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 .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 3-5, and 10 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by McGrath et al (US 2015/0367740 A1).
Regarding claim 1, McGrath et al teaches (see Figs. 1-3A): A method of operating a charging infrastructure (see Figs. 1 & 2A) for a plurality of electric vehicles (10), the method comprising: creating, by a central backend server (control system 60 may reside in one or more servers, see para. 0020) of the charging infrastructure, a global charging schedule for the plurality of electric vehicles and for a plurality of charging stations (30) of the charging infrastructure (for example, see step 220 in Fig. 3A and para. 0020-0022, 0029); determining, by the central backend server (60) of the charging infrastructure, a particular one of a plurality of charging stations (30) using the global charging schedule (see para. 0024-0026); sending, by the central backend server (60) of the charging infrastructure, data indicating the particular one of the plurality of charging stations (30) to one of the plurality of electric vehicles (for example, see step 230 in Fig. 3A and para. 0023, 0026, 0029-0032); and charging, by the particular one of the plurality of charging stations (30) of the charging infrastructure, a traction battery (see para. 0002-0003) of the one of the plurality of electric vehicles (10) that is connected to the particular one of the plurality of charging stations (see para. 0026, 0029-0032).
Regarding claim 3, McGrath et al teaches: The method according to claim 1, further comprising: registering, by the central backend server (60), each of the plurality of electric vehicles (10) and each of the plurality of charging stations (30) (for example, see step 210 in Fig. 3A and para. 0029, the server 60 receives data from vehicles 10 and charging stations 30, which can be considered registering).
Regarding claim 4, McGrath et al teaches the method according to claim 3, wherein the registering of the one of the plurality of electric vehicles (10) includes storing a storage capacity of the traction battery (the state of charge (SOC), see para. 0023, represents a storage capacity) of the one of the plurality of electric vehicles (10), and wherein the creating of the global charging schedule is based on the storage capacity (see para. 0024-0026 & 0029-0032).
Regarding claim 5, McGrath et al teaches: The method according to claim 3, wherein the registering of the particular one of the plurality of charging stations (30) includes storing a position (location of charging stations 30, see para. 0021) and a charging capacity (for example, rate of charging, see para. 0025) of the particular one of the plurality of charging stations (30), and wherein the creating of the global charging schedule is based on the position and the charging capacity of the particular one of the plurality of charging stations (see para. 0024-0026 & 0029-0032).
Regarding claim 10, McGrath et al teaches: A charging infrastructure (see Figs. 1-3A) for a plurality of electric vehicles (10), comprising: a plurality of charging stations (30); and a central backend server (control system 60 may reside in one or more servers, see para. 0020) connected (as shown in Fig. 2A) to the plurality of charging stations (30), wherein the central backend server (60), in operation, creates a global charging schedule for the plurality of electric vehicles (10) and for the plurality of charging stations (30) of the charging infrastructure (for example, see step 220 in Fig. 3A and para. 0020-0022, 0029), determines a particular one of the plurality of charging stations (30) using the global charging schedule (see para. 0024-0026), and sends data indicating the particular one of the plurality of charging stations (30) to one of the plurality of electric vehicles (10) (for example, see step 230 in Fig. 3A and para. 0023, 0026, 0029-0032), and wherein the particular one of the plurality of charging stations (30), in operation, charges a traction battery (see para. 0002-0003) of the one of the plurality of electric vehicles (10) that is connected to the particular one of the plurality of charging stations (30) (see para. 0026, 0029-0032).
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.
Claim(s) 2 and 6-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over McGrath et al (US 2015/0367740 A1) in view of Maeda et al (US 2022/0050143 A1).
Regarding claims 2 and 6-8, the teachings of McGrath et al, as applied to claim 1, have been discussed above. McGrath et al also teaches (regarding claim 6) transmitting, by each electric vehicle (10) of the plurality of electric vehicles, to the central backend server (60) a position of the electric vehicle (current location), a traction battery state of charge (SOC) (see para. 0023-0026 & 0029-0032).
McGrath et al does not specifically teach, (regarding claim 2) the creating of the global charging schedule includes minimizing a sum of a length of driving and a length of charging, and the method further comprises: determining, by the one of the plurality of electric vehicles, a travel route for a trip based on the data indicating the particular one of the plurality of charging stations; (regarding claim 6): transmitting, a starting location of a trip of the electric vehicle, a destination of the trip of the electric vehicle, and a planned travel route for the trip of the electric vehicle, wherein the creating of the global charging schedule is based on the starting location, destination, and planned travel route transmitted by each electric vehicle of the plurality of electric vehicles; (regarding claim 7): reserving, by the central backend server, the particular one of the plurality of charging stations according to the global charging schedule for a length of charging for the one of the plurality of electric vehicles based on a traction battery storage capacity and the traction battery state of charge transmitted by one of the plurality of electric vehicles; (regarding claim 8): wherein the creating of the global charging schedule is based on a plurality of reservations made for the plurality of charging stations.
Maeda et al teaches (see Figs. 1-5, 7 & 9) a method of operating a charging infrastructure (including charging stations 112) for a plurality of electric vehicles (102, 120), comprising: creating a charging schedule includes minimizing a sum of a length of driving and a length of charging (see the determination of arrival times and finish times shown in Fig. 9 and para. 0120), and the method further comprises: determining, by the one of the plurality of electric vehicles (102), a travel route for a trip based on the data indicating the particular one of the plurality of charging stations (see travel routines 704, travel paths 708 and station map 712 in Fig. 7 and para. 0100-0108); (regarding claim 6): transmitting, a starting location of a trip of the electric vehicle (determining travel routines and travel paths would necessarily include a starting location), a destination of the trip of the electric vehicle (determining travel routines and travel paths would necessarily include a destination), and a planned travel route (the travel path) for the trip of the electric vehicle, wherein the creating of the global charging schedule is based on the starting location, destination, and planned travel route transmitted by each electric vehicle of the plurality of electric vehicles (see travel routines 704, travel paths 708 and station map 712 in Fig. 7, Fig. 9 and para. 0100-0108, 0120); (regarding claim 7): reserving (see para. 0119-0122), by the central backend server (server 108, para. 0034-0035), the particular one of the plurality of charging stations according to the charging schedule for a length of charging for the one of the plurality of electric vehicles based on the traction battery state of charge (SOC) transmitted by one of the plurality of electric vehicles (see para. 0119-0122); (regarding claim 8): wherein the creating of the charging schedule is based on a plurality of reservations made for the plurality of charging stations (a position in the queue indicates a plurality of reservations, see para. 0012 & 0114).
In view of Maeda et al’s teachings, it would have been obvious to one of ordinary skill in the art prior to the effective filing date, to include with the method of McGrath et al, (regarding claim 2) the creating of the global charging schedule includes minimizing a sum of a length of driving and a length of charging, and the method further comprises: determining, by the one of the plurality of electric vehicles, a travel route for a trip based on the data indicating the particular one of the plurality of charging stations; (regarding claim 6): transmitting, a starting location of a trip of the electric vehicle, a destination of the trip of the electric vehicle, and a planned travel route for the trip of the electric vehicle, wherein the creating of the global charging schedule is based on the starting location, destination, and planned travel route transmitted by each electric vehicle of the plurality of electric vehicles; (regarding claim 7): reserving, by the central backend server, the particular one of the plurality of charging stations according to the global charging schedule for a length of charging for the one of the plurality of electric vehicles based on the traction battery state of charge transmitted by one of the plurality of electric vehicles; (regarding claim 8): wherein the creating of the global charging schedule is based on a plurality of reservations made for the plurality of charging stations; in order to create a more accurate charging schedule.
Regarding claim 7, McGrath et al as modified by Maeda et al does not specifically teach the data transmitted by the vehicle including a traction battery storage capacity.
However, since Maeda et al teaches calculating a finish time based on the state of charge (SOC) of the vehicle (102) and the charging speed of the charging station (112) (see para. 0121), it would have been obvious to one of ordinary skill in the art prior to the effective filing date to consider the battery storage capacity, since this information would be necessary in order to calculate an accurate amount of charging time.
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date to include, with the method of McGrath et al as modified by Maeda et al, the data transmitted by the vehicle including a traction battery storage capacity, since this would allow more accurate calculations of charging amounts needed and charging time needed at a particular charging speed of the charging station.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over McGrath et al (US 2015/0367740 A1) in view of Sugii et al “A Genetic-Algorithm based scheduling method of charging electric vehicles”.
Regarding claim 9, the teachings of McGrath et al, as applied to claim 1, have been discussed above.
McGrath et al does not teach wherein the creating of the global charging schedule includes using a genetic algorithm.
Sugii et al teaches the use of a genetic algorithm to create a charging schedule for electric vehicles (see the abstract and section 3, “SCHEDULING METHOD USING A GENETIC ALGORITHM”).
In view of Sugii et al’s teachings, it would have been obvious to one of ordinary skill in the art prior to the effective filing date to include, with the method of McGrath et al, wherein the creating of the global charging schedule includes using a genetic algorithm, since genetic algorithms are an efficient way to create a charging schedule within a reasonable computation time (see section 6, “SUMMARY” of Sujii et al).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mannepalli (US 12,083,920 B2) teaches a system and method for scheduling electric vehicle charging.
Pathipati (US 11,975,628 B1) teaches techniques for scheduling battery charging of service vehicles.
Masquelier et al (US 2023/0237855 A1) teaches optimizing fleet battery pack charging based on schedule data.
Starns (US 2019/0205842 A1) teaches charge scheduling across a fleet of electric vehicles.
Please also see the additional references cited on the attached PTO-892, which are directed to electric vehicle charging systems and methods.
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/JARED FUREMAN/Primary Examiner, Art Unit 2859