Prosecution Insights
Last updated: April 19, 2026
Application No. 18/454,674

METHOD AND APPARATUS FOR ESTIMATING INTERNAL STATE OF BATTERY BY USING ELECTROCHEMICAL MODEL OF BATTERY

Non-Final OA §101§102§103§DP
Filed
Aug 23, 2023
Examiner
COONS, LOGAN DOUGLAS
Art Unit
2857
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Samsung Electronics
OA Round
1 (Non-Final)
Grant Probability
Favorable
1-2
OA Rounds
2y 6m
To Grant

Examiner Intelligence

Grants only 0% of cases
0%
Career Allow Rate
0 granted / 0 resolved
-68.0% vs TC avg
Minimal +0% lift
Without
With
+0.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
14 currently pending
Career history
14
Total Applications
across all art units

Statute-Specific Performance

§101
30.4%
-9.6% vs TC avg
§103
34.8%
-5.2% vs TC avg
§102
17.4%
-22.6% vs TC avg
§112
13.0%
-27.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 0 resolved cases

Office Action

§101 §102 §103 §DP
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 . Foreign Priority Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed. DETAILED ACTION The following NON-FINAL Office Action is in response to application 18/454,674 filed on 08/23/2023. This communication is the first action on the merits. Status of Claims Claims 1-15 are currently pending and have been rejected as follows. Drawings The drawings filed on 08/23/2023 are accepted. IDS The information disclosure statements filed on 07/09/2024 and 07/24/2024 comply with the provisions of 37 CFR 1.97, 1.98 and MPEP § 609 and are considered. Claim Rejections – Double Patenting – 35 USC § 101 Non-Statutory The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. Claims 1, 3-9 and 11-15 are rejected on the grounds of provisional nonstatutory double patenting as being unpatentable over claims 1, 4-9 and 12-15 of co-pending patent application 18/456,113 (hereinafter “’113”). Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1, 3-9 and 11-15 are anticipated by claims 1, 4-9 and 12-15 of the ‘113 patent. Instant application Claim 1 ‘113 Claim 1 A method of estimating an internal state of a battery, the method comprising: acquiring at least one parameter of the battery; A method of diagnosing battery abnormalities comprising: acquiring at least one parameter of a battery and estimating the internal state of the battery by using an electrochemical model based on the at least one parameter the electrochemical model comprising a model configured to… estimate an internal state of the battery by using a difference between the internal lithium ion concentrations of the cathode and the anode. the electrochemical model being calculated based on a single particle model (SPM) with respect to a cathode and an anode of the battery an electrochemical model calculated based on a single particle model of a cathode and an anode of the battery wherein the electrochemical model comprises a model configured to calculate inner lithium-ion concentrations in the cathode and the anode based on a difference between diffusion of lithium ions in the cathode and the anode of the battery the electrochemical model comprising a model configured to calculate internal lithium ion concentrations of the cathode and the anode by considering a difference in diffusion of lithium ions between the cathode and the anode of the battery and to estimate the internal state of the battery based on the difference between the inner lithium-ion concentrations in the cathode and the anode. and to estimate an internal state of the battery by using a difference between the internal lithium ion concentrations of the cathode and the anode. Claim 2 The method of claim 1, wherein the at least one parameter comprises at least one of a voltage, a current, and a temperature of the battery. Claim 3 Claim 4 The method of claim 1, wherein the electrochemical model comprises a model configured to calculate inner lithium-ion concentrations in the cathode and the anode of the battery by discretizing the SPM with respect to the cathode and the anode of the battery into spheres each having a plurality of layers. The method of claim 1, wherein the electrochemical model comprises a model configured to calculate the internal lithium ion concentrations of the cathode and the anode of the battery by discretizing the single particle model of the cathode and the anode of the battery into a sphere having a plurality of layers Claim 4 Claim 4 The method of claim 3, wherein the electrochemical model comprises a model configured to calculate the inner lithium-ion concentrations in the cathode and the anode of the battery based on a diffusion coefficient according to concentration distributions in the cathode and the anode of the battery the electrochemical model comprises a model configured to calculate the internal lithium ion concentrations of the cathode and the anode of the battery… by using a diffusion coefficient according to concentration distributions of the cathode and the anode of the battery and wherein the diffusion coefficient is based on a concentration and a temperature of each layer from among the plurality of layers in the SPMs for the cathode and the anode of the battery. the diffusion coefficient being determined according to a concentration and a temperature of each layer of the plurality of layers of the single particle model Claim 5 Claim 5 The method of claim 3, wherein the electrochemical model comprises a model that estimates a voltage of the battery based on an overpotential value defined as a difference between a measured voltage of the battery and an open-circuit voltage (OCV) of the battery. The method of claim 4, wherein the electrochemical model comprises a model configured to estimate a voltage of the battery based on a value of an overpotential that is a difference between a measured voltage of the battery and an open-circuit voltage of the battery. Claim 6 Claim 6 The method of claim 5, wherein the electrochemical model comprises a model configured to calculate a priori overpotential value based on information about lithium-ion concentration in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery The method of claim 5, wherein the electrochemical model comprises a model configured to calculate a value of a priori overpotential by using information regarding a lithium ion concentration of an outermost layer from among the plurality of layers of the single particle model information about an average lithium-ion concentration in the cathode and the anode of the battery, information regarding an average lithium ion concentration of the cathode and the anode of the battery and voltage drop information of the battery, and to calculate the overpotential value based on the priori overpotential value and an overpotential proportional coefficient. and voltage drop information of the battery, and to calculate the value of the overpotential by using the value of the priori overpotential and a predetermined overpotential proportional coefficient Claim 7 Claim 7 The method of claim 6, wherein the overpotential proportional coefficient is an experimental value that simulates a relationship between the priori overpotential value and the overpotential value in a Butler-Volmer equation by using curve fitting. The method of claim 6, wherein the predetermined overpotential proportional coefficient comprises an experimental value for simulating, with a Butler-Volmer equation, a relationship between the value of the priori overpotential and the value of the overpotential by using curve fitting. Claim 8 Claim 8 A computer-readable program stored in a recording medium for executing the method according to claim 1 by using a computing device. A computer program stored in a recording medium to execute the method of claim 1 by using a computing apparatus. Claim 9 Claim 9 An apparatus for estimating an internal state of a battery, the apparatus comprising: a memory configured to store data that is generated by measuring at least one parameter of the battery; An apparatus for diagnosing battery abnormalities, the apparatus comprising: a memory configured to store data generated by measuring at least one parameter of a battery and a processor configured to estimate the internal state of the battery by using an electrochemical model that is calculated based on a single particle model (SPM) with respect to a cathode and an anode of the battery based on the at least one parameter and a processor configured to… estimate an internal state of the battery… by using an electrochemical model calculated based on a single particle model of a cathode and an anode of the battery… based on the at least one parameter wherein the electrochemical model comprises a model configured to calculate inner lithium-ion concentrations in the cathode and the anode based on a difference between diffusion of lithium ions in the cathode and the anode of the battery the electrochemical model comprising a model configured to calculate internal lithium ion concentrations of the cathode and the anode by considering a difference in diffusion of lithium ions between the cathode and the anode of the battery and estimates the internal state of the battery based on the difference between the inner lithium-ion concentrations in the cathode and the anode. and to estimate an internal state of the battery by using a difference between the internal lithium ion concentrations of the cathode and the anode. Claim 10 The apparatus of claim 9, wherein the at least one parameter comprises at least one of a voltage, a current, and a temperature of the battery. Claim 11 Claim 12 The apparatus of claim 9, wherein the electrochemical model comprises a model that calculates inner lithium-ion concentrations in the cathode and the anode of the battery by discretizing the SPM with respect to the cathode and the anode of the battery into spheres each having a plurality of layers. The apparatus of claim 9, wherein the electrochemical model comprises a model configured to calculate the internal lithium ion concentrations of the cathode and the anode of the battery by discretizing a single particle model of the cathode and the anode of the battery into a sphere having a plurality of layers Claim 12 Claim 12 The apparatus of claim 11, wherein the electrochemical model comprises a model configured to calculate the inner lithium-ion concentrations in the cathode and the anode of the battery based on a diffusion coefficient according to concentration distributions in the cathode and the anode of the battery, the electrochemical model comprising a model configured to calculate the internal lithium ion concentrations of the cathode and the anode of the battery by using a diffusion coefficient according to concentration distributions of the cathode and the anode of the battery and wherein the diffusion coefficient is based on a concentration and a temperature of each layer from among the plurality of layers in the SPM for the cathode and the anode of the battery. the diffusion coefficient being determined according to a concentration and a temperature of each layer of the plurality of layers of the single particle model. Claim 13 Claim 13 The apparatus of claim 11, wherein the electrochemical model comprises a model that estimates a voltage of the battery based on an overpotential value that is a difference between a measured voltage of the battery and an open-circuit voltage (OCV) of the battery. The apparatus of claim 12, wherein the electrochemical model comprises a model configured to estimate a voltage of the battery based on a value of an overpotential that is a difference between a measured voltage of the battery and an open-circuit voltage of the battery. Claim 14 Claim 14 The apparatus of claim 13, wherein the electrochemical model comprises a model configured to calculate a priori overpotential value based on information about lithium-ion concentration in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery The apparatus of claim 13, wherein the electrochemical model comprises a model configured to calculate a value of a priori overpotential by using information regarding a lithium ion concentration of an outermost layer from among the plurality of layers of the single particle model, information about an average lithium-ion concentration in the cathode and the anode of the battery, information regarding an average lithium ion concentration of the cathode and the anode of the battery and voltage drop information of the battery, and to calculate the overpotential value by using the priori overpotential value and an overpotential proportional coefficient. and voltage drop information of the battery, and to calculate the value of the overpotential by using the value of the priori overpotential and a predetermined overpotential proportional coefficient. Claim 15 Claim 15 The apparatus of claim 14, wherein the overpotential proportional coefficient is an experimental value that simulates a relationship between the priori overpotential value and the overpotential value in a Butler-Volmer equation by using curve fitting. The apparatus of claim 14, wherein the predetermined overpotential proportional coefficient comprises an experimental value for simulating, with a Butler-Volmer equation, a relationship between the value of the priori overpotential and the value of the overpotential by using curve fitting. In terms of the table above, each of the representative claims 1 and 9 are anticipated by claims 1 and 9 of ‘113. The dependent claim limitations not anticipated by ‘113 are identified in bold. However, in an analogous art, Howey is directed to providing a method and apparatus for estimating and controlling battery state. Therein Howey teaches wherein the at least one parameter comprises at least one of a voltage, a current, and a temperature of the battery; (Howey, para. [0017]; [“The present usage environment may include any one or any combination of any two or more of a current, a voltage, and a temperature of the battery.”] It would have been to one of ordinary skill in the art in view of the teachings of Howey to modify the processes of claims 1 and 9 by combining prior art elements according to known methods to yield predictable results (See MPEP Section 2143: Examples of Basic Requirements of a Prima Facie Case of Obviousness) given that, when diagnosing battery abnormalities and estimating the internal state of a battery using an electrochemical model, one of ordinary skill in the art would find it obvious to use at least one parameter comprising at least one voltage, a current, and a temperature of the battery. Therefore, claims 2 and 10, are obvious over the combination of the claims in ‘113 in view of Howey. 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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. A subject matter eligibility analysis is set forth below. See MPEP 2106. Representative Claim 1 recites: A method of estimating an internal state of a battery, the method comprising: acquiring at least one parameter of the battery; and estimating the internal state of the battery by using an electrochemical model based on the at least one parameter, the electrochemical model being calculated based on a single particle model (SPM) with respect to a cathode and an anode of the battery, wherein the electrochemical model comprises a model configured to calculate inner lithium-ion concentrations in the cathode and the anode based on a difference between diffusion of lithium ions in the cathode and the anode of the battery and to estimate the internal state of the battery based on the difference between the inner lithium-ion concentrations in the cathode and the anode. The claim limitations in the abstract idea have been highlighted in bold; the remaining limitations are “additional elements.” Similar limitations comprise the abstract ideas of claim 9. Under Step 1 of the analysis, claim 1 does belong to a statutory category, namely it is a process claim. Likewise, claim 9 is an apparatus claim. Under Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. Under Step 2A, Prong One, the broadest reasonable interpretation consistent with the specification of the steps recited in Claim 1 include at least one judicial exception, that being a mathematical process and/or mental step. This can be seen in the claimed process steps of “estimating the internal state of the battery by using an electrochemical model…” (See, for example, paras. [0064-0065] of the instant specification), and “the electrochemical model being calculated based on a single particle model (SPM)…” (See, for example, paras. [0057-0060], Equations 1-7 of the instant specification), and “wherein the electrochemical model comprises a model configured to calculate inner lithium-ion concentrations in the cathode and the anode based on a difference between diffusion of lithium ions in the cathode and the anode of the battery and to estimate the internal state of the battery based on the difference between the inner lithium-ion concentrations in the cathode and the anode…” (See, for example, paras. [0064-0066], Equations 8-11), each of which encompasses mathematical concepts requiring specific mathematical calculations to perform the methods described. In the alternative, or additionally, each of the recited judicial exceptions may be considered a mental process because they merely comprise data evaluations including calculations, capable of being performed using a pen and paper. Under the broadest reasonable interpretation, consistent with the specification, upon receipt of battery data such as state of charge (SOC)-open circuit voltage (OCV), charging/discharging current, terminal voltage and/or temperature, remaining battery capacity, discharge rate, etc…, a human would be capable of calculating the inner lithium-ion concentrations in the cathode and the anode based on a difference between the diffusion of lithium ions in the cathode and the anode of the battery and estimating the internal state of the battery based on the difference between the inner lithium-ion concentrations in the cathode and the anode using pen and paper and Equations 1-12 recited in the instant specification. While such calculations by pen and paper may be time consuming, they fall in the “mental processes” abstract idea grouping. Noting MPEP 2106.04(a)(2)(0I) “MENTAL PROCESSES,” “The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper” to be an abstract idea.” CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). Step 2A, Prong Two of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception(s) into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. 2019 PEG Section III(A)(2), 84 Fed. Reg. at 54-55. Each of the process steps “acquiring,” “estimating,” “calculate,” are recited as being performed by a computer “One or more of the above embodiments may be implemented in the form of a computer program that may be run in and/or executed by a computer through various elements, and the computer program may be recorded on a non-transitory computer-readable recording medium. Here, the medium may permanently (e.g., continuously) store the computer-executable program or temporarily store the computer-executable program for execution or downloading. In addition, the medium may be various recording units or storage units in the form of a single or several pieces of hardware combined with one another, and is not limited to a medium directly connecting to a certain computer system, but may be distributed over a network.” (See, for example, para. [0086] of the instant specification), and “there is provided an apparatus for estimating an internal state of a battery, the apparatus including: a memory configured to store data that is generated by measuring at least one parameter of the battery; and a processor configured to estimate the internal state of the battery by using an electrochemical model that is calculated based on a single particle model (SPM) with respect to a cathode and an anode of the battery based on the at least one parameter, wherein the electrochemical model includes a model configured to calculate inner lithium-ion concentrations in the cathode and the anode based on a difference between diffusion of lithium ions in the cathode and the anode of the battery and estimates the internal state of the battery based on the difference between the inner lithium-ion concentrations in the cathode and the anode.” (See, for example, para. [0016] of the instant specification). The computer is recited at a high level of generality (“processor”), and the computer is used as a tool to perform the generic computer functions as “the processor 150 controls overall operations of the apparatus for estimating the internal state of the battery” (See, for example, para. [0041] of the instant specification), which includes collecting data/information in the form of voltage, current and temperature (See, for example, para. [0034], FIG. 1, components 150, 120, 130, 140 of the instant specification) as “the processor 150 may perform basic arithmetic operations, logic operations, and input/output operations, for example, and may execute program codes stored in the memory 160. The processor 150 may store data in the memory 160 or load data stored in the memory 160.” (See, for example, para. [0042], FIG. 1 of the instant specification). Given the broadest reasonable interpretation in light of the specification, “acquiring” at least one parameter of the battery merely involves the use of a generic computer processing technology as “at least one parameter of the battery 110 denotes a component or a variable such as a terminal voltage, charging/discharging currents, and/or peripheral temperature of the battery 110.” (See, for example, para. [0043] of the instant specification), which doesn’t integrate the claim into a practical application. The step of “acquiring” is merely an insignificant extra solution activity namely collecting data/information for calculating the internal state of the battery. Claim 9 is analogous to claim 1. Additionally, claim 9 recites an apparatus comprising “a memory configured to store data that is generated by measuring at least one parameter of the battery; and a processor configured to estimate the internal state of the battery.” (See, for example, paras. [0042-0043], FIG. 1 of the instant specification). Thus, under Prong two, the recited generic computer components do not integrate the claimed subject matter into a particular practical application. Therefore, claim 9 is also ineligible and rejected under 35 U.S.C. 101. The recited additional elements can also be viewed as nothing more than an attempt to generally link the use of the judicial exceptions to the technological environment of a computer. Noting MPEP 2106.04(d)(I): “It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2A Prong Two. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception does not guarantee eligibility. Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 224, 110, USPQ2d 1976, 1983-84 (2014) (“The fact that a computer ‘necessarily exist[s] in the physical, rather than purely conceptual, realm, is beside the point”)”. Thus, under Step 2A, Prong Two, even when viewed in combination, these additional elements recited in claim 1, as well as claim 9, do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. No specific practical application is associated with the claimed method. For instance, nothing is done once the internal state of the battery is estimated. Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as described above with respect to Step 2A Prong Two, merely amount to a general purpose computer system that attempts to apply the abstract idea in a technological environment, limiting the abstract idea to a particular field of use, and/or merely insignificant extra-solution activity (Claims 1 and 9). Such insignificant extra-solution activity, e.g. data/information gathering, when re-evaluated under Step 2B is further found to be well-understood, routine and conventional as evidenced by MPEP 2106.05(d)(II) (describing conventional activities that include transmitting and receiving data over a network, electronic recordkeeping, storing and retrieving information from memory, and electronically scanning or extracting data from a physical document). Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fail to necessitate a conclusion that claims 1 and 9 amount to significantly more than the abstract idea. Therefore, claims 1 and 9 are rejected under 35 U.S.C. 101. Regarding dependent claims 2-8 and 10-15, these claims merely provide additional features/steps which are part of an expanded calculation model(s) and/or the generic equipment/components, so these limitations should be considered as more “insignificant extra-solution activity” and/or part of an expanded abstract idea of the independent claims. Therefore, these claims are found ineligible for the reasons described for parent claims 1 and 9. Regarding Claim 8, the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because the recited claim limitations of computer-readable program stored in a recording medium fail at Step 1 of the analysis given that it encompasses ineligible transitory signals. In Mentor Graphics v. EVE-USA, Inc., 851 F.3d 1275, 112 USPQ2d 1120 (Fed. Cir. 2017), claim interpretation was crucial to the court’s determination that claims to a “machine-readable medium” were not to a statutory category. In Mentor Graphics, the court interpreted the claims in light of the specification, which expressly defined the medium as encompassing “any data storage device” including random-access memory and carrier waves. Although random-access memory and magnetic tape are statutory media, carrier waves are not because they are signals similar to the transitory, propagating signals held to be non-statutory in Nuijten. 851 F.3d at 1294, 112 USPQ2d at 1133 (citing In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007)). Accordingly, because the broadest reasonable interpretation of the claims limitations in claim 8 mentioned above cover subject matter that does not fall into a statutory category, the claim as a whole thus fails the first criterion for eligibility. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claims 1-2 and 8-10 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Howey, U.S. Patent Publication US 2018/0198300 A1. Regarding Claim 1, Howey teaches a method of estimating an internal state of a battery (Howey, Abstract), where the method comprises: acquiring at least one parameter of the battery; (Howey, para. [0011]; [“The acquiring of the one or more parameters may include acquiring any one or any combination of any two or more of a diffusion time constant of a cathode of the battery, a diffusion time constant of an anode of the battery, and a charge transfer resistance, and the diffusion time constants and the charge transfer resistance correspond to the previous state.”]); and estimating the internal state of the battery by using an electrochemical model based on the at least one parameter; (Howey, para. [0014]; [“The electrochemical model is defined by a single particle model (SPM) and is expressed by the simplified parameters, and the simplified parameters may include…”]); (Howey, para. [0012]; [“The acquiring of the one or more parameters may include acquiring one or more parameters corresponding to the previous state from either one or both of a table generated by mapping the simplified parameters to states of the battery and a function that defines a relationship between the simplified parameters and the states, and a state of the battery may include either one or both of a state of charge (SOC) and a state of health (SOH) of the battery.”]); the electrochemical model being calculated based on a single particle model (SPM) with respect to a cathode and an anode of the battery; (Howey, para. [0014]; [“The electrochemical model is defined by a single particle model (SPM) and is expressed by the simplified parameters, and the simplified parameters may include any one or any combination of any two or more of a diffusion time constant of a cathode of the battery, a diffusion time constant of an anode of the battery, a kinetics time constant of the cathode, a kinetics time constant of the anode, a maximum theoretical electrode capacity of the cathode, and a maximum theoretical electrode capacity of the anode.”]); wherein the electrochemical model comprises a model configured to calculate inner lithium-ion concentrations in the cathode and the anode based on a difference between diffusion of lithium ions in the cathode and the anode of the battery; (Howey, para. [0047]; [“In this example, an electrode of the battery includes an active material that is a lithium compound, and the active material includes lithium ions (Li+).”]); (Howey, para. [0057], [Equation 1]; [“In the electrochemical model to which the SPM is applied, a diffusion of lithium in an active material of each of electrodes i (for example, an anode or a cathode) of a battery is governed by a Fickian diffusion equation expressed by Equation 1 in spherical coordinates.”]); PNG media_image1.png 50 306 media_image1.png Greyscale (Howey, para. [0058]; [“In Equation 1, ri denotes radial coordinates, ci denotes a lithium concentration profile, and Di denotes a lithium diffusion coefficient (assumed uniform) in an electrode i. The subscript i has either a positive value or negative value to represent a cathode domain or anode domain, respectively.”]); and to estimate the internal state of the battery based on the difference between the inner lithium-ion concentrations in the cathode and the anode; (Howey, para. [0047]; [“In this example, an electrode of the battery includes an active material that is a lithium compound, and the active material includes lithium ions (Li+).”]); (Howey, para. [0057], [Equation 1]; [“In the electrochemical model to which the SPM is applied, a diffusion of lithium in an active material of each of electrodes i (for example, an anode or a cathode) of a battery is governed by a Fickian diffusion equation expressed by Equation 1 in spherical coordinates.”]); PNG media_image1.png 50 306 media_image1.png Greyscale (Howey, para. [0058]; [“In Equation 1, ri denotes radial coordinates, ci denotes a lithium concentration profile, and Di denotes a lithium diffusion coefficient (assumed uniform) in an electrode i. The subscript i has either a positive value or negative value to represent a cathode domain or anode domain, respectively.”]); (Howey, para. [0081]; [“As described above…the battery state estimation apparatus estimates a present state of a battery using the electrochemical model…”]). Regarding Claim 2, Howey teaches the method of claim 1, wherein the at least one parameter comprises at least one of a voltage, a current, and a temperature of the battery; (Howey, para. [0017]; [“The present usage environment may include any one or any combination of any two or more of a current, a voltage, and a temperature of the battery.”] Regarding Claim 8, Howey teaches a computer-readable program stored in a recording medium for executing the method according to claim 1 by using a computing device; (Howey, para. [0045]; [“Referring to FIG. 1, in operation 101, a battery state estimation apparatus acquires parameters for estimating a present state (i.e., a current state) of a battery based on a previous state of the battery. The battery state estimation apparatus is an apparatus for estimating a battery state and is implemented as, for example, a processor(s) module configured to execute instructions stored on a non-transitory computer readable medium, a hardware module, or a combination thereof.]”); (Howey, para. [0147]; [“The instructions or software to control computing hardware, for example, one or more processors or computers, to implement the hardware components and perform the methods as described above, and any associated data, data files, and data structures, may be recorded, stored, or fixed in or on one or more non-transitory computer-readable storage media.”]). Regarding Claim 9, Howey teaches an apparatus for estimating an internal state of a battery, the apparatus comprising: a memory configured to store data that is generated by measuring at least one parameter of the battery; and a processor configured to…in the description of (Howey, para. [0045], FIG. 1; [“operation 101, a battery state estimation apparatus acquires parameters for estimating a present state (i.e., a current state) of a battery based on a previous state of the battery. The battery state estimation apparatus is an apparatus for estimating a battery state and is implemented as, for example, a processor(s) module configured to execute instructions stored on a non-transitory computer readable medium, a hardware module, or a combination thereof.]”); (Howey, para. [0147]; [“The instructions or software to control computing hardware, for example, one or more processors or computers, to implement the hardware components and perform the methods as described above, and any associated data, data files, and data structures, may be recorded, stored, or fixed in or on one or more non-transitory computer-readable storage media.”]); where a processor is configured to estimate the internal state of the battery by using an electrochemical model that is calculated based on a single particle model (SPM) with respect to a cathode and an anode of the battery based on the at least one parameter; (Howey, summary para. [0014]; [“The electrochemical model is defined by a single particle model (SPM) and is expressed by the simplified parameters, and the simplified parameters may include…”]); (Howey, para. [0012]; [“The acquiring of the one or more parameters may include acquiring one or more parameters corresponding to the previous state from either one or both of a table generated by mapping the simplified parameters to states of the battery and a function that defines a relationship between the simplified parameters and the states, and a state of the battery may include either one or both of a state of charge (SOC) and a state of health (SOH) of the battery.”]); (Howey, para. [0014]; [“The electrochemical model is defined by a single particle model (SPM) and is expressed by the simplified parameters, and the simplified parameters may include any one or any combination of any two or more of a diffusion time constant of a cathode of the battery, a diffusion time constant of an anode of the battery, a kinetics time constant of the cathode, a kinetics time constant of the anode, a maximum theoretical electrode capacity of the cathode, and a maximum theoretical electrode capacity of the anode.”]); wherein the electrochemical model comprises a model configured to calculate inner lithium-ion concentrations in the cathode and the anode based on a difference between diffusion of lithium ions in the cathode and the anode of the battery and estimates the internal state of the battery based on the difference between the inner lithium-ion concentrations in the cathode and the anode; (Howey, para. [0047]; [“In this example, an electrode of the battery includes an active material that is a lithium compound, and the active material includes lithium ions (Li+).”]); (Howey, para. [0057], [Equation 1]; [“In the electrochemical model to which the SPM is applied, a diffusion of lithium in an active material of each of electrodes i (for example, an anode or a cathode) of a battery is governed by a Fickian diffusion equation expressed by Equation 1 in spherical coordinates.”]); PNG media_image1.png 50 306 media_image1.png Greyscale (Howey, para. [0058]; [“In Equation 1, ri denotes radial coordinates, ci denotes a lithium concentration profile, and Di denotes a lithium diffusion coefficient (assumed uniform) in an electrode i. The subscript i has either a positive value or negative value to represent a cathode domain or anode domain, respectively.”]); (Howey, para. [70]; [“As described above…the battery state estimation apparatus estimates a present state of a battery using the electrochemical model…”]). Regarding Claim 10, Howey teaches the apparatus of claim 9, wherein the at least one parameter comprises at least one of a voltage, a current, and a temperature of the battery; (Howey, para. [0017]; [“The present usage environment may include any one or any combination of any two or more of a current, a voltage, and a temperature of the battery.”]). Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103, which forms the basis for all obviousness rejections set forth in this Office Action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 3-5 and 11-13 are rejected under 35 U.S.C. 103 as being unpatentable over Howey; in view of Hao (hereinafter “Hao”) U.S. Patent Publication No. US 2023/0280404 A1. Regarding Claim 3, Howey teaches the method of claim 1, wherein the electrochemical model comprises a model configured to calculate inner lithium-ion concentrations in the cathode and the anode of the battery…(Howey, para. [0047]; [“In this example, an electrode of the battery includes an active material that is a lithium compound, and the active material includes lithium ions (Li+).”]); PNG media_image1.png 50 306 media_image1.png Greyscale (Howey, para. [0058]; [“In Equation 1, ri denotes radial coordinates, ci denotes a lithium concentration profile, and Di denotes a lithium diffusion coefficient (assumed uniform) in an electrode i. The subscript i has either a positive value or negative value to represent a cathode domain or anode domain, respectively”]). Howey teaches the limitations of the parent claim as well as the limitations of claim 3 described above. However, Howey fails to teach an electrochemical model comprising a model configured to calculate inner lithium-ion concentrations in the cathode and anode of the battery by discretizing the SPM with respect to the cathode and the anode of the battery into spheres each having a plurality of layers. However, in an analogous art, Hao discloses a method and device for estimating battery state of charge based on an electrochemical model where the electrochemical model is a SPM or an extended model based on the SPM (Hao, para. [0069]) as well as the limitation: by discretizing the SPM with respect to the cathode and the anode of the battery into spheres each having a plurality of layers; (Hao, para. [0145]; [“Supposing it is divided into N discrete regions along the electrode thickness direction of the positive/negative electrode, each discrete region has a number of active particles, and each active particle has n radial nodes distributed along the radial direction. Cx,i represents the solid-phase lithium ion concentrations of the active particles of the x-th discrete region on the i-th radial node, x=1, 2, . . . N, i=0, 1, n, and n is the number of the radial nodes of positive/negative electrode particles.”]); (Hao, para. [0146]; [“Assuming that the initial value of the solid-phase lithium ion concentrations of each particle in each discrete region on the particle radial distribution is equal, that is, C.sub.x,i,0=C.sub.mean, C.sub.mean is the average concentration of the solid-phase lithium ions.”]); (Hao, para. [0147]; [“In the single particle model, the relationship between the SOC and the lithium ion concentration of the positive/negative electrode particles is determined…”]). Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using an electrochemical model comprising a model configured to calculate inner lithium-ion concentrations in the cathode and the anode of the battery, as taught by Howey, by discretizing the SPM, or an extended model based on the SPM, with respect to the cathode and the anode of the battery into spheres each having a plurality of layers, as taught by Hao, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Hao. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Hao to obtain the invention as specified in claim 3. Regarding Claim 4, Howey teaches the limitations of the parent claim as well as the limitations of claim 4, wherein the electrochemical model comprises a model configured to calculate the inner lithium-ion concentrations in the cathode and the anode of the battery based on a diffusion coefficient according to concentration distributions in the cathode and the anode of the battery; (Howey, para. [0047]; [“In this example, an electrode of the battery includes an active material that is a lithium compound, and the active material includes lithium ions (Li+).”]); (Howey, para. [0053], FIG. 2A; [“Thus, a concentration of lithium ions (Li+) included in the active material of the cathode, and a concentration of lithium ions (Li+) included in the active material of the anode vary depending on the charging and discharging. The battery state estimation apparatus calculates a current concentration distribution of lithium ions (Li+) in the cathode and the anode using the electrochemical model expressed by the simplified parameters, and estimates the present state of the battery.”]); and wherein the diffusion coefficient is based on a concentration and a temperature… (Howey, para. [0055], FIG. 2B; [“FIG. 2B illustrates an example of an SPM applied to an electrochemical model of a battery.”]); (Howey, para. [0056], FIG. 2B; [“Referring to FIG. 2B, the electrochemical model is defined by the SPM. A battery state estimation apparatus calculates a concentration distribution of lithium ions (Li+) in an active material from the SPM”]); (Howey, para. [0057], [Equation 1]; [“In the electrochemical model to which the SPM is applied, a diffusion of lithium in an active material of each of electrodes i (for example, an anode or a cathode) of a battery is governed by a Fickian diffusion equation expressed by Equation 1 in spherical coordinates.”]); PNG media_image1.png 50 306 media_image1.png Greyscale (Howey, para. [0058]; [“In Equation 1, ri denotes radial coordinates, ci denotes a lithium concentration profile, and Di denotes a lithium diffusion coefficient (assumed uniform) in an electrode i. The subscript i has either a positive value or negative value to represent a cathode domain or anode domain, respectively.”]); (Howey, para. [0081]; [“The diffusion time constant of the cathode is defined based on a radius of a particle of the cathode and a diffusion coefficient corresponding to the particle of the cathode. The diffusion time constant of the anode is defined based on a radius of a particle of the anode and a diffusion coefficient corresponding to the particle of the anode.”]); Howey teaches the limitations of the parent claim as well as the limitations of claim 4 described above. However, Howey fails to teach an electrochemical model comprising a model configured to calculate the inner lithium-ion concentrations in the cathode and the anode of the battery based on a diffusion coefficient according to concentration distributions in the cathode and the anode of the battery, and wherein the diffusion coefficient is based on a concentration and a temperature of each layer from among the plurality of layers in the SPMs for the cathode and the anode of the battery. However, in an analogous art, Hao discloses a method and device for estimating battery state of charge based on an electrochemical model where the electrochemical model is a SPM or an extended model based on the SPM (Hao, para. [0069]) as well as the limitation: of each layer from among the plurality of layers in the SPMs for the cathode and the anode of the battery; (Hao, para. [0145]; [“Supposing it is divided into N discrete regions along the electrode thickness direction of the positive/negative electrode, each discrete region has a number of active particles, and each active particle has n radial nodes distributed along the radial direction. Cx,i represents the solid-phase lithium ion concentrations of the active particles of the x-th discrete region on the i-th radial node, x=1, 2, . . . N, i=0, 1, n, and n is the number of the radial nodes of positive/negative electrode particles.”]). Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using an electrochemical model comprising a model configured to calculate inner lithium-ion concentrations in the cathode and the anode of the battery based on a diffusion coefficient according to concentration distributions in the cathode and the anode of the battery, and wherein the diffusion coefficient is based on a concentration and a temperature, as taught by Howey, by discretizing the SPM, or an extended model based on the SPM, with respect to the cathode and the anode of the battery into spheres each having a plurality of layers, as taught by Hao, and basing the diffusion coefficient on a concentration and a temperature, as taught by Howey, of each layer from among the plurality of layers in the SPMs for the cathode and the anode of the battery, as taught by Hao, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Hao. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Hao to obtain the invention as specified in claim 4. Regarding Claim 5, Howey teaches the limitations of the parent claim as well as the limitations of claim 5, wherein the electrochemical model comprises a model that estimates a voltage of the battery based on an overpotential value defined as a difference between a measured voltage of the battery and an open-circuit voltage (OCV) of the battery; (Howey, para. [0061]; [“Voltage Measurement Equation”]); (Howey, para. [0062]; [“Initial-boundary value problems, that is, Equations 1 through 3 for each electrode constitute a dynamic part of the SPM. A battery terminal voltage V is given by a nonlinear measurement equation expressed by Equation 5.”]); PNG media_image2.png 36 616 media_image2.png Greyscale (Howey, para. [0063]; [“In Equation 5, U.sub.− and U.sub.+ denote open-circuit potentials (OCPs) of an anode and a cathode. U.sub.− and U.sub.+ are empirical nonlinear functions of a surface stoichiometry of each particle x.sub.i.sup.s=c.sub.i.sup.s/c.sub.i.sup.max. η.sub.i denotes an overpotential and is a voltage drop due to a departure from an equilibrium potential associated with an intercalation/de-intercalation reaction in each electrode.”]). Howey teaches the limitations of the parent claim as well as the limitations of claim 5 described above. However, Howey fails to teach the limitations of claims 3 and 4 above specifically pertaining to discretizing the SPM with respect to the cathode and the anode of the battery into spheres each having a plurality of layers and of each layer from among the plurality of layers in the SPMs for the cathode and the anode of the battery. However, in an analogous art, Hao discloses these limitations as described in the analysis of claims 3 and 4. Therefore, before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using a combination of the teachings from Howey and Hao in order to monitor and maintain battery performance in real-time more effectively given that this method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Hao. Thus, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Hao to obtain the invention as specified in claim 5. Regarding Claim 11, Howey teaches the limitations of the parent claim 9 as well as the limitations of claim 11, wherein the electrochemical model comprises a model that calculates inner lithium-ion concentrations in the cathode and the anode of the battery… (Howey, para. [0047]; [“In this example, an electrode of the battery includes an active material that is a lithium compound, and the active material includes lithium ions (Li+).”]); PNG media_image1.png 50 306 media_image1.png Greyscale (Howey, para. [0058]; [“In Equation 1, ri denotes radial coordinates, ci denotes a lithium concentration profile, and Di denotes a lithium diffusion coefficient (assumed uniform) in an electrode i. The subscript i has either a positive value or negative value to represent a cathode domain or anode domain, respectively”]). Howey teaches the limitations of the parent claim described above. However, Howey fails to teach an electrochemical model comprising a model configured to calculate inner lithium-ion concentrations in the cathode and anode of the battery by discretizing the SPM with respect to the cathode and the anode of the battery into spheres each having a plurality of layers. However, in an analogous art, Hao discloses a method and device for estimating battery state of charge based on an electrochemical model where the electrochemical model is a SPM or an extended model based on the SPM (Hao, para. [0069]) as well as the limitation: by discretizing the SPM with respect to the cathode and the anode of the battery into spheres each having a plurality of layers; (Hao, para. [0145]; [“Supposing it is divided into N discrete regions along the electrode thickness direction of the positive/negative electrode, each discrete region has a number of active particles, and each active particle has n radial nodes distributed along the radial direction. Cx,i represents the solid-phase lithium ion concentrations of the active particles of the x-th discrete region on the i-th radial node, x=1, 2, . . . N, i=0, 1, n, and n is the number of the radial nodes of positive/negative electrode particles.”]). Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using an electrochemical model comprising a model configured to calculate inner lithium-ion concentrations in the cathode and the anode of the battery, as taught by Howey, by discretizing the SPM, or an extended model based on the SPM, with respect to the cathode and the anode of the battery into spheres each having a plurality of layers, as taught by Hao, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Hao. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Hao to obtain the invention as specified in claim 11. Regarding Claim 12, Howey teaches the limitations of parent claim 9 as well as the limitations of claim 12, wherein the electrochemical model comprises a model configured to calculate the inner lithium-ion concentrations in the cathode and the anode of the battery based on a diffusion coefficient according to concentration distributions in the cathode and the anode of the battery; (Howey, para. [0047]; [“In this example, an electrode of the battery includes an active material that is a lithium compound, and the active material includes lithium ions (Li+).”]); (Howey, para. [0053], FIG. 2A; [“Thus, a concentration of lithium ions (Li+) included in the active material of the cathode, and a concentration of lithium ions (Li+) included in the active material of the anode vary depending on the charging and discharging. The battery state estimation apparatus calculates a current concentration distribution of lithium ions (Li+) in the cathode and the anode using the electrochemical model expressed by the simplified parameters, and estimates the present state of the battery.”]); and wherein the diffusion coefficient is based on a concentration and a temperature… (Howey, para. [0055], FIG. 2B; [“FIG. 2B illustrates an example of an SPM applied to an electrochemical model of a battery.”]); (Howey, para. [0056], FIG. 2B; [“Referring to FIG. 2B, the electrochemical model is defined by the SPM. A battery state estimation apparatus calculates a concentration distribution of lithium ions (Li+) in an active material from the SPM”]); (Howey, para. [0057], [Equation 1]; [“In the electrochemical model to which the SPM is applied, a diffusion of lithium in an active material of each of electrodes i (for example, an anode or a cathode) of a battery is governed by a Fickian diffusion equation expressed by Equation 1 in spherical coordinates.”]); PNG media_image1.png 50 306 media_image1.png Greyscale (Howey, para. [0058]; [“In Equation 1, ri denotes radial coordinates, ci denotes a lithium concentration profile, and Di denotes a lithium diffusion coefficient (assumed uniform) in an electrode i. The subscript i has either a positive value or negative value to represent a cathode domain or anode domain, respectively.”]); (Howey, para. [0081]; [“The diffusion time constant of the cathode is defined based on a radius of a particle of the cathode and a diffusion coefficient corresponding to the particle of the cathode. The diffusion time constant of the anode is defined based on a radius of a particle of the anode and a diffusion coefficient corresponding to the particle of the anode.”]); Howey teaches the limitations of the parent claim 9 as well as the limitations of claim 12 described above. However, Howey fails to teach an electrochemical model comprising a model configured to calculate the inner lithium-ion concentrations in the cathode and the anode of the battery based on a diffusion coefficient according to concentration distributions in the cathode and the anode of the battery, and wherein the diffusion coefficient is based on a concentration and a temperature of each layer from among the plurality of layers in the SPM for the cathode and the anode of the battery. However, in an analogous art, Hao discloses a method and device for estimating battery state of charge based on an electrochemical model where the electrochemical model is a SPM or an extended model based on the SPM (Hao, para. [0069]) as well as the limitation: of each layer from among the plurality of layers in the SPM for the cathode and the anode of the battery; (Hao, para. [0145]; [“Supposing it is divided into N discrete regions along the electrode thickness direction of the positive/negative electrode, each discrete region has a number of active particles, and each active particle has n radial nodes distributed along the radial direction. Cx,i represents the solid-phase lithium ion concentrations of the active particles of the x-th discrete region on the i-th radial node, x=1, 2, . . . N, i=0, 1, n, and n is the number of the radial nodes of positive/negative electrode particles.”]). Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using an electrochemical model comprising a model configured to calculate inner lithium-ion concentrations in the cathode and the anode of the battery based on a diffusion coefficient according to concentration distributions in the cathode and the anode of the battery, and wherein the diffusion coefficient is based on a concentration and a temperature, as taught by Howey, by discretizing the SPM, or an extended model based on the SPM, with respect to the cathode and the anode of the battery into spheres each having a plurality of layers, as taught by Hao, and basing the diffusion coefficient on a concentration and a temperature, as taught by Howey, of each layer from among the plurality of layers in the SPMs for the cathode and the anode of the battery, as taught by Hao, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Hao. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Hao to obtain the invention as specified in claim 12. Regarding Claim 13, Howey teaches the limitations of the parent claim 9 as well as the limitations of claim 13, wherein the electrochemical model comprises a model that estimates a voltage of the battery based on an overpotential value that is a difference between a measured voltage of the battery and an open-circuit voltage (OCV) of the battery; (Howey, para. [0061]; [“Voltage Measurement Equation”]); (Howey, para. [0062]; [“Initial-boundary value problems, that is, Equations 1 through 3 for each electrode constitute a dynamic part of the SPM. A battery terminal voltage V is given by a nonlinear measurement equation expressed by Equation 5.”]); PNG media_image2.png 36 616 media_image2.png Greyscale (Howey, para. [0063]; [“In Equation 5, U.sub.− and U.sub.+ denote open-circuit potentials (OCPs) of an anode and a cathode. U.sub.− and U.sub.+ are empirical nonlinear functions of a surface stoichiometry of each particle x.sub.i.sup.s=c.sub.i.sup.s/c.sub.i.sup.max. η.sub.i denotes an overpotential and is a voltage drop due to a departure from an equilibrium potential associated with an intercalation/de-intercalation reaction in each electrode.”]). Howey teaches the limitations of the parent claim as well as the limitations of claim 13 described above. However, Howey fails to teach the limitations of claims 11 and 12 above specifically pertaining to discretizing the SPM with respect to the cathode and the anode of the battery into spheres each having a plurality of layers and of each layer from among the plurality of layers in the SPMs for the cathode and the anode of the battery. However, in an analogous art, Hao discloses these limitations as described in the analysis of claims 11 and 12. Therefore, before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using a combination of the teachings from Howey and Hao in order to monitor and maintain battery performance in real-time more effectively given that this method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Hao. Thus, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Hao to obtain the invention as specified in claim 13. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103, which forms the basis for all obviousness rejections set forth in this Office Action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 6-7 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Howey; in view of Hao; further in view of Lee US Patent Publication No. US 20230145602 A1. Regarding Claim 6, Howey teaches an electrochemical model (Howey: Abstract) as well as the limitations of the parent claim. However, Howey fails to teach an electrochemical model comprising a model configured to calculate a priori overpotential value based on information about lithium-ion concentration in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery, information about an average lithium-ion concentration in the cathode and the anode of the battery, and voltage drop information of the battery, and to calculate the overpotential value based on the priori overpotential value and an overpotential proportional coefficient. However, in an analogous art, Lee discloses a battery apparatus and method for predicting battery output including a “processor 150” and “terminal voltage estimation model 810” (Lee, para. [0078-0080], FIGS. 1 and 8-9), configured to estimate “an overpotential due to polarization at S960. Since the overpotential is caused by deviation of a potential at an electrode surface from an equilibrium potential, the processor 150 estimates the overpotential based on the surface SOC representing the potential at the electrode surface and the SOC representing the equilibrium potential. In some embodiments, the processor 150 may estimate the overpotential based on a value obtained by comparing the SOC and the surface SOC… In some embodiments, the processor 150 may estimate the overpotential V1[t+1] at time point (t+1) based on the overpotential V1[t], the SOC SOC[t], and the surface SOC SSOC[t] at time point t, using the terminal voltage estimation model 810. In some embodiments, the processor 150 may estimate the overpotential V1[t+1], for example, as in Equation 3.” (Lee, para. [0081]; [“In Equation 3, a denotes an overpotential coefficient.”]); (Lee, para. [0082]; [“In some embodiments, the overpotential coefficient a may be determined by experiments…In some embodiments, the processor 150 may predefine an initial value B1[0] of the overpotential for estimating the overpotential.”]); (Lee, para. [0052]; [“Referring to FIG. 2, the battery 110 includes a positive electrode (or cathode) 111, a negative electrode (or anode) 112, and an electrolyte 113…it is assumed that lithium is an active material causing a chemical reaction in the battery 110.”]); (Lee, para. [0057]; [“The SOC represents the average concentration (e.g., the average concentration at the electrode) inside the battery 110”]); Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using an electrochemical model, as taught by Howey, comprising a model configured to calculate a priori overpotential value based on information about lithium-ion concentration… information about an average lithium-ion concentration in the cathode and the anode of the battery, and voltage drop information of the battery, and to calculate the overpotential value based on the priori overpotential value and an overpotential proportional coefficient, as taught by Lee, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Lee. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Lee to obtain the invention as specified in claim 6. However, Howey and Lee fail to teach a model configured to calculate a priori overpotential value based on information about lithium-ion concentration in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery. However, in an analogous art, Hao discloses a method and device for estimating battery state of charge based on an electrochemical model where the electrochemical model is a SPM or an extended model based on the SPM (Hao, para. [0069]) as well as the limitation: in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery; (Hao, para. [0145]; [“Supposing it is divided into N discrete regions along the electrode thickness direction of the positive/negative electrode, each discrete region has a number of active particles, and each active particle has n radial nodes distributed along the radial direction. Cx,i represents the solid-phase lithium ion concentrations of the active particles of the x-th discrete region on the i-th radial node, x=1, 2, . . . N, i=0, 1, n, and n is the number of the radial nodes of positive/negative electrode particles.”]); (Hao, para. [0130], Equation [00015]; [“In this embodiment, a linear correction is made to the distribution of the lithium ion concentrations of the positive electrode particles along the radial direction, that is, the concentration correction value at the center of the sphere is 0, and the concentration correction value at the surface is the largest, and the concentration correction along the radial direction satisfies the formula of: wherein ΔCr+ is the correction amount of the lithium ion concentrations of the positive electrode particles at the radial distance r; k.sub.ΔU is the maximum surface lithium ion concentration difference; a is the correction coefficient that has a value in the range of 0-1. α=0.5 is selected in this case. It can be seen that when r=0, ΔCr+=0, indicating that the concentration correction value at the center of the sphere is 0; when r=1, ΔCr+ is the largest, indicating that the surface concentration correction value is the largest.”]); Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using an electrochemical model, as taught by Howey, comprising a model configured to calculate a priori overpotential value based on information about lithium-ion concentration… information about an average lithium-ion concentration in the cathode and the anode of the battery, and voltage drop information of the battery, and to calculate the overpotential value based on the priori overpotential value and an overpotential proportional coefficient, as taught by Lee, where the model configured to calculate a priori overpotential value based on information about lithium-ion concentration does so in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery, as taught by Hao, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Lee and Hao. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Lee with Hao’s teachings to obtain the invention as specified in claim 6. Regarding Claim 7, Howey teaches the limitations of the parent claim as well as a relationship based on an overpotential value given by a Butler Volmer equation by using curve fitting (Howey, para. [0063]; [“In Equation 5, U.sub.− and U.sub.+ denote open-circuit potentials (OCPs) of an anode and a cathode. U.sub.− and U.sub.+ are empirical nonlinear functions of a surface stoichiometry of each particle x.sub.i.sup.s=c.sub.i.sup.s/c.sub.i.sup.max. η.sub.i denotes an overpotential and is a voltage drop due to a departure from an equilibrium potential associated with an intercalation/de-intercalation reaction in each electrode. A relationship between a reaction rate j.sub.i and the overpotential η.sub.i is given by a Butler-Volmer kinetics equation expressed by Equation 6”]). However, Howey fails to specifically teach wherein the overpotential proportional coefficient is an experimental value that simulates a relationship between the priori overpotential value and the overpotential value. However, in an analogous art, Lee discloses a battery apparatus and method for predicting battery output including a “processor 150” and “terminal voltage estimation model 810” (Lee, para. [0078-0080], FIGS. 1 and 8-9), configured to estimate “an overpotential due to polarization at S960. Since the overpotential is caused by deviation of a potential at an electrode surface from an equilibrium potential, the processor 150 estimates the overpotential based on the surface SOC representing the potential at the electrode surface and the SOC representing the equilibrium potential. In some embodiments, the processor 150 may estimate the overpotential based on a value obtained by comparing the SOC and the surface SOC… In some embodiments, the processor 150 may estimate the overpotential V1[t+1] at time point (t+1) based on the overpotential V1[t], the SOC SOC[t], and the surface SOC SSOC[t] at time point t, using the terminal voltage estimation model 810. In some embodiments, the processor 150 may estimate the overpotential V1[t+1], for example, as in Equation 3.” (Lee, para. [0081]; [“In Equation 3, a denotes an overpotential coefficient.”]); (Lee, para. [0082]; [“In some embodiments, the overpotential coefficient a may be determined by experiments…In some embodiments, the processor 150 may predefine an initial value B1[0] of the overpotential for estimating the overpotential.”]); Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using a relationship based on an overpotential value given by a Butler Volmer equation by using curve fitting, as taught by Howey, wherein the overpotential proportional coefficient is an experimental value that simulates a relationship between the priori overpotential value and the overpotential value, as taught by Lee, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Lee. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Lee to obtain the invention as specified in claim 7. Regarding Claim 14, Howey teaches an electrochemical model (Howey: Abstract) as well as the limitations of the parent claim. However, Howey fails to teach an electrochemical model comprising a model configured to calculate a priori overpotential value based on information about lithium-ion concentration in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery, information about an average lithium-ion concentration in the cathode and the anode of the battery, and voltage drop information of the battery, and to calculate the overpotential value by using the priori overpotential value and an overpotential proportional coefficient. However, in an analogous art, Lee discloses a battery apparatus and method for predicting battery output including a “processor 150” and “terminal voltage estimation model 810” (Lee, para. [0078-0080], FIGS. 1 and 8-9), configured to estimate “an overpotential due to polarization at S960. Since the overpotential is caused by deviation of a potential at an electrode surface from an equilibrium potential, the processor 150 estimates the overpotential based on the surface SOC representing the potential at the electrode surface and the SOC representing the equilibrium potential. In some embodiments, the processor 150 may estimate the overpotential based on a value obtained by comparing the SOC and the surface SOC… In some embodiments, the processor 150 may estimate the overpotential V1[t+1] at time point (t+1) based on the overpotential V1[t], the SOC SOC[t], and the surface SOC SSOC[t] at time point t, using the terminal voltage estimation model 810. In some embodiments, the processor 150 may estimate the overpotential V1[t+1], for example, as in Equation 3.” (Lee, para. [0081]; [“In Equation 3, a denotes an overpotential coefficient.”]); (Lee, para. [0082]; [“In some embodiments, the overpotential coefficient a may be determined by experiments…In some embodiments, the processor 150 may predefine an initial value B1[0] of the overpotential for estimating the overpotential.”]); (Lee, para. [0052]; [“Referring to FIG. 2, the battery 110 includes a positive electrode (or cathode) 111, a negative electrode (or anode) 112, and an electrolyte 113…it is assumed that lithium is an active material causing a chemical reaction in the battery 110.”]); (Lee, para. [0057]; [“The SOC represents the average concentration (e.g., the average concentration at the electrode) inside the battery 110”]); Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using an electrochemical model, as taught by Howey, comprising a model configured to calculate a priori overpotential value based on information about lithium-ion concentration… information about an average lithium-ion concentration in the cathode and the anode of the battery, and voltage drop information of the battery, and to calculate the overpotential value by using the priori overpotential value and an overpotential proportional coefficient, as taught by Lee, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Lee. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Lee to obtain the invention as specified in claim 14. However, Howey and Lee fail to teach a model configured to calculate a priori overpotential value based on information about lithium-ion concentration in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery. However, in an analogous art, Hao discloses a method and device for estimating battery state of charge based on an electrochemical model where the electrochemical model is a SPM or an extended model based on the SPM (Hao, para. [0069]) as well as the limitation: in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery; (Hao, para. [0145]; [“Supposing it is divided into N discrete regions along the electrode thickness direction of the positive/negative electrode, each discrete region has a number of active particles, and each active particle has n radial nodes distributed along the radial direction. Cx,i represents the solid-phase lithium ion concentrations of the active particles of the x-th discrete region on the i-th radial node, x=1, 2, . . . N, i=0, 1, n, and n is the number of the radial nodes of positive/negative electrode particles.”]); (Hao, para. [0130], Equation [00015]; [“In this embodiment, a linear correction is made to the distribution of the lithium ion concentrations of the positive electrode particles along the radial direction, that is, the concentration correction value at the center of the sphere is 0, and the concentration correction value at the surface is the largest, and the concentration correction along the radial direction satisfies the formula of: wherein ΔCr+ is the correction amount of the lithium ion concentrations of the positive electrode particles at the radial distance r; k.sub.ΔU is the maximum surface lithium ion concentration difference; a is the correction coefficient that has a value in the range of 0-1. α=0.5 is selected in this case. It can be seen that when r=0, ΔCr+=0, indicating that the concentration correction value at the center of the sphere is 0; when r=1, ΔCr+ is the largest, indicating that the surface concentration correction value is the largest.”]); Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using an electrochemical model, as taught by Howey, comprising a model configured to calculate a priori overpotential value based on information about lithium-ion concentration… information about an average lithium-ion concentration in the cathode and the anode of the battery, and voltage drop information of the battery, and to calculate the overpotential value based on the priori overpotential value and an overpotential proportional coefficient, as taught by Lee, where the model configured to calculate a priori overpotential value based on information about lithium-ion concentration does so in an outermost layer from among the plurality of layers in the SPMs of the cathode and the anode of the battery, as taught by Hao, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Lee and Hao. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Lee with Hao’s teachings to obtain the invention as specified in claim 14. Regarding Claim 15, Howey teaches the limitations of the parent claim as well as a relationship based on an overpotential value given by a Butler Volmer equation by using curve fitting (Howey, para. [0063]; [“In Equation 5, U.sub.− and U.sub.+ denote open-circuit potentials (OCPs) of an anode and a cathode. U.sub.− and U.sub.+ are empirical nonlinear functions of a surface stoichiometry of each particle x.sub.i.sup.s=c.sub.i.sup.s/c.sub.i.sup.max. η.sub.i denotes an overpotential and is a voltage drop due to a departure from an equilibrium potential associated with an intercalation/de-intercalation reaction in each electrode. A relationship between a reaction rate j.sub.i and the overpotential η.sub.i is given by a Butler-Volmer kinetics equation expressed by Equation 6”]). However, Howey fails to specifically teach wherein the overpotential proportional coefficient is an experimental value that simulates a relationship between the priori overpotential value and the overpotential value. However, in an analogous art, Lee discloses a battery apparatus and method for predicting battery output including a “processor 150” and “terminal voltage estimation model 810” (Lee, para. [0078-0080], FIGS. 1 and 8-9), configured to estimate “an overpotential due to polarization at S960. Since the overpotential is caused by deviation of a potential at an electrode surface from an equilibrium potential, the processor 150 estimates the overpotential based on the surface SOC representing the potential at the electrode surface and the SOC representing the equilibrium potential. In some embodiments, the processor 150 may estimate the overpotential based on a value obtained by comparing the SOC and the surface SOC… In some embodiments, the processor 150 may estimate the overpotential V1[t+1] at time point (t+1) based on the overpotential V1[t], the SOC SOC[t], and the surface SOC SSOC[t] at time point t, using the terminal voltage estimation model 810. In some embodiments, the processor 150 may estimate the overpotential V1[t+1], for example, as in Equation 3.” (Lee, para. [0081]; [“In Equation 3, a denotes an overpotential coefficient.”]); (Lee, para. [0082]; [“In some embodiments, the overpotential coefficient a may be determined by experiments…In some embodiments, the processor 150 may predefine an initial value B1[0] of the overpotential for estimating the overpotential.”]); Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to determine the internal state of a battery using a relationship based on an overpotential value given by a Butler Volmer equation by using curve fitting, as taught by Howey, wherein the overpotential proportional coefficient is an experimental value that simulates a relationship between the priori overpotential value and the overpotential value, as taught by Lee, in order to monitor and maintain battery performance in real-time more effectively. This method of improving Howey was within the ability of one of ordinary skill in the art based on the teachings of Lee. Therefore, it would have been obvious to one of ordinary skill in the art to combine the teachings of Howey and Lee to obtain the invention as specified in claim 15. Pertinent Prior Art Gu, Ran, et al. “On the Suitability of Electrochemical-Based Modeling for Lithium-Ion Batteries.” IEEE Transactions on Transportation Electrification, vol. 2, no. 4, Dec. 2016, pp. 417–431, https://doi.org/10.1109/tte.2016.2571778. Accessed 5 July 2021. A modeling of lithium-ion cells using an electrochemical-based model including diffusion coefficients, an overpotential, and an extended SPM model which discretizes spherical particles into several shells as well as an electrochemical reaction for lithium-ion intercalation/deintercalation using the Butler-Volmer kinetics equation. Lin, Cheng, et al. “Evaluation of Electrochemical Models Based Battery State-of-Charge Estimation Approaches for Electric Vehicles.” Applied Energy, vol. 207, Dec. 2017, pp. 394–404, https://doi.org/10.1016/j.apenergy.2017.05.109. Accessed 29 Mar. 2021. An evaluation of electrochemical models based battery state-of-charge estimation approaches for electric vehicles including order-reduced models such as a SPM, diffusion coefficient, and a discretization process using an order-reduced model. The open-circuit potentials for different SoCs can be calculated using the relationship between the open-circuit potential and the SoC, and an overpotential based on a cathode/anode is used as well as the Butler-Volmer equation. Moura, Scott J, et al. Battery State Estimation for a Single Particle Model with Electrolyte Dynamics. Vol. 25, no. 2, 1 Mar. 2017, pp. 453–468, https://doi.org/10.1109/tcst.2016.2571663. A state estimation scheme for a reduced electrochemical battery model and deriving a SPM, which uses a discretization method. Linear spherical diffusion modeling including a diffusion coefficient as well as an electrolyte concentration overpotential, which is found by solving the Butler-Volmer equation. Conclusion An inquiry concerning this communication or earlier communication from the examiner should be directed to LOGAN D COONS whose telephone number is (571) 272-2698. (via email: logan.coons@uspto.gov “without a written authorization by applicant in place, the USPTO will not respond via internet e-mail to an internet correspondence” MPEP 502.02 II). The examiner can normally be reached on M-F 9:30am – 6pm ET. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SPE SHELBY A TURNER, can be reached at (571) 272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /LOGAN D COONS/Examiner, Art Unit 2857 /SHELBY A TURNER/Supervisory Patent Examiner, Art Unit 2857
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Prosecution Timeline

Aug 23, 2023
Application Filed
Dec 22, 2025
Non-Final Rejection — §101, §102, §103 (current)

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