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 .
DETAILED ACTION
Status of Claims
Claims 1, and 6-12 are pending Claims.
Claims 1, and 6-12 are rejected under 35 USC § 101.
Remarks
Based on the changes introduced by amendment of (02/17/2026) the 103 Rejections of Claims 1 and 6-12 are withdrawn. The arguments addressed to the 101 rejection is not persuasive.
Arguments
1. The Applicant argues (Pages 14 and 15):
“Amended independent claim 1 does not merely "involve" a mental process or
mathematical relationships, formulas, or calculations in the abstract. As clarified by the USPTO's August 2025 Memorandum and M.P.E.P. § 2106.04(a)(2)(I), claims that merely involve an exception (such as a mathematical concept) but are directed to a practical application are eligible and do not require further eligibility analysis. The present claim is not directed to a mental process or a mathematical concept per se, but rather to a technological solution implemented in a specific computing environment, namely an information processing device configured to analyze real-world battery operation data and dynamically control the selection of battery-state estimation algorithms Furthermore, independent claim 1 requires automated analysis of high-volume, time-series battery operation data including measurement time, voltage, and current ("analyz[ing] operation data of a battery," wherein "the operation data is time series data including measurement time, voltage, and current,"), calculation of multiple interrelated feature metrics derived from normalized power values ("calculat[ing] feature information" including C-rates "obtained by normalizing, by a rated power value, power values calculated by multiplying the voltage and the current," and ("calculat[ing] a switching ratio obtained by dividing a number of switchings between charging and discharging by a number of pieces of the operation data,") and rule-based selection among multiple estimation algorithms based on threshold and range comparisons ("select[ing], in accordance with the feature information, an estimation method among a plurality of estimation methods.") These operations cannot be practically performed in the human mind or by a human using a pen and paper. Accordingly, Applicant respectfully submits that the claimed features of amended independent claim 1 cannot be considered to encompass "mental processes" as defined in M.P.E.P. § 2106.04(a)(2)(III).”
The Examiner disagree with the assertion above. The claims just comprising mathematical steps/concepts, (see highlighted steps indicated as Abstract idea below in claims 1, and 10-12), which is performed by the computer. Even these steps can’t be performed by the human mind, the still directed to an Abstract Idea, because are considered to be equivalent to mathematical steps and fundamental aspect of mathematics, e.g., mathematical steps.
The claims 1, and 10-12 do not direct to any practical application.
Claim 12 just defining field of use for calculation and do not tied to any particular device.
The claim 12 is recite the “battery” which is just insignificant additional element.
The claims 1, 10, 11 and 12 do not comprise any significant elements/steps.
2. The Applicant argues (Page 16):
“According to M.P.E.P. § 2106.04(d)(I), a claim may integrate a judicial exception
into a practical application when it, for example, improves the functioning of a computer or another technology or technical field, or applies the exception in a meaningful way beyond merely linking it to a technological environment.”
The Claims 1 and 12 comprises the “a processor; and “a non-transitory computer-readable medium including programmed instructions”, as recited in claim 11 and “processing device” as recited in claim 10, is the parts of computer and software running on the computer. The computer is the general computer, which is not significantly more.
In the Claims 1, 10-12 of the current Application, were a computer/part of computer or software merely used as a tool to perform an existing process.
3. The Applicant argues (Page 19, lines 15-19; Page 20, lines 12-20 ):
“Therefore, when considered as a whole, independent claim 1 recites particular manner of improving the technology of battery state estimation and monitoring, rather than merely involving mathematical concepts or generic mental processes.”…“As explained above, amended independent claim 1 recites specific technical improvements that go beyond merely implementing an abstract idea on generic computer components. Specifically, the claimed invention provides a novel information processing system that that automatically selects, based on analyzed battery operation data, an estimation method most suitable for the actual charging and discharging behavior of a battery, rather than relying on pre-designated usage information, by calculating feature information from time-series voltage and current data and applying rule-based selection criteria.”
In order to amount to significantly more than the abstract idea, the claim must have additional elements which make the claim, taken as a whole, significantly more than the abstract idea. For claim 1, and 10-12 for instance, does not comprising any significant steps or additional elements. Claims 12 just comprising the battery and processor. The battery just well-known and general battery in the related technology.
The claim does not perform any physical measurement by battery, what is being measured, how it is measured, and when it is measured.
The present claims do not recite an improvement in a particular computer system, or in computer components, or functioning of a computer or in any computer-related technology.
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, and 6-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more as addressed below.
The new 2019 Revised Patent Subject Matter Eligibility Guidance published in the Federal Register (Vol. 84 No. 4, Jan 7, 2019 pp 50-57) has been applied and the claims are deemed as being patent ineligible.
The current 35 USC 101 analysis is based on the current guidance (Federal Register vol. 79, No. 241. pp. 74618-74633). The analysis follows several steps. Step 1 determines whether the claim belongs to a valid statutory class. Step 2A prong 1 identifies whether an abstract idea is claimed. Step 2A prong 2 determines whether an abstract idea is integrated into a practical application. If the abstract idea is integrated into a practical application the claim is patent eligible under 35 USC 101. Last, step 2B determines whether the claims contain something significantly more than the abstract idea. In most cases the existence of a practical application predicates the existence of an additional element that is significantly more.
Under the Step 1 of the eligibility analysis, we determine whether the claims are to a
statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C.
101: Process, machine, manufacture, or composition of matter. The below claim is considered to be in a statutory category (process).
Under Step 1 of the analysis, claims 1, and 10-12 does belong to a statutory category, namely it is a process claim.
Under Step 2A Prong 1, the independent claims 1 and 10-12 includes abstract ideas as highlighted (using a bold font) below.
“1. An information processing device comprising one or more processors configured to:
analyze operation data of a battery and calculate feature information indicating a feature of charging/discharging by the battery;
select, in accordance with the feature information, an estimation method among a plurality of estimation methods for estimating a state of the battery from the operation data; and
estimate the state from the operation data using the selected estimation method,
wherein
the operation data is time series data including measurement time, voltage, and
current,
the feature information includes: a mean ratio that is a ratio of a charging C-rate mean value that is a mean of C-rates during charging to a discharging C-rate mean value that is a mean of the C-rates during discharging, the C-rates being obtained by normalizing, by a rated power value, power values calculated by multiplying the voltage and the current; a data number ratio that is a ratio of a charging data number as a number of pieces of data of the C-rates during charging to a discharging data number as a number of pieces of data of the C-rates during discharging; and a switching ratio obtained by dividing a number of switchings between charging and discharging by a number of pieces of the operation data,
the plurality of estimation methods include a first estimation method that
estimates the state using magnitude of fluctuation in the voltage, a second estimation method that estimates the state using a difference between a mean value of the voltage during charging and a mean value of the voltage during discharging, and a third estimation method that estimates the state using a mean value of fluctuation in the voltage, and
the one or more processors are configured to:
select the first estimation method, when the switching ratio is greater than
a first threshold,
select the second estimation method, when the switching ratio is equal to or less than the first threshold, the data number ratio is outside a first specified range, and the mean ratio is outside a second specified range, and
select the third estimation method, when the switching ratio is equal to or
less than the first threshold, and the data number ratio is outside a within the first
specified range or the mean ratio is outside a within the second specified range.”.
“10. An information processing method executed by an information processing device, the information processing method comprising:
analyzing operation data of a battery and calculating feature information indicating a feature of charging/discharging by the battery;
selecting, in accordance with the feature information, an estimation method among a plurality of estimation methods for estimating a state of the battery from the operation data; and
estimating the state from the operation data using the selected estimation method, wherein
the operation data is time series data including measurement time, voltage, and
current,
the feature information includes: a mean ratio that is a ratio of a charging C-rate mean value that is a mean of C-rates during charging to a discharging C-rate mean value that is a mean of the C-rates during discharging, the C-rates being obtained by normalizing, by a rated power value, power values calculated by multiplying the voltage and the current; a data number ratio that is a ratio of a charging data number as a number of pieces of data of the C-rates during charging to a discharging data number as a number of pieces of data of the C-rates during discharging; and a switching ratio obtained by dividing a number of switchings between charging and discharging by a number of pieces of the operation data,
the plurality of estimation methods include a first estimation method that
estimates the state using magnitude of fluctuation in the voltage, a second estimation method that estimates the state using a difference between a mean value of the voltage during charging and a mean value of the voltage during discharging, and a third estimation method that estimates the state using a mean value of fluctuation in the voltage, and
the selecting includes:
selecting the first estimation method, when the switching ratio is greater
than a first threshold,
selecting the second estimation method, when the switching ratio is equal to or less than the first threshold, the data number ratio is outside a first specified range, and the mean ratio is outside a second specified range, and selecting the third estimation method, when the switching ratio is equal to or less than the first threshold, and the data number ratio is outside a within the first specified range or the mean ratio is outside a within the second specified range.”
“11. A computer program product comprising a non-transitory computer-readable medium including programmed instructions, the instructions causing a computer to execute:
analyzing operation data of a battery and calculating feature information indicating a feature of charging/discharging by the battery;
selecting, in accordance with the feature information, an estimation method among a plurality of estimation methods for estimating a state of the battery from the operation data; and
estimating the state from the operation data using the selected estimation method, wherein
the operation data is time series data including measurement time, voltage, and
current,
the feature information includes: a mean ratio that is a ratio of a charging C-rate mean value that is a mean of C-rates during charging to a discharging C-rate mean value that is a mean of the C-rates during discharging, the C-rates being obtained by normalizing, by a rated power value, power values calculated by multiplying the voltage and the current; a data number ratio that is a ratio of a charging data number as a number of pieces of data of the C-rates during charging to a discharging data number as a number of pieces of data of the C-rates during discharging; and a switching ratio obtained by dividing a number of switchings between charging and discharging by a number of pieces of the operation data,
the plurality of estimation methods include a first estimation method that
estimates the state using magnitude of fluctuation in the voltage, a second estimation method that estimates the state using a difference between a mean value of the voltage during charging and a mean value of the voltage during discharging, and a third estimation method that estimates the state using a mean value of fluctuation in the voltage, and
the selecting includes:
selecting the first estimation method, when the switching ratio is greater
than a first threshold,
selecting the second estimation method, when the switching ratio is equal to or less than the first threshold, the data number ratio is outside a first specified range, and the mean ratio is outside a second specified range, and selecting the third estimation method, when the switching ratio is equal to or less than the first threshold, and the data number ratio is outside a within the first specified range or the mean ratio is outside a within the second specified range”.
“12. An information processing system comprising:
a battery; and
one or more processors configured to:
analyze operation data of the battery and calculate feature information indicating a feature of charging/discharging by the battery;
select, in accordance with the feature information, an estimation method among a plurality of estimation methods for estimating a state of the battery from the operation data; and
estimate the state from the operation data using the selected estimation method, wherein
the operation data is time series data including measurement time, voltage, and
current,
the feature information includes: a mean ratio that is a ratio of a charging C-rate mean value that is a mean of C-rates during charging to a discharging C-rate mean value that is a mean of the C-rates during discharging, the C-rates being obtained by normalizing, by a rated power value, power values calculated by multiplying the voltage and the current; a data number ratio that is a ratio of a charging data number as a number of pieces of data of the C-rates during charging to a discharging data number as a number of pieces of data of the C-rates during discharging; and a switching ratio obtained by dividing a number of switchings between charging and discharging by a number of pieces of the operation data,
the plurality of estimation methods include a first estimation method that
estimates the state using magnitude of fluctuation in the voltage, a second estimation method that estimates the state using a difference between a mean value of the voltage during charging and a mean value of the voltage during discharging, and a third estimation method that estimates the state using a mean value of fluctuation in the voltage, and
the one or more processors are configured to:
select the first estimation method, when the switching ratio is greater than
a first threshold,
select the second estimation method, when the switching ratio is equal to or less than the first threshold, the data number ratio is outside a first specified range, and the mean ratio is outside a second specified range, and
select the third estimation method, when the switching ratio is equal to or
less than the first threshold, and the data number ratio is outside a within the first
specified range or the mean ratio is outside a within the second specified range.”.
The highlighted steps indicated as Abstract idea are considered to be equivalent to mathematical steps and fundamental aspect of mathematics or directed to mental processes performed in the human mind (including observation, evaluation and opinion).
Under step 2A prong 2,
The claims 1, and 10-12 do not comprises any particular field of use and claims do not direct to any practical application.
Claim 12 does not direct to any practical application, the claim 12 just defining field of use for calculation and do not tied to any particular device.
The claim 12 is recite the “battery” which is just insignificant additional element.
The claims 1, 10, 11 and 12 do not comprise any significant elements/steps.
Under step 2B
The Claim 1 does not comprise any additional steps/elements.
The claim 12 is recite the “battery”, which is just insignificant additional element.
Regarding Claims 1, 11 and 12 comprises the ”A computer program product comprising a non-transitory computer-readable medium including programmed instructions” and “processor” these are merely a general computer and generic pieces of the computer and software running on the computer. The general computer and software running on the computer do not make the claims significantly more than the abstract idea. All of these additional elements are generic computer and generic components of the computer, which are in light of Alice, as not being significantly more.
The depended claims 6, and 9 are merely extend the details of the abstract idea of mathematical concepts, more particularly mathematical calculations or mental steps as accrued.
Claims 7 and 8 recited the output notification information, which is consider as an insignificant extra solution activity.
Claim 8 just additionally describes the type of outputting data.
Therefore claims 6-9 are similarly rejected under 35 U.S.C. 101.
Examiner note regarding the prior art of the record:
Regarding Claims 1, 10, 11 and 12, Woll (US Pub.20220170993A1), disclose an information processing device/[system ]/[method executed by an information processing device](controller of an electrical energy store as disclosed in para [0042], caring out method steps from fig. 1, claim 21) comprising one or more processors configured to/[A computer program product comprising a non-transitory computer-readable medium including programmed instructions, the instructions causing a computer to execute]:
analyze operation data of a battery (detect operating state of electrical energy store 101 in Fig. 1) and calculate feature information indicating a feature of charging/discharging by the battery(see claim 18, where (ii) a charging or discharging of the electrical energy store at an associated charge rate or discharge rate);
select, in accordance with the feature information, an estimation method among a plurality of estimation methods for estimating a state of the battery from the operation data (para [0031]-[0038], where a selection through machine learning of the method among various methods and /or models resulting in the greatest accuracy of the state of health, first method between 103 and 111 and second method between 106 and 111 in Fig. 1); and
estimate the state from the operation data using the selected estimation method(para [0031]-[0038], Fig. 1, # 111, evaluated the values for the state of health).
Shimawaki et al., (US Pub.20230213585A1 discloses:
wherein the operation data is time series data including measurement time, voltage, and current (Fig. 2, para [0073], where measurement data include, for example, a current, a voltage and temperature…the actual result data indicate measurement data such as current, voltage, and temperature at a certain number of charge and discharge times, and transition of SOH at the subsequent numbers of charge and discharge times), and
the one or more processors are configured to calculate (para [0094], Fig. 4 is a diagram illustrating an example of a hardware configuration of the model generation apparatus 10. The model generation apparatus 10 includes a bus 1010, a processor 1020, a memory 1030, a storage device 1040; para [0096], where processor 1020 is a processor achieved by a Central Processing Unit (CPU), a Graphics Processing Unit (GPU)), as the feature information, part of or all of:
a ratio that is a ratio of a charging C-rate value that is a of C-rates during charging to a discharging C-rate value that is a of the C-rates during discharging, the C-rates being obtained by normalizing,[values] (See Fig, 10, where number of charge and discharge times (voltage, current and temperature corresponds to the values in the table), output is β the sum of charges and discharges;
That is considered similar to the number of switches because a switch is defined as change of current sign between a charge and a discharge, e.g., how quickly the a battery charges or discharges relative to its total capacity switching from charge to discharge or vice versa).
a data number ratio that is a ratio of a charging data number as a number of pieces of data of the C-rates during charging to a discharging data number as a number of pieces of data of the C-rates during discharging (Fig. 10, number of charge and discharge times (voltage, current and temperature), e.g., each data in table represent the number of pieces of data and data number ratio represent the each measured values of current voltage and temperature).
Shimawaki in the combined system applied above in order to more simply processing information for the analyzing operation data of the battery system.
Makam et.al., (US Pat. 11112462B2) discloses mean of C-rates during charging to a discharging (Fig. 7, where Average C-Rate(1/HR).;
a switching ratio obtained by dividing a number of switching’s between charging and discharging by a number of pieces of the operation data (Fig. 7, where Average SOC is (X2+X3)/2, Col. 6 , lines 35-60, where the number of charge-discharge full cycles, and in an aspect half cycles, that the battery experiences during each use period at each discrete combination of average SOC… average SOC for each charge-discharge full cycle and the DOD for each charge-discharge full cycle are calculated as follows: SOC is (X1+X2)/2, where X.sub.1 is the SOC at the beginning of the charge-discharge full cycle, X.sub.2 is the SOC at the end of the first charge-discharge half cycle of charge-discharge full cycle, e.g., switching ration corresponds for one charge-discharge cycle).
Hooshmand (US Pub. 20200011932) disclose normalizing, by a rated power value, power values calculated by multiplying the voltage and the current (para [0050], where Charge and discharge rates are calculated based on their normalized rates for each charge and discharge event respectively, neglecting the idle periods. The average charge and discharge rates for the weekly profile will be the arithmetic average of calculated rates:
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).
Hu et.al., (US Pat. 9255971B2) disclose the plurality of estimation methods include a second estimation method that estimates the state using a difference between a mean value of the voltage (Fig. 4, where voltage difference ratio).
Bae (US Pub.2021318388A1) discloses estimates the state using a value of fluctuation in the voltage(see Fig. 12).
The prior art of record does not teach or fairly suggest a device having the steps of:
“calculate the feature information including the mean ratio, the data number ratio, and the switching ratio; and
select the second estimation method, when the switching ratio is equal to or less than a first threshold, the data number ratio is outside a first specified range, and the mean ratio is outside a second specified range select the third estimation method, when the switching ratio is equal to or less than a first threshold, and
the data number ratio is outside a first specified range or the mean ratio is outside a second specified range”.
Claims 6-9 are not rejected under 102/103 Rejection as being dependent from an base claim 1.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
1. Mikhaylik et al., (US Pub. 20220271537A1).
2. Otani (JP2016048617-A ).
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.
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/KALERIA KNOX/
Examiner, Art Unit 2857
/MICHAEL J DALBO/Primary Examiner, Art Unit 2857