DETAILED ACTION
Status of Claims
This is a non-final action in reply to the response filed on October 13, 2025.
Claims 1-20 are currently pending and have been examined. Claims 1 and 10-16 have been withdrawn.
Claims 2-9 and 17-20 have been examined.
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 .
Election/Restriction
Applicant’s election without traverse of Group II: claims 2-9 and 17-20 in the reply filed on 10/13/2025 is acknowledged.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 17-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
As per claim 17 recites a detection of a trigger event in order to present decisions to remedy the cause of the trigger event. Claim 18 which depends of claim 17 display fleet effects based on alternative configurations. Examiner is not clear are the alternative configurations the same as the decisions to remedy the cause of the trigger event? Are the fleet effects the same as the consequences of the decisions? The claims were examined as best understood. Appropriate correction is required.
Claim 17 recites the limitation "the cause" and “the operation”. There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 2-5 and 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Trimboli et al., (US 11,913,798 A1) hereinafter “Trimboli” in view of Lowenthal et al., (US 11,341,785 B2) hereinafter “Lowenthal”.
Claim 2:
Trimboli as shown discloses a method for electric vehicle fleet management, the method comprising:
providing an interface to display charging session characteristics of one or more vehicles in a fleet; (col. 4, lines 20-22: “The user is presented (e.g., via the communications interface 30 or the mobile application 32) a set of goals 50 and asked for input, i.e., select one or more session goals.” Col. 1, lines 43-44: “The predefined set of goals may include charging time minimization and cost minimization”);
receiving, via the interface, an alternative configuration to the charging session characteristics of one of the vehicles; (col. 4, lines 24-27: “the set of goals 50 may include a first session goal 52 of minimizing cost, a second session goal 54 of minimizing charging time to full and a third session goal 56 of the maximum range added within a specific time limit.” Col. 3, lines 3-4: “The system 10 provides the opportunity to optimize each charge session individually based on a selected goal”);
calculating one or more fleet effects to the charging session characteristics of the vehicles in the fleet caused by the alternative configuration; displaying, through the interface, the fleet effects; and upon receipt of acceptance to the alternative configuration (col. 4, lines 41-51: “generating a recommended charging profile respectively for one or more stops along the route 16, based in part on the session goal(s) (selected in block 106) and the respective station parameters (obtained in block 104). The recommended charging profile is chosen from a plurality of charging profiles. For example, the controller C may recommend a first stop (a ten-minute charging session in a first charging location) with a corresponding recommended charging profile and a second stop (thirty-minute charging session in a second charging location) with a corresponding recommended charging profile.” Col. 6, lines 26-28: “the system 10 (via execution of method 100) provides multiple charging profiles optimized for different goals, such as charge time available, desired range to be added and/or cost minimization.” And col. 4, lines 34-36: “the session goal/scenario selections may be made by the controller C to notify the user of the recommendation and seek acceptance or acknowledgment”);
providing instructions to one or more charging stations associated with the one or more vehicles to implement the alternative configuration (col. 5, lines 42-50: “The recommended charging profile may include predefined location-based settings. In one example, a fixed setting is placed to charge for 10 minutes at a charging station 42 on the way home from work for a user. In another example, a fixed setting is placed to add 150 miles at a specific charging station 42 to complete a trip to a weekend cottage. Each of the charging profiles may be separately calibrated in order to optimize the energy demand for the selected session goal.”);
Trimboli is silent with regard to a vehicle fleet management. However, Lowenthal in an analogous art of electric vehicle management for the purpose of providing vehicle fleet management as shown does in col. lines “FIG. 6 illustrates an exemplary electric vehicle status user interface of a software program for managing electric vehicles. […] The status information 600 as discussed in block 408 includes summary information 610 having the charging status of the plurality of electric vehicles. The status information also includes vehicle status information 620 for each electric vehicle that includes a license plate identifier, a charging status, a charging station, a power delivered to each battery in unit of kW, an energy delivered to each battery in units of kWh, a charging session time, and a time period until a battery is fully charged.”
Both Trimboli and Lowenthal teach electric vehicle management. Trimboli teaches in the Abstract: “optimizing charging for a vehicle having a rechargeable energy storage unit and travelling on a route includes a controller.” Lowenthal teaches in the Abstract “managing a plurality of electric vehicles with a fleet management portal.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Lowenthal would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Lowenthal to the teaching of Trimboli would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as the vehicle fleet management into similar systems. Further, as noted by Lowenthal “managing one or more fleets of electric vehicles includes monitoring one or more fleets of electric vehicles using a fleet management portal associated with a server.” (Lowenthal, Abstract).
Claim 3:
Trimboli as shown discloses the following limitations:
determining suggested changes to the charging session characteristics of the vehicles, the suggested changes being based on the fleet effects; displaying, through the interface, the suggested changes; and upon receipt of the acceptance to the alternative configuration, (col. 4, lines 41-51: “generating a recommended charging profile respectively for one or more stops along the route 16, based in part on the session goal(s) (selected in block 106) and the respective station parameters (obtained in block 104). The recommended charging profile is chosen from a plurality of charging profiles. For example, the controller C may recommend a first stop (a ten-minute charging session in a first charging location) with a corresponding recommended charging profile and a second stop (thirty-minute charging session in a second charging location) with a corresponding recommended charging profile.” Col. 6, lines 26-28: “the system 10 (via execution of method 100) provides multiple charging profiles optimized for different goals, such as charge time available, desired range to be added and/or cost minimization.” And col. 4, lines 34-36: “the session goal/scenario selections may be made by the controller C to notify the user of the recommendation and seek acceptance or acknowledgment”);
providing instructions to the one or more charging stations associated with the one or more vehicles to implement the suggested changes (col. 5, lines 5-25: “Based on Table 1 above, if a vehicle 12 was charging for ten minutes, the controller C may select the fifth charging profile (which has the highest energy value in the ten-minute category) to maximize the energy gained. If the vehicle 12 was charging for a total of twenty minutes, the controller C may select the third charging profile (which has the highest energy value in the twenty-minute category) to maximize the energy gained. Similarly, if the vehicle 12 was charging for a total of thirty minutes, the controller C may select the second charging profile (which has the highest energy value in the thirty-minute category) to maximize the energy gained.”):
Claim 4:
Trimboli as shown discloses the following limitations:
wherein the suggested changes include at least one of an optimization of an aggregate cost, an aggregate real cost, or aggregate emissions of a charging site (col. 6, lines 26-28: “the system 10 (via execution of method 100) provides multiple charging profiles optimized for different goals, such as charge time available, desired range to be added and/or cost minimization.”);
Claim 5:
Trimboli teaches as explained above the one or more effects of the charging session characteristics. Trimboli is silent with regard to the following limitations. However, Lowenthal in an analogous art of electric vehicle management for the purpose of providing the following limitations as shown does:
wherein calculating the one or more fleet effects to the charging session characteristics includes maintaining a relative prioritization of charging sessions (col. 7, lines 36-43: “determine availability of charge transfer devices for recharging their electric vehicles 150. A user profile contains financial account information—details required for payment—and may also include information such as whether the vehicle operator wants to: charge the electric vehicle only during periods of lower power rates; not charge the vehicle during periods of high power grid load; and sell power to the local grid.”);
Both Trimboli and Lowenthal teach electric vehicle management. Trimboli teaches in the Abstract: “optimizing charging for a vehicle having a rechargeable energy storage unit and travelling on a route includes a controller.” Lowenthal teaches in the Abstract “managing a plurality of electric vehicles with a fleet management portal.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Lowenthal would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Lowenthal to the teaching of Trimboli would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as maintaining a relative prioritization of charging sessions into similar systems. Further, as noted by Lowenthal “managing one or more fleets of electric vehicles includes monitoring one or more fleets of electric vehicles using a fleet management portal associated with a server.” (Lowenthal, Abstract).
Claim 8:
Trimboli as shown discloses the following limitations:
wherein the charging session characteristics include one or more of: a finished charging time of a charging session; energy delivered during the charging session; cost of the charging session; maximum charging rate during the charging session; energy losses during the charging session; and greenhouse gas emissions during the charging session (col. 1, lines 43-44: “The predefined set of goals may include charging time minimization and cost minimization.” See also col. 5, lines 3: “Each of the charging profiles may be separately calibrated in order to optimize the energy demand for the selected session goal”);
Claim 9:
Trimboli as shown discloses the following limitations:
wherein the alternative configuration to the charging session characteristics is a change [in a relative prioritization of charging sessions] (col. 6, lines 26-28: “the system 10 (via execution of method 100) provides multiple charging profiles optimized for different goals, such as charge time available, desired range to be added and/or cost minimization.”);
Trimboli as explained above teaches the change by providing alternative configuration of the charging session characteristics. Trimboli is silent with regard to the following limitations. However, Lowenthal in an analogous art of electric vehicle management for the purpose of providing the following limitations as shown does:
in a relative prioritization of charging sessions (col. 7, lines 36-43: “determine availability of charge transfer devices for recharging their electric vehicles 150. A user profile contains financial account information—details required for payment—and may also include information such as whether the vehicle operator wants to: charge the electric vehicle only during periods of lower power rates; not charge the vehicle during periods of high power grid load; and sell power to the local grid.”);
Both Trimboli and Lowenthal teach electric vehicle management. Trimboli teaches in the Abstract: “optimizing charging for a vehicle having a rechargeable energy storage unit and travelling on a route includes a controller.” Lowenthal teaches in the Abstract “managing a plurality of electric vehicles with a fleet management portal.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Lowenthal would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Lowenthal to the teaching of Trimboli would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as a relative prioritization of charging sessions into similar systems. Further, as noted by Lowenthal “managing one or more fleets of electric vehicles includes monitoring one or more fleets of electric vehicles using a fleet management portal associated with a server.” (Lowenthal, Abstract).
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Trimboli et al., (US 11,913,798 A1) hereinafter “Trimboli” and Lowenthal et al., (US 11,341,785 B2) hereinafter “Lowenthal” as applied to claims 2 and 18 above, further in view of Moura et al., (US 2022/0188946 A1) hereinafter “Moura”.
Claim 6:
Trimboli teaches in col. 4, lines 9-17: “The respective station parameters may include the presence of brown-out conditions (a reduction in or restriction on the availability of electrical power in a particular area) at the charging stations 42. The respective station parameters may include other infrastructure-based settings, such as a limitation to 30 minutes of charging based on a high volume of station need imposed by the charging stations 42, or other high use grid-based adjustments. Trimboli in view of Lowenthal is silent with regard to the following limitations. However, Moura in an analogous art of electric vehicle management for the purpose of providing the following limitations as shown does:
determining and displaying external effects to the charging session characteristics of the vehicles caused by external sources; displaying, through the interface, the external effects; (¶ 0038: “Upon accessing a native application or a website, charging session options are presented to each customer. Pricing and/or carbon intensity of each option is updated in real time based on the time-varying cost of energy for both the site host and the electricity provider, maximum power constraints and/or demand charges, greenhouse gas emissions associated with electricity production, and charge point demand, with the objective of maximizing financial value for the charge point operator while meeting customer expectations for quality of service.”);
and upon receipt of the acceptance to the alternative configuration, providing instructions to the one or more charging stations associated with the one or more vehicles implement the external changes (¶ 0038: “Customers may choose a “regular” charging session, in which the vehicle starts charging immediately and continues at full power until the vehicle is charged or the customer ends the charging session, or a “scheduled” option with a reserved session duration and guaranteed energy delivery.”);
Both Trimboli and Moura teach electric vehicle management. Trimboli teaches in the Abstract: “optimizing charging for a vehicle having a rechargeable energy storage unit and travelling on a route includes a controller.” Moura teaches in the Abstract “user is presented with menu of price-differentiated charging services, which differ in per-unit price and the energy delivery schedule.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Moura would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Moura to the teaching of Trimboli in view of Lowenthal would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as determining and displaying external effects to the charging session characteristics of the vehicles caused by external sources; displaying, through the interface, the external effects; and upon receipt of the acceptance to the alternative configuration, providing instructions to the one or more charging stations associated with the one or more vehicles implement the external changes into similar systems. Further, as noted by Moura “The pricing control policy realizes benefits in three aspects: (i) net profits gain, (ii) overstay reduction, and (iii) increased quality-of-service.” (Moura, Abstract).
Claim 7:
Trimboli teaches in col. 4, lines 9-17: “The respective station parameters may include the presence of brown-out conditions (a reduction in or restriction on the availability of electrical power in a particular area) at the charging stations 42. The respective station parameters may include other infrastructure-based settings, such as a limitation to 30 minutes of charging based on a high volume of station need imposed by the charging stations 42, or other high use grid-based adjustments. Trimboli in view of Lowenthal is silent with regard to the following limitations. However, Moura in an analogous art of electric vehicle management for the purpose of providing the following limitations as shown does:
wherein the external sources include: power availability (¶ 0038: “Upon accessing a native application or a website, charging session options are presented to each customer. Pricing and/or carbon intensity of each option is updated in real time based on the time-varying cost of energy for both the site host and the electricity provider, maximum power constraints and/or demand charges, greenhouse gas emissions associated with electricity production, and charge point demand, with the objective of maximizing financial value for the charge point operator while meeting customer expectations for quality of service.”);
Both Trimboli and Moura teach electric vehicle management. Trimboli teaches in the Abstract: “optimizing charging for a vehicle having a rechargeable energy storage unit and travelling on a route includes a controller.” Moura teaches in the Abstract “user is presented with menu of price-differentiated charging services, which differ in per-unit price and the energy delivery schedule.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Moura would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Moura to the teaching of Trimboli in view of Lowenthal would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as wherein the external sources include: power availability into similar systems. Further, as noted by Moura “The pricing control policy realizes benefits in three aspects: (i) net profits gain, (ii) overstay reduction, and (iii) increased quality-of-service.” (Moura, Abstract).
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim 17 is rejected under 35 U.S.C. 102(a)(2) as being anticipated by Hancock et al., (US 2025/0033517 A1) hereinafter “Hancock”.
Claim 17:
Hancock as shown discloses a processing system, the system comprising:
a memory comprising computer-executable instructions; and a processor configured to execute the computer-executable instructions and cause the processing system to perform at least the following (¶ 0124: “a system, method, or computer-readable medium having digital instructions stored thereon for execution by a digital processor”);
detect a trigger event that affects charging characteristics of at least one vehicle in a fleet; provide, via an interface, a prompt regarding the trigger event (¶ 0119: “ GUI of FIG. 24 , an asset management predictor of the system may provide digital alerts to the user. For example, the GUI may provide the alert 2402 that, without attention, a demand penalty is expected for the following day without if no intervention in taken.”);
present, via the interface, decisions to remedy the cause of the trigger event; provide, via the interface, consequences of the decisions to charging characteristics of one or more additional vehicles in the fleet (¶ 0119: “Similarly presented to the user is the notification 2404 as to a potential solution to energy management that may reduce or mitigate any potential energy issues. In this example, the alert 2404 relates to the operation of facility asset, namely the HVAC system of the facility, which, in this case, is indicated in association with the provision of two suggestions that may mitigate the predicted overage (i.e. to shut down the facility asset at a certain time or discharge unused energy stored in EVs to mitigate energy use from the grid during EV charge-ups). Similarly, the GUI alerts 2406 the user as to the excess charge needed at the end of the shift, and thus suggests re-allocation of charging times for those EVs.”);
receive, via the interface, an input accepting one of the decisions; provide the accepted decision to at least one of a fleet management system or a charge management system; and provide instructions that affect the operation of at least one charging station based on the accepted decision (¶ 0118: “a designated energy management regime, and/or suggestions related thereto, may be output to a user, such as a facility manager and/or fleet operator, for evaluation and/or implementation. For example, and in accordance with various embodiments, FIG. 24 is a schematic of an exemplary graphical user interface (GUI) via which a user may interact with an energy management system. In this example, the system, or a method executing the same, received as input energy management data and computed an energy management regime that addressed several deficiencies with respect to historical energy management in view of upcoming operational conditions. The system then digitally directs operation of assets in the facility (e.g. EV charging stations and/or other energy consumption assets in the facility) via the GUI for instance though the provision of indicators and/or controls that the user may review and/or select to realise the improved management of energy in associate with the facility.” See also ¶ 0119: “As noted above, in this latter example, the alert 2406 is provided with the user-selectable option to enable the optimised charging plan via the GUI, wherein charging will automatically be digitally directed via the system upon user selection.”);
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Hancock et al., (US 2025/0033517 A1) hereinafter “Hancock” in view of Trimboli et al., (US 11,913,798 A1) hereinafter “Trimboli”.
Claim 18:
Hancock as shown discloses the following limitations:
provide an interface to display charging session characteristics of one or more vehicles in a fleet (¶ 0026: “the energy optimisation engine is configured to digitally direct operation of said one or more of the charge stations or said energy assets via a graphical user interface (GUI) displaying to a user data related to said energy distribution instructions.” See also ¶ 0090: “the provision to a user via a graphical user interface (GUI) a report descriptive of the designated or prescribed energy distribution regime, or the direct or user-selectable operation of one or more energy assets and/or charging stations in accordance with the energy distribution regime”);
Hancock is silent with regard to the following limitations. However, Trimboli in an analogous art of electric vehicle management for the purpose of providing the following limitations as shown does:
receive, via the interface, an alternative configuration to the charging session characteristics of one of the vehicles; (col. 4, lines 24-27: “the set of goals 50 may include a first session goal 52 of minimizing cost, a second session goal 54 of minimizing charging time to full and a third session goal 56 of the maximum range added within a specific time limit.” Col. 3, lines 3-4: “The system 10 provides the opportunity to optimize each charge session individually based on a selected goal”);
calculate one or more fleet effects to the charging session characteristics of the vehicles in the fleet caused by the alternative configuration; display, through the interface, the fleet effects; and upon receipt of acceptance to the alternative configuration (col. 4, lines 41-51: “generating a recommended charging profile respectively for one or more stops along the route 16, based in part on the session goal(s) (selected in block 106) and the respective station parameters (obtained in block 104). The recommended charging profile is chosen from a plurality of charging profiles. For example, the controller C may recommend a first stop (a ten-minute charging session in a first charging location) with a corresponding recommended charging profile and a second stop (thirty-minute charging session in a second charging location) with a corresponding recommended charging profile.” Col. 6, lines 26-28: “the system 10 (via execution of method 100) provides multiple charging profiles optimized for different goals, such as charge time available, desired range to be added and/or cost minimization.” And col. 4, lines 34-36: “the session goal/scenario selections may be made by the controller C to notify the user of the recommendation and seek acceptance or acknowledgment”);
provide instructions to one or more charging stations associated with the one or more vehicles to implement the alternative configuration (col. 5, lines 42-50: “The recommended charging profile may include predefined location-based settings. In one example, a fixed setting is placed to charge for 10 minutes at a charging station 42 on the way home from work for a user. In another example, a fixed setting is placed to add 150 miles at a specific charging station 42 to complete a trip to a weekend cottage. Each of the charging profiles may be separately calibrated in order to optimize the energy demand for the selected session goal.”);
Both Hancock and Trimboli teach electric vehicle management. Hancock teaches in the Abstract “directing energy use within a facility comprising charging stations for charging a fleet of electric vehicles, using an energy optimisation engine.” Trimboli teaches in the Abstract: “optimizing charging for a vehicle having a rechargeable energy storage unit and travelling on a route includes a controller.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Trimboli would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Trimboli to the teaching of Hancock would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as receive, via the interface, an alternative configuration to the charging session characteristics of one of the vehicles; calculate one or more fleet effects to the charging session characteristics of the vehicles in the fleet caused by the alternative configuration; display, through the interface, the fleet effects; and upon receipt of acceptance to the alternative configuration, provide instructions to one or more charging stations associated with the one or more vehicles to implement the alternative configuration into similar systems. Further, as noted by Trimboli “the system 10 (via execution of method 100) provides multiple charging profiles optimized for different goals, such as charge time available, desired range to be added and/or cost minimization.” (Trimboli, col. 6, lines 25-28).
Claim 19:
Hancock is silent with regard to the following limitations. However, Trimboli in an analogous art of electric vehicle management for the purpose of providing the following limitations as shown does:
determining suggested changes to the charging session characteristics of the vehicles, the suggested changes being based on the fleet effects; displaying, through the interface, the suggested changes; and upon receipt of the acceptance to the alternative configuration, (col. 4, lines 41-51: “generating a recommended charging profile respectively for one or more stops along the route 16, based in part on the session goal(s) (selected in block 106) and the respective station parameters (obtained in block 104). The recommended charging profile is chosen from a plurality of charging profiles. For example, the controller C may recommend a first stop (a ten-minute charging session in a first charging location) with a corresponding recommended charging profile and a second stop (thirty-minute charging session in a second charging location) with a corresponding recommended charging profile.” Col. 6, lines 26-28: “the system 10 (via execution of method 100) provides multiple charging profiles optimized for different goals, such as charge time available, desired range to be added and/or cost minimization.” And col. 4, lines 34-36: “the session goal/scenario selections may be made by the controller C to notify the user of the recommendation and seek acceptance or acknowledgment”);
providing instructions to the one or more charging stations associated with the one or more vehicles to implement the suggested changes (col. 5, lines 5-25: “Based on Table 1 above, if a vehicle 12 was charging for ten minutes, the controller C may select the fifth charging profile (which has the highest energy value in the ten-minute category) to maximize the energy gained. If the vehicle 12 was charging for a total of twenty minutes, the controller C may select the third charging profile (which has the highest energy value in the twenty-minute category) to maximize the energy gained. Similarly, if the vehicle 12 was charging for a total of thirty minutes, the controller C may select the second charging profile (which has the highest energy value in the thirty-minute category) to maximize the energy gained.”);
Both Hancock and Trimboli teach electric vehicle management. Hancock teaches in the Abstract “directing energy use within a facility comprising charging stations for charging a fleet of electric vehicles, using an energy optimisation engine.” Trimboli teaches in the Abstract: “optimizing charging for a vehicle having a rechargeable energy storage unit and travelling on a route includes a controller.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Trimboli would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Trimboli to the teaching of Hancock would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as determining suggested changes to the charging session characteristics of the vehicles, the suggested changes being based on the fleet effects; displaying, through the interface, the suggested changes; and upon receipt of the acceptance to the alternative configuration, providing instructions to the one or more charging stations associated with the one or more vehicles to implement the suggested changes into similar systems. Further, as noted by Trimboli “the system 10 (via execution of method 100) provides multiple charging profiles optimized for different goals, such as charge time available, desired range to be added and/or cost minimization.” (Trimboli, col. 6, lines 25-28).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Hancock et al., (US 2025/0033517 A1) hereinafter “Hancock” and Trimboli et al., (US 11,913,798 A1) hereinafter “Trimboli” as applied to claim 18 above, further in view of Moura et al., (US 2022/0188946 A1) hereinafter “Moura”.
Claim 20:
Hancock teaches in ¶ 0097: “to draw on EV battery charge, for instance during peak energy cost times when there is available excess EV battery charge, or instructions to operate directly from the grid but in accordance with a schedule and power use that is defined in accordance with energy supply data and one or more conditions associated therewith”. Trimboli teaches in col. 4, lines 9-17: “The respective station parameters may include the presence of brown-out conditions (a reduction in or restriction on the availability of electrical power in a particular area) at the charging stations 42. The respective station parameters may include other infrastructure-based settings, such as a limitation to 30 minutes of charging based on a high volume of station need imposed by the charging stations 42, or other high use grid-based adjustments. Hancock in view of Trimboli in is silent with regard to the following limitations. However, Moura in an analogous art of electric vehicle management for the purpose of providing the following limitations as shown does:
determine and displaying external effects to the charging session characteristics of the vehicles caused by external sources; display, through the interface, the external effects; (¶ 0038: “Upon accessing a native application or a website, charging session options are presented to each customer. Pricing and/or carbon intensity of each option is updated in real time based on the time-varying cost of energy for both the site host and the electricity provider, maximum power constraints and/or demand charges, greenhouse gas emissions associated with electricity production, and charge point demand, with the objective of maximizing financial value for the charge point operator while meeting customer expectations for quality of service.”);
and upon receipt of the acceptance to the alternative configuration, providing instructions to the one or more charging stations associated with the one or more vehicles implement the external changes (¶ 0038: “Customers may choose a “regular” charging session, in which the vehicle starts charging immediately and continues at full power until the vehicle is charged or the customer ends the charging session, or a “scheduled” option with a reserved session duration and guaranteed energy delivery.”);
Both Hancock and Moura teach electric vehicle management. Hancock teaches in the Abstract “directing energy use within a facility comprising charging stations for charging a fleet of electric vehicles, using an energy optimisation engine.” Moura teaches in the Abstract “user is presented with menu of price-differentiated charging services, which differ in per-unit price and the energy delivery schedule.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Moura would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Moura to the teaching of Hancock in view Trimboli would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as determine and displaying external effects to the charging session characteristics of the vehicles caused by external sources; display, through the interface, the external effects; and upon receipt of the acceptance to the alternative configuration, providing instructions to the one or more charging stations associated with the one or more vehicles implement the external changes into similar systems. Further, as noted by Moura “The pricing control policy realizes benefits in three aspects: (i) net profits gain, (ii) overstay reduction, and (iii) increased quality-of-service.” (Moura, Abstract).
Conclusion
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/NADJA N CHONG CRUZ/
Primary Examiner, Art Unit 3623