DETAILED ACTION
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
2. 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 (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
In view of the new 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register Vol. 84, No. 4, January 7, 2019), the Examiner has considered the claims and has determined that under step 1, claims 1-9 are to a process, claims 10-19 are to a machine, and claim 20 is to an article of manufacture. Next under the new step 2A prong 1 analysis, the claims are considered to determine if they recite an abstract idea (judicial exception) under the following groupings: (a) mathematical concepts, (b) certain methods of organizing human activity, or (c) mental processes. The independent claims contain at least the following bolded limitations (see representative independent claims) that fall into the grouping of mathematical concepts:
1. A method for monitoring a parameter of a battery pack, wherein the method comprises:
acquiring a first pre-estimated resistance value corresponding to the battery pack at a t-th cycle based on a preset state estimation equation and an internal resistance value of the battery pack at a (t−1)-th cycle,
wherein t represents the current number of cycles of the battery pack, the current number of cycles represents the number of charges and discharges cumulatively completed by the battery pack, and the preset state estimation equation represents a conversion relationship between the internal resistance value at the (t−1)-th cycle and the first pre-estimated resistance value, where t≥2;
determining a second pre-estimated resistance value corresponding to the t-th cycle based on a pre-configured mapping relationship, wherein the pre-configured mapping relationship represents a conversion relationship between t and the second pre-estimated resistance value; and
determining an internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value, wherein the preset state estimation equation is:
X
^
t
-
=
F
X
^
t
-
1
-
+
w
t
,
wherein
X
^
t
-
represents the first pre-estimated resistance value,
X
^
t
-
1
-
represents the internal resistance value at the (t−1)-th cycle, F represents a first preset coefficient matrix, and wt represents engineering noise;
determining the internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value comprises:
optimizing the second pre-estimated resistance value based on a preset optimization equation, so as to obtain a second optimized resistance value,
wherein the preset optimization equation represents a conversion relationship between the second pre-estimated resistance value and the second optimized resistance value; and
correcting the first pre-estimated resistance value and the second optimized resistance value based on a preset correction equation, so as to obtain the internal resistance value at the t-th cycle;
wherein the preset optimization equation is:
Zt=HXmeasurement value + ΔPt,
where Zt represents the second optimized resistance value, Xmeasurement value represents the second pre-estimated resistance value, H represents a second preset coefficient matrix, and ΔPt represents a measurement error;
wherein the preset correction equation is:
X
^
t
=
X
^
t
-
+
K
t
(
Z
t
-
H
X
^
t
-
)
,
where
K
t
=
P
t
-
1
P
t
-
1
+
Q
+
R
,
X
^
t
represents the internal resistance value at the t-th cycle,
X
^
t
-
represents the first pre-estimated resistance value, Zt represents the second optimized resistance value, H represents the second preset coefficient matrix, Kt represents a gain value at the t-th cycle, Pt-1 represents an error covariance correction value at the (t−1)-th cycle, and Q and R are covariance matrices of input and output measurement noises respectively.
10. An apparatus for monitoring a parameter of a battery pack, wherein the apparatus comprises a processor and a memory, wherein the memory is used to store one or more programs, and the one or more programs, when being executed by the processor, cause the processor to execute following operations:
acquiring a first pre-estimated resistance value corresponding to the battery pack at a t-th cycle based on a preset state estimation equation and an internal resistance value of the battery pack at a (t−1)-th cycle,
wherein t represents the current number of cycles of the battery pack, the current number of cycles represents the number of charges and discharges cumulatively completed by the battery pack, and the preset state estimation equation represents a conversion relationship between the internal resistance value at the (t−1)-th cycle and the first pre-estimated resistance value, where t≥2;
determining a second pre-estimated resistance value corresponding to the t-th cycle based on a pre-configured mapping relationship, wherein the pre-configured mapping relationship represents a conversion relationship between t and the second pre-estimated resistance value; and
determining an internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value, wherein the preset state estimation equation is:
X
^
t
-
=
F
X
^
t
-
1
-
+
w
t
,
wherein
X
^
t
-
represents the first pre-estimated resistance value,
X
^
t
-
1
-
represents the internal resistance value at the (t−1)-th cycle, F represents a first preset coefficient matrix, and wt represents engineering noise;
determining the internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value comprises:
optimizing the second pre-estimated resistance value based on a preset optimization equation, so as to obtain a second optimized resistance value, wherein the preset optimization equation represents a conversion relationship between the second pre-estimated resistance value and the second optimized resistance value; and
correcting the first pre-estimated resistance value and the second optimized resistance value based on a preset correction equation, so as to obtain the internal resistance value at the t-th cycle;
wherein the preset optimization equation is:
Zt=HXmeasurement value + ΔPt,
where Zt represents the second optimized resistance value, Xmeasurement value represents the second pre-estimated resistance value, H represents a second preset coefficient matrix, and ΔPt represents a measurement error;
wherein the preset correction equation is:
X
^
t
=
X
^
t
-
+
K
t
(
Z
t
-
H
X
^
t
-
)
,
where
K
t
=
P
t
-
1
P
t
-
1
+
Q
+
R
,
X
^
t
represents the internal resistance value at the t-th cycle,
X
^
t
-
represents the first pre-estimated resistance value, Zt represents the second optimized resistance value, H represents the second preset coefficient matrix, Kt represents a gain value at the t-th cycle, Pt-1 represents an error covariance correction value at the (t−1)-th cycle, and Q and R are covariance matrices of input and output measurement noises respectively.
20. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, following operations are executed:
acquiring a first pre-estimated resistance value corresponding to the battery pack at a t-th cycle based on a preset state estimation equation and an internal resistance value of the battery pack at a (t−1)-th cycle,
wherein t represents the current number of cycles of the battery pack, the current number of cycles represents the number of charges and discharges cumulatively completed by the battery pack, and the preset state estimation equation represents a conversion relationship between the internal resistance value at the (t−1)-th cycle and the first pre-estimated resistance value, where t≥2;
determining a second pre-estimated resistance value corresponding to the t-th cycle based on a pre-configured mapping relationship, wherein the pre-configured mapping relationship represents a conversion relationship between t and the second pre-estimated resistance value; and
determining an internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value, wherein the preset state estimation equation is:
X
^
t
-
=
F
X
^
t
-
1
-
+
w
t
,
wherein
X
^
t
-
represents the first pre-estimated resistance value,
X
^
t
-
1
-
represents the internal resistance value at the (t−1)-th cycle, F represents a first preset coefficient matrix, and wt represents engineering noise;
determining the internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value comprises:
optimizing the second pre-estimated resistance value based on a preset optimization equation, so as to obtain a second optimized resistance value, wherein the preset optimization equation represents a conversion relationship between the second pre-estimated resistance value and the second optimized resistance value; and
correcting the first pre-estimated resistance value and the second optimized resistance value based on a preset correction equation, so as to obtain the internal resistance value at the t-th cycle;
wherein the preset optimization equation is:
Zt=HXmeasurement value + ΔPt,
where Zt represents the second optimized resistance value, Xmeasurement value represents the second pre-estimated resistance value, H represents a second preset coefficient matrix, and ΔPt represents a measurement error;
wherein the preset correction equation is:
X
^
t
=
X
^
t
-
+
K
t
(
Z
t
-
H
X
^
t
-
)
,
where
K
t
=
P
t
-
1
P
t
-
1
+
Q
+
R
,
X
^
t
represents the internal resistance value at the t-th cycle,
X
^
t
-
represents the first pre-estimated resistance value, Zt represents the second optimized resistance value, H represents the second preset coefficient matrix, Kt represents a gain value at the t-th cycle, Pt-1 represents an error covariance correction value at the (t−1)-th cycle, and Q and R are covariance matrices of input and output measurement noises respectively.
The bolded limitations above amount to mathematical concepts because they describe various steps of a mathematical algorithm to calculate parameters of a first pre-estimated resistance value, second pre-estimated resistance value, internal resistance value, second optimized resistance value, corrected first pre-estimated resistance value and corrected second optimized resistance value. The bolded limitations also explicitly recite mathematical calculations with variable definitions and formulas of a preset state estimation equation, a preset optimization equation, and a preset correction equation. Some calculations are described with words, such as "determining an internal resistance value of the battery pack at the t-th cycle based on the first-pre-estimated resistance value and the second pre-estimated resistance value," but it is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula."(see MPEP 2106.04(a)(2) I.).
Next in step 2A prong 2, the independent claims are analyzed to determine whether there are additional elements or combination of elements that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception such that it is more than a drafting effort designed to monopolize the exception, in order to integrate the judicial exception into a practical application. These limitations have been identified and underlined above, and are not indicative of integration into a practical application because: (1) the recitations of "an apparatus comprising a processor and a memory, wherein the memory is used to store one or more programs, and the one or more programs, when being executed by the processor, cause the processor to execute following operations" and "a non-transitory computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, following operations are executed," amount to mere instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)).
Next in step 2B, the independent claims are considered to determine if they recite additional elements that amount to an inventive concept (“significantly more”) than the recited judicial exception.
The recitations of "an apparatus comprising a processor and a memory, wherein the memory is used to store one or more programs, and the one or more programs, when being executed by the processor, cause the processor to execute following operations" and "a non-transitory computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, following operations are executed," are limitations that do not add something significantly more because they amount to mere instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). The use of generic computer equipment is considered insignificant additional elements. As recited in the MPEP, 2106.07(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection (see Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94).
Dependent claims 2-9 and 11-19 contain additional limitations that fall under the abstract idea grouping of mathematical concepts, as they describe further calculation steps as part of the overall mathematical algorithm. Dependent claims 7 and 17 describe giving an alarm in response to determining that the short-circuit count is greater than a preset threshold a number of times, but the issuing of an alarm amounts to insignificant post-solution outputting activity of a calculation result, and does not provide an integration into a practical application or significantly more (see MPEP 2106.05(g)). The MPEP states that when “Whether the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output)”, the limitations can be mere data gathering or data output (MPEP 2106.05(g) Insignificant Extra- Solution Activity, in particular item (3)).
3. An invention is not rendered ineligible for patent simply because it involves an abstract concept. Applications of such concepts "to a new and useful end" remain eligible for patent protection (see Alice Corp., 134 S. Ct. at 2354 (quoting Benson, 409 U.S. at 67)). However, "a claim for a new abstract idea is still an abstract idea" (see Synopsys v. Mentor Graphics Corp. _F.3d_, 120 U.S.P.Q. 2d1473 (Fed. Cir. 2016)). There needs to be additional elements or combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception or render the claim as a whole to be significantly more than the exception itself in order to demonstrate “integration into a practical application” or an “inventive concept.” For instance, further physical applications using the calculated internal resistance value of the battery pack at the t-th cycle to drive a physical change in operation, transformation, or repair/maintenance of a technology or technical process could provide integration into a practical application to demonstrate an improvement to the technology or technical field. Otherwise, the claims amount to only the abstract mathematical calculation of a numerical data-based result, without any further integration into a practical application or significantly more.
Allowable Subject Matter
4. Claims 1-20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action.
5. The following is a statement of reasons for the indication of allowable subject matter: In regards to claim 1, the closest prior art, Huang et al. (US Pat. Pub. 2017/0370995, hereinafter "Huang") at least teaches a method for monitoring a parameter of a battery pack (Huang abstract teaches a method for monitoring a parameter such as a state of a charge of a battery pack), wherein the method comprises:
acquiring a first pre-estimated resistance value corresponding to the battery pack at a t-th cycle based on a preset state estimation equation and an internal resistance value of the battery pack at a (t−1)-th cycle (Huang paragraph [0014] teaches constantly updating an internal resistance of a battery model (preset state estimation equation) based on the change of the state of charge over time, and paragraph [0015] and [0024] teach where the internal resistance is updated based on the battery internal resistance of the previous (t-1)-th cycle).
6. However, claim 1 contains allowable subject matter because the closest prior art, Huang et al. (US Pat. Pub. 2017/0370995) fails to anticipate or render obvious a method for monitoring a parameter of a battery pack, wherein the method comprises: wherein t represents the current number of cycles of the battery pack, the current number of cycles represents the number of charges and discharges cumulatively completed by the battery pack, and the preset state estimation equation represents a conversion relationship between the internal resistance value at the (t−1)-th cycle and the first pre-estimated resistance value, where t≥2; determining a second pre-estimated resistance value corresponding to the t-th cycle based on a pre-configured mapping relationship, wherein the pre-configured mapping relationship represents a conversion relationship between t and the second pre-estimated resistance value; and determining an internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Similarly, claim 10 contains allowable subject matter because the closest prior art, Huang et al. (US Pat. Pub. 2017/0370995) fails to anticipate or render obvious an apparatus for monitoring a parameter of a battery pack, wherein thein the apparatus comprises a processor and a memory, wherein the memory is used to store one or more programs, and the one or more programs, when executed by the processor, cause the processor to execute following operations: wherein t represents the current number of cycles of the battery pack, the current number of cycles represents the number of charges and discharges cumulatively completed by the battery pack, and the preset state estimation equation represents a conversion relationship between the internal resistance value at the (t−1)-th cycle and the first pre-estimated resistance value, where t≥2; determining a second pre-estimated resistance value corresponding to the t-th cycle based on a pre-configured mapping relationship, wherein the pre-configured mapping relationship represents a conversion relationship between t and the second pre-estimated resistance value; and determining an internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Similarly, claim 20 contains allowable subject matter because the closest prior art, Huang et al. (US Pat. Pub. 2017/0370995) fails to anticipate or render obvious a non-transitory computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, following operations are executed: wherein t represents the current number of cycles of the battery pack, the current number of cycles represents the number of charges and discharges cumulatively completed by the battery pack, and the preset state estimation equation represents a conversion relationship between the internal resistance value at the (t−1)-th cycle and the first pre-estimated resistance value, where t≥2; determining a second pre-estimated resistance value corresponding to the t-th cycle based on a pre-configured mapping relationship, wherein the pre-configured mapping relationship represents a conversion relationship between t and the second pre-estimated resistance value; and determining an internal resistance value of the battery pack at the t-th cycle based on the first pre-estimated resistance value and the second pre-estimated resistance value, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Pertinent Art
7. Applicants are directed to consider additional pertinent prior art included on the Notice of References Cited (PTOL 892) attached herewith. The Examiner has pointed out particular references contained in the prior art of record within the body of this action for the convenience of the Applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply. Applicant, in preparing the response, should consider fully the entire reference as potentially teaching all or part of the claimed invention, as well as the context of the of the passage as taught by the prior art or disclosed by the Examiner. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
B. Kim (US Pat. Pub. 2011/0301891) discloses Method of Diagnosing Deterioration of Cell of Battery for Vehicle.
C. Zhong et al. (US Pat. Pub. 2017/0234934) discloses Power System and State of Charge Estimation.
D. Kawai et al. (Us Pat. Pub. 2019/0064276) discloses Battery State Estimating Device.
Conclusion
8. Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAUL D LEE whose telephone number is (571)270-1598. The examiner can normally be reached on M to F, 9:30 am to 6 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Arleen Vazquez can be reached at 571-272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PAUL D LEE/Primary Examiner, Art Unit 2857 1/8/2025