Prosecution Insights
Last updated: April 19, 2026
Application No. 18/717,106

BATTERY DATA MANAGEMENT APPARATUS AND OPERATING METHOD THEREOF

Non-Final OA §102
Filed
Jun 06, 2024
Examiner
HOQUE, FARHANA AKHTER
Art Unit
2858
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
LG Energy Solution, Ltd.
OA Round
1 (Non-Final)
86%
Grant Probability
Favorable
1-2
OA Rounds
2y 6m
To Grant
97%
With Interview

Examiner Intelligence

Grants 86% — above average
86%
Career Allow Rate
737 granted / 859 resolved
+17.8% vs TC avg
Moderate +11% lift
Without
With
+11.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
21 currently pending
Career history
880
Total Applications
across all art units

Statute-Specific Performance

§101
2.1%
-37.9% vs TC avg
§103
46.8%
+6.8% vs TC avg
§102
42.2%
+2.2% vs TC avg
§112
5.3%
-34.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 859 resolved cases

Office Action

§102
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 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 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. Claims 1-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhou et al. (U.S. Publication No. US2024/0053402 A1). With respect to claim 1, Zhou et al. discloses a battery data management apparatus (see abstract, Fig. 1 system block diagram) comprising: a controller configured to determine whether a battery is abnormal based on battery data (see processor 81 shown in Fig. 8), determine an abnormality level of the battery based on whether the battery is abnormal (para 0092, lines 1-8; shows the steps to analyze battery life degradation), and classify and store the battery data in a plurality of storages, based on the abnormality level of the battery (memory 82 shown in Fig. 8); and a memory comprising the plurality of storages and a temporary storage configured to temporarily storing store the battery data (para 0095, lines 1-6, see storage controller in the CPU). With respect to claim 2, Zhou et al. discloses the battery data management apparatus of claim 1, wherein the controller is further configured to store the battery data in any one of the plurality of storages, which corresponds to the abnormality level of the battery (extract a life degradation curve based on the function curve; perform life degradation analysis on the battery based on the life degradation curve; S14 and S15; Fig. 1). With respect to claim 3, Zhou et al. discloses the battery data management apparatus of claim 1, wherein the controller is further configured to, based on priorities of a plurality of storing regions of any one of the plurality of storages, store the battery data in any one of the plurality of storing regions (para 0090, lines 1-5). With respect to claim 4, Zhou et al. discloses the battery data management apparatus of claim 1, wherein the controller is further configured to, when diagnosing that the battery is in an abnormal state (para 0004, lines 1-5), obtain battery data stored in the temporary storage at a time when the battery is diagnosed as being in the abnormal state (para 0095, lines 1-13), and obtain battery data stored in the temporary storage after an elapse of a specific period, and classify and store the battery data in the plurality of storages (para 0006, lines 1-11). With respect to claim 5, Zhou et al. discloses the battery data management apparatus of claim 1, wherein the controller is further configured to determine whether the battery corresponds to an abnormal level in descending order of a risk level of the abnormality level (para 0010, lines 1-7). With respect to claim 6, Zhou et al. discloses the battery data management apparatus of claim 1, wherein the memory stores the battery data at regular intervals in a circular queue of the temporary storage (para 0034, lines 1-8). With respect to claim 7, Zhou et al. discloses the battery data management apparatus of claim 1, wherein the battery data comprises at least any one of voltage, current, temperature, and diagnosis information of the battery (para 0036, lines 1-3; obtaining battery data of a device, wherein the battery data comprise a voltage and a current of a battery of the device). With respect to claim 8, Zhou et al. discloses an operating method of a battery data management apparatus, the operating method comprising: temporarily storing battery data (para 0092, lines 1-8; shows the steps to analyze battery life degradation); determining whether the battery is abnormal, based on the battery data (para 0092, lines 1-8; shows the steps to analyze battery life degradation); determining an abnormal level of the battery based on whether the battery is abnormal (para 0092, lines 1-8; shows the steps to analyze battery life degradation); and classifying and storing the battery data in a plurality of storages, based on the abnormal level of the battery (para 0006, lines 1-11). With respect to claim 9, Zhou et al. discloses the operating method of claim 8, wherein the determining of the abnormal level of the battery based on whether the battery is abnormal comprises storing the battery data in any one of the plurality of storages, which corresponds to the abnormality level of the battery (para 0092, lines 1-8; shows the steps to analyze battery life degradation). With respect to claim 10, Zhou et al. discloses the operating method of claim 8, wherein the classifying and storing of the battery data in the plurality of storages (para 0092, lines 1-8; shows the steps to analyze battery life degradation), based on the abnormal level of the battery, comprises, based on priorities of a plurality of storing regions of any one of the plurality of storages , storing the battery data in any one of the plurality of storing regions (extract a life degradation curve based on the function curve; perform life degradation analysis on the battery based on the life degradation curve; S14 and S15; Fig. 1). With respect to claim 11, Zhou et al. discloses the operating method of claim 8, wherein the temporarily storing of the battery data comprises, when diagnosing that the battery is in an abnormal state (para 0092, lines 1-8; shows the steps to analyze battery life degradation), obtaining battery data stored in the a temporary storage at a time when the battery is diagnosed as being in the abnormal state (para 0067, lines 1-10), and obtaining battery data stored in the temporary storage after an elapse of a specific period, and classifying and storing the battery data in the plurality of storages (para 0006, lines 1-11). With respect to claim 12, Zhou et al. discloses the operating method of claim 8, wherein the determining of the abnormal level of the battery based on whether the battery is abnormal comprises determining whether the battery corresponds to an abnormal level in descending order of-of a risk level of the abnormality level (para 0013, lines 1-10). With respect to claim 13, Zhou et al. discloses the operating method of claim 8, wherein the temporarily storing of the battery data comprises storing the battery data at regular intervals in a circular queue of the temporary storage (para 0034, lines 1-8). With respect to claim 14, Zhou et al. discloses the battery data management apparatus of claim 1, wherein the controller is further configured to control at least one of states or operations of the battery based on the abnormality level (para 0013, lines 1-10). With respect to claim 15, Zhou et al. discloses the operating method of claim 8, further comprising: controlling at least one of states or operations of the battery based on the abnormality Level (para 0013, lines 1-10). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FARHANA AKHTER HOQUE whose telephone number is (571)270-7543. The examiner can normally be reached Monday-Friday, 7:30am-4:00pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Eman A Alkafawi can be reached at 571-272-4448. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /FARHANA A HOQUE/Primary Examiner, Art Unit 2858
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Prosecution Timeline

Jun 06, 2024
Application Filed
Feb 21, 2026
Non-Final Rejection — §102 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
86%
Grant Probability
97%
With Interview (+11.2%)
2y 6m
Median Time to Grant
Low
PTA Risk
Based on 859 resolved cases by this examiner. Grant probability derived from career allow rate.

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