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 § 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a Judicial Exception without significantly more.
Independent Claims
As Claims 1, 8 and 15:
Step 1: Are the Claims to a process, machine, manufacture or composition of matter? Yes.
Step 2A: Are the Claims directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? Yes, the Claims is an abstract idea. See the analysis below.
The Claim recites:
A method of predicting a health of a battery, comprising:
obtaining a battery data indicative of a parameter of the battery;
partitioning the battery data into a plurality of subsets;
determining a score for each of the plurality of subsets, wherein each score is related to the health of the battery;
generating an overall score from the scores from each of the subsets; and
predicting the health of the battery from the overall score.
The non-emphasized limitations describe abstract processes while emphasized limitations recited additional limitation(s).
Regarding the non-emphasized limitations:
Step 2A prong 1:
Limitations “partitioning the battery data into a plurality of subsets;
determining a score for each of the plurality of subsets, wherein each score is related to the health of the battery;
generating an overall score from the scores from each of the subsets; and
predicting the health of the battery from the overall score.” is/are directed to a mental processes group of abstract idea. Mental processes are defined as concepts that can practically be performed in the human mind, or by a human using pen and paper as a physical aid. Examples of mental processes includes observations, evaluations, judgements and opinions.
These steps are considered mental processes group of abstract idea.
Step 2A prong 2:
Limitations “obtaining a battery data indicative of a parameter of the battery; ” are insignificant extra solution activity. See MPEP §2106.05(g).
The Claim(s) does not recite additional elements that integrate the judicial exception into a practical application.
Step 2B: Does the Claim recite additional elements that integrate the Judicial Exception into a practical application? No.
Limitation “obtaining a battery data indicative of a parameter of the battery; ” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i. Receiving or transmitting data over a network, e.g., using the Internet to gather data).
The claim is directed to mental processes group of abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Dependent Claims
As Claims 2, 9 and 16, the Claims recite “wherein determining the score for a subset further comprises inputting the subset into a machine learning model that generates the score.”
The non-emphasized limitations describe abstract processes while emphasized limitations recited additional limitation(s).
Step 2A: Are the Claims directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? Yes, the Claims is an abstract idea. Prong 1: There are no additional abstract idea(s). Prong 2: The limitation “wherein determining the score for a subset further comprises inputting the subset into a machine learning model that generates the score” are insignificant extra solution activity. See MPEP §2106.05(g). Claim(s) does not recite additional elements that integrate the judicial exception into a practical application.
Step 2B: Does the Claim recite additional elements that amount to significantly more than the Judicial Exception? No. The Limitations “wherein determining the score for a subset further comprises inputting the subset into a machine learning model that generates the score” were considered insignificant extra solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i. Receiving or transmitting data over a network, e.g., using the Internet to gather data). The Claim is not patent eligible.
As Claims 3, 10 and 17, the Claims recite “wherein determining the score for a subset further comprises inputting the subset into a plurality of machine learning models to generate a plurality of scores and generating the overall score further comprises generating a weighted sum of the scores that includes multiplying a score by a probabilistic coefficient associated with the machine learning model.”
The non-emphasized limitations describe abstract processes while emphasized limitations recited additional limitation(s).
Step 2A: Are the Claims directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? Yes, the Claims is an abstract idea. Prong 1: The limitation “wherein determining the score for a subset further comprises inputting the subset into a plurality of machine learning models to generate a plurality of scores and generating the overall score further comprises generating a weighted sum of the scores that includes multiplying a score by a probabilistic coefficient associated with the machine learning model.” is directed to mathematical calculations group of abstract idea. Prong 2: There are no additional limitations. Claim(s) does not recite additional elements that integrate the judicial exception into a practical application.
Step 2B: Does the Claim recite additional elements that amount to significantly more than the Judicial Exception? No. There are no additional limitations. The Claim is not patent eligible.
As Claims 4, 11 and 18, the Claims recite “further comprising adjusting a probabilistic coefficient for the machine learning based on an evaluation metric associated with a machine learning model.”
The non-emphasized limitations describe abstract processes while emphasized limitations recited additional limitation(s).
Step 2A: Are the Claims directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? Yes, the Claims is an abstract idea. Prong 1: The limitation “further comprising adjusting a probabilistic coefficient for the machine learning based on an evaluation metric associated with a machine learning model.” is directed to mathematical calculations group of abstract idea. Prong 2: There are no additional limitations. Claim(s) does not recite additional elements that integrate the judicial exception into a practical application.
Step 2B: Does the Claim recite additional elements that amount to significantly more than the Judicial Exception? No. There are no additional limitations. The Claim is not patent eligible.
As Claim 5, 12, 19, the Claim recites “further comprising determining whether the plurality of subsets is at least one of: (i) non-overlapping; and (ii) obtained using a same partitioning method.”
The non-emphasized limitations describe abstract processes while emphasized limitations recited additional limitation(s).
Step 2A: Are the Claims directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? Yes, the Claims is an abstract idea. Prong 1: There are no additional abstract idea(s). Prong 2: The limitation “further comprising determining whether the plurality of subsets is at least one of: (i) non-overlapping; and (ii) obtained using a same partitioning method” are insignificant Mere Instruction to Apply an Exception (See MPEP §2106.05(f)). Claim(s) does not recite additional elements that integrate the judicial exception into a practical application.
Step 2B: Does the Claim recite additional elements that amount to significantly more than the Judicial Exception? No. The Claim is not patent eligible.
As Claim 6, 13, 20, the Claim recites “further comprising fusing the scores to generate a plurality of subset scores and fusing the plurality of subset scores to generate the overall score.”
The non-emphasized limitations describe abstract processes while emphasized limitations recited additional limitation(s).
Step 2A: Are the Claims directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? Yes, the Claims is an abstract idea. Prong 1: There are no additional abstract idea(s). Prong 2: The limitation “further comprising fusing the scores to generate a plurality of subset scores and fusing the plurality of subset scores to generate the overall score” are insignificant Mere Instruction to Apply an Exception (See MPEP §2106.05(f)). Claim(s) does not recite additional elements that integrate the judicial exception into a practical application.
Step 2B: Does the Claim recite additional elements that amount to significantly more than the Judicial Exception? No. The Claim is not patent eligible.
As Claim 7, 14, the Claim recites “further comprising partitioning the battery data into subsets based on a difference in a behavior of scores for the subsets.”
The non-emphasized limitations describe abstract processes while emphasized limitations recited additional limitation(s).
Step 2A: Are the Claims directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? Yes, the Claims is an abstract idea. Prong 1: There are no additional abstract idea(s). Prong 2: The limitation “further comprising partitioning the battery data into subsets based on a difference in a behavior of scores for the subsets” are insignificant Mere Instruction to Apply an Exception (See MPEP §2106.05(f)). Claim(s) does not recite additional elements that integrate the judicial exception into a practical application.
Step 2B: Does the Claim recite additional elements that amount to significantly more than the Judicial Exception? No. The Claim is not patent eligible.
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) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jindal et al. (U.S. 2023/0333166 hereinafter Jindal) in view of Garcia et al. (U.S. 2018/0143257 hereinafter Garcia).
As claim 1, Jindal teaches a method of predicting a health of a battery, comprising:
obtaining a battery data indicative of a parameter of the battery (Jindal (¶0037 line 4-9, fig. 2 item 202), system obtains a set of battery attributes);
partitioning the battery data into a plurality of subsets (Jindal (¶0037 line 4-9, fig. 2 item 206), battery attributes are classified into a first subset, a second subset and a third subset);
determining a score for each of the plurality of subsets, wherein each score is related to the health of the battery (Jindal (¶0038 line 1-10, fig. 2 item 208, 210, 212), machine learning is applied to each subset to generate different scores);
predicting the health of the battery from the overall score (Jindal (¶0044 line 1-5), system predict a remaining life of the battery).
Jindal may not explicitly disclose:
generating an overall score from the scores from each of the subsets; and
Garcia teaches:
generating an overall score from the scores from each of the subsets (Garcia (¶0123 line 1-3, ¶0125 line 4-10), Three health metrics are used to compute SOH. Decision fusion algorithm by taking average or using a weighted sum model); and
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify overall score of Jindal instead be score fusion taught by Garcia, with a reasonable expectation of success. The motivation would be to “computes all these health metrics and combines two or more of them using a decision fusion algorithm to produce a more robust and comprehensive assessment of battery conditions”.
As Claim 2, besides Claim 1, Jindal in view of Garcia teaches wherein determining the score for a subset further comprises inputting the subset into a machine learning model that generates the score (Jindal (¶0038 line 1-10, fig. 2 item 208, 210, 212), machine learning is applied to each subset to generate different scores).
As Claim 3, besides Claim 2, Jindal in view of Garcia teaches wherein determining the score for a subset further comprises inputting the subset into a plurality of machine learning models to generate a plurality of scores and generating the overall score further comprises generating a weighted sum of the scores that includes multiplying a score by a probabilistic coefficient associated with the machine learning model (Garcia (¶0123 line 1-3, ¶0125 line 4-10), Three health metrics are used to compute SOH. Decision fusion algorithm by taking average or using a weighted sum model).
As Claim 4, besides Claim 3, Jindal in view of Garcia teaches further comprising adjusting a probabilistic coefficient for the machine learning based on an evaluation metric associated with a machine learning model (Garcia (¶101 last 5 lines), a decision fusion algorithm may weigh the three estimates associated with a given N, (e.g., Ne) based on a confidence measure constructed from using different factors such as information about these algorithms and observed performance.).
As Claim 5, besides Claim 1, Jindal in view of Garcia teaches further comprising determining whether the plurality of subsets is at least one of: (i) non-overlapping; and (ii) obtained using a same partitioning method (Jindal (¶0049 last 9 lines, fig. 4 item 304, 306, 308), the battery attributes may be grouped or classified into different subsets ( e.g., 304, 306, and 308) based on properties and/or characteristics of the battery attributes. Further, feature vectors may be selected/derived from the subsets 304, 306, and 308 and the selected/derived feature vectors may be fed into different machine learning models (e.g., a memory prediction model 310, a swelling prediction model 312, and a performance prediction model 314)).
As Claim 6, besides Claim 1, Jindal in view of Garcia teaches further comprising fusing the scores to generate a plurality of subset scores and fusing the plurality of subset scores to generate the overall score (Garcia (¶0123 line 1-3, ¶0125 line 4-10), Three health metrics are used to compute SOH. Decision fusion algorithm by taking average or using a weighted sum model).
As Claim 7, besides Claim 1, Jindal in view of Garcia teaches further comprising partitioning the battery data into subsets based on a difference in a behavior of scores for the subsets (Jindal (¶0049 last 9 lines, fig. 4 item 304, 306, 308), the battery attributes may be grouped or classified into different subsets (e.g., 304, 306, and 308) based on properties and/or characteristics of the battery attributes).
As Claim 8, Jindal in view of Garcia teaches a system for predicting a health of a battery, comprising:
a sensor configured to obtain a battery data indicative of a parameter of the battery (Jindal (¶0037 line 2-5), using passive and active measurements collected from a set of distributed sensors in order to estimate and predict the health and performance of electrochemical cells, batteries, and battery systems.); and
a processor (Jindal (¶0035 line 5), processor 202) configured to:
The rest of the Claim is rejected for the same reasons as Claim 1.
As Claim 9-14, the Claim are rejected for the same reasons as Claim 2-7, respectively.
As Claim 15-20, the Claims are rejected for the same reasons as Claims 1-6, respectively.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Shin et al. (U.S. 2025/0224701) teaches the use of different score to evaluate battery system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NHAT HUY T NGUYEN whose telephone number is (571)270-7333. The examiner can normally be reached M-F: 12:00-8:00 EST.
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/NHAT HUY T NGUYEN/ Primary Examiner, Art Unit 2147
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