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 .
Status of Claims
Claims 1-22 are pending.
Claims 1, 8, and 15 have been amended.
Claims 21 and 22 are new.
Response to Amendment
Objection to Specification: Applicant’s amendments to the specification overcome the objections to the specification. Objection to the specification are withdrawn
Rejections Under 35 U.S.C. §101: Applicant’s amended claims do not overcome the rejection of record. The rejections under 101 are maintained.
Rejections Under 35 U.S.C. §103: Applicant’s claims 1, 8, and 15 have been amended to change the scope of the claimed invention. Specifically, limitations pertaining to at least “apply a plurality of weightings to charging location data comprising data, the rating data comprising aggregated user ratings”
Response to Arguments
Rejection Under 35 U.S.C. §101: Applicant's arguments filed 06/27/2025 have been fully considered but they are not persuasive.
Applicant argues, “Claim Rejections under 35 U.S.C. §101 Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is allegedly directed to patent-ineligible subject matter.
Applicant respectfully traverses these rejections.
The Office has released Patent Subject Matter Eligibility guidelines that clarify how to apply the Alice Mayo test (Alice Corp. Pty. Ltd v. CLS Bank Int'l, 573 U.S. 208, 217-18, 134 S.Ct. 2437 (2014) (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 132 S.Ct. 1289 (2012))) for determining subject matter eligibility, which are referred to collectively as the "2019 PEG" See generally 2019 Revised Patent Subject Matter Eligibility Guidelines, 84 FR 50 ("Guidelines"); and October 2019 Update to the Revised Patent Subject Matter Eligibility Guidelines (the "October 2019 Update"). Part 1 of the Alice Mayo test is Step 2A of the Guidelines, which the Guidelines split into two prongs. Part 2 of the Alice Mayo test is Step 2B of the Guidelines.
At Step 1 of the 2019 PEG, an examiner is to consider whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. If so, the analysis continues to Step 2A Prong 1, otherwise the claim is not patent eligible and the analysis ends.
At Step 2A Prong 1, an examiner is to evaluate whether each claim recites a judicial exception. If so, the analysis continues to Step 2A Prong 2, otherwise the claim is patent eligible and the analysis ends.
At Step 2A Prong 2, an examiner is to evaluate whether each claim integrates the exception into a practical application. If so, the claim is patent eligible and the analysis ends, otherwise the analysis continues to Step 2B.
Finally, at Step 2B, an examiner is to evaluate whether each claim provides "significantly more" than the judicial exception. If so, the claim is patent eligible and the analysis ends, otherwise the claim is not patent eligible and the analysis ends.
The rejection of Applicant's claims under Section 101 should be reversed under the first prong of Step 2A of the USPTO Guidelines because the claims are not directed to a judicial exception.
Applicant's claims are eligible under the first prong of the Step 2A analysis because the features recited in the claims, let alone the claims as a whole, are not directed to a law of nature, a natural phenomenon, or an abstract idea. Contrary to the Examiner's assertion that the pending claims are directed to an abstract idea, the pending claims are not directed to any of the groupings ID-1030-US of abstract ideas identified in the Guidelines. For example, claims 1-22 do not recite mathematical concepts, mental processes, or certain methods of organizing human activity, as the Examiner asserts. Therefore, Applicant requests that the rejection under § 101 be reversed.”
Examiner respectfully disagrees, that the pending claims are not directed to any of the groupings of abstract ideas identified in the Guidelines and that claims 1-22 do not recite mathematical concepts, mental processes, or certain methods of organizing human activity, as Applicant asserts, as independent claims recite limitations such as “apply a plurality of weightings to charging location data comprising data, the rating data comprising aggregated user ratings” and “determine, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes and the weighted charging location data” which fall within the mental process(es) grouping of abstract ideas. The “applying” and “determining” limitations are mental process(es) as they particularly pertain to concepts that can be performed in the human including observation, evaluation, judgement and/or opinion and further are recited at a high generality that would not exclude the limitations from being performed in the human mind or by a human using a pen and paper (see at least MPEP § 2106.04(a)(2), subsection III).
Applicant also argues, “2. The rejection under Section 101 should be reversed under the second prong of USPTO Step 2A because the claims integrate the alleged abstract idea into a practical application.
While Applicant believes the claims do not recite an abstract idea, Applicant asserts that the alleged abstract idea is nevertheless integrated into a practical application.
Regarding the second prong of the Step 2A inquiry, Applicant submits that the currently pending claims are directed to an improvement in technology. Therefore, Applicant requests that the rejection under § 101 should be reversed.”
Examiner respectfully disagrees, that the abstract idea is nevertheless integrated into a practical application because the pending claims are directed to an improvement in technology, as in order to show improvement to technology or technical field “the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology” (see at least MPEP § 2106.05(a) and MPEP § 2106.05(f)). Specifically the claims as currently drafted, merely recite instructions to perform a method of searching for a charging location and outputting charging location search results on generic component(s) or machinery (computer processor (processor) and display device). Therefore due to the recitation of the processor and display device at a high generality and the mere recitation of instructions to perform the method on these generic components, for example in the limitations of “access a request for a charging location for an electric vehicle (EV), wherein the request comprises a plurality of charging location request attributes associated with the EV” and " output, via a display device, the charging location search result” the claim(s) would not qualify as an improvement to an existing technology.
Applicant further argues, “3. The rejection under Section 101 should be reversed under USPTO Step 2B because the claims provide an inventive concept.
Applicant respectfully submits that the claims recite an inventive concept that amounts to significantly more than an abstract idea and are therefore eligible subject matter under Section 101. For at least this additional reason, Applicant respectfully requests reversal of this rejection.”
Examiner respectfully disagrees, that the claims recite an inventive concept that amounts to significantly more than an abstract idea, as the claims amount to nothing more than an instruction to apply the abstract idea using a generic computer which the courts have found to not be enough to qualify as “significantly more” when recited in a claim with a judicial exception (see at least MPEP § 2106.05(f)). Therefore the 101 rejection is maintained.
Rejection Under 35 U.S.C. §103: Applicant's arguments filed 06/27/2025 have been fully considered but they are not persuasive.
Applicant argues, “For obviousness under 35 U.S.C. § 103, each and every limitation must be taught or suggested by the prior art reference, or references when combined or modified (MPEP 2143). It
should therefore be noted that Applicant need only point out a single limitation in each claim that is not disclosed, taught, or suggested by any reference identified in the Office Action to overcome the prior art-based rejections. The following discussion therefore should not be construed as an exhaustive listing of every distinguishing feature set forth in the claims.
Applicant submits that Teske in view of Becker and Nikulin does not disclose all of the features of currently amended claim 1. For example, Teske in view of Becker and Nikulin does not disclose "apply[ing] a plurality of weightings to charging location data comprising ranking data and rating data, the rating data comprising aggregated user ratings" and "determin[ing], using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes and the weighted charging location data."
Nikulin generally discloses an intelligent route planning system that detects and gathers information about a vehicle and occupants of the vehicle to determine a navigation route for the vehicle. See Abstract. In particular, Nikulin discloses that the route planning system can weigh the characteristics of an occupant and characteristics of charging stations when determining a preference for one charging station over another charging station, for example, by placing more weight on the cost of a charging station or on occupant characteristics such as occupant charging pattern and/or driving pattern. See ¶ [0033]. Separately, Nikulin discloses techniques for identifying rest stops to be added to a navigation route. See, e.g., ¶ [0054]. With respect to identifying rest stops along a navigation route, Nikulin discloses that occupant age (e.g., infant occupant, young occupant, elderly occupant) and rest stop rating (e.g., one-star, two-star, three- star, etc.) can be considered when determining a route. See id.
Notably, although Nikulin discloses that the route planning system can weigh the characteristics of charging stations when determining which charging station should be selected during route planning and, separately, further discloses techniques for routing a vehicle to a rest stop based on occupant age and rest stop rating, Nikulin fails to disclose that a plurality of weightings are applied to charging location data that includes both ranking data and rating data, as now required by amended claim 1. That is, as described above, the "ratings" disclosed by Nikulin are applied only to rest stops - Nikulin is entirely silent regarding implementing ratings for charging stations, much less that weightings are applied to such rating data.
For at least the reasons presented above, Nikulin fail to disclose the cited portion of amended claim 1.
Teske and Becker fail to cure the deficiencies of Nikulin set forth above.
In view of the above statements, the cited references fail to disclose all of the features of amended claim 1. Accordingly, Applicant respectfully submits that amended claim 1 is in condition for allowance. Claims 8 and 15 have been amended to recite similar features as claim 1 and are therefore also in condition for allowance. The remaining claims are dependent on one of the independent claims and are therefore allowable at least based on their dependency.”
Examiner respectfully disagrees, in response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). In particular Teske (US2019/0383637A1), hereinafter Teske, teaches wherein the request comprises a plurality of charging location request attributes associated with the EV (see at least [0005] “charging station query including one or more parameters”) and determine, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes (see at least [0048] “If the charging query includes one or more targeted connector codes (e.g., "YES" at 504) and/or once a targeted connector code is determined/mapped at 506/508, the method includes using the targeted connector code(s) as a search key to identify charging stations that fit the parameters of the charging query (e.g., charging stations that are compatible with the targeted connector code(s)), as indicated at 510.”), and suggests “rating data, the rating data comprising aggregated user ratings” and determine, using an electric vehicle management system, a charging location search result based on the rating data (see at least [0064] “The user may provide input to user interface 800 and/or another user interface window for the application providing user interface 800 in order to select other settings for filtering charging station search results. Example additional settings include...minimum charging station rating from one or more user review databases”).
Nikulin et al. (US2018/0143029A1), hereinafter Nikulin, teaches apply a plurality of weightings to charging location data comprising ranking data and rating data (see at least [0033] “It should be appreciated that in some examples, the route planning system 100 can weigh the characteristics of the occupant and the charging stations when determining a preference for charging station 215 over charging station 214.” and [0053] “in some examples, the characteristics of the charging stations include a charging manufacturer, a cost associated with using the charging station, or a capability to interface a charge connector on the vehicle with a charging station.” also see at least [0047]) and place weight on the rating of a particular rest stop (see at least [0054] “Further, the intelligent route planning system 100 of vehicle 220 can search for ratings (e.g., one-star, two-star, three-star, four-star, five-star, etc.) and place weight on the rating of a particular rest stop when determining the route.”).
It would have been obvious to one having ordinary skill in the art to combine the teachings of Teske and Nikulin in order to teach the limitations "apply[ing] a plurality of weightings to charging location data comprising ranking data and rating data, the rating data comprising aggregated user ratings" and "determin[ing], using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes and the weighted charging location data” as a rest stop could reasonably be interpretated as and/or synonymous with a charge station as the charge station may encompass rest facilities as described in at least paragraph [0047] of Nikulin. Therefore the 103 rejection is maintained.
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 1-22 are rejected under 35 U.S.C. §101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1, 8, and 15 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite one or more computer-storage media, a computerized system, and a computer-implemented method.
Claim 1 recites claim limitations “apply a plurality of weightings to charging location data comprising data, the rating data comprising aggregated user ratings” and “determine, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes and the weighted charging location data”, Claim 8 recites claim limitations “applying a plurality of weightings to charging location data comprising data, the rating data comprising aggregated user ratings” and “determining, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes and the weighted charging location data” and Claim 15 recites claim limitations “applying a plurality of weightings to charging location data comprising data, the rating data comprising aggregated user ratings” and “determining, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes and the weighted charging location data”, respectively, as drafted, is a process that, under the broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is other than reciting a (computer) processor, nothing in the claim precludes the steps from being performed in the mind. For example, but for the recitation of a (computer) processor, the claim encompasses a person observing a request for a charging location with certain specified attributes and cross referencing the attributes with ranking or rating data factored in in order to determine a suitable charging location based on the attributes and the aid of pen and a paper map. If a claim limitation, under the 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. Accordingly, the claims recite an abstract idea.
Claims 1, 8, and 15 recite the additional element “access(ing) a request for a charging location for an electric vehicle (EV), wherein the request comprises a plurality of charging location request attributes associated with the EV” which is recited at a high generality and amounts to mere data gathering which is a form of insignificant extra-solution activity and Claims 1, 8, and 15 recite the additional element “output(ting), via a display device, the charging location search result” which is recited at a high generality and amounts to mere displaying/outputting of data which is a form of insignificant extra-solution activity.
Claims 1, 8, and 15 as a whole merely describe how to generally “apply” the concept of searching for a charging location. The claimed computer component (computer processor or processor) is recited at a high generality and is merely invoked as a tool to perform an existing process. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract ideas. As such the claims are ineligible.
Claims 2-7, 9-14, and 16-22 are similarly rejected as they do not recite additional elements that integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
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 1, 3-8, 10-15, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Teske (US2019/0383637A1) in view of Becker (US2016/0176307A1) in further view of Nikulin et al. (US2018/0143029A1), hereinafter Teske, Becker, and Nikulin respectively.
Regarding claim 1, (Currently Amended) Teske teaches one or more computer-storage media having computer-executable instructions embodied thereon that, when executed by a computing system having a processor and memory, cause the processor to (see at least [0030] “A query servicing unit 120 is included in the server 102 to process charging station queries from the client device 104. For example, the query servicing unit 120 may include instructions executable by a processor of the server 102”): access a request for a charging location for an electric vehicle (EV) (see at least [0005] “An example method for identifying charging options for charging an electric vehicle includes receiving a charging station query including one or more parameters. also see at least [0046] “a charging query may request information regarding locations of charging stations”), wherein the request comprises a plurality of charging location request attributes associated with the EV (see at least [0005] “charging station query including one or more parameters”); determine, using an electric vehicle management system (see at least [0045] “FIG. 5 is a flow chart of an example method 500 for servicing a charging station query. Method 500 may be performed at a server, such as server 102 of FIG. 1.”), a charging location search result based on the plurality of charging location request attributes (see at least [0048] “If the charging query includes one or more targeted connector codes (e.g., "YES" at 504) and/or once a targeted connector code is determined/mapped at 506/508, the method includes using the targeted connector code(s) as a search key to identify charging stations that fit the parameters of the charging query (e.g., charging stations that are compatible with the targeted connector code(s)), as indicated at 510.”); and output, via a display device, the charging location search result (see at least [0005] “The results of the charging station query may be output by transmitting mapping data for the charging stations to a requesting device (e.g., a client device).” also see at least [0033] “In examples where the output (e.g., the query response) from the server 102 is processed by the application of the client device 104 for display, the application may generate display instructions that are provided to a display controller 128 of the client device 104 in order to control a display of the client device 104 and/or a display communicatively coupled to the client device 104 (e.g., a display in a vehicle console, an external monitor, a display of a different client device, etc.) to output a graphical indication of the query response from the server 102.”).
Examiner interprets that request for a charging location (request) is encompassed at least by charging station query. Examiner interprets that charging location request attributes associated with the EV to be at least, “explicit parameters or derived parameters that are selected to identify charging locations” (see at least [0019] from Applicant’s Specification as filed), and is encompassed at least by query parameters and/or one or more parameters. Examiner interprets that charging location search result is encompassed at least by charging stations that fit the parameters of the charging query. Examiner interprets that the claim is written in the alternative and therefore only one of the limitations needs to be addressed.
Teske does not explicitly teach but suggests apply a plurality of weightings to charging location data comprising data, the rating data comprising aggregated user ratings; and determine, using an electric vehicle management system, a charging location search result based on the weighted charging location data (see at least [0064] “The user may provide input to user interface 800 and/or another user interface window for the application providing user interface 800 in order to select other settings for filtering charging station search results. Example additional settings include...minimum charging station rating from one or more user review databases”).
Examiner interprets that rating data is at least values of features of user ratings (e.g., convenience, safety, reliability) of a charging location (see at least [0019] from Applicant’s Specification) and is encompassed at least by minimum charging station rating from one or more user review databases. Examiner also interprets that the rating data comprising aggregated user ratings is encompassed one or more user review databases.
Becker more explicitly teaches one or more computer-storage media having computer-executable instructions embodied thereon that, when executed by a computing system having a processor and memory, cause the processor to (see at least [0037] “The previously mentioned methods can also be implemented as a computer program or as a computer program stored on a storage medium. Here, on the mobile station or at the control centre a microprocessor can be suitably programmed by a computer program for carrying out the respective method steps.”): access a request for a charging location for an electric vehicle (EV) (see at least [0049] “If a user wants to find a charging station, then he or she can transmit a charge request (22) to the central computer 12 via his or her mobile station 14.”), wherein the request comprises a plurality of charging location request attributes associated with the EV (see at least [0016] “According to one embodiment, it is proposed that information regarding a charging type of the electric vehicle and/or a plug type of the electric vehicle and/or a user identification and/or a remaining range of the electric vehicle and/or a state of charge of a battery of the electric vehicle is additionally contained in the charge request.”); determine, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes (see at least [0027] “dependent on the comparison result a prioritisation can be made such that the greater the match between the charge request and the charging station information the further up in the tuple the corresponding charging station information is arranged.”); and output, via a display device, the charging location search result (see at least [0056] “ This tuple is transmitted back to the mobile station 14 via the internet 10 and the gateway 8 and the mobile network 6 by the central computer 12 (24).” also see at least [0057] “On the mobile station 14, the information from the tuple can be displayed in the order in which it was stored, for example.”).
Examiner interprets that charging location request attributes associated with the EV is encompassed at least by that information regarding a charging type of the electric vehicle and/or a plug type of the electric vehicle and/or a user identification and/or a remaining range of the electric vehicle and/or a state of charge of a battery of the electric vehicle.
Nikulin teaches apply a plurality of weightings to charging location data comprising see at least [0033] “It should be appreciated that in some examples, the route planning system 100 can weigh the characteristics of the occupant and the charging stations when determining a preference for charging station 215 over charging station 214.” and [0053] “in some examples, the characteristics of the charging stations include a charging manufacturer, a cost associated with using the charging station, or a capability to interface a charge connector on the vehicle with a charging station.” also see at least [0047]); determine, using an electric vehicle management system, a charging location search result based on the weighted charging location data (see at least [0054] “Further, the intelligent route planning system 100 of vehicle 220 can search for ratings (e.g., one-star, two-star, three-star, four-star, five-star, etc.) and place weight on the rating of a particular rest stop when determining the route.”).
Examiner also interprets that ranking data can refer to values that correspond to features of a charging location (e.g., type of charging supported, connector types, status of charging stations, and compatibility with EVs) (see at least [0019] from Applicant’s Specification as filed) and is encompassed at least by characteristics of the charging stations.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Teske of one or more computer-storage media having computer-executable instructions embodied thereon that, when executed by a computing system having a processor and memory, cause the processor to: access a request for a charging location for an electric vehicle (EV), wherein the request comprises a plurality of charging location request attributes associated with the EV; determine, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes; and output, via a display device, the charging location search result with the more explicit teaching of the same found in Becker with a reasonable expectation of success. One would have been motivated to do so to enable more efficient servicing of charging queries and/or requests to locate nearby charging stations in order to allow an electric vehicle to reach a destination without running out of battery charge (see at least Teske [0023]). It would have also been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Teske of using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes and suggested teaching of Teske of apply a plurality of weightings to charging location data comprising ranking data and rating data; and determine, using an electric vehicle management system, a charging location search result based on the weighted charging location data with the more explicit teaching of the same found in Nikulin. One could combine the teachings in order to have one or more computer-storage media having computer-executable instructions embodied thereon that, when executed by a computing system having a processor and memory, cause the processor to: access a request for a charging location for an electric vehicle (EV), wherein the request comprises a plurality of charging location request attributes associated with the EV; apply a plurality of weightings to charging location data comprising ranking data and rating data, the rating data comprising aggregated user ratings; determine, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes and the weighted charging location data; and output, via a display device, the charging location search result with a reasonable expectation of success. One would have been motivated to do so to enable more efficient servicing of charging queries and/or requests to locate nearby charging stations in order to allow an electric vehicle to reach a destination without running out of battery charge (see at least Teske [0023]).
Regarding claim 3, (Original) the combination of Teske, Becker, and Nikulin teaches the one or more computer storage media of claim 1 as detailed above.
Teske teaches wherein the charging location request attributes include user data and EV data that support determining the charging location search result (see at least [0030] “Query parameters may include parameters such as one or more targeted connector codes, one or more locations, one or more charging networks, a connector count per targeted connector code, a threshold distance from a selected location/route, a targeted charging time/amount/level (e.g., which may be expressed as a percentage of a capacity of an energy storage device of the vehicle), and/or other parameters.” also see at least [0034] and [0048]).
Examiner interprets that charging location request attributes associated with the EV to be at least, “explicit parameters or derived parameters that are selected to identify charging locations” (see at least [0019] from Applicant’s Specification as filed), and is encompassed at least by query parameters or one or more parameters. Examiner interprets that user navigation preferences, user charging location preferences are examples of user data (see at least [0019] from Applicant's Specification as filed) and is encompassed at least by a threshold distance from a selected location/route. Examiner also interprets that EV type, EV charging specifications, EV battery range are examples of EV data (see at least [0019] from Applicant's Specification as filed) and is encompassed at least by a targeted charging time/amount/level (e.g., which may be expressed as a percentage of a capacity of an energy storage device of the vehicle).
Regarding claim 4, (Previously Presented) the combination of Teske, Becker, and Nikulin teaches the one or more computer storage media of claim 1 as detailed above.
Teske teaches wherein the request is received from the EV or a mobile device (see at least [0045] “The charging query may be received from a client device,”), the EV or the mobile device is associated with a user having a plurality of user preferences in the plurality of charging location request attributes (see at least [0034] “The client device 104 illustrated in FIG. 1 may include an end user device, such as a device to which a user directly provides input (e.g., requesting charging station queries, setting user preferences, inputting user/vehicle information, etc.)”), wherein the charging location search result is communicated to the EV or the mobile device (see at least [0005] “The results of the charging station query may be output by transmitting mapping data for the charging stations to a requesting device (e.g., a client device).” also see at least [0033] “As described above, the server 102 may transmit an output of the query servicing unit 120 to the client device 104.”).
Examiner interprets that request is encompassed by charging query (query) and mobile device is encompassed by client device. Examiner also interprets that the claim is written in the alternative and therefore only one of the limitations needs to be addressed.
Regarding claim 5, (Original) the combination of Teske, Becker, and Nikulin teaches the one or more computer storage media of claim 1 as detailed above.
Teske teaches wherein a charging location search engine and a location-based service of the electric vehicle management system are implemented as an integrated searching platform via an automotive navigation engine (see at least [0071] “FIG. 11 is a flow chart of an example method 1100 for performing a trip planning operation using standardized connector codes (e.g., for identifying charging stations along candidate routes)...Method 1100 may be performed at a server, such as server 102 of FIG. 1 and/or server 604 of FIG. 6). At 1102, the method includes receiving at least one connector code, a starting location, and a destination for a vehicle. An example user interface for entering information pertaining to the above parameters is described below with respect to FIG. 12.” also see at least [0046], [0052], [0079]-[0081] and Figs.11-13).
Examiner interprets that an automotive navigation engine is encompassed at least by server 102 or server 604 as they are capable of performing a trip planning operation. Examiner also interprets a charging location search engine and a location-based service are encompassed at least by identifying charging stations along candidate routes.
Regarding claim 6, (Original) the combination of Teske, Becker, and Nikulin teaches the one or more computer storage media of claim 1 as detailed above.
Teske teaches wherein the request is associated with a navigation route of the EV (see at least [0071] “FIG. 11 is a flow chart of an example method 1100 for performing a trip planning operation using standardized connector codes (e.g., for identifying charging stations along candidate routes)...Method 1100 may be performed at a server, such as server 102 of FIG. 1 and/or server 604 of FIG. 6). At 1102, the method includes receiving at least one connector code, a starting location, and a destination for a vehicle” also see at least [0046], [0052], [0079]-[0081] and Figs.11-13), wherein the charging location is a charging location search result that is generated based on the navigation route (see at least [0072] “At 1104, the method includes identifying charging stations in a region associated with the starting location and the destination that are compatible with the connector code(s)...the server may use the connector codes as a search key to identify charging stations, within the region of the starting location and the destination, that include connectors matching the connector codes.”).
Regarding claim 7, (Original) the combination of Teske, Becker, and Nikulin teaches the one or more computer storage media of claim 1 as detailed above.
Teske teaches wherein determining charging location based on the plurality of charging location request attributes and one or more of the ranking data or rating data is based on matching the plurality of charging location request attributes to charging location ranking features of the ranking data or charging location rating features of the rating data (see at least [0048] “If the charging query includes one or more targeted connector codes (e.g., "YES" at 504) and/or once a targeted connector code is determined/mapped at 506/508, the method includes using the targeted connector code(s) as a search key to identify charging stations that fit the parameters of the charging query (e.g., charging stations that are compatible with the targeted connector code(s)), as indicated at 510. Charging stations that are determined to fit the parameters of the charging query may include charging stations that match all or a portion of the parameters. Matching a parameter relating to a connector code may include offering a charging connector that is compatible with the connector code, while matching a parameter relating to a location may include being located in an area within a threshold distance of the location (e.g., where the threshold may be set based on user preferences, specified in the query, and/or set to a default value, which may correspond to a range (on a full battery charge) of a vehicle associated with the query).”).
Examiner also interprets that the claim is written in the alternative and therefore only one of the limitations needs to be addressed. Examiner interprets that matching the plurality of charging location request attributes to charging location ranking features of the ranking data is encompassed at least by using the targeted connector code(s) as a search key to identify charging stations that fit the parameters of the charging query (e.g., charging stations that are compatible with the targeted connector code(s)), as indicated at 510.
Regarding claim 8, (Currently Amended) Teske teaches a computerized system comprising: one or more computer processors (see at least [0083] “With reference to FIG. 14, the computing environment 1400 includes one or more processing units”); and computer memory (see at least [0083] “memory 1420, 1425) storing computer-useable instructions that, when used by the one or more computer processors, cause the one or more computer processors to perform operations comprising (see at least [0083] “The memory 1420, 1425 stores software 1480 implementing one or more innovations described herein, in the form of computer-executable instructions suitable for execution by the processing unit(s)” also see at least [0082]): accessing a request for a charging location for an electric vehicle (EV) (see at least [0005] “An example method for identifying charging options for charging an electric vehicle includes receiving a charging station query including one or more parameters. also see at least [0046] “a charging query may request information regarding locations of charging stations”), wherein the request comprises a plurality of charging location request attributes associated with the EV (see at least [0005] “charging station query including one or more parameters”); determining, using an electric vehicle management system (see at least [0045] “FIG. 5 is a flow chart of an example method 500 for servicing a charging station query. Method 500 may be performed at a server, such as server 102 of FIG. 1.”), a charging location search result based on the plurality of charging location request attributes (see at least [0048] “If the charging query includes one or more targeted connector codes (e.g., "YES" at 504) and/or once a targeted connector code is determined/mapped at 506/508, the method includes using the targeted connector code(s) as a search key to identify charging stations that fit the parameters of the charging query (e.g., charging stations that are compatible with the targeted connector code(s)), as indicated at 510.”); and outputting, via a display device, the charging location search result (see at least [0005] “The results of the charging station query may be output by transmitting mapping data for the charging stations to a requesting device (e.g., a client device).” also see at least [0033] “In examples where the output (e.g., the query response) from the server 102 is processed by the application of the client device 104 for display, the application may generate display instructions that are provided to a display controller 128 of the client device 104 in order to control a display of the client device 104 and/or a display communicatively coupled to the client device 104 (e.g., a display in a vehicle console, an external monitor, a display of a different client device, etc.) to output a graphical indication of the query response from the server 102.”).
Examiner interprets that request for a charging location (request) is encompassed at least by charging station query. Examiner interprets that charging location request attributes associated with the EV to be at least, “explicit parameters or derived parameters that are selected to identify charging locations” (see at least [0019] from Applicant’s Specification as filed), and is encompassed at least by query parameters and/or one or more parameters. Examiner interprets that charging location search result is encompassed at least by charging stations that fit the parameters of the charging query. Examiner interprets that the claim is written in the alternative and therefore only one of the limitations needs to be addressed.
Teske does not explicitly teach but suggests applying a plurality of weightings to charging location data comprising data, the rating data comprising aggregated user ratings; determining, using an electric vehicle management system, a charging location search result based on the weighted charging location data (see at least [0064] “The user may provide input to user interface 800 and/or another user interface window for the application providing user interface 800 in order to select other settings for filtering charging station search results. Example additional settings include...minimum charging station rating from one or more user review databases”).
Examiner interprets that rating data is at least values of features of user ratings (e.g., convenience, safety, reliability) of a charging location (see at least [0019] from Applicant’s Specification) and is encompassed at least by minimum charging station rating from one or more user review databases. Examiner also interprets that the rating data comprising aggregated user ratings is encompassed one or more user review databases.
Becker more explicitly teaches a computerized system comprising: one or more computer processors; and computer memory storing computer-useable instructions that, when used by the one or more computer processors, cause the one or more computer processors to perform operations comprising (see at least [0037] “The previously mentioned methods can also be implemented as a computer program or as a computer program stored on a storage medium. Here, on the mobile station or at the control centre a microprocessor can be suitably programmed by a computer program for carrying out the respective method steps.”): accessing a request for a charging location for an electric vehicle (EV) (see at least [0049] “If a user wants to find a charging station, then he or she can transmit a charge request (22) to the central computer 12 via his or her mobile station 14.”), wherein the request comprises a plurality of charging location request attributes associated with the EV (see at least [0016] “According to one embodiment, it is proposed that information regarding a charging type of the electric vehicle and/or a plug type of the electric vehicle and/or a user identification and/or a remaining range of the electric vehicle and/or a state of charge of a battery of the electric vehicle is additionally contained in the charge request.”); determining, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes (see at least [0027] “dependent on the comparison result a prioritisation can be made such that the greater the match between the charge request and the charging station information the further up in the tuple the corresponding charging station information is arranged.”); and outputting, via a display device, the charging location search result (see at least [0056] “ This tuple is transmitted back to the mobile station 14 via the internet 10 and the gateway 8 and the mobile network 6 by the central computer 12 (24).” also see at least [0057] “On the mobile station 14, the information from the tuple can be displayed in the order in which it was stored, for example.”).
Examiner interprets that charging location request attributes associated with the EV is encompassed at least by that information regarding a charging type of the electric vehicle and/or a plug type of the electric vehicle and/or a user identification and/or a remaining range of the electric vehicle and/or a state of charge of a battery of the electric vehicle.
Nikulin teaches applying a plurality of weightings to charging location data comprising data (see at least [0033] “It should be appreciated that in some examples, the route planning system 100 can weigh the characteristics of the occupant and the charging stations when determining a preference for charging station 215 over charging station 214.” and [0053] “in some examples, the characteristics of the charging stations include a charging manufacturer, a cost associated with using the charging station, or a capability to interface a charge connector on the vehicle with a charging station.” also see at least [0047]); determining, using an electric vehicle management system, a charging location search result based on the weighted charging location data (see at least [0054] “Further, the intelligent route planning system 100 of vehicle 220 can search for ratings (e.g., one-star, two-star, three-star, four-star, five-star, etc.) and place weight on the rating of a particular rest stop when determining the route.”).
Examiner also interprets that ranking data can refer to values that correspond to features of a charging location (e.g., type of charging supported, connector types, status of charging stations, and compatibility with EVs) (see at least [0019] from Applicant’s Specification as filed) and is encompassed at least by characteristics of the charging stations.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Teske of a computerized system comprising: one or more computer processors; and computer memory storing computer-useable instructions that, when used by the one or more computer processors, cause the one or more computer processors to perform operations comprising: accessing a request for a charging location for an electric vehicle (EV), wherein the request comprises a plurality of charging location request attributes associated with the EV; determining, using an electric vehicle management system, a charging location search result based on the plurality of charging location request attributes; and outputting, via a display device, the charging location search result with the more explicit teaching of the same found in Becker with a reasonable expectation of success. One would have been motivated to do so to enable more efficient servicing of charging queries and/or requests to locate nearby charging stations in order to allow an electric vehicle to reach a destination without running out of battery charge (see at least Teske [0023]). It would have also been obvious to one having ordinary skill in the art befo