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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-3, 5-11, 13-15, and 17-20 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.
Specifically, representative Claim 2 recites:
A computer-implemented method, comprising:
retrieving, by a processor device of a computer system, reference data of a reference cell, the reference data including at least one initial aging parameter at beginning of life of the reference cell, and usage conditions of the reference cell including usage condition values,
measuring, by the processor device, at least one initial aging parameter of each electrical energy storage cell of an electrical energy storage system at beginning of life of each electrical energy storage cell, and at least one usage condition value for each electrical energy storage cell;
calculating, by the processor device, a first similarity value that indicates a relative relationship between one measured initial aging parameter for each electrical energy storage cell and the corresponding initial aging parameter at beginning of life of the reference cell,
calculating, by the processor device, a second similarity value that indicates a relative relationship between one usage condition value for each electrical energy storage cell and the corresponding usage condition value of the reference cell,
determining, by the processor device, a final similarity value for each electrical energy storage cell based on all similarity values of the respective electrical energy storage cell,
predicting, by the processor device, an aging evolution of each electrical energy storage cell based on the final similarity values, and
providing, by the processor device, data indicating the aging evolution of each electrical energy storage cell.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (process).
Additionally, claim 18 is not directed toward any of the four statutory categories as it is considered “software per se” (see MPEP 2106.03 I. Products that do not have a physical or tangible form, such as information (often referred to as "data per se") or a computer program per se (often referred to as "software per se") when claimed as a product without any structural recitations;).
Under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) and mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion.
For example, steps of “calculating a first similarity value that indicates a relative relationship between one measured initial aging parameter for each electrical energy storage cell and the corresponding initial aging parameter at beginning of life of the reference cell (calculation), and
calculating a second similarity value that indicates a relative relationship between one usage condition value for each electrical energy storage cell and the corresponding usage condition value of the reference cell (calculation)” are treated by the Examiner as belonging to mathematical concept grouping, while the steps of “determining a final similarity value for each electrical energy storage cell based on all similarity values of the respective electrical energy storage cell (determination based on previous calculations),
predicting an aging evolution of each electrical energy storage cell based on the final similarity values (inference based on previous determination), and
providing data indicating the aging evolution of each electrical energy storage cell (sharing results)” are treated as belonging to mental process grouping.
Similar limitations comprise the abstract ideas of Claim 1.
Next, under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
The above claims comprise the following additional elements:
Claim 1: a processor device, retrieve reference data of a reference cell, the reference data including at least one initial aging parameter at beginning of life of the reference cell, and usage conditions of the reference cell including usage condition values, measure at least one initial aging parameter of each electrical energy storage cell of an electrical energy storage system at beginning of life of each electrical energy storage cell, and at least one usage condition value for each electrical energy storage cell;
Claim 2: retrieving, by a processor device of a computer system, reference data of a reference cell, the reference data including at least one initial aging parameter at beginning of life of the reference cell, and usage conditions of the reference cell including usage condition values, measuring, by the processor device, at least one initial aging parameter of each electrical energy storage cell of an electrical energy storage system at beginning of life of each electrical energy storage cell, and at least one usage condition value for each electrical energy storage cell;
The additional elements of “retrieving reference data of a reference cell, the reference data including at least one initial aging parameter at beginning of life of the reference cell, and usage conditions of the reference cell including usage condition values, and
measuring at least one initial aging parameter of each electrical energy storage cell of an electrical energy storage system at beginning of life of each electrical energy storage cell, and at least one usage condition value for each electrical energy storage cell” are not qualified for a meaningful limitation because they are generally recited and represent mere data gathering steps and only add insignificant extra-solution activity to the judicial exception. A processor device and a computer (generic processor) are generally recited and are not qualified as particular machines.
In conclusion, the above additional elements, considered individually and in combination with the other claim elements do not reflect an improvement to other technology or technical field, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
However, the above claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B analysis).
The claims, therefore, are not patent eligible.
With regards to the dependent claims, claims 3, 5-11, 13-15, and 17-20 provide additional features/steps which are part of an expanded algorithm, so these limitations should be considered part of an expanded abstract idea of the independent claims.
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.
Claim(s) 1-3, 5-11, 14, and 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hooshyar (WO 2021213654 A1).
Regarding Claim 1, Hooshyar teaches a computer system comprising a processor device configured to:
retrieve reference data of a reference cell, the reference data including at least one initial aging parameter at beginning of life of the reference cell, and usage conditions of the reference cell including usage condition values (Hooshyar p. 4, Line 1, creating a set of battery usage classifications, wherein each battery usage classification is associated with at least one set of predefined operating parameter ranges, for each battery usage classification, determining at least one expected ageing curve associated with each battery usage classification, classifying the planned usage of the battery unit in accordance with the set of battery usage classifications, wherein the prediction of the expected service life is determined based on the at least one expected ageing curve of the battery usage classification associated with the classified planned usage. Also see p. 4, Line 27, Optionally, the simulation of ageing is performed based on battery cell operational data obtained in battery cell tests, wherein the battery cell tests are carried out for at least one type of battery cell comprised in the battery unit. The battery cell tests may be laboratory battery cell tests. The battery unit may comprise different types of battery cells, in which case battery cell tests for at least some of the different types of cells may be carried out. The battery cell tests may be carried out at least for the battery cell type(s) expected to have a major influence on the ageing behaviour of the battery unit.),
measure at least one initial aging parameter of each electrical energy storage cell of an electrical energy storage system at beginning of life of each electrical energy storage cell, and at least one usage condition value for each electrical energy storage cell (Hooshyar p. 9, Line 26, In a second step S2, carried out during usage of the battery unit 202 within the ESS 200 of the vehicle 201, operational data relating to an actual usage of the battery unit 202 are obtained. This may be realized by collecting measurement data obtained from various sensors and measurement devices of the ESS 200, and also by calculating operational data based on such data.);
predict an aging evolution of each electrical energy storage cell based on the final similarity values (Hooshyar p. 10, Line 1, In a third step S3, an actual service life of the battery unit 202 is predicted based on at least the obtained operational data. The actual service life is herein defined as the time between the beginning of the service life BOL and the end of the service life EOL1 in the first application of the battery unit 202, as illustrated by ageing curves 1, 2, 3 in fig. 4. Also see p. 11, Line 31, Furthermore, the predicted actual service life of the battery unit 202 may be determined based on the expected ageing curve 1, 2 or 3 of the battery usage classification associated with the classified actual usage. See Fig. 2 S3 and Fig. 4), and
provide data indicating the aging evolution of each electrical energy storage cell (Hooshyar p. 10, Line 24, In a further optional step S8, information is provided to the user of the battery unit 202, the information relating to the predicted actual service life of the battery unit 202.).
Hooshyar does not seem to explicitly teach to calculate a first similarity value that indicates a relative relationship between one initial aging parameter for each electrical energy storage cell and the corresponding initial aging parameter at beginning of life of the reference cell,
calculate a second similarity value that indicates a relative relationship between one usage condition value for each electrical energy storage cell and the corresponding usage condition value of the reference cell, and
determine a final similarity value for each electrical energy storage cell based on all similarity values of the respective electrical energy storage cell.
However, Hooshyar teaches predicting the service life of a battery based on comparing measured usage classifications and parameters with reference usage classes and parameters (Hooshyar p. 10, Line 31 – p. 12, Line 8, S1-1) Creating a set of battery usage classifications, wherein each battery usage classification is associated with at least one set of predefined operating parameter ranges. Such usage classifications may include e.g. light, medium and harsh usages, each being associated with predefined operating parameter ranges in terms of e.g. temperature, depth of discharge (DoD), state of charge (SoC), charging rate, and/or charging pattern of the battery unit 202. […] The step S3 of predicting the actual service life of the battery unit 202 may comprise classifying the actual usage of the battery unit 202 in accordance with the set of battery usage classifications. […] Furthermore, the predicted actual service life of the battery unit 202 may be determined based on the expected ageing curve 1, 2 or 3 of the battery usage classification associated with the classified actual usage.).
Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the instant application, to modify Hooshyar to explicitly teach calculate a first similarity value that indicates a relative relationship between one initial aging parameter for each electrical energy storage cell and the corresponding initial aging parameter at beginning of life of the reference cell,
calculate a second similarity value that indicates a relative relationship between one usage condition value for each electrical energy storage cell and the corresponding usage condition value of the reference cell, and
determine a final similarity value for each electrical energy storage cell based on all similarity values of the respective electrical energy storage cell, to explicitly disclose the parameters and conditions that are used to select the right curve to use during estimation of the battery’s service life (see MPEP 2143 I. (E) "Obvious to try" – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success; It would be obvious to be able to show intermediate steps when performing the calculations with real values).
Regarding Claim 2, Hooshyar teaches a computer-implemented method, comprising:
retrieving, by a processor device of a computer system, reference data of a reference cell, the reference data including at least one initial aging parameter at beginning of life of the reference cell, and usage conditions of the reference cell including usage condition values (Hooshyar p. 4, Line 1, creating a set of battery usage classifications, wherein each battery usage classification is associated with at least one set of predefined operating parameter ranges, for each battery usage classification, determining at least one expected ageing curve associated with each battery usage classification, classifying the planned usage of the battery unit in accordance with the set of battery usage classifications, wherein the prediction of the expected service life is determined based on the at least one expected ageing curve of the battery usage classification associated with the classified planned usage. Also see p. 4, Line 27, Optionally, the simulation of ageing is performed based on battery cell operational data obtained in battery cell tests, wherein the battery cell tests are carried out for at least one type of battery cell comprised in the battery unit. The battery cell tests may be laboratory battery cell tests. The battery unit may comprise different types of battery cells, in which case battery cell tests for at least some of the different types of cells may be carried out. The battery cell tests may be carried out at least for the battery cell type(s) expected to have a major influence on the ageing behaviour of the battery unit.),
measuring, by the processor device, at least one initial aging parameter of each electrical energy storage cell of an electrical energy storage system at beginning of life of each electrical energy storage cell, and at least one usage condition value for each electrical energy storage cell (Hooshyar p. 9, Line 26, In a second step S2, carried out during usage of the battery unit 202 within the ESS 200 of the vehicle 201, operational data relating to an actual usage of the battery unit 202 are obtained. This may be realized by collecting measurement data obtained from various sensors and measurement devices of the ESS 200, and also by calculating operational data based on such data.);
predicting, by the processor device, an aging evolution of each electrical energy storage cell based on the final similarity values (Hooshyar p. 10, Line 1, In a third step S3, an actual service life of the battery unit 202 is predicted based on at least the obtained operational data. The actual service life is herein defined as the time between the beginning of the service life BOL and the end of the service life EOL1 in the first application of the battery unit 202, as illustrated by ageing curves 1, 2, 3 in fig. 4. Also see p. 11, Line 31, Furthermore, the predicted actual service life of the battery unit 202 may be determined based on the expected ageing curve 1, 2 or 3 of the battery usage classification associated with the classified actual usage. See Fig. 2 S3 and Fig. 4), and
providing, by the processor device, data indicating the aging evolution of each electrical energy storage cell (Hooshyar p. 10, Line 24, In a further optional step S8, information is provided to the user of the battery unit 202, the information relating to the predicted actual service life of the battery unit 202.).
Hooshyar does not seem to explicitly teach calculating, by the processor device, a first similarity value that indicates a relative relationship between one measured initial aging parameter for each electrical energy storage cell and the corresponding initial aging parameter at beginning of life of the reference cell,
calculating, by the processor device, a second similarity value that indicates a relative relationship between one usage condition value for each electrical energy storage cell and the corresponding usage condition value of the reference cell, and
determining, by the processor device, a final similarity value for each electrical energy storage cell based on all similarity values of the respective electrical energy storage cell.
However, Hooshyar teaches predicting the service life of a battery based on comparing measured usage classifications and parameters with reference usage classes and parameters (Hooshyar p. 10, Line 31 – p. 12, Line 8, S1-1) Creating a set of battery usage classifications, wherein each battery usage classification is associated with at least one set of predefined operating parameter ranges. Such usage classifications may include e.g. light, medium and harsh usages, each being associated with predefined operating parameter ranges in terms of e.g. temperature, depth of discharge (DoD), state of charge (SoC), charging rate, and/or charging pattern of the battery unit 202. […] The step S3 of predicting the actual service life of the battery unit 202 may comprise classifying the actual usage of the battery unit 202 in accordance with the set of battery usage classifications. […] Furthermore, the predicted actual service life of the battery unit 202 may be determined based on the expected ageing curve 1, 2 or 3 of the battery usage classification associated with the classified actual usage.).
Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the instant application, to modify Hooshyar to explicitly teach calculating, by the processor device, a first similarity value that indicates a relative relationship between one measured initial aging parameter for each electrical energy storage cell and the corresponding initial aging parameter at beginning of life of the reference cell,
calculating, by the processor device, a second similarity value that indicates a relative relationship between one usage condition value for each electrical energy storage cell and the corresponding usage condition value of the reference cell, and
determining, by the processor device, a final similarity value for each electrical energy storage cell based on all similarity values of the respective electrical energy storage cell, to explicitly disclose the parameters and conditions that are used to select the right curve to use during estimation of the battery’s service life (see MPEP 2143 I. (E) "Obvious to try" – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success; It would be obvious to be able to show intermediate steps when performing the calculations with real values).
Regarding Claim 3, Hooshyar (as stated above) does not explicitly teach wherein the similarity values for each cell are stored in an indexed way to associate each cell with their similarity values.
However, Hooshyar discloses that the battery unit may comprise different types of cells and different tests may be required for those cells to simulate aging (Hooshyar p. 4, Line 28, Optionally, the simulation of ageing is performed based on battery cell operational data obtained in battery cell tests, wherein the battery cell tests are carried out for at least one type of battery cell comprised in the battery unit. The battery cell tests may be laboratory battery cell tests. The battery unit may comprise different types of battery cells, in which case battery cell tests for at least some of the different types of cells may be carried out. The battery cell tests may be carried out at least for the battery cell type(s) expected to have a major influence on the ageing behaviour of the battery unit.).
It would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the instant application, to modify Hooshyar (as stated above) to explicitly teach wherein the similarity values for each cell are stored in an indexed way to associate each cell with their similarity values, to ensure that the data is properly attributed for analysis and use throughout the predicting of the battery service life (see MPEP 2143 I. (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results; and (E) "Obvious to try" – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success; It is obvious to index data so that it is sorted with at least its origin for future reference.).
Regarding Claim 5, Hooshyar (as stated above) does not explicitly teach wherein the location of the electrical energy storage cell in the electrical energy storage system relative the other electrical energy storage cells includes one index for the position of the cell in the energy storage system indicative of the pack (pth pack), within the pack indicative of the module (mth module) of the pack, and within the module indicating ith row out of ns cells in series, jth column out of np cells in parallel.
However, Hooshyar teaches multiple cells with a battery monitoring unit that is able to analyze each individual cell (Hooshyar p. 8, Line 23, A sensor unit (not shown) may be arranged for collecting operational data, i.e. measurement data relating to operating conditions of the ESS 200 or of individual battery packs 202. […] Measurement data from each sensor unit is transmitted to an associated battery management unit (BMU) 204, which is configured for managing the individual battery pack 202 during operation of the bus 201. The BMU must necessarily be able to distinguish each individual cell in each pack through some organized naming convention).
It would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the instant application, to modify Hooshyar (as stated above) to explicitly teach wherein the location of the electrical energy storage cell in the electrical energy storage system relative the other electrical energy storage cells includes one index for the position of the cell in the energy storage system indicative of the pack (pth pack), within the pack indicative of the module (mth module) of the pack, and within the module indicating ith row out of ns cells in series, jth column out of np cells in parallel.
Regarding Claim 6, Hooshyar (as stated above) further teaches wherein the initial aging parameter is one of initial capacity, initial resistance, and initial heat transfer coefficient of the respective cell (Hooshyar p. 9, Line 32, The operational data may for example include data relating to battery temperature, depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern. Also see p. 8, Line. 29, The BMU 204 can also be configured for determining parameters indicating and controlling the condition or capacity of the battery pack 202, such as the state of charge (SOC), the state of health (SOH), the state of power (SOP) and the state of energy (SOE) of the battery pack 202.).
Regarding Claim 7, Hooshyar (as stated above) further teaches calculating a similarity value for at least two of the initial aging parameters included in the reference data (Hooshyar p. 9, Line 32, The operational data may for example include data relating to battery temperature, depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern. Also see p. 8, Line. 29, The BMU 204 can also be configured for determining parameters indicating and controlling the condition or capacity of the battery pack 202, such as the state of charge (SOC), the state of health (SOH), the state of power (SOP) and the state of energy (SOE) of the battery pack 202. The data may include one up to all of the examples of initial parameters listed, with at least one being capacity, and steps S1-1 to S1-3 describe how the reference curves are determined for comparison for the measured data).
Regarding Claim 8, Hooshyar (as stated above) further teaches calculating a similarity value for each of the initial aging parameters included in the reference data (Hooshyar p. 9, Line 32, The operational data may for example include data relating to battery temperature, depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern. Also see p. 8, Line. 29, The BMU 204 can also be configured for determining parameters indicating and controlling the condition or capacity of the battery pack 202, such as the state of charge (SOC), the state of health (SOH), the state of power (SOP) and the state of energy (SOE) of the battery pack 202. The data may include one up to all of the examples of initial parameters listed, with at least one being capacity, and steps S1-1 to S1-3 describe how the reference curves are determined for comparison for the measured data).
Regarding Claim 9, Hooshyar (as stated above) further teaches wherein the usage conditions include temperature of the cell, operating voltage, energy throughput, current throughput, and ambient temperature, for each cell (Hooshyar p. 9, Line 30, The operational data may for example include measurement data relating to temperature, such as battery temperature and ambient temperature. It may also include operational data relating to depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern of the battery unit 202. ).
Regarding Claim 10, Hooshyar (as stated above) further teaches comprising calculating a similarity value for at least two of the usage conditions (Hooshyar p. 9, Line 30, The operational data may for example include measurement data relating to temperature, such as battery temperature and ambient temperature. It may also include operational data relating to depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern of the battery unit 202. Also see p. 10 Line 31 – p. 11, Line 29. The data may include one up to all of the examples of operational data listed, and steps S1-1 to S1-3 describe how the reference curves are determined for comparison for the measured data).
Regarding Claim 11, Hooshyar (as stated above) further teaches comprising calculating a similarity value for each of the usage conditions (Hooshyar p. 9, Line 30, The operational data may for example include measurement data relating to temperature, such as battery temperature and ambient temperature. It may also include operational data relating to depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern of the battery unit 202. Also see p. 10 Line 31 – p. 11, Line 29. The data may include one up to all of the examples of operational data listed, and steps S1-1 to S1-3 describe how the reference curves are determined for comparison for the measured data).
Regarding Claim 14, Hooshyar (as stated above) does not explicitly teach wherein each electrical energy storage cell is assigned a unique similarity value.
However, Hooshyar teaches that the battery unit may comprise different types of cells and different tests may be required for those cells to simulate aging (Hooshyar p. 4, Line 28, Optionally, the simulation of ageing is performed based on battery cell operational data obtained in battery cell tests, wherein the battery cell tests are carried out for at least one type of battery cell comprised in the battery unit. The battery cell tests may be laboratory battery cell tests. The battery unit may comprise different types of battery cells, in which case battery cell tests for at least some of the different types of cells may be carried out. The battery cell tests may be carried out at least for the battery cell type(s) expected to have a major influence on the ageing behaviour of the battery unit.).
Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the instant application, to modify Hooshyar (as stated above) to explicitly teach wherein each electrical energy storage cell is assigned a unique similarity value, because each individual cell will have its own parameters that are analyzed for that particular cell.
Regarding Claim 17, Hooshyar (as stated above) further teaches a vehicle comprising the processor device to perform the method of claim 2 (Hooshyar p. 9, Line 13, A method for monitoring battery ageing of a battery unit in an energy storage system of a vehicle, such as of the battery pack 202 in the ESS 200 of the bus 201 illustrated in fig. 1).
Regarding Claim 18, Hooshyar (as stated above) further teaches a computer program product comprising program code for performing, when executed by the processor device, the method of claim 2 (Hooshyar p. 12, Line 17, Embodiments within the scope of the present disclosure include program products comprising machine- readable medium for carrying or having machine-executable instructions or data structures stored thereon.).
Regarding Claim 19, Hooshyar (as stated above) further teaches control system comprising one or more control units configured to perform the method of claim 2 (Hooshyar p. 12, Line 15, The control functionality of the example embodiments may be implemented using existing computer processors, or by a special purpose computer processor for an appropriate system, incorporated for this or another purpose, or by a hardwire system.).
Regarding Claim 20, Hooshyar (as stated above) further teaches a computer program product comprising program code for performing, when executed by the processor device, the method of claim 2 (Hooshyar p. 12, Line 17, Embodiments within the scope of the present disclosure include program products comprising machine- readable medium for carrying or having machine-executable instructions or data structures stored thereon. […] By way of example, such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer or other machine with a processor.).
Claim(s) 4 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hooshyar (as stated above) in view of Stocker et al. (WO 2022171993 A1), hereinafter “Stocker”.
Regarding Claim 4, Although Hooshyar teaches a battery management unit, Hooshyar (as stated above) is not relied upon to explicitly teach adapting control strategies for a management system of the electrical energy storage system using the predicted aging evolution as input to reduce an ageing pace of the electrical energy storage system.
Stocker teaches adapting control strategies for a management system of the electrical energy storage system using the predicted aging evolution as input to reduce an ageing pace of the electrical energy storage system (Stocker p. 28, Line 19, An electric vehicle’s battery management system 14 may manage battery usage (e.g. charge and discharge rates may be altered, maximum charge may be altered, etc.) according to battery health data. Battery health data may be input to the battery management system following a battery health check undertaken during a vehicle service or safety inspection. Also see p. 29, Line 9, The battery management system 14 may be configured to manage various aspects of battery usage, including for example maximum power consumption or maximum battery temperature, according to certain limits determined by the battery health data. For example, a battery management system may be configured to reduce the maximum possible power consumption of a battery in order to protect the battery once the battery health data indicates that the battery has degraded a certain amount.).
It would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the instant application, to modify Hooshyar (as stated above) in view of Stocker to explicitly teach adapting control strategies for a management system of the electrical energy storage system using the predicted aging evolution as input to reduce an ageing pace of the electrical energy storage system, to use the battery management unit to both perform health checks of the battery and make adjustments accordingly (Stocker p. 29, Line 34, On-board battery health checks may be integrated with the battery management system 14 to manage battery usage according to the gathered battery health data.).
Regarding Claim 16, Hooshyar (as stated above) further teaches wherein the reference data includes initial aging parameters being initial capacity, initial resistance, and initial heat transfer coefficient of the respective cell (Hooshyar p. 9, Line 32, The operational data may for example include data relating to battery temperature, depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern. Also see p. 8, Line. 29, The BMU 204 can also be configured for determining parameters indicating and controlling the condition or capacity of the battery pack 202, such as the state of charge (SOC), the state of health (SOH), the state of power (SOP) and the state of energy (SOE) of the battery pack 202.), and
wherein the usage conditions include temperature, operating voltage, energy throughput, current throughput, and ambient temperature for each cell (Hooshyar p. 9, Line 30, The operational data may for example include measurement data relating to temperature, such as battery temperature and ambient temperature. It may also include operational data relating to depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern of the battery unit 202. ), the method comprising:
calculating a similarity value for each of the initial aging parameters (Hooshyar p. 9, Line 32, The operational data may for example include data relating to battery temperature, depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern. Also see p. 8, Line. 29, The BMU 204 can also be configured for determining parameters indicating and controlling the condition or capacity of the battery pack 202, such as the state of charge (SOC), the state of health (SOH), the state of power (SOP) and the state of energy (SOE) of the battery pack 202. The data may include one up to all of the examples of initial parameters listed, with at least one being capacity, and steps S1-1 to S1-3 describe how the reference curves are determined for comparison for the measured data), and
calculating a similarity value for each of the usage conditions (Hooshyar p. 9, Line 30, The operational data may for example include measurement data relating to temperature, such as battery temperature and ambient temperature. It may also include operational data relating to depth of discharge (DoD), state of charge (SoC), charging rate, and charging pattern of the battery unit 202. Also see p. 10 Line 31 – p. 11, Line 29. The data may include one up to all of the examples of operational data listed, and steps S1-1 to S1-3 describe how the reference curves are determined for comparison for the measured data).
Although Hooshyar teaches a battery management unit, Hooshyar (as stated above) is not relied upon to explicitly teach adapting control strategies for a management system of the electrical energy storage system using the predicted aging evolution as input to reduce an ageing pace of the electrical energy storage system.
Stocker teaches adapting control strategies for a management system of the electrical energy storage system using the predicted aging evolution as input to reduce an ageing pace of the electrical energy storage system (Stocker p. 28, Line 19, An electric vehicle’s battery management system 14 may manage battery usage (e.g. charge and discharge rates may be altered, maximum charge may be altered, etc.) according to battery health data. Battery health data may be input to the battery management system following a battery health check undertaken during a vehicle service or safety inspection. Also see p. 29, Line 9, The battery management system 14 may be configured to manage various aspects of battery usage, including for example maximum power consumption or maximum battery temperature, according to certain limits determined by the battery health data. For example, a battery management system may be configured to reduce the maximum possible power consumption of a battery in order to protect the battery once the battery health data indicates that the battery has degraded a certain amount.).
It would have been obvious to one of ordinary skill in the art, prior to the effective filing date of the instant application, to modify Hooshyar (as stated above) in view of Stocker to explicitly teach adapting control strategies for a management system of the electrical energy storage system using the predicted aging evolution as input to reduce an ageing pace of the electrical energy storage system, to use the battery management unit to both perform health checks of the battery and make adjustments accordingly (Stocker p. 29, Line 34, On-board battery health checks may be integrated with the battery management system 14 to manage battery usage according to the gathered battery health data.).
Examiner notes that there are currently no prior art rejections for claims 12, 13, and 15.
Allowable Subject Matter
Claim 12 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: The Cited prior art of record, as best understood by the Examiner, does not seem to fairly teach or suggest applying a physical model of the electrical energy storage system layout including active or passive coolant flow for modelling a temperature of each electrical energy storage cell as a function of position of the electrical energy storage cell in the electrical energy storage system, and calculating the corresponding similarity values based on relative relationships between the modelled temperatures of each cell compared to the temperature of the reference cell according to the retrieved usage condition data.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Yoon (US 20210148985 A1) discloses a Device And Method For Analyzing Soh.
Petisme et al. (US 20230176137 A1) discloses a Method And System For Determining A Remaining Useful Lifetime Of A Battery.
Arzberger (US 20230033057 A1) discloses a Method, Apparatus And Computer Program Product For Estimating The Service Life Of Battery Storage Systems.
Hinterberger et al. (US 20200225291 A1) discloses a Measurement Arrangement, High-Voltage Battery, Motor Vehicle And Method For Determining A Complex Impedance.
Battery University (BU-908: Battery Management System (BMS), BatteryUniversity.com, 4 November 2021) discloses Battery Management System basics.
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/CHRISTIAN T BRYANT/Examiner, Art Unit 2863