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 .
Response to Arguments/Amendment
Amendment and argument filed on 03/27/2026 are considered. Claims 1-8 are amended and new claims 9-13 are added.
Claim objection: Claims 1, 7 and 8 are amended to correct informalities. The claim objection is withdrawn.
Double patenting: Examiner views the independent claims 1, 7, 8 in co-pending application are still same as the instant independent claims 1, 7 and 8. Therefore the double patenting rejection is maintained.
Claim interpretation: Applicant amended claims 1-8 to recite sufficient structure to perform the claimed function. Therefore, claim interpretation is withdrawn.
Claim rejection under 35 U.S.C 112: The amendment of claim 6 overcomes the rejection under112. The rejection is withdrawn. A new unclear term in noticed in the claims, which is addressed below.
Claim rejection under 35 U.S.C 101:
Applicant argues “The Office Action rejects claim 1-8 under 35 U.S.C. § 101 as being directed to non-statutory subject matter, and in particular as allegedly being abstract ideas. In particular, the Office Action alleges that the claims are directed to the abstract idea of mathematical concepts and mental processes. Applicant respectfully submits that the claims as currently recited are directed toward statutory subject matter. In particular, as articulated in MPEP § 2106, the claims are not directed toward an abstract idea.
Under MPEP § 2106.1, the evaluation of whether a claim is directed toward an abstract idea is a two-part inquiry under the Alice/Mayo test. In Prong One, examiners evaluate whether the claim recites a judicial exception. In Prong Two, examiners evaluate the claims as a whole to determine whether the claim recites additional elements that integrate the exception into a practical application of that exception.
Prong One: Evaluate Whether the Claim Recites a Judicial Exception
To determine whether a claim recites an abstract idea in Prong One, examiners are to: (1) identify the specific limitation(s) in the claim under examination that the examiner believes recites an abstract idea; and (2) determine whether the identified limitation(s) fall within at least one of the groupings of abstract ideas in MPEP § 2106.04(a). If the identified limitation(s) falls within the subject matter groupings of abstract ideas enumerated therein, analysis should proceed to Prong Two to evaluate whether the claim integrates the abstract idea into a practical application. MPEP § 2106.04(a).
The Office Action asserts that the claims relate to "mathematical concepts and mental processes." Applicant respectfully disagrees and submits that claim 1 does not recite a mathematical concept but, at the most, is merely based on or involves a mathematical concept. See, e.g., Thales Visionix, Inc. v. United States, 850 F.3d 1343, 1348-49, 121 USPQ2d 1898, 1902-03 (Fed. Cir. 2017) (determining that the claims to a particular configuration of inertial sensors and a particular method of using the raw data from the sensors in order to more accurately calculate the position and orientation of an object on a moving platform did not merely recite "the abstract idea of using 'mathematical equations for determining the relative position of a moving object to a moving reference frame'.").
Similarly, claim 1 has been amended to recite sufficient structure (similar to the configuration of inertial sensors in Thales Visionix) that the claim does not recite the mathematical concept. Claim 1 recites in part: "an energy storage device comprising a plurality of energy storage cells; a plurality of sensors coupled to the energy storage device and configured to measure voltage of the plurality of energy storage cells; and a battery controller." (Emphasis added). Claim 1 further recites limitations that involve mathematical operations (e.g., "create learning data from plural pieces of measurement data of the energy storage device") in the same way that Thales Visionix involved calculating the position and orientation of an object on a moving platform using raw data from the sensors. Therefore, claim 1 does not recite the mathematical concept but is rather, at the most, merely based on or involves a mathematical concept.
The Office Action further asserts that the claims relate to "mental processes." Applicant respectfully disagrees. Claim 1, as amended, cannot be practically performed in the human mind. Claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations. See SRI Int'l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1304 (Fed. Cir. 2019) (declining to identify the claimed collection and analysis of network data as abstract because "the human mind is not equipped to detect suspicious activity by using network monitors and analyzing network packets as recited by the claims").
As previously discussed, claim 1 has been amended to recite sufficient structure that claim 1 cannot be practically performed in the human mind. Claim 1 recites an energy storage device, energy storage cells, a plurality of sensors configured to measure voltage of the plurality of energy storage cells, and a battery controller. A human mind cannot measure voltage of the plurality of energy storage cells. Nor can a human mind: (1) create learning data from plural pieces of measurement data of the energy storage device such that the plural pieces of measurement data are grouped based on a configuration of the energy storage device, (2) store a model using the created learning data to output a score corresponding to whether or not abnormal measurement data is included in the plural pieces of measurement data when the plural pieces of measurement data is input, (3) detect an abnormality or a sign of abnormality of the energy storage device based on a score output by inputting the measurement data to the model, (4) determine an electric power distribution using an electric power adjustment of the energy storage device based on the abnormality or the sign of the abnormality. Therefore, the claims do not relate to mental processes.
Applicant submits that for the above reasons the claims 1-8 as a whole are not drawn to an abstract idea but are drawn toward patentable subject matter. Therefore, Applicant respectfully submits that the claims are not directed toward a judicial exception and thus do not recite an abstract idea.”
Examiner respectfully disagrees above the applicant’s above argument. The recited devices, energy storage cells, a plurality of sensors configured to measure voltage of the plurality of energy storage cells, and a battery controller are part of the additional elements to the claims. Examiner does not consider these recites devices or sensors a mental or mathematical ideas, the recited devices and sensor are required elements to gather or collect the measurement data. The measured data are to be further analyzed (i.e., the above steps 1-4 are mathematical or mental process). Therefore, the independent claims still recite mental or mathematical steps.
Applicant argues “ Prong Two: If the Claim Recites A Judicial Exception, Evaluate Whether The Judicial Exception Is Integrated Into A Practical Application
Assuming, arguendo, that the claims are directed to one of the subject matter groupings of abstract ideas enumerated under Prong One, which Applicant does not concede, Applicant respectfully asserts that the concepts of claims 1-8 are integrated into a practical application such that the claims are not directed toward an abstract idea.
"In Prong Two, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception." MPEP § 2106.04 II.A.2. In this instance, Applicant respectfully asserts that claims 1-8 are clearly a practical application, in that the claims generate and produce a tangible result that provides a meaningful improvement over existing technology as recognized by the specification. See, e.g., MPEP § 2106.05.
According to MPEP § 2106.04(d)(1), "[i]mplementing ajudicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim" is indicative of an additional element that may integrate the exception into a practical application.
Applicant respectfully submits that when considered as a whole, the claims are integrated into a practical application. Claim 1 recites an energy storage device, energy storage cells, a plurality of sensors configured to measure voltage of the plurality of energy storage cells, and a battery controller. Claim 1 further recites a processor configured to perform various operations. For example, claim 1 recites: "create learning data from plural pieces of measurement data of the energy storage device such that the plural pieces of measurement data are grouped based on a configuration of the energy storage device." Therefore, the configuration of the energy storage device is involved in creating the learning data from plural pieces of measurement data of the energy storage device. Therefore, the alleged judicial exception is used in conjunction with a particular machine (i.e., energy storage device) that is integral to the claim.
Additionally, the MPEP makes clear that the improvement need only be that-an improvement- even if "it may not be an improvement over well-understood, routine, conventional activity." MPEP § 2106.04(d)(1). Additionally, there is no requirement that the improvement be from the judicial exception, or the additional elements alone. Rather, "it is important for examiners to analyze the claims as a whole when determining whether the claim provides an improvement to the functioning of computers or an improvement to other technology or a technical field." MPEP § 2106.05(a).
For at least these reasons, Applicant respectfully submits that claims 1-8 are not directed toward an abstract idea. Applicant therefore respectfully requests that the Examiner withdraw the rejections of independent claims 1, 7, and 8 and dependent claims 2-6 under 35 U.S.C. § 101.”
Examiner respectfully disagrees the above argument because the amended independent claims that are presented for examination do not integrate into practical application. As examiner discussed above the additional elements and the limitations with abstract ideas do not integrate each other to provide the practical application of the claimed invention. Courts have also identified such limitations with an insignificant extra-solution activity do not integrate a judicial exception into a practical application. For example, testing a system for a response, the response being used to determine system malfunction, In re Meyers, 688 F.2d 789, 794; 215 USPQ 193, 196-97 (CCPA 1982). Please refer to MPEP 2106.05 (g) (3).
Similarly, the claimed limitation were found to be suggested or taught by applied prior art Park. Therefore, the invention is determined to be well known, routine and conventional. Please see prior art rejection. Similarly, the claims as a whole cannot be realized to provide improvement in the functioning of computers or an improvement to other technology or a technical field. Therefore the amended claims are still directed towards an abstract ideas and do not overcome the rejection under 35 U.S.C 101.
A non-statutory subject matter 101 rejection for claim 8 is withdrawn by the appropriate amendment to the claim 8.
Claim rejection under 35 U.S.C 103:
Applicant argues “Claims 1-4, 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Naha et al. US 20190120908 Al herein after "Naha" in view of Park et al US 20170126027 Al herein after "Park".
Claim 1 has been amended to recite in part: "create learning data from plural pieces of measurement data of the energy storage device such that the plural pieces of measurement data are grouped based on a configuration of the energy storage device." Naha does not teach or suggest this limitation. Furthermore, claim 1 has been amended to recite: "wherein the creating the learning data comprises a statistical processing for each group of the plural pieces of measurement data." Naha does not teach or suggest this limitation either.
Park does not cure the defects of Naha. Park does not teach or suggest: "create learning data from plural pieces of measurement data of the energy storage device such that the plural pieces of measurement data are grouped based on a configuration of the energy storage device" or "wherein the creating the earning data comprises a statistical processing for each group of the plural pieces of measurement data." Therefore, the rejection against claims 1-4, 7, and 8 should be withdrawn.
Claims 5 and 6 were rejected are rejected under 35 U.S.C. 103 as being unpatentable over Naha and Park in view of Shibuya et al US 20150169393 Al herein after "Shibuya."
Shibuya does not cure the defects of Naha and Park. Therefore, claims 5 and 6, being dependent on claim 1, should be allowable for at least the same reasons.”
Examiner respectfully disagrees the above argument because, examiner views prior art Park in paragraphs [0026], [0078] and [0090] discuss creating machine learning data from averages and differences (i.e., statistical processing) for each group of multiple physical measurements of battery or power storage device. Therefore, park is applicable for the argued limitation.
The independent and dependent claims are accordingly addressed below in their respective section.
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 1-13 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.
Regarding independent claims 1, 7, 8 recite “… measurement data are grouped based on a configuration of the energy storage device” it is unclear what a configuration mean in this claim limitation. Configuration has broad and general meaning; examiner is unable to exactly determine what the applicant intended meaning for “configuration”. Therefore, the independent claims are rejection under 112 (b). Examiner considers configuration to be any kind of arrangement. Applicant is suggested to amend this limitation by providing clear and exact meaning for configuration.
Claims 11-13 recite “The abnormality detection device according to claim 7” Claim 7 is a method claim. Therefore, it is unclear whether the dependent claims 11-13 actually referring according to method or device claim 7.
Double Patenting
Claim 1, 7, 8 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1, 7, 8 of copending Application No. 18256147 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because:
Instant claim 1, 7, 8 is anticipated by claim 1, 7, 8 of Application No. 18256147.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
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 1-13 are rejected under 35 U.S.C 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, natural phenomenon, or an abstract idea) without significantly more.
Specifically, claim 1 recites:
An abnormality detection device comprising:
an energy storage device comprising a plurality of energy storage cells;
a plurality of sensors coupled to the energy storage device and configured to measure voltage of the plurality of energy storage cells;
a battery controller comprising:
a processor configured to:
create learning data from plural pieces of measurement data of the energy storage device such that the plural pieces of measurement data are grouped based on a configuration of the energy storage device;
store a model learned using the created learning data to output a score corresponding to whether or not abnormal measurement data is included in the plural pieces of measurement data when the plural pieces of measurement data is input;
detect an abnormality or a sign of abnormality of the energy storage device based on a score output by inputting the plural pieces of measurement data to the model; and
determine an electric power distribution using an electric power adjustment of the energy storage device based on the abnormality or the sign of the abnormality,
wherein the creating the learning data comprises a statistical processing for each group of the plural pieces of measurement data.
The claim limitations in the abstract idea have been highlighted in bold above.
Under the step 1 of the eligibility analysis, it is determined whether the claims are drawn to a statutory category by considering whether the claimed subject matter fall within the four statutory categories of patentable subject matter identified by 35 U.S.C 101: process, machine, manufacture, or composition of matter. The above claim is considered to be in the statutory category of (machine).
Under the step 2A, prong one, it is considered whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into groupings of subject matter when recited as such in a claim limitation, that cover mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) and mental process – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion.
For example, a step of “create learning data from plural pieces of measurement data of the energy storage device such that the plural pieces of measurement data are grouped based on a configuration of the energy storage device (considered to be a mathematical step);
store a model learned using the created learning data to output a score corresponding to whether or not abnormal measurement data is included in the plural pieces of measurement data when the plural pieces of measurement data is input (considered to be a mathematical step);
detect an abnormality or a sign of abnormality of the energy storage device based on a score output by inputting the plural pieces of measurement data to the model (considered to be a mental step); and
determine an electric power distribution using an electric power adjustment of the energy storage device based on the abnormality or the sign of the abnormality (considered to be a mental step),
wherein the creating the learning data comprises a statistical processing for each group of the plural pieces of measurement data. (considered to be a mathematical step);
These mathematical and mental steps represent that, under their broadest reasonable interpretation, covers performance of the limitation in the mind. That is, nothing in the claim element precludes the step from practically being performed in the mind.
Similar limitations comprise the abstract ideas of the independent claims 7 and 8.
Next, under the step 2A, prong two, it is considered whether the claim that recites a judicial exception is integrated into a practical application.
In this step, it is evaluated whether the claim recites meaningful additional elements that integrate the exception into a practical application of that exception.
In claim 1, the additional elements/steps are: energy storage device, energy storage cells, sensors, battery controller, processor. The above additional elements/steps (hardware) are recited in generality and represent extra solution activity to the judicial exception. The additional element in the preamble of “An abnormality detection…” is not qualified for a meaningful limitation because it only generally links the use of the judicial exception to a particular technological environment or field of use. There are not any meaningful additional elements in claim 1 that can be considered to integrate the recited abstract ideas into practical application.
In claim 7, the additional elements/steps recite the similar additional elements/steps as of claim 1. The additional elements/steps (program/software – method) are recited in generality and represent extra- solution activity to the judicial exception. The additional element in the preamble of “An abnormality detection…” is not qualified for a meaningful limitation because it only generally links the use of the judicial exception to a particular technological environment or field of use. There are not any meaningful additional elements in claim 7 that can be considered to integrate the recited abstract ideas into practical application.
In claim 8, the additional element is: a non-transitory computer readable storage medium storing a computer program configured to cause a computer to. The above additional elements/steps (a non-transitory computer readable storage medium storing a computer program configured to cause a computer to – generic computer equipment) are recited in generality and represent extra solution activity to the judicial exception. The additional element in the preamble of “[a non-transitory computer readable storage medium storing a computer program configured to cause a computer to…]” is not qualified for a meaningful limitation because it is only generally links the use of the judicial exception to a particular technology environment or field of use. The storage medium and the program recited are not qualified as particular machines; a generic computer equipment that is well understood and conventional and is significantly insufficient.
In conclusion, the above additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the step 2B.
Considering the claim as a whole, one of ordinary skill in the art would not know the practical application of the present invention since the claims do not apply or use the judicial exception in some meaningful way.
The independent claims 1, 7 and 8, therefore, are not patent eligible.
With regards to the dependent claims, the claims 2-6, 9-13 comprise the analogous subject matter and also comprise additional features/steps which are the part of an expanded abstract idea of the independent claim 1 (additionally comprising mathematical relationship/mental process steps) and, therefore, the dependent claims are not eligible without additional elements that reflect a practical application and qualified for significantly more for substantially similar reason as discussed with regards to claim 1, 7 and 8.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-4, 7-10, 12, is/are rejected under 35 U.S.C. 102(a) (1)/(a) (2) as being anticipated by Park US 20170126027 A1.
Regarding claim 1, Park teaches an abnormality detection device comprising:
an energy storage device comprising a plurality of energy storage cells ([0060] A battery is, for example, a battery module or a battery cell. Thus, a plurality of batteries may represent a plurality of battery modules or battery cells. As respective batteries, each of the modules may include a single battery cell or a plurality of battery cells, in which case the plurality of battery cells may be connected to one another in series or parallel.);
From above paragraph examiner views the battery (i.e., energy storage device) includes multiple battery cells (i.e., energy storage cells).
a plurality of sensors coupled to the energy storage device and configured to measure voltage of the plurality of energy storage cells ([0061] Herein, the term physical quantities of a plurality of batteries refers to, for example, a voltage, a current, and/or a temperature, each representing a different physical quantity, of each battery, battery cell, and/or battery module, or any combination of the same.
a battery controller comprising (para [0138] Examples of hardware components include controllers,):
a processor configured to (para [0121] Fig. 10 a processor 1020):
create learning data from plural pieces of measurement data of the energy storage device (para [0064] Additionally, in one or more embodiments, one or more processing devices may be specially or particularly configured or controlled to implement one or more of the battery management methods discussed herein, as only examples, through reference to such one or more memories that record sensed or measured physical properties for one or more batteries, battery cells, or battery modules for a period of time, for example, as well as one or more feature extraction and/or feature distribution models, for example, that may have been pre-learned based on normal training data, for example.);
From above paragraphs examiner views the processing device creates a learning data from physical properties data (i.e., measurements data-voltage, current and temperature of battery)
such that the plural pieces of measurement data are grouped based on a configuration of the energy storage device (para [0084] Here, the battery management apparatus projects the unbalance data 310 to the feature space using a feature extraction model 320. [0085] The feature extraction model 320 is a model defined in advance, as discussed above. For example, normal physical quantities dynamically varying based on charging and/or discharging of a plurality of normal batteries);
Examiner views the unbalanced measurement data is grouped in 310 and the normal data is grouped in 320. The unbalanced and normal data is viewed as configuration or combination or arrangement of the energy storage device.
store a model learned using the created learning data ([0078] For example, the feature distribution model may learn an area or range of operation of the same normal battery used for the unbalance feature mode. [0124] In an embodiment, the memory 1030 stores the feature extraction model used to extract the feature data and the feature distribution model used to estimate the battery safety.).
Herein examiner views the model learned or created is stored in the memory (i.e., storage unit) to output a score corresponding to whether or not abnormal measurement data is included in the plural pieces of measurement data when the plural pieces of measurement data is input (Fig. 9. Para [0114] In operation 910, the battery management apparatus derives unbalance data using physical quantity difference information calculated based on first physical quantities of a plurality of batteries… [0118] In operation 940, the battery management apparatus determines a battery state based on the estimated similarity. The battery state is, for example, one of a normal state and an abnormal state… The battery management apparatus compares the probability data to a probability threshold. When the probability data fails to meet, e.g., is less than, the probability threshold, the battery management apparatus determines that the battery is in the abnormal state.)
Herein examiner views an abnormal state or data indication (i.e., output a score) of anomaly or abnormal data included in the battery physical quantity measurement data (i.e., plurality of pieces of measurement) is determined when the measurement data is input and compared to the probability threshold.
detect an abnormality or a sign of abnormality of the energy storage device based on a score output by inputting the plural pieces of measurement data to the model ([0084] Referring to FIG. 3, a battery management apparatus acquires or extracts feature data 330 by projecting unbalance data 310 to a feature space. Here, the battery management apparatus projects the unbalance data 310 to the feature space using a feature extraction model 320.
[0085] The feature extraction model 320 is a model defined in advance, as discussed above. For example, normal physical quantities dynamically varying based on charging and/or discharging of a plurality of normal batteries, for example, voltages, currents, and/or temperatures of the plurality of normal batteries,
Para [0086] As illustrated in FIG. 3, a dimension of the unbalance data may be d, a dimension of the feature extraction model 320 may be d×p, resulting in a dimension of the feature data 330 being p. The unbalance data 310 having a high dimension is thus converted into the feature data 330 having a low dimension. The battery management apparatus uses the feature data 330 to detect an abnormal state of the battery pack including the plurality of batteries.);
Above paragraphs and Fig. 3, examiner views the processor or battery management apparatus (i.e., detection unit) detects an abnormal state of the battery based on the output feature data 330 (i.e., see in Fig. 3 reduced dimension- score) by inputting the measurements data (i.e., voltage, current, temperature) to the model 320;
determine an electric power distribution using an electric power adjustment of the energy storage device based on the abnormality or the sign of the abnormality ([0081][0099], [0104], [0106] Thus, a dynamical change in voltage data would occur due to a change in a battery's internal resistance and a change in current based on required power. In response to the change in current, voltage data of the plurality of battery cells may similarly change.
para [0111] Further to the discussion of above with regard to operation 250 of FIG. 2, in operation 860, the battery management determines… cell balancing in operation 880. Also, when the battery safety is determined to not meet, e.g., is less than or equal to, the second threshold, the battery management apparatus generates a control signal to output a feedback in operation 890. Here, in one or more embodiments, when the battery safety is determined to not meet the second threshold the battery management apparatus may also perform the cell balancing.).
[0125] Accordingly, in one or more embodiments, the processor 1020 is configured to implement any one, combination, or all of the battery management methods described herein with reference to FIGS. 1 through 9.
From above paragraphs examiner views processor (i.e., a determination unit) that determines a battery management system (i.e., electric power distribution) using a control signal or cell balancing – change in voltage, current (i.e., electric power adjustment function) of the battery (i.e., energy storage device) based on the battery safety not meeting the thresholds (i.e., abnormality or the sign of abnormality).
wherein the creating the learning data comprises a statistical processing for each group of the plural pieces of measurement data ([0026] The unbalance data may include at least one of first difference information indicating respective first differences between an average value of the physical quantities
Para [0090] In response to a generation of a corresponding feature distribution model, a distribution and an average of the normal feature data may be calculated, and probability distribution information also calculated.
Par [0078] For example, the feature distribution model may learn an area or range of operation of the same normal battery used for the unbalance feature model.[0079] In one or more embodiments, the feature distribution model is trained through machine learning.).
Here examiner views creating learning data comprises averages, differences (i.e., statistical processing) for unbalanced and normal (i.e., each group) measurement data.
Regarding claim 2, Park teaches an abnormality detection device, Park teaches wherein the determining the electric power distribution using the electric power adjustment of the energy storage device is based on the abnormality or the sign of abnormality and plural pieces of measurement data (([0081][0099], [0104], [0106] Thus, a dynamical change in voltage data would occur due to a change in a battery's internal resistance and a change in current based on required power. In response to the change in current, voltage data of the plurality of battery cells may similarly change.
para [0111] Further to the discussion of above with regard to operation 250 of FIG. 2, in operation 860, the battery management determines… cell balancing in operation 880. Also, when the battery safety is determined to not meet, e.g., is less than or equal to, the second threshold, the battery management apparatus generates a control signal to output a feedback in operation 890. Here, in one or more embodiments, when the battery safety is determined to not meet the second threshold the battery management apparatus may also perform the cell balancing.).
[0125] Accordingly, in one or more embodiments, the processor 1020 is configured to implement any one, combination, or all of the battery management methods described herein with reference to FIGS. 1 through 9.
From above paragraphs examiner views processor (i.e., a determination unit) that determines a battery management system (i.e., electric power distribution) using a control signal or cell balancing – change in voltage, current (i.e., electric power adjustment function) of the battery (i.e., energy storage device) based on the battery safety not meeting the thresholds (i.e., abnormality or the sign of abnormality) obtained from the detection unit (i.e., detection of an abnormality of a battery using the measurement data, please see above in paragraph [0084]-[0086])
Regarding claim 3, Park teaches the abnormality detection device according to claim 2, Park teaches wherein the energy storage device includes a bank in which a plurality of modules including the plurality of energy storage cells are connected in series (Fig. 8 para [0128] The battery 1180 includes a plurality of battery modules 1181 through 1183. Para [0106] Similarly, a plurality of battery cells connected in series in one battery module have the same current value).
Examiner views battery 1180 as a bank which includes modules 1181-1183 with multiple cells connected in series.
determining the electric power distribution using the electric power adjustment of the energy storage device is based on the abnormality or the sign of abnormality and a state of the bank obtained from the plural pieces of measurement data ([0081] [0099], [0104], [0106] Thus, a dynamical change in voltage data would occur due to a change in a battery's internal resistance and a change in current based on required power. In response to the change in current, voltage data of the plurality of battery cells may similarly change.
para [0111] Further to the discussion of above with regard to operation 250 of FIG. 2, in operation 860, the battery management determines… cell balancing in operation 880. Also, when the battery safety is determined to not meet, e.g., is less than or equal to, the second threshold, the battery management apparatus generates a control signal to output a feedback in operation 890. Here, in one or more embodiments, when the battery safety is determined to not meet the second threshold the battery management apparatus may also perform the cell balancing.).
[0125] Accordingly, in one or more embodiments, the processor 1020 is configured to implement any one, combination, or all of the battery management methods described herein with reference to FIGS. 1 through 9.
From above paragraphs examiner views processor (i.e., a determination unit) that determines a battery management system (i.e., electric power distribution) using a control signal or cell balancing – change in voltage, current (i.e., electric power adjustment function) of the battery (i.e., energy storage device) based on the battery safety not meeting the thresholds (i.e., abnormality or the sign of abnormality) obtained from the detection unit (i.e., detection of an abnormality of a battery using the measurement data, please see above in paragraph [0084]-[0086]). Examiner views the measurement data from battery cells provide a state of a battery bank.
Regarding claim 4, Park teaches the abnormality detection device according to claim 2, Park teaches wherein in the energy storage device, a bank in which a plurality of modules including a plurality of energy storage cells are connected in series (see above claim 3) (Park does not clearly show a plurality of banks connected in parallel to form a domain).
However, examiner view a person skilled in the art would add or connect extra battery banks connected in a well-known (for example please see US 20130053909 A1 Fig. 1-6) parallel configuration (i.e., to form a domain) to increase a total capacity of a battery system and arrive at the present invention. and
determining the electric power distribution using the electric power adjustment of the energy storage device is based on the abnormality or the sign of abnormality and a state of bank obtained from the plural pieces of measurement data ([0081] [0099], [0104], [0106] Thus, a dynamical change in voltage data would occur due to a change in a battery's internal resistance and a change in current based on required power. In response to the change in current, voltage data of the plurality of battery cells may similarly change.
para [0111] Further to the discussion of above with regard to operation 250 of FIG. 2, in operation 860, the battery management determines… cell balancing in operation 880. Also, when the battery safety is determined to not meet, e.g., is less than or equal to, the second threshold, the battery management apparatus generates a control signal to output a feedback in operation 890. Here, in one or more embodiments, when the battery safety is determined to not meet the second threshold the battery management apparatus may also perform the cell balancing.).
[0125] Accordingly, in one or more embodiments, the processor 1020 is configured to implement any one, combination, or all of the battery management methods described herein with reference to FIGS. 1 through 9.
From above paragraphs examiner views processor (i.e., a determination unit) that determines a battery management system (i.e., electric power distribution) using a control signal or cell balancing – change in voltage, current (i.e., electric power adjustment function) of the battery (i.e., energy storage device) based on the battery safety not meeting the thresholds (i.e., abnormality or the sign of abnormality) obtained from the detection unit (i.e., detection of an abnormality of a battery using the measurement data, please see above in paragraph [0084]-[0086]). Examiner views the measurement data from battery cells provide a state of a battery bank.
Examiner views the parks technique or idea would be applicable to the battery system having plurality of battery banks, where each bank is connected in parallel configuration.
Regarding claim 9, Park teaches the abnormality detection device according to claim 1, wherein the statistical processing comprises calculating an average data ([0026] The unbalance data may include at least one of first difference information indicating respective first differences between an average value of the physical quantities. Para [0090] In response to a generation of a corresponding feature distribution model, a distribution and an average of the normal feature data may be calculated, and probability distribution information also calculated.
Here examiner views data comprises averages (i.e., statistical processing) for unbalanced and normal (i.e., each group) measurement data.
Claim 7, 8 are rejected as claim 1 having same claim limitation.
Claim 10 is rejected as claim 9 having same claim limitation.
Regarding claim 12, Park teaches the abnormality detection device according to claim 7, wherein the determining comprises determining to continue participation in the electric power distribution, taking type of the abnormality or the sign of abnormality into consideration (para [0098] The fourth graph 640 represents a battery risk over time. The battery risk is an absolute value of a battery safety and thus, the battery risk may be substantially the same or similar criterion as the battery safety. Depending on the case, the battery management apparatus may apply the battery risk to determine whether a battery is in an abnormal state in lieu of the battery safety. For example, the battery management apparatus estimates the battery risk based on distribution information of the feature data and compares the battery risk to a threshold. When the battery risk fails to meet, e.g., is less than, the threshold, feedback is provided to a user.).
From Fig. 6, 7 and above paragraph examiner views the feature data for battery charging and discharging (i.e., power distribution) is determined considering battery risk failure (i.e., the battery sign of abnormality).
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) 5, 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park in view of Shibuya (US 20150169393 A1)
Regarding claim 5, Park teaches the abnormality detection device according to claim 1, Park teaches detecting an abnormality or a sign of abnormality of the energy storage device in the detection target period based on a score output from the model ([0084] Referring to FIG. 3, a battery management apparatus acquires or extracts feature data 330 by projecting unbalance data 310 to a feature space. Here, the battery management apparatus projects the unbalance data 310 to the feature space using a feature extraction model 320.
[0085] The feature extraction model 320 is a model defined in advance, as discussed above. For example, normal physical quantities dynamically varying based on charging and/or discharging of a plurality of normal batteries, for example, voltages, currents, and/or temperatures of the plurality of normal batteries,
Para [0086] As illustrated in FIG. 3, a dimension of the unbalance data may be d, a dimension of the feature extraction model 320 may be d×p, resulting in a dimension of the feature data 330 being p. The unbalance data 310 having a high dimension is thus converted into the feature data 330 having a low dimension. The battery management apparatus uses the feature data 330 to detect an abnormal state of the battery pack including the plurality of batteries.);
Above paragraphs and Fig. 3, examiner views the processor or battery management apparatus (i.e., detection unit) detects an abnormal state of the battery based on the output feature data 330 (i.e., see in Fig. 3 reduced dimension- score) by inputting the measurement data (i.e., voltage, current, temperature) to the model 320.
Park does not clearly teach creating the learning data is created from the plural pieces of measurement data read for a read target period among the plural pieces of measurement data measured in time series and
inputting, to a model learned by the learning data, the plural pieces of measurement data in a detection target period that is a same period as the read target period.
Shibuya teaches creating the learning data is created from the plural pieces of measurement data read for a read target period among the plural pieces of measurement data measured in time series and (Fig. 2 and 3. para [0046] ... sensor signals 102 in the period designated by the sensor signal storing unit 103 as a learning period are inputted (S301).)
[0017] A system embodying this technique makes possible early detection of anomaly in …deterioration or aging of mounted batteries,
From above figures and paragraph examiner views the learning data is generated from the measurements data read from sensors for a read target period (i.e., in fig. 2 see day/hours), among measurements data are obtained in time series from equipment (i.e., battery). Examiner considers the creation be performed by a processor (i.e., creation unit).
inputting, to a model learned by the learning data, (claim 4… at the step of detecting anomaly, anomaly model is generated by using the learned data)),
Examiner considers the detection be performed by a processor (i.e., detection unit).
the plural pieces of measurement data in a detection target period that is a same period as the read target period ([0085] In an anomaly measurement display window 906, the processing number of the anomaly measurement, threshold and determination result in the designated learning period and testing period are displayed. Further, the periods used for learning are marked with circles above. In a sensor signal display window 907, the output level of a designated sensor in a designated period is displayed.),
From Fig. 9A and 9B examiner views the 906 as the abnormal measurement data in a detection target period (09/01 to 09/03) is a same period as the 907-sensor signal (i.e., read target) period 09/01 to 09/03.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Shibuya into Park for the purpose of creating learning data from measurements data in time series from a battery and determining an abnormality in a battery by using a model in the detection target period same as the read target period so that the battery failure can be accurately determined in real time and the battery system can be prevented from damages.
Claim 6 is rejected as claim 5 having same limitations.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park in view of Lee et al US 20210190878 A1 herein after “Lee”.
Regarding claim 11, Park teaches the abnormality detection device according to claim 7, Park does not clearly teach wherein the determining comprises determining to continue participation in the electric power distribution, taking expected life of the energy storage device into consideration.
Lee teaches wherein the determining comprises determining to continue participation in the electric power distribution, taking expected life of the energy storage device into consideration ([0145] Here, an initial expected life may be an expected life estimated from the battery in a BOL state. That is, the expected life of the battery B set as the initial expected life may be estimated and changed by the processor 130″ as the battery B is charged and discharged.).
From above paragraph examiner views the expected life of the battery is estimated and considered during charging and discharge of the power (i.e., participate in electric power distribution).
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Lee into Park for the purpose of participating in charging or discharging of electric power and estimating the expected life of battery, so that the accurate remaining life of the battery can be determined.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park in view of Gerlovin US 20130057198 A1
Regarding claim 13, Park teaches the abnormality detection device according to claim 7, Park does not clearly teach wherein the determining comprises determining to continue participation in the electric power distribution while suppressing charge-discharge amount of one energy storage device, for which the abnormality or the sign of abnormality has been detected, and causing another energy storage device to increase charge-discharge amount.
Gerlovin teaches wherein the determining comprises determining to continue participation in the electric power distribution while suppressing charge-discharge amount of one energy storage device, for which the abnormality or the sign of abnormality has been detected, and causing another energy storage device to increase charge-discharge amount (para [0049] A hierarchical balancing system as shown in FIGS. 8A-B may be configured to compensate for a fault condition in one of the 2-cell opto-isolated balancing circuits 920 A-F by conducting a module-to-module transfer as described in the following example. For example, in a battery pack comprised of modules as illustrated in FIG. 9B, where N=10, assume that within module 2 (FIG. 8B), the 2-Cell Balancing circuit 920A (FIG. 8A) is non-operational due to a damaged power transistor P1, P2 in one of its opto-isolated switches (FIG. 4). ... At the module level, specifically, module balancing circuit 930A operates to transfer energy from module 2 to adjacent module 3. When energy is transferred from module 2 to module 3, energy from all cells in module 2 (including the overcharged top most cell) is transferred to module 3. The amount of energy transferred to each cell in module 3 is dependent on the relative impedance of each of the cells).
From above paragraph examiner views the energy (charge discharge) from module 2 is suppressed due to damaged power transistor (i.e., abnormality is detected), the energy is increased or transferred to module 3 because of the detected damaged in module 2.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing of the invention to have incorporated Gerlovin into Park for the purpose of increasing or decreasing charging or discharging of electric power in battery modules when a fault is detected in a module so that a proper power balancing can be performed to insure safety in the electrical power system.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tajima et al US 20210224599 A1 discusses anomaly/abnormality detection in battery system.
Takahashi et al US 20200355749 A1 discusses abnormality detection in battery.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHARAD TIMILSINA whose telephone number is (571)272-7104. The examiner can normally be reached Monday-Friday 9:00-5:00.
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, Catherine Rastovski can be reached at 571-270-0349. 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.
/SHARAD TIMILSINA/Examiner, Art Unit 2857 /Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
Prosecution Insights