DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office action is responsive to the amendment filed on 12/15/2025. The claim(s) 1- 6, 9- 14, & 17- 22 is/are pending, of which the claim(s) 1, 9, & 17 is/are in independent form. The claims 7- 8, 15- 16, & 23- 29 were cancelled by applicant.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Response to Arguments
I) Arguments against the Claim Rejections - 35 USC § 101
Applicant's arguments with respect to Claim Rejections - 35 USC § 101 filed 12/15/2025 have been fully considered but they are not persuasive.
As to amended independent claims 1 & 9, applicant argues claims’ reciting of using of “one or more machine learning models” preclude an interpretation of a mental process. Specifically, applicant argues that
“amended claim 1 recites at least one additional feature of inputting data into a machine learning model to preclude an interpretation of a mental process. Therefore, claim 1 does not recite an abstract idea and the answer to Step 2A, Prong 1 is "NO". Similarly, claim 9 has been amended to recite similar features and claims 2-6 and 10-14 are dependent on claims 1 and 9, respectively. Accordingly, Applicant respectfully requests that the rejection of claims 1-6 and 9-14 be withdrawn.”
See Remarks, page 11
Response: Examiner respectfully disagrees. As fully set forth below in the updated 101 rejection, the adding of “into one or more machine learning models” is akin to mere using a computer, or merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Here, the claimed “one or more machine learning models” is recited at very high level of generality without specifying how these various four inputs interact to generate three outputs (namely: additional charging point, optimal location of each charging point, or optimal storage capacity). Examiner agrees that “machine learning models” themselves cannot be performed in human’s mind but remaining features of the input step can be practically performed in human’s mind. The “machine learning models” are treated as “additional elements” and considered in Step 2A, Prong 1 and Step B.
Just because claim limitations are tied to generic computer element with software model (“machine learning models” an example AI), they do not automatically become non-abstract if the performed steps also can be performed manually as in this case. Please note that “In Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea”, MPEP 2106.04 III. (C). Here, mere using of the “machine learning model” to perform an action that is otherwise possible to perform manually still is an abstract idea. This is so because it is an example of performing a mental process in a computer environment.
Furthermore, the input step of claim is broad enough to determine number of charging points for a small location such as within a zip code area that merely can have few charging stations (e.g., 5-10 numbers). Human mind can evaluate various available parameters such as those in the claim to determine where and how many more charging stations and capacity for the battery would be optimum choices using their judgement. Such decision merely requires solving of a mathematical problem and human mind can solve these problems with the aid of pen and paper at most. Therefore, the outstanding 101 rejections are respectfully maintained.
II) Arguments against Claim Rejections - 35 USC § 103
1) As to claims 17- 22, applicant’s arguments with respect to claim(s) 17- 22 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.
Specifically, newly discovered US 20120203726 A1 to Klabjan is relied on to teach the features challenged in the arguments.
2) As to claims 1 & 9, applicant's arguments filed 12/15/2025 have been fully considered but they are not persuasive.
As to claims 1 & 9, applicant’s arguments, see Remarks, filed 12/15/2025 with respect to 1 & 9 have been fully considered and are persuasive. The 103 of claims 1 & 9 has been withdrawn.
Claim Objections
Claims 17- 22 objected to because of the following informalities:
As to claim 17, in line 8-9, “and a number of electric energy storage devices” should be changed to “and a the number of electric energy storage devices” to clearly link this element with “one or more electric energy storage devices” line 3.
The claims 18- 22, these claims are also objected because of their dependency with objected claim 17.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1- 6 & 9- 14 rejected under 35 U.S.C. 101 because the claimed invention is directed to Judicial Exception (“abstract idea”) without significantly more.
As to claim 1:
1. An electrification system 1for electrification of a fleet of vehicles using an energy distribution system, the energy distribution system comprising a number of electric energy storage devices defining an electric energy storage capacity associated with each vehicle in a group of vehicles in the fleet, and a group of installed charging points, each installed charging point being associated with a location in an area, the electrification system comprising:
[1] a processor; and at least one non-transitory memory containing instructions which when executed by the processor cause the electrification system to:
[a] receive positional information relating to a position of a plurality of vehicles in the fleet over time;
[b] receive energy consumption information relating to energy consumed by the plurality of vehicles in the fleet over time; and
[c] input the received positional information, the energy consumption information, the electric energy storage capacity associated with each vehicle in the group of vehicles and the locations associated with the installed charging points of the group of installed charging points into one or more machine learning models to determine a number of additional charging points, an optimal location within the area associated with each of the additional charging points and an optimal electric energy storage capacity associated with each of the plurality of vehicles, that minimizes the number of additional charging points maximizes utilizations of the optimal electric energy storage capacities.
1. Step 1: Yes. The claim is to a system with a processor and computer readable memory, which is one of the four categories of patent eligible subject matter.
2. Step 2A, Prong 1: Yes. The claim(s) recite(s) the limitation [c]. This limitation as drafted, is a process, that under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, namely “machine learning model” which is an AI. That is, other than reciting “machine learning models” nothing in the claim element precludes the step from practically being performed in the mind via observation, evaluation, judgment, opinion at most with the aid of pen and paper. For example, but for the “one or more machine learning models”, the inputting (considering or evaluating the available data or inputted data) to determine steps in the context of this claim encompasses the user manually evaluating four inputs (the received positional information, the energy consumption information, the electric energy storage capacity associated with each vehicle in the group of vehicles and the locations associated with the installed charging points of the group of installed charging points) to generate three optimal outputs (number of additional charging points, an optimal location within the area associated with each of the additional charging points and an optimal electric energy storage capacity associated with each of the plurality of vehicles that minimizes the number of additional charging points is minimized and maximizes utilizations of the optimal electric energy storage capacities). Furthermore, the claim recites using a processor and memory to input data into a “machine learning models” to determine claimed outputs, it is also used merely to automate the inputting data to determine outputs hence is akin to apply the exception using a generic computer component. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Please note that “judicial exceptions need not be old or long-prevalent, and that even newly discovered or novel judicial exceptions are still exceptions” as in this case. That is, while the claim recites novel subject matter, it still is an abstract idea since it can be practically performed in human’s mind. Accordingly, the claim recites an abstract idea because this limitation under BRI can be reasonably performed in human’s mind.
3. Step 2A, Prong 2: No. This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements shown above with bold emphasis. The additional elements are:
- a processor; and at least one non-transitory memory containing instructions which when executed by the processor cause the electrification system to:
- receive positional information relating to a position of a plurality of vehicles in the fleet over time;
- receive energy consumption information relating to energy consumed by the plurality of vehicles in the fleet over time.
- “into one or more machine learning models” of input step.
The additional element of “a processor and at least one non-transitory memory containing instructions” and “machine learning models” (e.g., a general purpose Artificial Intelligence AI) are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component. The generic computer can execute an AI element like claimed “one or more machine learning models” and are also can be called off-the-shelf computer before filing of the invention as can be clear to PHOSITA.
The other additional elements of “receive positional information relating to a position of a plurality of vehicles in the fleet over time;
receive energy consumption information relating to energy consumed by the plurality of vehicles in the fleet over time” are also recited at a high level of generality as general means of data gathering to input into a model and perform the determine step. Hence, both receiving steps are akin to adding data gathering type of the insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g). The individual and combination of additional elements fail to integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the above abstract idea. Even considering the claim as a whole, the additional elements continue to remain using off-the-shelf computer to automate the abstract idea by gathering some data but fails to impose a meaningful limits on the judicial exception. The claim is directed to an abstract idea.
4. Step 2B: No. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element(s) of receiving steps amount(s) to no more than adding insignificant extra-solution activity. Examiner takes an Official notice that these receiving steps are well-understood, routine, conventional activity by relying on the cited 2prior arts as evidence under Berkheimer memo. The using of a processor and memory along with inputting data into “into one or more machine learning models” amounts to mere automating the inputs of the data to perform input and determining step using generic computer components (a computer with machine learning models). The additional elements when considered separately and in combination do not add significantly more (also known as an “inventive concept”) to the exception and do not impose a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize or preempt the judicial exception. Additionally, the claim 1 does not reflect an improvement to the function of a computer or to another technology or technical field. Here, using of the models are merely automating otherwise a manual process and the claim as a whole does not provide an inventive concept. The claim is not patent eligible.
Regarding claim 9:
1. Step 1: Yes. The claim is to a computer-implemented method, which is one of the four categories of patent eligible subject matter.
2. Step 2A, Prong 1: Yes. The claim recites the limitations of “input the received positional information, the energy consumption information, the electric energy storage capacity associated with each vehicle in the group of vehicles and the locations associated with the installed charging points of the group of installed charging points ” as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “into one or more machine learning models,” nothing in the claim element precludes the step from practically being performed in the mind. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas as in this case. Accordingly, the claim recites an abstract idea.
3. Step 2A, Prong 2: No. This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements of:
“receiving positional information relating to a position of a plurality of vehicles in the fleet over time;”
“receiving energy consumption information relating to energy consumed by the plurality of vehicles in the fleet over time” and
“into one or more machine learning models” in inputting step.
The limitation (“for electrification of a fleet of vehicles using an energy distribution system, the energy distribution system comprising a number of electric energy storage devices defining an electric energy storage capacity associated with each vehicle in a group of vehicles in the fleet, and a group of installed charging points, each installed charging point being associated with a location in an area”) of the preamble is not positively recited and hence do not receive patentable weight. Only for the sake of argument, if this were to be required limitation it can be an additional element but is akin to generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h).
Here, both receiving steps are recited at very high level of generality and hence are mere data gathering step or adding of insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g). The using of one or more machine learning model is also recited at very high level of generality such that they amount no more than mere implementing an abstract idea on a computer- see MPEP 2106.05(f). Accordingly, additional elements individually or in combination do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
4. Step 2B: No. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amounts to no more than mere instructions to apply the exception using a generic computer component, “machine learning models” and adding of insignificant extra-solution activity for the receiving step. Furthermore, both receiving steps are only well-understood, routine, conventional activity and examiner takes an Official notice to that effect by relying on the prior cited arts for Berkheimer memo. Mere instructions to apply an exception using a generic computer component (with machine learning models) and using of well-understood and routine insignificant extra-solution activity cannot provide an inventive concept. The claim is not patent eligible under 101.
Regarding dependent claims 2 & 10, these claims depend on claims 1 & 9 respectively, and therefore recite the same abstract idea and additional elements outlined above. These dependent claims further require the limitation of “set limits on the number of additional charging points and the optimal electric energy storage capacities associated with the plurality of vehicles based on the received further constraint information” but this too can be practically performed in human’s mind and hence still abstract. The limitation of “receive further constraint information” is an additional element. However, this too does not go beyond adding of a well-known, routine, and conventional extra-solution activity and hence cannot provide a practical application and an inventive step even considering together with other additional elements. The receiving of constraints in optimization art is well-known in the art per Berkheimer memo. These claims are not patent eligible.
Regarding claims 3- 4 & 11- 12, they depend on claims 2 & 10 respectively, and therefore recite the same abstract idea and additional elements outlined above in claims 2 & 10. These claims introduce new limitations but they too can be practically performed in human’s mind hence still mental processes based abstract ideas. They do not recite any new additional elements. If the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) as in this case. Therefore, these claims also fail to provide a practical application in Step 2A Prong 2 and an inventive step in step 2B. These claims are not patent eligible.
Regarding dependent claims 5- 6 & 13- 14, they depend on claims 1 & 9 respectively. Therefore these claims recite the same abstract idea and additional elements outlined above. These dependent claims further introduce other limitations but they too can be practically performed in human’s mind, at most with the aid of pen and paper hence merely recite another judicial exception. These claims fail to provide a practical application and an inventive step. They are not patent eligible.
Claim Rejections - 35 USC § 103
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Klabjan et al. (US 20120203726 A1) in view of Yang (US 20220281343 A1, Foreign Application Date: 2019-07-30, reference of record).
Regarding claim 17, Klabjan teaches an energy distribution system for a fleet of vehicles [“electric vehicles for the specified area”, the energy distribution system comprising: (Abstract, [022]);
[a] one or more electric energy storage devices [“recharge electric vehicle batteries”. PHOSITA knows that at least each of the electric vehicles of Klabjan can have a battery to provide operating power] associated with each vehicle in a group of vehicles ([020, 062]); and
[b] one or more electric charging points [“At block 270, charging station(s) are allocated based on street level address”] configured to
wherein [i] the specific locations [“optimize the electric vehicle charging station location plan for the specified area”, blocks 160 and 170 provide recommendations for charging infrastructure] of the one or more charging points and [ii] a number of electric energy storage devices [“electric vehicle demand forecast information”, “At block 120, a demand for electric vehicles is forecast for the selected area” or “block 210, a number of potential EV buyers is forecast” suggests number of vehicles each having number of batteries] are determined using one or more machine learning models [e.g., “using a regression”-which is known supervised machine learning as can be clear to PHOSITA] to process (i) previous location information [“information regarding location”] and (ii) previous energy consumption information [“information regarding location, driver habits and available power information… includes an optimizer to optimize the electric vehicle charging station location plan for the specified area based on driving pattern and electric vehicle demand forecast information for the specified area” and “Vehicle range is a factor for determining the locations and number of charging stations”. The driver habits and “vehicle range” related information provides information about power/energy consumption] associated with the group of vehicles ([023-031, 036-038, 048], claim 4).
Klabjan fails to teach its charging stations being configured to wirelessly charge the one or more electric energy storage devices as claimed.
Yang teaches a server managing wireless charging of a vehicle on a road having pluralities of the wireless charging stations. Specifically, Yang teaches An energy distribution system comprising:
one or more electric charging points [“At each intersection, a chargeable region capable of wireless charging is provided in a predetermined region or location“] configured to wirelessly charge the one or more electric energy storage devices, each electric charging point being positioned at a specific location in an area (Fig. 1, [049]).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Yang and Klabjan because they both related to installing charging stations at pluralities of the location of an area where the vehicles with energy storage devices are expected to travel and (2) have the one or more charging points of Klabjan to include at least one or more wireless types of the charging stations to allow wireless charging of the vehicles of Klabjan. Additionally, having one or more charging stations being wireless type as in Yang allows wirelessly charge the storage devices (batteries) of the electric vehicles even when they are waiting for traffic signals thereby improving drivers satisfactions (Yang [054]).
Claim(s) 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Klabjan in view of Yang, and further in view of Zhamu et al. (US 20180330893 A1, reference of record).
Regarding claim 18-19, Klabjan in view of Yang teaches the energy distribution system of claim 17, wherein the one or more electric energy storage devices comprise batteries.
However, Klabjan in view of Yang fails to teach:
energy storage devices comprise one or more low storage capacity, rapid recharge, high cycle life electric energy storage devices as in claim 18
wherein the one or more low storage capacity, rapid recharge, high cycle life electric energy storage devices comprise supercapacitors as in claim 19.
However, Zhamu teaches an energy distribution system for a fleet of vehicles comprising:
one or more electric energy storage devices associated with each vehicle in a group of vehicles, wherein the one or more electric energy storage devices comprise one or more low storage capacity, rapid recharge, high cycle life electric energy storage devices, wherein the one or more low storage capacity, rapid recharge, high cycle life electric energy storage devices comprise supercapacitors. [“ultracapacitors or supercapacitors, are being considered for use in hybrid electric vehicles (EVs) where they can supplement a battery used in an electric car to provide bursts of power needed for rapid acceleration”] ([002, 0100]).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Zhamu and Klabjan in view of Yang because they both related to improving electric vehicles’ battery utilization to minimize range anxiety and (2) modify some of the vehicles of the Klabjan in view of Yang to include supercapacitors in addition to its batteries. Doing so would provide bursts of power needed for rapid acceleration for the vehicles of the Klabjan in view of Yang (Zhamu,[002]).
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Klabjan in view of Yang, and further in view Long (US 20170294941 A1, reference of record).
Regarding claim 20, Klabjan in view of Yang teaches/suggests the energy distribution system of any one of The energy distribution system of any one of wherein the one or more electric charging points are configured to wirelessly [“wireless charging services for wirelessly charging a vehicle while the vehicle is at a standstill”] charge the one or more electric energy storage devices
Klabjan in view of Yang fails to teach what specific technique (i.e., using of Resonant Magnetic Induction (RMI) charging) its system utilizes to implement its wireless charging.
Long teaches an energy distribution system comprising one or more electric charging points that are configured to wirelessly charge the one or more electric energy storage devices using Resonant Magnetic Induction (RMI) charging [“the use of dynamic charging may be accomplished using resonant magnetic induction”] ([051, 055]).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Long and Klabjan in view of Yang because they both related to wireless charging for the batteries of the electric vehicles while they are in motion and (2) have some of the charging stations of the Klabjan in view of Yang to use Resonant Magnetic Induction (RMI) charging as in Long. Doing so the batteries of the vehicles of the Klabjan in view of Yang can be charged while the vehicles are in motion so that arriving at the destination would be faster (Long [051]).
Claim(s) 21-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Klabjan in view of Yang, and further in view Kinav (US 20150343920 A1, reference of record).
Regarding claim 21, Klabjan in view of Yang teaches an energy distribution system of claim 17 as set forth above.
However, Klabjan in view of Yang may or may not teach its system to include a secondary electric energy source associated with each vehicle in the group of vehicles, each secondary electric energy source associated with a vehicle being configured to charge the electric energy storage devices associated with the vehicle.
Kinav teaches an energy distribution system to include a secondary electric energy source [“internal combustion engine-generator 120”] associated with each vehicle [“an electric vehicle 100”, analogous to vehicles of Klabjan in view of Yang] in the group of vehicles, each secondary electric energy source [battery 110] associated with a vehicle being configured to charge the electric energy storage devices associated with the vehicle ([013-014, 027]).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Kinav and Klabjan in view of Yang because they both related to maximizing travel range of the electric vehicle battery and (2) modify the system of Klabjan in view of Yang to include secondary electric energy source as in Kinav. Doing so would allow to continue to charge the batteries of electric vehicles of the Klabjan in view of Yang in cases of emergency which is no longer limited by time, places or facility (Kinav, [027]).
Regarding claim 22, the combination of Klabjan, Yang, and Kinav teaches the energy distribution system of claim 21, wherein the secondary electric energy source comprises an internal combustion engine and an electric generator (Kinav, [027] Fig. 1).
Allowable Subject Matter
Claims 1- 6 & 9- 14 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action. Specifically, the claims 1 & 9 recite novel and non-obvious subject matter of the references of the record.
Conclusion
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 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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
1) Kumar (US 20210276447 A1) teaches controls the EV charging infrastructure using machine learning ([009]).
2) Ahtikari (US 20220305934 A1) teaches enter basic information of the location of the EV charging station 401 to the trained machine learning model 305 ([085]).
Contacts
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANTOSH R. POUDEL whose telephone number is (571)272-2347. The examiner can normally be reached Monday - Friday (8:30 am - 5:00 pm).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached at (571) 272-2279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SANTOSH R POUDEL/ Primary Examiner, Art Unit 2115
1 The limitation of the preamble (“for electrification of a fleet of vehicles using an energy distribution system, the energy distribution system comprising a number of electric energy storage devices defining an electric energy storage capacity associated with each vehicle in a group of vehicles in the fleet, and a group of installed charging points, each installed charging point being associated with a location in an area”) is an intended use limitation and is not positively recited. Therefore, this portion of the preamble does not receive patentable weight.
2 Dai et al. (US 20130222158 A1, paras. [025-026, 033]); Richter et al. (US 20140188304 A1, [020-021]); Borugian et al. (US 20030097218 A1, para. 022); Basir (US 20100161165 A1, para. 005); Sworski et al. (US 20190299794 A1, para. 015).