trivial, obvious improvement.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-7 and 11-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Daniel (US 2021/0221247).
Regarding claim 1, Daniel teaches a method comprising (see Fig. 1): determining, by a control system (see para 0022, and algorithms 12, para 0127 Fig. 1), an amount of energy presently available from an existing power grid connection (see central Grid 23, para 0127, Fig. 1); determining, by the control system, an amount of energy presently received from a solar array (see solar 31 para 0127; Fig. 1 and 4); identifying, by the control system, a present state-of-charge level of a stationary battery (see battery 23; para 0050); determining, by the control system, charging requirements for each of a first plurality of electric vehicles (see para 0210); and allocating, by the control system, energy to charge a first plurality of electric vehicles, wherein energy is allocated from at least one of the existing power grid connection, the solar array, or the stationary battery (see at EV charger 34, EV 35 connected to power grid 23 or solar 31 or battery 32) based on: the amount of energy presently available from the existing power grid connection (see para 0014, 0050 0127 and 0130); the amount of energy presently received from the solar array (see para 0200 and 0201); the present state-of-charge level of the stationary battery (see para 0200 and 0201) and the charging requirements for each of the first plurality of electric vehicles (see para 0210).
Regarding claim 11, Daniel teaches an apparatus (see Fig. 1)comprising: a solar array configured to generate energy in response to received sunlight (see solar 31 para 0127; Fig. 1 and 4); a stationary battery configured to store energy (see ); and a control system (see para 0022, and algorithms 12, para 0127 Fig. 1) configured to: determine an amount of energy presently available from an existing power grid connection (see central Grid 23, para 0127, Fig. 1); determine an amount of energy presently received from the solar array (see solar production, 0047, 0133 and 0142); identify a present state-of-charge level of the stationary battery (see battery 23, para 0050); determine charging requirements for each of a first plurality of electric vehicles and allocate energy to charge a first plurality of electric vehicles (see para 0210), wherein the energy is allocated from at least one of the solar array, the existing power grid connection, or the stationary battery (see at EV charger 34, EV 35 connected to power grid 23 or solar 31 or battery 32) based on: the amount of energy presently available from the existing power grid connection (see para 0133); the amount of energy presently received from the solar array (see solar 31 para 0127; Fig. 1 and 4); and the present state-of-charge level of the stationary battery (see para 0050, ) and the charging requirements for each of the first plurality of electric vehicles (see para 0210).
Regarding claims 2 and 12, Daniel teaches wherein energy is further allocated from at least one of the existing power grid connection, the solar array, or the stationary battery based on an amount of charge an electric vehicle is requesting or offering (see para 0014, 0050, 0127, 0200 and 0201).
Regarding claims 3 and 13, Daniel teaches wherein allocating energy is further based on at least one of: a price of energy presently available from the existing power grid connection (see 23; Fig. 1 and 4; para 0014; 0050; 0130; 0141 and 0141); an estimated price of energy from the existing power grid connection in the near future; or; energy currently being consumed by an electric service to which the control system is coupled.
Regarding claims 4 and 14, Daniel teaches wherein the control system is further configured to allocate energy based on: current energy needs to charge the first plurality of electric vehicles (see para 0127, 0200 and 0201); and future energy needs to charge a second plurality of electric vehicles (see 0014, 0047 and 0138).
Regarding claims 5 and 15, Daniel teaches wherein allocating energy is further based on at least one of: a present state-of-charge level of each of the first plurality of electric vehicles (see para 0050, 0141 and 0204); a present state-of-charge level of each of the second plurality of electric vehicles; a charging priority associated with at least a portion of the first plurality of electric vehicles; or forecast energy expected to be received from the solar array in the future.
Regarding claim 6, Daniel teaches wherein allocating energy is further based on a price of energy from the existing power grid connection at a future time (see 0014, 0135, 0141, 0161 and 0180).
Regarding claim 7, Daniel teaches wherein allocating energy to charge a first plurality of electric vehicles is further performed by an artificial intelligence engine (see para 0050, 0127, 0200 and 0201).
Regarding claim 16, Daniel teaches further comprising an artificial intelligence engine coupled to the control system and configured to manage charging of the first plurality of electric vehicles (see para 0127, 0200 and 0201).
Regarding claim 17, Daniel teaches wherein the artificial intelligence engine is further configured to prioritize and schedule charging activities associated with the first plurality of electric vehicles (see para 0014, 0018, 0127, 0200, and 0201).
Claim Rejections - 35 USC § 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, 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 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Daniel in view of Hosseini et al (US 2023/0297860).
Regarding claims 8 and 18, Daniel teaches the method/ apparatus of claims 1 and 11 respectively.
Yet does not disclose wherein allocating energy to charge a first plurality of electric vehicles is further based on data from a Large Language Model (LLM).
However, Hosseini in the field of methods for enabling application of autonomous economic agents of artificial intelligence (see para 0065, 0070, 0071 and 0146).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Daniel with the teachings of Hosseini by allocating energy to charge a first plurality of electric vehicles is further based on data from a Large Language Model (LLM) in order to automat and enhance numerous tasks that improve the efficiency, accessibility, and dependability of charging foundation by analyze user preferences, and generate optimal suggestions.
Claims 9, 10, 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Daniel in view of Liu et al (US 2020/0082352).
Regarding claims 9 and 19, Daniel teaches the method of claim 1; the apparatus of claim 11, respectively.
Yet, does not disclose wherein determining charging requirements for each of the first plurality of electric vehicles includes determining, for each of the first plurality of electric vehicles, at least one of battery depletion, required charging intervals, miles driven, upcoming charging needs, predicted future charging needs, or historical charging patterns.
However, Liu in the same filed teaches determining charging requirements for each of the first plurality of electric vehicles includes determining, for each of the first plurality of electric vehicles, at least one of battery depletion, required charging intervals, miles driven, upcoming charging needs, predicted future charging needs, or historical charging patterns (see 0077, 0078-0081 and 0090)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Daniel with the teachings of Liu by having determining charging requirements for each of the first plurality of electric vehicles includes determining, for each of the first plurality of electric vehicles, at least one of battery depletion, required charging intervals, miles driven, upcoming charging needs, predicted future charging needs, or historical charging patterns in order to provide Grid Stability, Load Balancing, Extended Battery Lifespan, Improved Customer Satisfaction, Improved Efficiency and Reduced Energy Consumption.
Regarding claims 10 and 20, Daniel teaches the method of claim 1; the apparatus of claim 11, respectively.
Yet, does not disclose wherein the control system is further configured to: schedule a charging order for the first plurality of electric vehicles, wherein the charging order for charging the first plurality of electric vehicles is determined based on at least one of each vehicle's charging priority, charging rate, charging method, vehicle type, battery depletion, required charging intervals, miles driven, upcoming charging needs, predicted future charging needs, or historical charging patterns.
However, Liu in the same filed teaches the control system is further configured to: schedule a charging order for the first plurality of electric vehicles, wherein the charging order for charging the first plurality of electric vehicles is determined based on at least one of each vehicle's charging priority, charging rate, charging method, vehicle type, battery depletion, required charging intervals, miles driven, upcoming charging needs, predicted future charging needs, or historical charging patterns (see 0077, 0078-0081 and 0090).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Daniel with the teachings of Liu by having the control system is further configured to: schedule a charging order for the first plurality of electric vehicles, wherein the charging order for charging the first plurality of electric vehicles is determined based on at least one of each vehicle's charging priority, charging rate, charging method, vehicle type, battery depletion, required charging intervals, miles driven, upcoming charging needs, predicted future charging needs, or historical charging patterns in order to provide Grid Stability, Load Balancing, Extended Battery Lifespan, Improved Customer Satisfaction, Improved Efficiency and Reduced Energy Consumption
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 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 CFR 1.17(a)) pursuant to 37 CFR 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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/ELIM ORTIZ/ Primary Examiner, Art Unit 2836