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 .
The amendment filed on May 13, 2026 has been considered.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on May 13, 2026 has been entered.
Election/Restrictions
Claims 13 and 14 are withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected Species II due to Species I, claims 1, 2, 4, 5, 8-10, and 12 being constructively elected by original presentation, there being no allowable generic or linking claim.
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.
Claim 5 is 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.
Claim 5, it is unclear whether the first label is set to the feature value of the learning battery for one or more charging and discharging cycles up to a cycle at or before the predetermined charging and discharging cycle. Examiner interprets the first label is set to the feature value of the learning battery for one or more charging and discharging cycles up to a cycle at the predetermined charging and discharging cycle.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 12 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 12 recites steps that are already recited in claim 1. Thus, claim 12 depends from claim 1 but does not further limit claim 1. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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, 2, 4, 5, 8-10, and 12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Pursuant to the 2019 Revised Patent Subject Matter Eligibility Guidance (MPEP 2106), the following analysis is made:
Under step 1 of the Guidance, the claims fall within a statutory category.
Under step 2A, prong 1, claim 1 recites an abstract idea of “judging a state of the learning battery based on the feature value and a criterion value corresponding to the feature value” (evaluation/judgment, mental process), “setting a label for the feature value of the learning battery based on the state of the learning battery judged by the first state judging unit” (evaluation, mental process), “learning a classification model for judging a state of an analysis battery based on the feature value of the learning battery” (evaluation/judgment, mental process), “judging the state of the analysis battery based on the learned classification model (evaluation/judgment, mental process); “when the state of the learning battery is judged to be in the normal state, a label corresponding to the feature value of the learning battery for a corresponding normal charging and discharging cycle is set to a first label” (evaluation/judgment, mental process), “when the state of the learning battery is judged to be in the defective state, a label corresponding to the feature value of the learning battery for a corresponding defective charging and discharging cycle is set to a second label” (evaluation/judgment, mental process), “the number of times that the state of the learning battery is judged as the defective state is counted, and when the counted number is equal to or greater than a criterion number, a label corresponding to the feature value of the learning battery after a last charging and discharging cycle at which the state of the learning battery is judged as the defective state is set to the second label” (evaluation/judgment, mental process).
The mere nominal recitation of a generic processor (controllers) does not take the claim limitation out of the abstract idea (MPEP 2106.04(a)(2) (III)).
Under step 2A, prong 2, the claim limitations are not integrated into a practical application (MPEP 2106.04(d)(I)).
Extracting a feature value of a learning battery at a charging and discharging cycle of the learning battery is directed to an insignificant extra solution activity of data gathering (see MPEP 2106.05(g)).
Under step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea (MPEP 2106.05(A)).
The remaining dependent claims 2, 4, 5, and 8-10 do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea.
Claims 2, 4, 5, 8-10, and 12 are directed to an abstract idea.
Accordingly, claims 1 and its respective dependent claims 2, 4, 5, 8-10, and 12 are patent ineligible under 35 USC 101.
Prior Art Note
Claim 1, 2, 4, 5, 8-10, and 12 do not have prior art rejections.
The combination as claimed wherein a battery management apparatus comprising the number of times that the state of the learning battery is judged as the defective state is counted, and when the counted number is equal to or greater than a criterion number, a label corresponding to the feature value of the learning battery after a last charging and discharging cycle at which the state of the learning battery is judged as the defective state (claim 1) is not disclosed, suggested, or made obvious by the prior art of record.
Response to Arguments
Applicant's arguments filed on May 13, 2026 have been fully considered.
Applicant’s arguments and amendment with respect to the drawing objection have been fully considered and are persuasive. The drawing objection has been withdrawn.
Applicant’s arguments and amendment with respect to the claim objections have been fully considered and are persuasive. The claim objections have been withdrawn.
With respect to the rejection under 35 USC 112(b), Applicants argue “claim 5 is being revised herewith to recite "wherein in case where the state of the learning battery is judged to be in the normal state at the predetermined charging and discharging cycle, the first label is set to the feature value of the learning battery for one or more charging and discharging cycles up to a cycle before the predetermined charging and discharging cycle" (emphasis added). Accordingly, the claim is not contradictory, because it indicates that the first label is set to the feature value for charging and discharging cycles leading up to the cycle before the predetermined charging and discharging cycle, in a case where the state of the learning battery is judged to be in a normal state at the predetermined charging and discharging cycle. That is, depending on whether the state of the learning battery is in a normal state at the predetermined charging and discharging cycle, the first label is set for these one or more charging and discharging cycles preceding the predetermined charging and discharging cycle.”
Examiner’s position is that the claim recites “in case where the state of the learning battery is judged to be in the normal state at the predetermined charging and discharging cycle, the first label is set to the feature value of the learning battery for one or more charging and discharging cycles up to a cycle before the predetermined charging and discharging cycle”. This limitation is indefinite because it is unclear how the first label can be set … before the predetermined charging and discharging cycle, when we are already at the predetermined charging and discharging cycle (learning battery is judged … at the predetermined charging and discharging cycle).
With respect to the rejection under 35 USC 101, Applicants argue “the Examiner erroneously boils the technological improvement in the entirety of the claimed invention down to a single step, namely that of "extracting a feature value of a learning battery at a charging and discharging cycle of the learning battery" (page 5 of Office Action), and goes on to assert that extracting a feature value is allegedly conventional (citing U.S. 2016/0231386 to Sung et al. (hereinafter "Sung"), U.S. 2019/0392320 to Kim (hereinafter "Kim") and U.S. 2022/0052389 to Kwon (hereinafter "Kwon") and as such cannot constitute a technological improvement that would impart patent eligibility. (Pages 4-7 of Office Action).
Examiner position, as discussed in the prior advisory, is that a claimed technological improvement that is indicative of integration into a practical application, must comply with MPEP 2106.05(a). Pursuant to MPEP 2106.05(a), "[a]n indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art."
The instant published application explains the challenges of prior art to secure a large amount of training/learning data (see paragraphs 0006-0007). The technical solution is explained in paragraph 0067, i.e., "[t]he battery management apparatus 100 may secure a large amount of learning data for learning the classification model by extracting the feature value of the battery at EVERY charging and discharging cycle in consideration of these features of the battery" (paragraph 0067). However, the technical solution is not expressed in the claims. Instead, the claims recite "extracting a feature value of a learning battery at A charging and discharging cycle of the learning battery" (claim 1).” Accordingly, "extracting a feature value of a learning battery at a charging and discharging cycle of the learning battery" is not a technological improvement disclosed/claimed pursuant to MPEP 2106.05(a).
Nevertheless, "extracting a feature value of a learning battery at a/every charging and discharging cycle of the learning battery" is a conventional feature because it has already been taught by prior art (see Sung et al. US 2016/0231386, paragraph 0105, lines 5-7; Kim US 2019/0392320, Abstract, lines 4-7; Kwon et al. US 2022/0052389, Abstract, lines 6-10).
Applicants further argue “as described in the instant specification, aspects of the invention as claimed provide for a way to secure large amounts of learning data to be used for a learning a classification model, even when only a limited number of learning batteries are available to inform the classification model (see, e.g., paragraph [0008] of the U.S. PG-Pub. No. 2023/0358812 corresponding to the instant application (hereinafter referred to as the "812 Publication")). The invention as claimed thus provides for a technological improvement in the area of learning models applied to battery diagnostics, because learning data needed to train the model can be supplied even from a limited number of learning batteries.”
Examiner’s position is that paragraph 0008, does not explain the details of an unconventional technical solution to a prior technical problem, e.g., securing a large amount of learning data for learning the classification model by extracting the feature value of the battery at every charging and discharging cycle in consideration of these features of the battery.
Applicants further argue “[t]he number of times the learning battery is determined to be in the defective state is counted, and when the counted number meets a criterion number, the label corresponding to the feature value is set to the second label after a last charging and discharging cycle at which the state of the battery was judged. (See, paragraphs [0102]-[0106] of the '813 Publication).”
Examiner’s position is that paragraphs 0102-0106 do not appear to be unconventional technical solutions to a prior technical problem, as explained in paragraphs 0006-0007.
Applicants further argue “[a]s described by the specification, the determination of the state of the battery may be affected by temporary noise due to measurement errors, and the state of the battery may even be temporarily restored (paragraph [0107] of the '813 Publication).”
Examiner’s position is that paragraph 0107 does not appear to explain a technical problem of prior art and an unconventional technical solution to the prior technical problem. The problem of noise is not an exclusive prior art problem.
Applicants further argue "[i]n particular, claim 1 is directed to a battery pack and recites the practical application of "judging the state of the analysis battery based on the learned classification model." Accordingly, the claim 1 (and claim 12) as amended are believed to be in compliance with 35 U.S.C. § 101, because the claims include the practical application of determining a state of an analysis battery, based on the extracting of feature values and setting of labels for feature values in a learning battery, and using these feature values to learn a classification model that is used to judge the state of the analysis battery, such as for example to judge the state of the analysis battery as being in a normal or defective state (see, e.g., paragraph [0065] of the U.S. PG-Pub. No. 2023/0358812 corresponding to the instant application (hereinafter referred to as the "812 Publication")."
Examiner's position is that "judging the state of the analysis battery based on the learned classification model", "setting of labels for feature values in a learning battery [based on the state of the learning battery based on the feature value of the learning battery", "learning a classification model that is used to judge the state of the analysis battery based on the feature value of the learning battery", "judging the state of the analysis battery as being in a normal or defective state" are directed to an abstract idea because they each involves an evaluation process. A practical application is missing from the claims. For example, in what practical application is the normal/defective battery state applied/used after the state is determined?
Applicants further argue "the battery pack as recited in claim 1 (and corresponding method of claim 12) that has the ability to judge the state of the analysis battery, provides a significant technological advancement that is more than mere routine and conventional extra-solution activity."
Examiner's position is that judging the state of the analysis battery is an abstract idea because it involves an evaluation process. Further, as discussed above, the claims are not directed to a technological improvement. Thus, they are not indicative of integration into a practical application.
Applicants further argue “none of these references disclose or suggest the technological improvement of selecting when to set the first and second labels according to whether a criterion number has been reached that is indicative of a defective battery for a certain number of charging and discharging cycles (e.g., setting from the first label to the second label after charging and discharging cycle C3), as with the battery bank as claimed.”
Examiner’s position is that “selecting when to set the first and second labels according to whether a criterion number has been reached that is indicative of a defective battery for a certain number of charging and discharging cycles” is not discussed in the specification as a technical solution (e.g., paragraph 0067) to a prior technical problem (see paragraphs 0005, 0006).
Applicants further argue “[a]s described in the instant application, conventional methods can require a large amount of training data in order to form a good model for judging of an analysis battery (paragraphs [0005]-[0006] of the '812 Publication). Also, as the life expectancy of the learning battery increases, the time required for the charging and discharging cycles may also increase proportionally, so that the time required to secure the learning data may also increase (paragraph [0006] of the '812 Publication). Furthermore, there may be a limit to the amount of learning data that can be secured from a limited number of learning batteries (paragraph [0006] of the '812 Publication). In contrast, the battery pack as claimed (and corresponding method of claim 12) provides the significant technological advancement of quickly securing a large amount of learning data for learning a classification model from a limited number of batteries (paragraph [0025] of the '812 Publication).”
Examiner’s position is that the technical solution is explained in paragraph 0067, i.e., "[t]he battery management apparatus 100 may secure a large amount of learning data for learning the classification model by extracting the feature value of the battery at every charging and discharging cycle in consideration of these features of the battery" (paragraph 0067). However, the technical solution is not expressed in the claims. Instead, the claims recite "extracting a feature value of a learning battery at a charging and discharging cycle of the learning battery" (claims 1, 12).” Accordingly, "extracting a feature value of a learning battery at a charging and discharging cycle of the learning battery" is not a technological improvement disclosed/claimed pursuant to MPEP 2106.05(a).
Applicant’s remaining arguments have been considered but are traversed in view of the discussions and the grounds of rejection discussed above.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael Nghiem whose telephone number is (571) 272-2277. The examiner can normally be reached on M-F.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Schechter can be reached at (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/MICHAEL P NGHIEM/Primary Examiner, Art Unit 2857 June 12, 2026
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