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 .
Election/Restrictions
With respect to the remarks regarding the restriction requirement, the restriction of 2/11/26 is withdrawn in order to accelerate prosecution of Group I-II (Claims 1-20).
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/11/24 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
Drawings
The drawings were received on 4/11/23. These drawings are acceptable.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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.
Claims 1-2, 5-9, 12-16, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over DE 102019213125 A1 (DE’125) in view of WO 2022024885 A1 (WO’885) and further in view of WO 2021118118 A1 (WO’118).
As to Claim 1:
DE’125 discloses a vehicle (motor vehicle 2) comprising: an electric motor (electrically powered or drivable motor vehicle); a battery pack (vehicle battery 4) electrically coupled to the electric motor; and a battery management system (controller 16) coupled to the battery pack, the battery management system comprising a memory (memory 18), computer readable instructions (operating software), and one or more processors (microcontroller with a processor) for executing the computer readable instructions;
the computer readable instructions controlling the one or more processors to perform operations comprising:
measuring a cell pressure (gas pressure P inside the cell housing 8) of a cell of the battery pack where the pressure is evaluated based on the battery voltage (U); and
responsive to the pressure exceeding a threshold (limit values pmax), identifying the cell of the battery pack as a degraded cell (malfunctions such as “increased aging” or “abnormal cell behavior”) (pp. 6–9).
However, DE’125 does not explicitly disclose measuring a first and second cell pressure specifically at a “reference voltage,” determining a “moving average of cell pressure progression” from those measurements, or determining an “estimate of remaining cycles” for the degraded cell.
WO’885 teaches a battery diagnostic method that includes a “moving average step (S61)” to calculate moving average values for battery parameters (such as capacity Qmax and resistance coefficients) across multiple cycles (K) to reduce measurement noise and error; and teaches predicting a “replacement time” (remaining cycles) for a battery pack by extrapolating an approximation function indicating deterioration on a time axis and notifying the user (pp. 8, 16, 18).
WO’118 teaches a method for diagnosing battery degradation by measuring voltage information specifically on the basis of “reference voltages (Vref)” for each cell in each of “multiple cycles”; and calculating “change rates” (progression) of deviations to diagnose relative degradation degrees (pp. 5–7).
DE’125, WO’885, and WO’118 are analogous arts because they are in the field of battery management and degradation monitoring for electric vehicles, and they address the same technical problem of accurately detecting battery health states and predicting end-of-life based on the analysis of cyclic sensor data collected from electrochemical cells.
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the reference voltage measurement protocol of WO’118 into the pressure-based diagnostic system of DE’125 to ensure that the internal cell pressure readings are taken at consistent, comparable states across cycles. Furthermore, it would have been obvious to apply the moving average algorithm and life prediction extrapolation taught by WO’885 to the cycle-to-cycle pressure progression data recorded by DE’125. A person of ordinary skill in the art would have been motivated to make these modifications to improve the reliability and accuracy of battery health predictions by filtering out measurement noise from the internal pressure data, which DE’125 identifies as a critical indicator of cell aging and malfunction, and to provide the user with a specific, actionable estimate of the remaining service life of the battery.
As to Claim 2:
DE’125 discloses the vehicle of claim 1 (as established in the rejection of Claim 1) (pp. 6–9); and a battery management system (controller 16) comprising a memory (memory 18) wherein the controller evaluates the gas pressure based on a stored family of characteristics or a stored reference curve (pp. 8–9).
However, DE’125 does not explicitly disclose that the battery management system is further configured to “build” a lookup table configured to provide, as output, an “estimate of an available cycle life remaining” for a battery cell.
WO’885 teaches a battery pack diagnostic device and method that utilizes a “battery table” stored in a storage device and specifically teaches that “the table is automatically generated”; and further teaches using the stored data to “predict the replacement time of the battery pack” (i.e., provide as output an estimate of available cycle life remaining) by extrapolating an approximation function indicating deterioration on a time axis (pp. 4–5, 16).
Additionally, WO’118 teaches diagnosing a relative degradation degree based on change rates of voltage deviations calculated for multiple cycles relative to a reference voltage (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to configure the battery management system of DE’125 to build and utilize its stored tables to provide a specific output of remaining cycle life (replacement time) as taught by WO’885. A person of ordinary skill in the art would have been motivated to automate the generation of the diagnostic tables and provide a concrete remaining life estimate to the user to improve maintenance predictability and vehicle reliability, utilizing the reference voltage measurement protocol of WO’118 and the moving average filtering of WO’885 to refine the pressure-based aging detection logic disclosed in DE’125.
As to Claim 5:
DE’125 discloses the vehicle of claim 4 (as established in the rejection of Claim 4) (pp. 6–9); and a predetermined end-of-life condition for a degraded cell (malfunctions such as “increased aging” or “abnormal cell behavior”) wherein the predetermined end-of-life condition comprises an expected cell pressure surge above a predetermined threshold (limit values pmax) (pp. 8–9).
However, DE’125 does not explicitly disclose that the estimate of remaining cycles is calculated specifically as a “number of cycles” until the condition is met, nor does it disclose the alternative condition of a “percentage of prior cells failed.”
WO’885 teaches a battery pack diagnostic method that predicts a “replacement time” (estimate of remaining cycles) for a battery pack by calculating an approximation function extrapolated on a time axis based on deteriorating battery parameters (p. 16).
WO’118 teaches a method for diagnosing battery degradation by measuring voltage information specifically on the basis of “reference voltages” for each cell in each of “multiple cycles” to track the progression of deterioration (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to combine the pressure-surge threshold detection logic of DE’125 with the life-prediction extrapolation logic of WO’885. Specifically, it would have been obvious to a person of ordinary skill in the art to use the predetermined pressure limit (pmax) identified in DE’125 as the specific “end-of-life” target in the extrapolation model of WO’885 to output the estimate as a “number of cycles.” A person of ordinary skill in the art would have been motivated to provide the remaining life estimate in terms of cycles to allow the vehicle operator to clearly understand the remaining utility and safety margin of the battery pack before a critical pressure event occurs, utilizing the reference voltage measurement protocol of WO’118 to ensure data consistency across the multiple cycles used for the extrapolation.
As to Claim 6:
DE’125 discloses the vehicle of claim 2 (as established in the rejection of Claim 2) (pp. 6–9); and wherein the battery management system (controller 16) is further configured to determine one of a charging condition and a discharging condition of the battery pack (characterizing reference measurements by means of “load charge and / or load discharge” profiles and monitoring “charging or fast charging” processes) (pp. 7–8).
However, DE’125 does not explicitly disclose measuring a first and second cell pressure specifically at a “reference voltage,” determining a “moving average of cell pressure progression” from those measurements, or “building” a lookup table configured to provide an “estimate of available cycle life remaining” as the output responsive to identifying a degraded cell.
WO’885 teaches a battery pack diagnostic method that includes a “moving average step (S61)” to calculate moving average values for battery parameters across multiple cycles to reduce measurement noise (p. 8); and teaches that “the table is automatically generated” (built) to predict a “replacement time” (estimate of cycle life remaining) by extrapolating a deterioration function (pp. 4–5, 16). Furthermore, WO’885 teaches determining charging/discharging conditions by separating data for each “run and each charge” (p. 6).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages” over multiple cycles to track deterioration rates (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the cycle-based reference voltage protocol of WO’118 and the moving average and life prediction logic of WO’885 into the pressure-based monitoring system of DE’125. A person of ordinary skill in the art would have been motivated to configure the BMS to determine charging and discharging conditions, as taught by DE’125 and WO’885, to ensure that the pressure measurements used for the moving average progression are correctly categorized. Determining the operational state (charge vs. discharge) allows the BMS to apply the correct reference curves or table data, thereby providing a more precise and reliable estimate of the battery’s remaining service life based on the physical aging indicators detected during specific vehicle usage modes.
As to Claim 7:
DE’125 discloses the vehicle of claim 6 (as established in the rejection of Claim 6) (pp. 6–9); a battery management system (controller 16) coupled to the battery pack; and wherein an operating state variable (voltage U) of the battery cell is regulated based on the evaluation of the gas pressure (P) (pp. 8–9).
However, DE’125 does not explicitly disclose adjusting a “charging voltage limitation” or “operational voltage limitation” specifically for a “degraded cell” using a “lookup table.”
WO’885 teaches a battery pack diagnostic device that utilizes a “battery table” (lookup table) stored in a storage device to maintain and update battery parameters such as resistance and capacity for the purpose of health monitoring and life prediction (pp. 4–5).
WO’118 teaches a method for managing battery cells where, when the deterioration of a specific cell is accelerating (identifying a degraded cell), the system is configured to “reduce the upper limit of the voltage” of that specific cell to mitigate further degradation (pp. 6–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the operational voltage adjustment taught by WO’118 into the pressure-based diagnostic framework of DE’125. Specifically, once a cell is identified as a “degraded cell” based on the pressure progression logic established in DE’125, a person of ordinary skill in the art would be motivated to adjust (reduce) the charging or operational voltage limits for that cell, as taught by WO’118, to prevent the “rapid pressure increases” or surges associated with advanced aging described in DE’125. Furthermore, it would have been obvious to store and implement these adjusted voltage limits using the “lookup table” structure taught by WO’885 to allow for the efficient, cell-specific control required to prolong the service life of the battery pack.
As to Claim 8:
DE’125 discloses a battery management system (controller 16) comprising a memory (memory 18), computer readable instructions (operating software), and one or more processors (microcontroller with a processor) for executing the computer readable instructions;
the computer readable instructions controlling the one or more processors to perform operations comprising:
measuring a cell pressure (gas pressure P inside the cell housing 8) of a cell of a battery pack where the pressure is evaluated based on the battery voltage (U); and
responsive to the pressure exceeding a threshold (limit values pmax), identifying the cell of the battery pack as a degraded cell (malfunctions such as “increased aging” or “abnormal cell behavior”) (pp. 6–9).
However, DE’125 does not explicitly disclose measuring a first and second cell pressure specifically at a “reference voltage,” determining a “moving average of cell pressure progression” from those measurements, or determining an “estimate of remaining cycles” for the degraded cell.
WO’885 teaches a battery pack diagnostic method that includes a “moving average step (S61)” to calculate moving average values for battery parameters across multiple cycles to reduce measurement noise and error (p. 8); and teaches predicting a “replacement time” (estimate of remaining cycles) for a battery pack by extrapolating an approximation function indicating deterioration on a time axis and notifying the user (pp. 16, 18).
WO’118 teaches a method for diagnosing battery degradation by measuring cell parameters specifically on the basis of “reference voltages (Vref)” for each cell in each of “multiple cycles”; and calculating “change rates” (progression) of deviations to diagnose relative degradation degrees (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the reference voltage measurement protocol of WO’118 into the pressure-based monitoring system of DE’125 to ensure that the internal cell pressure readings are taken at consistent, comparable states across cycles. Furthermore, it would have been obvious to apply the moving average algorithm and life prediction logic of WO’885 to the cycle-to-cycle pressure progression data recorded by DE’125. A person of ordinary skill in the art would have been motivated to make these modifications to improve the reliability and accuracy of battery health predictions by filtering out measurement noise from the internal pressure data, which DE’125 identifies as a critical indicator of cell aging and malfunction, and to provide the user with a specific, actionable estimate of the remaining service life of the battery.
As to Claim 9:
DE’125 discloses the battery management system (controller 16) of claim 8 (as established in the rejection of Claim 8) (pp. 6–9); and a battery management system comprising a memory (memory 18) wherein the controller evaluates parameters based on a stored family of characteristics or a stored reference curve (pp. 8–9).
However, DE’125 does not explicitly disclose that the battery management system is further configured to “build” a lookup table configured to provide, as output, an “estimate of an available cycle life remaining” for a battery cell.
WO’885 teaches a battery pack diagnostic device and method that utilizes a “battery table” stored in a storage device and specifically teaches that “the table is automatically generated”; and further teaches using the stored data to “predict the replacement time of the battery pack” (i.e., provide as output an estimate of available cycle life remaining) by extrapolating an approximation function indicating deterioration on a time axis (pp. 4–5, 16).
Additionally, WO’118 teaches diagnosing a relative degradation degree based on change rates of deviations calculated for multiple cycles relative to a reference voltage (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to configure the battery management system of DE’125 to build and utilize its stored tables to provide a specific output of remaining cycle life (replacement time) as taught by WO’885. A person of ordinary skill in the art would have been motivated to automate the generation of the diagnostic tables and provide a concrete remaining life estimate to the user to improve maintenance predictability and system reliability, utilizing the reference voltage measurement protocol of WO’118 and the moving average filtering of WO’885 to refine the pressure-based aging detection logic disclosed in DE’125.
As to Claim 12:
DE’125 discloses the battery management system of claim 11 (as established in the rejection of claim 11) (pp. 6–9); a degraded cell (malfunctions such as “increased aging” or “abnormal cell behavior”); and a predetermined end-of-life condition for the degraded cell (identifying overpressure or safety-critical states) wherein the predetermined end-of-life condition comprises an expected cell pressure surge above a predetermined threshold (limit values pmax) (pp. 8–9).
However, DE’125 does not explicitly disclose that the estimate of remaining cycles is calculated specifically as a “number of cycles” until the condition is met, nor does it disclose the alternative condition of a “percentage of prior cells failed.”
WO’885 teaches a battery pack diagnostic method that predicts a “replacement time” (estimate of remaining cycles) for a battery pack by calculating an approximation function extrapolated on a time axis based on deteriorating battery parameters until a replacement limit is reached (p. 16).
WO’118 teaches a method for diagnosing battery degradation by measuring voltage information specifically on the basis of “reference voltages (Vref)” for each cell in each of “multiple cycles” to track the progression of deterioration (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to combine the pressure-surge threshold detection logic of DE’125 with the life-prediction extrapolation logic of WO’885. Specifically, it would have been obvious to a person of ordinary skill in the art to utilize the predetermined pressure limit (pmax) identified in DE’125 as the specific “end-of-life” target in the extrapolation model of WO’885 to output the life estimate as a “number of cycles” until said surge is expected to occur. A person of ordinary skill in the art would have been motivated to provide the remaining life estimate in terms of cycles to allow the system to proactively manage the battery and notify the operator of the remaining utility and safety margin before a critical pressure event occurs, utilizing the reference voltage measurement protocol of WO’118 to ensure data consistency across the multiple cycles required for the extrapolation.
As to Claim 13:
DE’125 discloses a battery management system (controller 16) comprising a memory (memory 18), computer readable instructions (operating software), and one or more processors (microcontroller with a processor) for executing the computer readable instructions;
the computer readable instructions controlling the one or more processors to perform operations comprising:
measuring a cell pressure (gas pressure P occurring within the cell housing 8) of a cell of a battery pack where the gas pressure is evaluated based on the battery voltage (U);
responsive to the pressure exceeding a threshold (limit values pmax), identifying the cell of the battery pack as a degraded cell (identifying malfunctions such as “increased aging”); and
the battery management system is further configured to determine one of a charging condition and a discharging condition of the battery pack (monitoring gas pressure development during “load charge and / or load discharge” profiles and “charging or fast charging” processes) (pp. 6–9).
However, DE’125 does not explicitly disclose measuring a first and second cell pressure specifically at a “reference voltage,” determining a “moving average of cell pressure progression” from those measurements, “building” a lookup table configured to provide an “estimate of an available cycle life remaining,” or determining an “estimate of remaining cycles” for the degraded cell.
WO’885 teaches a battery pack diagnostic method that includes a “moving average step (S61)” to calculate moving average values for battery parameters across multiple cycles (K) to reduce measurement noise and error (p. 8); teaches that “the table is automatically generated” (built) to predict a “replacement time” (estimate of available cycle life remaining) by extrapolating a deterioration function (pp. 4–5, 16); and teaches determining charging and discharging conditions by separating data for each “run and each charge” (p. 6).
WO’118 teaches a method for diagnosing battery degradation by measuring cell parameters specifically on the basis of “reference voltages (Vref)” for each cell in each of “multiple cycles” to track the progression of deterioration; and calculating “change rates” (progression) of deviations to diagnose relative degradation degrees (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the reference voltage measurement protocol of WO’118 into the pressure-based monitoring system of DE’125 to ensure consistent and comparable data across multiple cycles, and to apply the moving average algorithm and life prediction logic of WO’885 to the resulting pressure progression data. Furthermore, it would have been obvious to configure the BMS to determine charging and discharging conditions, as taught by DE’125 and WO’885, to ensure that the pressure measurements used for the moving average are correctly categorized and compared against appropriate reference curves or lookup table data. A person of ordinary skill in the art would have been motivated to make these modifications to improve the diagnostic accuracy and maintenance predictability of the system by filtering out cycle-to-cycle measurement noise and providing a concrete, actionable estimate of the battery’s remaining service life based on the physical aging indicators detected during specific operational modes.
As to Claim 14:
DE’125 discloses a battery management system (controller 16) comprising a memory (memory 18), computer readable instructions, and one or more processors (microcontroller); performing operations comprising measuring a cell pressure (gas pressure P inside the cell housing 8) where the pressure is evaluated based on the battery voltage (U); responsive to the pressure exceeding a threshold (pmax), identifying the cell as a degraded cell (identifying malfunctions such as “increased aging”); the battery management system is further configured to determine one of a charging condition and a discharging condition (monitoring pressure during “load charge and / or load discharge”); and an operating state variable (voltage U) of the battery cell is regulated based on the evaluation of the gas pressure (pp. 6–9).
However, DE’125 does not explicitly disclose measuring a first and second cell pressure specifically at a “reference voltage,” determining a “moving average of cell pressure progression” from those measurements, “building” a lookup table configured to provide an “estimate of available cycle life remaining,” or specifically adjusting a “charging voltage limitation” or “operational voltage limitation” of the degraded cell using the lookup table.
WO’885 teaches a battery pack diagnostic method that includes a “moving average step (S61)” to calculate moving average values for battery parameters across multiple cycles to reduce measurement noise (p. 8); teaches that “the table is automatically generated” (built) to predict a “replacement time” (estimate of cycle life remaining) by extrapolating a deterioration function (pp. 4–5, 16); and teaches determining charging/discharging conditions by separating data for each “run and each charge” (p. 6).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages (Vref)” over multiple cycles to track deterioration rates; and further teaches that when the deterioration of a specific cell is accelerating (identifying a degraded cell), the system is configured to “reduce the upper limit of the voltage” of that specific cell to mitigate further degradation (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the cycle-based reference voltage protocol of WO’118 and the moving average and life prediction logic of WO’885 into the pressure-based monitoring system of DE’125. Furthermore, it would have been obvious to configure the BMS to adjust the charging or operational voltage limitations of a cell identified as degraded based on the pressure progression, as taught by WO’118, using the parameters stored in the built lookup table described by WO’885. A person of ordinary skill in the art would have been motivated to make these modifications to proactively manage the health of individual cells and prevent the “rapid pressure increases” or surges associated with advanced aging described in DE’125, thereby extending the overall service life and safety of the battery pack.
As to Claim 15:
DE’125 discloses a method for lowering a risk of cell pressure surge in a battery pack (operating a battery cell while monitoring for “rapid pressure increase” or overpressure to ensure safety), the method comprising:
measuring a cell pressure (gas pressure P inside the cell housing 8) of a cell of the battery pack where the pressure is evaluated based on the battery voltage (U); and
responsive to the pressure exceeding a threshold (limit values pmax), identifying the cell of the battery pack as a degraded cell (malfunctions such as “increased aging”) (pp. 6–9).
However, DE’125 does not explicitly disclose measuring a first and second cell pressure specifically at a “reference voltage,” determining a “moving average of cell pressure progression” from those measurements, or determining an “estimate of remaining cycles” for the degraded cell.
WO’885 teaches a battery diagnostic method that includes a “moving average step (S61)” to calculate moving average values for battery parameters across multiple cycles (K) to reduce measurement noise and error (p. 8); and teaches predicting a “replacement time” (estimate of remaining cycles) for a battery pack by extrapolating an approximation function indicating deterioration on a time axis and notifying the user (pp. 16, 18).
WO’118 teaches a method for diagnosing battery degradation by measuring cell parameters specifically on the basis of “reference voltages (Vref)” for each cell in each of “multiple cycles”; and calculating “change rates” (progression) of deviations to diagnose relative degradation degrees (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the reference voltage measurement protocol of WO’118 into the pressure-based monitoring system of DE’125 to ensure that the internal cell pressure readings are taken at consistent, comparable states across cycles. Furthermore, it would have been obvious to apply the moving average algorithm and life prediction logic of WO’885 to the cycle-to-cycle pressure progression data recorded by DE’125. A person of ordinary skill in the art would have been motivated to make these modifications to improve the reliability and accuracy of battery health predictions by filtering out measurement noise from the internal pressure data, which DE’125 identifies as a critical indicator of cell aging and malfunction, and to provide the user with a specific, actionable estimate of the remaining service life of the battery pack.
As to Claim 16:
DE’125 discloses the method of claim 15 (as established in the rejection of Claim 15) (pp. 6–9); and further discloses utilizing stored lookup tables (stored limit values and reference curves/families of characteristics) for the evaluation of cell parameters such as internal pressure (P) relative to voltage (U) and temperature (T) (pp. 8–9).
However, DE’125 does not explicitly disclose measuring a first and second cell pressure specifically at a “reference voltage,” determining a “moving average of cell pressure progression” from those measurements, or “building” a lookup table specifically configured to provide, as output, an “estimate of an available cycle life remaining.”
WO’885 teaches a battery pack diagnostic method that includes a “moving average step (S61)” to calculate moving average values for battery parameters across multiple cycles to reduce measurement noise (p. 8); and specifically teaches that “the table is automatically generated” (built) and stored in a storage device as a battery table (pp. 4–5); and further teaches using the stored data in said table to predict a “replacement time” (i.e., provide as output an estimate of available cycle life remaining) by extrapolating an approximation function on a time axis (p. 16).
Additionally, WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages” over multiple cycles to track deterioration rates and determine degradation degrees (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the reference voltage measurement protocol of WO’118 and the moving average filtering and life prediction logic of WO’885 into the pressure-based monitoring method of DE’125. Furthermore, it would have been obvious to a person of ordinary skill in the art to configure the system to “build” its lookup tables by automatically generating them from the processed pressure data, as taught by WO’885, to provide a concrete, actionable output of the remaining cycle life. A person of ordinary skill in the art would have been motivated to automate the table generation and life prediction to improve the accuracy and usability of the diagnostic method, ensuring the user is notified of the remaining service life based on the physical aging indicators (pressure) detected across operational cycles.
As to Claim 19:
DE’125 discloses the method of claim 15 (as established in the rejection of claim 15) (pp. 6–9); a degraded cell (malfunctions such as “increased aging” or “abnormal cell behavior”); a predetermined end-of-life condition for the degraded cell (identifying safety-critical states or malfunctions based on pressure evaluation); and wherein the predetermined end-of-life condition comprises an expected cell pressure surge above a predetermined threshold (limit values pmax) (pp. 8–9).
However, DE’125 does not explicitly disclose that the estimate of remaining cycles for the degraded cell is calculated specifically as a “number of cycles” until the expected surge condition is met.
WO’885 teaches a battery pack diagnostic method that predicts a “replacement time” (estimate of remaining cycles) for a battery pack by calculating an approximation function extrapolated on a time axis based on deteriorating battery parameters until a replacement limit is reached (p. 16).
WO’118 teaches a method for diagnosing battery degradation by measuring cell parameters specifically on the basis of “reference voltages (Vref)” for each cell in each of “multiple cycles” to track the progression of deterioration over time (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to combine the pressure-surge threshold detection logic of DE’125 with the life-prediction extrapolation logic of WO’885. Specifically, it would have been obvious to a person of ordinary skill in the art to utilize the predetermined pressure limit (pmax) identified in DE’125 as the specific “end-of-life” target in the life-prediction model of WO’885 to output the estimate as a “number of cycles” until said pressure surge is expected to occur. A person of ordinary skill in the art would have been motivated to provide the remaining life estimate in terms of cycles to allow the system to proactively manage the battery and notify the operator of the remaining utility and safety margin before a critical pressure event occurs, utilizing the reference voltage measurement protocol of WO’118 to ensure data consistency across the multiple cycles required for the extrapolation.
As to Claim 20:
DE’125 discloses the method of claim 16 (as established in the rejection of claim 16) (pp. 6–9); and the method further comprises determining one of a charging condition and a discharging condition of the battery pack (characterizing reference measurements by means of “load charge and / or load discharge” profiles and specifically monitoring “charging or fast charging” processes) (pp. 7–8).
However, DE’125 does not explicitly disclose measuring a first and second cell pressure specifically at a “reference voltage,” determining a “moving average of cell pressure progression” from those measurements, or “building” a lookup table specifically configured to provide, as output, an “estimate of an available cycle life remaining.”
WO’885 teaches a battery pack diagnostic method that includes a “moving average step (S61)” to calculate moving average values for battery parameters across multiple cycles (K) to reduce measurement noise and error (p. 8); specifically teaches that “the table is automatically generated” (built) and stored in a storage device as a battery table (pp. 4–5); and further teaches using the stored data in said table to predict a “replacement time” (i.e., provide as output an estimate of available cycle life remaining) by extrapolating an approximation function on a time axis (p. 16). Furthermore, WO’885 teaches determining charging and discharging conditions by separating and processing data for each “run and each charge” (p. 6).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages (Vref)” for each cell in each of “multiple cycles” to track the progression of deterioration over time (pp. 5–7).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the reference voltage measurement protocol of WO’118 and the moving average filtering and life prediction logic of WO’885 into the pressure-based monitoring method of DE’125. A person of ordinary skill in the art would have been motivated to configure the diagnostic method to determine charging and discharging conditions, as taught by DE’125 and WO’885, to ensure that the pressure measurements used for the cycle-to-cycle moving average are correctly categorized and evaluated against the appropriate stored reference curves or table data. Categorizing the measurements by operational mode (charge vs. discharge) allows the system to filter out mode-specific artifacts, thereby providing a more precise and reliable estimate of the battery’s remaining service life based on the physical aging indicators (pressure) detected across operational cycles.
Claims 3-4, 10-11, and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over DE 102019213125 A1 (DE’125) in view of WO 2022024885 A1 (WO’885) and further in view of WO 2021118118 A1 (WO’118), as applied to Claim 2 above, and further in view of US 20190111800 A1 (US’800).
As to Claim 3:
DE’125 discloses the vehicle and battery management system of claim 2 (as established in the rejection of Claim 2) (pp. 6–9); and the lookup table (stored family of characteristics and reference curves) comprising, as inputs, a cell voltage (U), a change in cell pressure (gas pressure P or development of pressure Δp), and a cell temperature (T) (pp. 8–9).
WO’885 teaches a battery pack diagnostic method that includes a “moving average step” to calculate values for battery parameters across multiple “cycle-to-cycle” iterations to reduce measurement noise (p. 8); and teaches that “the table is automatically generated” (built) to predict a “replacement time” (estimate of cycle life remaining) (pp. 3–5, 9, 16).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages (Vref)” over multiple cycles to track deterioration rates and determine degradation (pp. 5–7).
US’800 teaches a system for managing battery life that identifies “operating limits” (operational voltage windows) and usage profiles as key variables for preserving battery life; and specifically teaches using these voltage operating limits as inputs to a model to calculate and report the “remaining useful life” of the battery ([0033], [0055]).
However, DE’125 does not explicitly disclose that the lookup table is a “four dimensional (4D)” lookup table or that it specifically includes an “operational voltage window” as a fourth input parameter for determining the cycle life estimate.
WO’885 and WO’118 teach the algorithmic logic for processing data cycle-to-cycle and utilizing tables to output life estimates. US’800 provides the remaining missing limitation by teaching that the “operating limits” or “voltage window” in which a battery is utilized is a critical deterministic factor for its aging and remaining life. US’800 teaches that a battery management system should utilize these limits as an input to a stored diagnostic structure to provide a remaining life estimate ([0033], [0055]).
DE’125, WO’885, WO’118, and US’800 are analogous arts because they are in the field of battery management and degradation monitoring for electric vehicles and energy storage systems. Each reference addresses the same technical problem of accurately determining and predicting battery health and remaining service life based on the analysis of multi-variate operational sensor data.
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the cycle-based reference voltage protocol of WO’118 and the life prediction logic of WO’885 into the pressure-based monitoring system of DE’125. Furthermore, it would have been obvious to expand the multi-dimensional lookup table or reference curves of DE’125 into a “four dimensional (4D)” structure by including the “operational voltage window” taught by US’800 as a specific fourth input. A person of ordinary skill in the art would have been motivated to include the operational voltage window from US’800 as a discrete input dimension to the diagnostic tables because it was well known in the art that the depth of discharge and the specific voltage range of operation significantly influence the rate of physical degradation (and thus pressure progression) in an electrochemical cell. Combining the pressure/voltage/temperature monitoring of DE’125 with the voltage-window sensitivity of US’800 within the cycle-tracking framework of WO’885 and WO’118 results in a significantly more accurate and individualized “remaining cycle life” estimate that reflects the specific usage profile of the vehicle.
As to Claim 4:
DE’125 discloses the vehicle and battery management system of claim 3 (as established in the rejection of Claim 3) (pp. 6–9); and a method for determining an estimate of battery state comprising inputting a cell voltage (U), a change in cell pressure (gas pressure P or development of pressure Δp), and a cell temperature (T) to a lookup table (stored family of characteristics and reference curves) (pp. 8–9).
WO’885 teaches a battery pack diagnostic method that includes a “moving average step” to calculate values for battery parameters across multiple “cycle-to-cycle” iterations to reduce measurement noise (p. 8); and teaches that “the table is automatically generated” (built) to predict a “replacement time” (estimate of cycle life remaining) (pp. 4–5, 16).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages (Vref)” over multiple cycles to track deterioration rates and determine degradation (pp. 5–7).
US’800 teaches a system for managing battery life that identifies “operating limits” (operational voltage windows) and usage profiles as key variables for preserving battery life; and specifically teaches using these voltage operating limits as inputs to a model or table to calculate and report the “remaining useful life” (remaining cycles) of the battery ([0033], [0055]).
However, DE’125 does not explicitly disclose inputting a “change in cycle-to-cycle cell pressure” specifically derived from a moving average, nor does it disclose inputting an “operational voltage window” to the lookup table and receiving the “estimate of remaining cycles” as the specific output.
WO’885 and WO’118 provide the cycle-based processing logic for calculating the pressure progression (change in cycle-to-cycle pressure) and using automatically generated tables to output a life estimate. US’800 provides the remaining missing limitation by teaching that the “operating limits” or “voltage window” in which a battery is utilized is a critical deterministic factor for its aging and remaining life. US’800 teaches that a battery management system should utilize these limits as an input to a stored diagnostic structure to provide a remaining life estimate ([0033], [0055]).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the cycle-based reference voltage protocol of WO’118 and the life prediction logic of WO’885 into the pressure-based monitoring system of DE’125. Furthermore, it would have been obvious to a person of ordinary skill in the art to configure the BMS to input the “operational voltage window” taught by US’800 along with the cycle-to-cycle pressure change, voltage, and temperature into the lookup table to receive the “remaining cycles” estimate. A person of ordinary skill in the art would have been motivated to include the operational voltage window from US’800 as a discrete input dimension to the diagnostic tables of DE’125 because it was well known in the art that the depth of discharge and the specific voltage range of operation significantly influence the rate of physical degradation (and thus pressure progression) in an electrochemical cell. Combining these known variables into a single table lookup allows the BMS to provide a significantly more accurate and individualized “remaining cycle life” estimate that accounts for the specific usage profile and operational limits of the vehicle’s battery pack.
As to Claim 10:
DE’125 discloses the battery management system of claim 9 (as established in the rejection of claim 9) (pp. 6–9); and the lookup table (stored family of characteristics or reference curves) comprising, as inputs, a cell voltage (U), a change in cell pressure (gas pressure P or development of pressure Δp), and a cell temperature (T) (pp. 8–9).
WO’885 teaches a battery management system that includes a “moving average step” to calculate values for battery parameters across multiple “cycle-to-cycle” iterations to reduce measurement noise (p. 8); and teaches that “the table is automatically generated” (built) to predict a “replacement time” (estimate of cycle life remaining) (pp. 4–5, 16).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages (Vref)” over multiple cycles to track deterioration rates and identify degraded cells (pp. 5–7).
US’800 teaches a system for managing battery life that identifies “operating limits” (operational voltage windows) and usage profiles as key variables for preserving battery life; and specifically teaches using these voltage operating limits as inputs to a model or table to calculate and report the “remaining useful life” of the battery ([0033], [0055]).
However, DE’125 does not explicitly disclose that the lookup table is a “four dimensional (4D)” lookup table or that it specifically includes an “operational voltage window” as a fourth input parameter for determining the cycle life estimate.
WO’885 and WO’118 provide the cycle-based processing logic for calculating the pressure progression and utilizing automatically built tables to output life estimates. US’800 provides the remaining missing limitation by teaching that the “operating limits” or “voltage window” in which a battery is utilized is a critical deterministic factor for its aging and remaining life. US’800 teaches that a battery management system should utilize these limits as a discrete input to a stored diagnostic structure to provide a remaining life estimate ([0033], [0055]).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the cycle-based reference voltage protocol of WO’118 and the life prediction logic of WO’885 into the pressure-based monitoring system of DE’125. Furthermore, it would have been obvious to a person of ordinary skill in the art to expand the multi-dimensional lookup table or reference curves of DE’125 into a “four dimensional (4D)” structure by including the “operational voltage window” taught by US’800 as a specific fourth input. A person of ordinary skill in the art would have been motivated to include the operational voltage window from US’800 as a discrete input dimension to the diagnostic tables of DE’125 because it was well known in the art that the depth of discharge and the specific voltage range of operation significantly influence the rate of physical degradation (and thus pressure progression) in an electrochemical cell. Combining these known variables into a single 4D table lookup allows the BMS to provide a significantly more accurate and individualized “remaining cycle life” estimate that accounts for the specific usage profile and operational limits of the vehicle’s battery pack.
As to Claim 11:
DE’125 discloses the battery management system of claim 10 (as established in the rejection of claim 10) (pp. 6–9); and wherein determining the operating state comprises inputting a first cell voltage (U), a first change in cell pressure (gas pressure P or development of pressure Δp), and a first cell temperature (T) to the lookup table (stored family of characteristics and reference curves) (pp. 8–9).
WO’885 teaches a battery pack diagnostic method that includes a “moving average step” to calculate values for battery parameters across multiple “cycle-to-cycle” iterations to reduce measurement noise (p. 8); and teaches inputting battery parameters to an automatically generated table to predict a “replacement time” (estimate of remaining cycles) (pp. 4–5, 16).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages (Vref)” over multiple cycles to track deterioration rates and determine degradation (pp. 5–7).
US’800 teaches a system for managing battery life that identifies “operating limits” (operational voltage windows) and usage profiles as key variables for preserving battery life; and specifically teaches inputting these voltage operating limits to a model or table to calculate and report the “remaining useful life” (remaining cycles) of the battery ([0033], [0055]).
However, DE’125 does not explicitly disclose that the inputting step specifically utilizes a “first change in cycle-to-cycle cell pressure” derived from a moving average, nor does it disclose inputting a “first operational voltage window” to the lookup table to receive the cycle estimate.
WO’885 and WO’118 provide the cycle-based moving average logic required to calculate the cycle-to-cycle pressure progression (change) used as an input for life prediction. US’800 provides the remaining missing limitation by teaching that a battery’s “operating limit” (voltage window) is a critical input parameter that must be factored into the diagnostic structure (table or model) to provide an accurate report of the “remaining useful life” ([0033], [0055]).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the cycle-based reference voltage protocol of WO’118 and the moving average and life prediction logic of WO’885 into the pressure-based monitoring system of DE’125. Furthermore, it would have been obvious to a person of ordinary skill in the art to configure the BMS to input the “operational voltage window” taught by US’800 along with the voltage, temperature, and cycle-to-cycle pressure change into the diagnostic lookup table to receive the “remaining cycles” estimate. A person of ordinary skill in the art would have been motivated to include the operational voltage window from US’800 as a discrete input parameter because it was well known in the art that the depth of discharge and the specific voltage range of operation significantly influence the rate of physical degradation (and thus the pressure progression trend) in an electrochemical cell. Inputting these four known deterministic variables into a single table lookup allows the BMS to provide a significantly more accurate and individualized remaining cycle life estimate that accounts for the specific usage profile and operational limits of the vehicle’s battery pack.
As to Claim 17:
DE’125 discloses the method of claim 16 (as established in the rejection of claim 16) (pp. 6–9); and the lookup table (stored family of characteristics and reference curves) comprising, as inputs, a cell voltage (U), a change in cell pressure (gas pressure P or development of pressure Δp), and a cell temperature (T) (pp. 8–9).
WO’885 teaches a battery diagnostic method that includes a “moving average step” to calculate values for battery parameters across multiple “cycle-to-cycle” iterations to reduce measurement noise (p. 8); and teaches that “the table is automatically generated” (built) to predict a “replacement time” (estimate of cycle life remaining) (pp. 4–5, 16).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages (Vref)” over multiple cycles to track deterioration rates and determine degradation (pp. 5–7).
US’800 teaches a system for managing battery life that identifies “operating limits” (operational voltage windows) and usage profiles as key variables for preserving battery life; and specifically teaches using these voltage operating limits as inputs to a model to calculate and report the “remaining useful life” of the battery ([0033], [0055]).
However, DE’125 does not explicitly disclose that the lookup table is a “four dimensional (4D)” lookup table or that it specifically includes an “operational voltage window” as a fourth input parameter for determining the cycle life estimate.
WO’885 and WO’118 provide the cycle-based processing logic for calculating the pressure progression (change in cycle-to-cycle pressure) and using automatically generated tables to output life estimates. US’800 provides the remaining missing limitation by teaching that the “operating limits” or “voltage window” in which a battery is utilized is a critical deterministic factor for its aging and remaining life. US’800 teaches that a battery management system should utilize these limits as a discrete input to a stored diagnostic structure to provide a remaining life estimate ([0033], [0055]).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the cycle-based reference voltage protocol of WO’118 and the life prediction logic of WO’885 into the pressure-based monitoring system of DE’125. Furthermore, it would have been obvious to expand the multi-dimensional lookup table or reference curves of DE’125 into a “four dimensional (4D)” structure by including the “operational voltage window” taught by US’800 as a specific fourth input. A person of ordinary skill in the art would have been motivated to include the operational voltage window from US’800 as a discrete input dimension to the diagnostic tables because it was well known in the art that the depth of discharge and the specific voltage range of operation significantly influence the rate of physical degradation (and thus pressure progression) in an electrochemical cell. Combining the pressure/voltage/temperature monitoring of DE’125 with the voltage-window sensitivity of US’800 within the cycle-tracking framework of WO’885 and WO’118 results in a significantly more accurate and individualized “remaining cycle life” estimate that reflects the specific usage profile of the vehicle.
As to Claim 18:
DE’125 discloses the method of claim 17 (as established in the rejection of claim 17); and wherein determining the operating state comprises inputting a first cell voltage (U), a first change in cell pressure (gas pressure P or development of pressure Δp), and a first cell temperature (T) to the lookup table (stored family of characteristics and reference curves) (pp. 6–9; 8–9).
WO’885 teaches a method that includes a “moving average step” to calculate values for battery parameters across multiple “cycle-to-cycle” iterations to reduce measurement noise (p. 8); and teaches inputting battery parameters to a diagnostic table to predict a “replacement time” (estimate of remaining cycles) (pp. 4–5, 16).
WO’118 teaches measuring cell parameters specifically on the basis of “reference voltages (Vref)” over multiple cycles to track deterioration rates and determine degradation (pp. 5–7).
US’800 teaches a system for managing battery life that identifies “operating limits” (operational voltage windows) and usage profiles as key variables for preserving battery life; and specifically teaches inputting these voltage operating limits to a model or table to calculate and report the “remaining useful life” (remaining cycles) of the battery ([0033], [0055]).
However, DE’125 does not explicitly disclose that the inputting step of the method specifically utilizes a “first change in cycle-to-cycle cell pressure” derived from a moving average, nor does it disclose inputting a “first operational voltage window” to the lookup table and receiving an “estimate of remaining cycles” as the specific output.
WO’885 and WO’118 provide the cycle-based moving average logic required to calculate the cycle-to-cycle pressure progression (change) used as an input for life prediction in a method. US’800 provides the remaining missing limitation by teaching that a battery’s “operating limit” (voltage window) is a critical input parameter that must be factored into the diagnostic structure (table or model) within a management method to provide an accurate report of the “remaining useful life” ([0033], [0055]).
It would have been obvious to a person skilled in the art before the effective filing date of the instant application to incorporate the cycle-based reference voltage protocol of WO’118 and the moving average and life prediction logic of WO’885 into the pressure-based monitoring method of DE’125. Furthermore, it would have been obvious to a person of ordinary skill in the art to configure the method to input the “operational voltage window” taught by US’800 along with the voltage, temperature, and cycle-to-cycle pressure change into the diagnostic lookup table to receive the “remaining cycles” estimate. A person of ordinary skill in the art would have been motivated to include the operational voltage window from US’800 as a discrete input parameter because it was well known in the art that the depth of discharge and the specific voltage range of operation significantly influence the rate of physical degradation (and thus the pressure progression trend) in an electrochemical cell. Inputting these four known deterministic variables into a single table lookup allows the method to provide a significantly more accurate and individualized remaining cycle life estimate that accounts for the specific usage profile and operational limits of the vehicle’s battery pack.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
JP 4539735 B2 discloses a battery management control device that controls input / output of a battery device associated with deterioration of the battery device used as a power source of an electric vehicle.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JIMMY K VO whose telephone number is (571)272-3242. The examiner can normally be reached Monday - Friday, 8 am to 6 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tong Guo can be reached at (571) 272-3066. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JIMMY VO/
Primary Examiner
Art Unit 1723
/JIMMY VO/Primary Examiner, Art Unit 1723
Prosecution Insights