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 § 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 (i.e., changing from AIA to pre-AIA ) 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1is/are rejected under 35 U.S.C. 103 as being unpatentable over Eger et al. (US 2014/0225565) in view of Zhu (US 2019/0389314, cited by applicant)
Regarding claim 1,
Eger et al. teaches a method and apparatus providing electrical energy in (see fig. 1) with a charging system for executing a charging process during a charging frame, comprising: one or more electric vehicles (EV) chargers (110); a load management system (LMS) (see fig. 4) capable of controlling the one or more EV chargers (110); a network system comprising one or more wired or wireless connections for linking the one or more EV chargers to the load management system (see fig. 1 and 4); and a precision-time energy-based control algorithm for dynamically regulating an output power of the one or more EV chargers to meet a preset charging profile (see session management, parametrization, change management of figs. 4 and 5). According to Eger in (see para 0074-0103) that a charging profile can be dynamically adjusted based on load management. Furthermore, for instance in (see fig. 5), a charging frame can be divided into different or a plurality of time intervals (time sessions) which reads on the charging frame is divided into a plurality of sections.
However, Eger fails to teach that the LMS is configured to adjust the output power of each section for compensating an energy shortage in previous sections.
Zhu teaches an adaptive electric vehicle charging based on grid monitoring in (see fig. 1) wherein a charging facility management system, equivalent to an LMS, can be used to control the level of charging from a plurality of charging stations in (see para 0057, 0059) wherein peaks can be adjusted to compensate for previous deficiencies from previous sessions or time intervals.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Zhu into that of Eger thus making it possible to dynamically charge EVs based on power availability and load management for a dynamic balancing of power to multiple charging stations based on demand also.
Claim(s) 2-6 and 9-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eger et al. (US 2014/0225565) in view of Zhu (US 2019/0389314, cited by applicant) and further in view of Cater (US 2021/0268929) and further in view of Karner et al. (US 2013/0127417).
Regarding claim 2, The combination does not teach the claimed limitation comprising wherein the precision-time energy-based control algorithm comprises: collecting EV chargers’ data, including voltage, current, number of phases, charging time, and charging energy; and controlling the output power of the EV charger to a predetermined value at a predetermined time.
Cater teaches a dynamic charging system in (see figs. 1 and 3) wherein data including charging current, voltage, charging data and so forth in (see para 0034, 0043, 0044, 0046, 0049, 0051, 0062-0066, 0091, 0104) can be determined to control charging of an EV based on dynamic parameters.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Cater into the combination thus making it possible to adjust power dynamically to a plurality of chargers based on load demand and power availability as stipulated by Cater.
The combination including Cater (claim 10), Eger et al. (para 0166) for instance teaches charging station identification and conversion or management of different type of power in (see para 0090 of Zhu) but fails to teach determining or identifying the charging station in order words with a power generation type which includes the AC type and/or DC type generated by the charger.
Karner et al. teaches a charging system wherein chargers can be of a different type and denoted as such with different capability or specifications in (see para 0035-0037) and charge data can be monitored as well in (see para 0046, 0050). Power can be dynamically adjusted in (see para 0059).
Therefore, it would have been obvious to one of ordinary skill in the art before or during the effective filing date of the claimed invention that knowing the ID of a charger would make it possible to know it’s charging capability either a single phase of three phase charger to regulate or dynamically control incoming power to and meet the needs of the loads
Regarding claim 3, see the explanation as set forth regarding claim 3 wherein Karner teaches a charging station or stations with single or three phase capabilities.
Regarding claims 4-6, The combination teaches wherein the charging process is divided into a plurality of stages, and wherein each of the plurality of stages is programmable reads on programmable time sessions or intervals of a charging duration which can be dynamically adjusted based on machine learning or algorithms in (see Eger et al. (0069-0095)., Zhu et al. (para 0068) and Cater (para 0045, 0062, 0065, 0100) analyzing historical data associated with charging stations and EVs to be charged.
Regarding claim 9, The combination including Eger and Zhu (see para 0068, 0118, 0126 of Zhu, see figs. 4/5, para 0075-0101 of Eger et al. ) teaches dynamic adjustment of charging current based on load demand and power availability which reads on wherein the LMS increases a charging current limit if an accumulated charging energy is less than an expected value as defined by the preset charging profile read by the examiner as increasing charging current to a remaining plurality of charging stations based on the demands of the load, during low peaks over a time interval or sessions.
. Regarding claim 10, The combination including Eger and Zhu (see para 0068, 0118, 0126 of Zhu, see figs. 4/5, para 0075-0101 ) teaches dynamic adjustment of charging current based on load demand and power availability which reads on wherein the LMS decreases a charging current limit if an accumulated charging energy is more than an expected value as defined by the preset charging profile read by the examiner as lowering charging current to a plurality of charging stations based on the demands of the load over a time interval or sessions during peak load.
Regarding claim 11, see the explanation as set forth regarding claims 2 and 9. The combination renders obvious wherein the LMS regulates the charging current in order to maintain the charging process in keeping with the preset charging profile within a time frame.
Regarding claim 12, see the explanation as set forth regarding claims 2 and 9. The combination renders obvious wherein the LMS regulates the charging current in order to maintain the charging process in keeping with the preset charging profile within a time frame.
Claim(s) 7 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eger et al. (US 2014/0225565) in view of Zhu (US 2019/0389314, cited by applicant) and further in view of Cater (US 2021/0268929) and further in view of Karner et al. (US 2013/0127417) and further in view of Feng et al. (US 2023/0231403 A1).
Regarding claim 7, The combination teaches accumulated energy patterns over a time interval, charging current, charging current limit in (see fig. 5, para 0074-0094, para 0118, 0151-0168 of Eger et al., ) and charging current for future charging (see para 0094, 0099 of Eger) but fails to wherein the precision-time energy-based control algorithm derivates a function of time, an accumulated charging energy, an output current limit, and a charging current of the next section.
The combination fails to teach an algorithm which derivates as a function of time and other parameters.
Feng et al. teaches a battery charging system in (see para 0040-0045, 0055) with an algorithm, which derivates as a function of time battery charging parameters and battery parameters such as current limit, charging current for future sessions which can be updated in a table for future charging decisions in (see para 0048-0049, 0059).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Feng into the combination thus making it possible to make charging decisions dynamically based on monitored or determined and stored charging parameters.
Regarding claim 8, see the explanation as set forth regarding claim 6.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20040169489 teaches detection of AC type in (para 0044).
Karlgaard et al. teaches power distribution in (see fig. 9) with loads (EV) coupled to EV chargers controlled by an LMS
Beaude et al. (US 2019/0344680) which teaches a charger capable of regulating power to EVs by regulating power in time slots (see para 0068-0100).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rex Barnie whose telephone number is (571)272-7492. The examiner can normally be reached 8AM-5PM.
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/REXFORD N BARNIE/Supervisory Patent Examiner, Art Unit 2836
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