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 .
Claims
Claims 1-11 filed on 01/10/2025 are fully considered. Of the above claims, claims 4-8 and 10 have been amended through a preliminary amendment filed on 01/10/2025.
Claim Objections
Claim 4 is objected to because of the following informalities:
Regarding claim 4, the examiner believes that the recitation of “a plurality of the correspondence relationships” in line 3 should also recite including the correspondence relationship recited previously.
Further regarding claim 4, the recitation of “a correspondence relationship” in line 5 refers to a previously recited limitation.
Appropriate correction is required.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-6 and 8-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kawahara et al. (US 2025/0180656 A1) in view of Yagi et al. (US 2022/0381845 A1).
Regarding claim 1, Kawahara et al. teach an estimation device (battery characteristic estimating device 100; FIG. 2), comprising:
an acquisition portion that acquires time-series data of a current and a voltage of an energy storage device (the acquisition unit 110 acquires time series data of a current value, a voltage value, a temperature, and the like of the battery 40 from the communication device 50 using a communication interface; [0042]; Figs 1-2);
a calculation portion that calculates time-series data of an amount of electricity or an SOC, based on the time-series data of the current acquired by the acquisition portion (in addition, the acquisition unit 110 calculates a discharge capacity by accumulating current values included in the acquired time series data and stores the discharge capacity in the storage unit 140 as time series data 142; [0042]; Figs 1-2);
a generation portion that generates a partial charge/discharge profile of the energy storage device, based on the time-series data of the current acquired by acquisition portion and the time-series data of the amount of electricity or the SOC calculated by the calculation portion (the OCV curve estimating unit 130 converts a reference positive-electrode OCP curve 148 into a positive-electrode OCP curve 148 representing a change of an open circuit electric potential with respect to a discharge capacity of the positive electrode in accordance with a first parameter group; [0046]; Figs 1-2); and
an estimation portion that estimates an overall discharge characteristic of the energy storage device, based on a parameter of the energy storage device (the positive-electrode scaling factor a and the positive-electrode shift amount b represent one example of “first parameter group”; [0050]; the negative-electrode scaling factor c and the negative-electrode shift amount d represent one example of “second parameter group”; [0053]; diagram illustrating one example of an OCV curve 152 derived on the basis of the positive-electrode OCP curve 148 and the negative-electrode OCP curve 150; [0055]; Figs 4-6).
Further regarding claim 1, Kawahara et al. do not teach the parameter representing an internal state amount of the energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in the overall discharge characteristic of the energy storage device approaches the partial charge/discharge profile.
Further regarding claim 1, Yagi et al. teach a parameter representing an internal state amount of an energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in an overall discharge characteristic of the energy storage device approaches a partial charge/discharge profile (based on the verification described above, to appropriately estimate the internal states of the battery cell formed of the active material similar to that in the test element A, it is necessary to estimate the aforementioned correction coefficient DCa for at least the negative electrode; [0101]; Figs 2-5, 8) for the purpose of appropriately estimating the internal states of the battery cell.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to incorporate the parameter representing an internal state amount of the energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in the overall discharge characteristic of the energy storage device approaches the partial charge/discharge profile, as taught by Yagi et al., into Kawahara et al. for the purpose of appropriately estimating the internal states of the battery cell.
Regarding claim 2, Kawahara et al. teach an adjustment portion that adjusts the parameter, based on a correspondence relationship between a capacity of the energy storage device and the parameter (the reference positive-electrode OCP curve 148 and the reference negative-electrode OCP cure 150 may be standardized to an arbitrary value as long as there is a mathematical model functioning as a reference for optimizing the first parameter group and the second parameter group; [0054]; Figs 3-6; the OCV curve estimating unit 130 performing the optimization, that is, adjustment of the parameters).
Regarding claim 3, Kawahara et al. do not teach wherein the adjustment portion adjusts the parameter in such a way that a profile of a predetermined section in the overall discharge characteristic related to a capacity associated with the parameter approaches the partial charge/discharge profile.
Further regarding claim 3, Yagi et al. teach an adjustment portion adjusts the parameter in such a way that a profile of a predetermined section in the overall discharge characteristic related to a capacity associated with the parameter approaches the partial charge/discharge profile (based on the verification described above, to appropriately estimate the internal states of the battery cell formed of the active material similar to that in the test element A, it is necessary to estimate the aforementioned correction coefficient DCa for at least the negative electrode; [0101]; Figs 2-5, 8) for the purpose of appropriately estimating the internal states of the battery cell.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to incorporate wherein the adjustment portion adjusts the parameter in such a way that a profile of a predetermined section in the overall discharge characteristic related to a capacity associated with the parameter approaches the partial charge/discharge profile, as taught by Yagi et al., into Kawahara et al. for the purpose of appropriately estimating the internal states of the battery cell.
Regarding claim 4, Kawahara et al. teach wherein
a plurality of the correspondence relationships are set in accordance with a state of the energy storage device (each of G1 and G2 represents a set of estimation data 144 relating to a plurality of times of traveling of the vehicle 10; [0056]; FIG. 7; the OCV curve estimating unit 130 optimizes the first parameter group and the second parameter group such that a value of an error function representing error between the estimated OCV curve 152 and the integrated data 146 is a predetermined value or less; [0058]; FIG. 8), and
the adjustment portion selects a correspondence relationship to be used for specifying the parameter in accordance with the state of the energy storage device (a mathematical model fca(x), Fca(X), fan(x), Fan(X); [0049]-[0054]).
Regarding claim 5, Kawahara et al. teach wherein the adjustment portion generates the correspondence relationship, based on the partial charge/discharge profile (each of G1 and G2 represents a set of estimation data 144 relating to a plurality of times of traveling of the vehicle 10; [0056]; FIG. 7; the OCV curve estimating unit 130 optimizes the first parameter group and the second parameter group such that a value of an error function representing error between the estimated OCV curve 152 and the integrated data 146 is a predetermined value or less; [0058]; FIG. 8).
Regarding claim 6, Kawahara et al. teach wherein the estimation portion estimates the overall discharge characteristic of the energy storage device, based on the parameter, and a positive electrode monopolar characteristic and a negative electrode monopolar characteristic of the energy storage device (the positive-electrode scaling factor a and the positive-electrode shift amount b represent one example of “fist parameter group”; [0050]; the negative-electrode scaling factor c and the negative-electrode shift amount d represent one example of “second parameter group”; [0053]; diagram illustrating one example of an OCV curve 152 derived on the basis of the positive-electrode OCP curve 148 and the negative-electrode OCP curve 150; [0055]; Figs 4-6).
Regarding claim 8, Kawahara et al. teach a diagnostic device comprising: a processing unit that diagnoses a capacity of an energy storage device, based on the overall discharge characteristic estimated by the estimation device (the communication device 50 receives information representing characteristics of the battery 40 that have been diagnosed and transmitted by the battery; [0040]; step S106, is error within predetermined value; FIG. 9).
Regarding claim 9, Kawahara et al. teach an estimation method causing a computer to execute processes (method of operating the battery characteristic estimating device 100; FIG. 2; the acquisition unit 110, the data filtering unit 120, and the OCV curve estimating unit 130, for example, are realized by a hardware processor such as central processing unit executing a program; [0041]; process performed by the battery characteristic estimating device 100; Figs 9-10) of:
acquiring time-series data of a current and a voltage of an energy storage device (the acquisition unit 110 acquires time series data of a current value, a voltage value, a temperature, and the like of the battery 40 from the communication device 50 using a communication interface; [0042]; Figs 1-2);
calculating time-series data of an amount of electricity or an SOC, based on the acquired time-series data of the current (in addition, the acquisition unit 110 calculates a discharge capacity by accumulating current values included in the acquired time series data and stores the discharge capacity in the storage unit 140 as time series data 142; [0042]; Figs 1-2);
generating a partial charge/discharge profile of the energy storage device, based on the acquired time-series data of the current and the calculated time-series data of the amount of electricity or the SOC (the OCV curve estimating unit 130 converts a reference positive-electrode OCP curve 148 into a positive-electrode OCP curve 148 representing a change of an open circuit electric potential with respect to a discharge capacity of the positive electrode in accordance with a first parameter group; [0046]; Figs 1-2); and
estimating an overall discharge characteristic of the energy storage device, based on a parameter of the energy storage device (the positive-electrode scaling factor a and the positive-electrode shift amount b represent one example of “fist parameter group”; [0050]; the negative-electrode scaling factor c and the negative-electrode shift amount d represent one example of “second parameter group”; [0053]; diagram illustrating one example of an OCV curve 152 derived on the basis of the positive-electrode OCP curve 148 and the negative-electrode OCP curve 150; [0055]; Figs 4-6).
Further regarding claim 9, Kawahara et al. do not teach the parameter representing an internal state amount of the energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in the overall discharge characteristic of the energy storage device approaches the partial charge/discharge profile.
Further regarding claim 9, Yagi et al. teach a parameter representing an internal state amount of an energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in an overall discharge characteristic of the energy storage device approaches a partial charge/discharge profile (based on the verification described above, to appropriately estimate the internal states of the battery cell formed of the active material similar to that in the test element A, it is necessary to estimate the aforementioned correction coefficient DCa for at least the negative electrode; [0101]; Figs 2-5, 8) for the purpose of appropriately estimating the internal states of the battery cell.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to incorporate the parameter representing an internal state amount of the energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in the overall discharge characteristic of the energy storage device approaches the partial charge/discharge profile, as taught by Yagi et al., into Kawahara et al. for the purpose of appropriately estimating the internal states of the battery cell.
Regarding claim 10, Kawahara et al. teach a non-transitory computer medium having therein an estimation program for causing a computer to execute processes (method of operating the battery characteristic estimating device 100; FIG. 2; the acquisition unit 110, the data filtering unit 120, and the OCV curve estimating unit 130, for example, are realized by a hardware processor such as central processing unit executing a program; a program may be stored in advance in a storage device; [0041]; process performed by the battery characteristic estimating device 100; Figs 9-10) of:
acquiring time-series data of a current and a voltage of an energy storage device (the acquisition unit 110 acquires time series data of a current value, a voltage value, a temperature, and the like of the battery 40 from the communication device 50 using a communication interface; [0042]; Figs 1-2);
calculating time-series data of an amount of electricity or an SOC, based on the acquired time-series data of the current (in addition, the acquisition unit 110 calculates a discharge capacity by accumulating current values included in the acquired time series data and stores the discharge capacity in the storage unit 140 as time series data 142; [0042]; Figs 1-2);
generating a partial charge/discharge profile of the energy storage device, based on the acquired time-series data of the current and the calculated time-series data of the amount of electricity or the SOC (the OCV curve estimating unit 130 converts a reference positive-electrode OCP curve 148 into a positive-electrode OCP curve 148 representing a change of an open circuit electric potential with respect to a discharge capacity of the positive electrode in accordance with a first parameter group; [0046]; Figs 1-2); and
estimating an overall discharge characteristic of the energy storage device, based on a parameter of the energy storage device (the positive-electrode scaling factor a and the positive-electrode shift amount b represent one example of “fist parameter group”; [0050]; the negative-electrode scaling factor c and the negative-electrode shift amount d represent one example of “second parameter group”; [0053]; diagram illustrating one example of an OCV curve 152 derived on the basis of the positive-electrode OCP curve 148 and the negative-electrode OCP curve 150; [0055]; Figs 4-6).
Further regarding claim 10, Kawahara et al. do not teach the parameter representing an internal state amount of the energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in the overall discharge characteristic of the energy storage device approaches the partial charge/discharge profile.
Further regarding claim 10, Yagi et al. teach a parameter representing an internal state amount of an energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in an overall discharge characteristic of the energy storage device approaches a partial charge/discharge profile (based on the verification described above, to appropriately estimate the internal states of the battery cell formed of the active material similar to that in the test element A, it is necessary to estimate the aforementioned correction coefficient DCa for at least the negative electrode; [0101]; Figs 2-5, 8) for the purpose of appropriately estimating the internal states of the battery cell.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to incorporate the parameter representing an internal state amount of the energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in the overall discharge characteristic of the energy storage device approaches the partial charge/discharge profile, as taught by Yagi et al., into Kawahara et al. for the purpose of appropriately estimating the internal states of the battery cell.
Regarding claim 11, Kawahara et al. teach a diagnostic method causing a computer to execute processes (method of operating the battery characteristic estimating device 100; FIG. 2; the communication device 50 receives information representing characteristics of the battery 40 that have been diagnosed and transmitted by the battery; [0040]; the acquisition unit 110, the data filtering unit 120, and the OCV curve estimating unit 130, for example, are realized by a hardware processor such as central processing unit executing a program; [0041]; process performed by the battery characteristic estimating device 100; step S106, is error within predetermined value; FIG. 9-10) of:
acquiring time-series data of a current and a voltage of an energy storage device (the acquisition unit 110 acquires time series data of a current value, a voltage value, a temperature, and the like of the battery 40 from the communication device 50 using a communication interface; [0042]; Figs 1-2);
calculating time-series data of an amount of electricity or an SOC, based on the acquired time-series data of the current (in addition, the acquisition unit 110 calculates a discharge capacity by accumulating current values included in the acquired time series data and stores the discharge capacity in the storage unit 140 as time series data 142; [0042]; Figs 1-2);
generating a partial charge/discharge profile of the energy storage device, based on the acquired time-series data of the current and the calculated time-series data of the amount of electricity or the SOC (the OCV curve estimating unit 130 converts a reference positive-electrode OCP curve 148 into a positive-electrode OCP curve 148 representing a change of an open circuit electric potential with respect to a discharge capacity of the positive electrode in accordance with a first parameter group; [0046]; Figs 1-2);
estimating an overall discharge characteristic of the energy storage device, based on a parameter of the energy storage device (the positive-electrode scaling factor a and the positive-electrode shift amount b represent one example of “fist parameter group”; [0050]; the negative-electrode scaling factor c and the negative-electrode shift amount d represent one example of “second parameter group”; [0053]; diagram illustrating one example of an OCV curve 152 derived on the basis of the positive-electrode OCP curve 148 and the negative-electrode OCP curve 150; [0055]; Figs 4-6); and
diagnosing a capacity of the energy storage device, based on the estimated overall discharge characteristic (the communication device 50 receives information representing characteristics of the battery 40 that have been diagnosed and transmitted by the battery; [0040]; step S106, is error within predetermined value; FIG. 9-10).
Further regarding claim 11, Kawahara et al. do not teach the parameter representing an internal state amount of the energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in the overall discharge characteristic of the energy storage device approaches the partial charge/discharge profile.
Further regarding claim 11, Yagi et al. teach a parameter representing an internal state amount of an energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in an overall discharge characteristic of the energy storage device approaches a partial charge/discharge profile (based on the verification described above, to appropriately estimate the internal states of the battery cell formed of the active material similar to that in the test element A, it is necessary to estimate the aforementioned correction coefficient DCa for at least the negative electrode; [0101]; Figs 2-5, 8) for the purpose of appropriately estimating the internal states of the battery cell.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to incorporate the parameter representing an internal state amount of the energy storage device and the parameter being adjusted in such a way that a profile of a predetermined section in the overall discharge characteristic of the energy storage device approaches the partial charge/discharge profile, as taught by Yagi et al., into Kawahara et al. for the purpose of appropriately estimating the internal states of the battery cell.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kawahara et al. (US 2025/0180656 A1) as modified by Yagi et al. (US 2022/0381845 A1) as applied to claim 1 above, and further in view of Ukumori et al. (US 2020/0182938 A1).
Regarding claim 7, Kawahara et al. as modified by Yagi et al. do not teach wherein the parameter includes a positive electrode effectiveness and a charge reserve capacity of a negative electrode.
Further regarding claim 7, Ukumori et al. teach a parameter includes a positive electrode effectiveness and a charge reserve capacity of a negative electrode (further, since SOC-OCV of the energy storage device also changes depending on a state of a counter electrode, it is necessary to estimate an internal state of the energy storage device also including the state of the counter electrode, in order to control the energy storage device; [0012]-[0013], [0072]-[0077]) for the purpose controlling the energy storage device with changes in the state of the electrodes.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to incorporate wherein the parameter includes a positive electrode effectiveness and a charge reserve capacity of a negative electrode, as taught by Ukumori et al., into Kawahara et al. as modified by Yagi et al. for the purpose of controlling the energy storage device with changes in the state of the electrodes.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KENDRICK X LIU whose telephone number is (571)270-3798. The examiner can normally be reached MWFSa 10am-8pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Douglas X Rodriguez can be reached at (571) 431-0716. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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28 September 2026
/KENDRICK X LIU/Examiner, Art Unit 2853
/DOUGLAS X RODRIGUEZ/Supervisory Patent Examiner, Art Unit 2853
