CTFR 18/783,021 CTFR 96343 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 12-151 AIA 26-51 12-51 Status of Claims This action is in reply to the patent application filed on March 2, 2026. Claims 1-20 are currently pending and have been examined. This action is made FINAL. The examiner would like to note that this application is being handled by examiner Christine Huynh. Response to Arguments 07-37 AIA Applicant's arguments filed March 2, 2026 have been fully considered but they are not persuasive. With respect to the 35 U.S.C. 101 rejection, applicants argue in pages 9-10 that the amendments have overcome the 101 and that independent claims 1 and 11 are not directed towards a mental process. Specifically, the Applicant argues that the claim includes “determining, by the controller, a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time”, which amount to significantly more than the abstract idea or a human activity but instead is a practical application and that because the limitations are coupled with a physical system (ex, a memory, a processor), then the limitations overcome the 35 U.S.C. 101 rejection. However, the examiner respectfully disagrees, because the amended language is still directed to a mental process, and simply including a memory, processor, or controller does not integrate the abstract idea into a practical application. The amended limitation, “ wherein the at least one instruction executed by the controller is configured to cause the vehicle battery control apparatus to determine a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time ” still falls into the mental processes grouping of abstract ideas as “determine a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time” in the context of this claim could be a mental process as a person could at data collected and forming a simple judgement from the comparison using the given data, which would be an abandonment time and a predetermined time. With this information give, a person can determine a first calendar aging model. This limitation is a process that, under broadest reasonable interpretation, covers the performance of the limitation in the mind but for the recitation of generic computer components. The “controller” is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component and therefore including a memory, processor, or controller does not integrate the abstract idea into a practical application. Therefore, the claims as amended are still directed to an abstract idea. Accordingly, the 35 U.S.C. 101 rejection is maintained. See detailed rejection below . Applicant’s arguments with respect to claim(s) 1 and 11 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Applicant argues that Kim does not teach “determine a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time”. Applicant argues that Fujita fails to account for the deficiencies of Kim because the Examiner cites only Kim, to support such features. However, the examiner respectfully disagrees, because the limitation “wherein the at least one instruction executed by the controller is configured to cause the vehicle battery control apparatus to determine a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time” was added and therefore does not rely only on Kim. Kim teaches (“In another example, the diagnostic analysis data may comprise operation characteristic accumulative information for the battery 51 and may include at least one selected from the group consisting of an accumulative operation time for each voltage section, an accumulative operation time for each current section, and an accumulative operation time for each temperature section for the battery 51 mounted to the electric vehicle 50.” [0079], “The database 60 includes a degradation look-up table storage unit 64. The degradation look-up table storage unit 64 is an information storage area in which voltage profile information according to SOC is recorded for each degree of degradation of the battery 51. The area in which the voltage profile information is stored for each degree of degradation is allocated to each battery assigned with the same battery model code. The degradation look-up table storage unit 64 may be defined in advance using data provided by a battery manufacturer and stored in the database 60.” [0082], “ when the electric vehicle 50 is parked, the battery service server 30 may collect the diagnostic analysis data about the battery 51 of the electric vehicle 50 through the network 40 from the communication device 20 separately installed in the parking place, and store the same in the database 60” [0101], “the battery service server 30 determines whether the operation characteristic profile of the battery 51 is collected in a preset degradation estimation voltage section. To this end, the battery service server 30 may examine the voltage distribution of the voltage profile according to the change of SOC. If the determination is YES, the battery service server 30 may determine a charge capacity change amount by integrating the current data measured in the degradation estimation voltage section, and determine the ratio of the charge capacity change amount to a reference charge capacity change amount as the degree of degradation.” [0111]) where the collected battery data from a battery during a period of time including when the vehicle is parked is compared to reference data from a reference model. The calendar aging data including the state of charge and the temperature of the battery is collected and stored, and can be compared database information, which can be used to determine the capacity and degradation of the battery. Fujita teaches (“Left-at-high-charge-level duration rate D is one of the degrees of battery degradation which is defined by t/t 0 , where t represents the time period over which the secondary battery V1 is left unused in a state of a certain SOC (for example, 90%) or more, and t 0 represents the elapsed time from the date of manufacture of the battery to the present, and is a characteristic value in which the degree of battery degradation increases as left-at-high-charge-level duration rate D increases. The time period t over which the secondary battery V1 is left unused in a state of the certain SOC or more and the elapsed time t 0 from the date of manufacture of the battery to the present are read out from the memory of the battery controller V4 via the vehicle controller V5 .” [0028]), which shows comparing the time in which the battery is left unused to a time threshold, for example, determining when the vehicle battery is left unused is greater than a predetermined time. Therefore, claims 1 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (US 20230182575 A1) in view of Fujita et al. (US 20130317690 A1). See detailed rejection below. Dependent claims rejected for the same reasons as listed above due to dependency. See detailed rejection below . Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Regarding claims 1-20: 101 Analysis – Step 1 Claims 1-10 are directed to an apparatus for vehicle battery control and claims 11-20 are directed to a method for vehicle battery control which are/is one of the statutory categories of invention. (Step 1: YES) 101 Analysis – Step 2A, Prong I Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. Claim 11 is similar to independent claim 1. Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites: A vehicle battery control apparatus, comprising: a memory storing at least one instruction; and a controller operatively connected to the memory, wherein the at least one instruction executed by the controller, is configured to cause the vehicle battery control apparatus to: obtain at least one of driving durability data according to a driving state of a host vehicle or calendar aging data according to a parking state of the host vehicle, or any combination thereof; obtain degradation data of a battery of the host vehicle using at least some of the driving durability data or the calendar aging data, or the any combination thereof; and compare reference data identified based on a predetermined reference model with the degradation data to determine a degradation state of the battery , wherein the at least one instruction executed by the controller is configured to cause the vehicle battery control apparatus to determine a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time . The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, the limitation “compare reference data…” falls into the mental processes grouping of abstract ideas as comparing reference data to the state of the battery could be done mentally for example using a pen and paper to compare the values of the given reference data and the current state of the value, solving for the difference in states, and making a determination regarding the degradation of the battery. The limitation, “determine a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time” in the context of this claim could be a mental process as a person could at data collected and forming a simple judgement from the comparison using the given data. This limitation is a process that, under broadest reasonable interpretation, covers the performance of the limitation in the mind but for the recitation of generic computer components. With respect to claims 1 and 11, other than reciting “a controller”, nothing in the claim limitations precludes the idea from practically being performed in the human mind. The recitation of generic components in a claim does not necessarily preclude that claim from reciting an abstract idea. (Step 2A-Prong 1: YES. The claims recite an abstract idea) 101 Analysis – Step 2A, Prong II Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract idea into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” The claims recite elements additional to the abstract concepts. However, these additional elements fail to integrate the abstract idea into a practical application. In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”): A vehicle battery control apparatus, comprising: a memory storing at least one instruction ; and a controller operatively connected to the memory, wherein the at least one instruction executed by the controller, is configured to cause the vehicle battery control apparatus to : obtain at least one of driving durability data according to a driving state of a host vehicle or calendar aging data according to a parking state of the host vehicle, or any combination thereof ; obtain degradation data of a battery of the host vehicle using at least some of the driving durability data or the calendar aging data, or the any combination thereof ; and compare reference data identified based on a predetermined reference model with the degradation data to determine a degradation state of the battery , wherein the at least one instruction executed by the controller is configured to cause the vehicle battery control apparatus to determine a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time . For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application. The “ obtain at least one of driving durability data …”, “ obtain degradation data of a battery of the host vehicle …”, and “ accumulate and store the driving durability data …” limitations are insignificant extra-solution activities that merely use a computer (controller) to perform the process. The hardware/software is/are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic component or it is merely insignificant extra solution activity. In particular, the obtaining steps amounts to mere data gathering, which is a form of insignificant extra-solution activity and accumulating and storing the driving durability data amounts to mere data storing. Lastly, the “memory”, “processor”, “and “controller” is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, claim 1 and 11 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application) The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. See Applicant’s specification para. [ 00262-00264 ] about implantation using general purpose or special purpose computing devices and MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly more as well as MPEP 2106.05(d), as well as MPEP 2106.05(g), if applicable. Accordingly, these additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. Thus, claims 1 and 11 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more) Dependent claims further define the abstract idea that is present in their respective independent claims 1 and 11 thus correspond to mental process and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the dependent claims are directed to an abstract idea. Thus, claims 1-20 are not patent-eligible. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-23-aia AIA 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. 07-20-02-aia AIA 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. 07-21-aia AIA Claim (s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (US 20230182575 A1) in view of Fujita et al. (US 20130317690 A1), which were both provided in the IDS sent on February 25, 2025 . Regarding claims 1-20: With respect to claims 1 and 11 , Kim teaches: a memory storing at least one instruction ; (“The storage means 52a is a non-transitory memory device and is a computer storage medium capable of writing and/or erasing and/or modifying and/or transferring data.” [0056]) a controller operatively connected to the memory , (“The electric vehicle control device 52 is a computer device that controls the charging/discharging operation of t battery 51, and measures the voltage, current, and temperature of the battery 51 during charging/discharging of the battery 51 and records the same in a storage means 52a. The electric vehicle control device 52 may also perform a control operation for a mechanical mechanism and/or an electronic mechanism related to the operation of the electric vehicle 50.” [0055]) obtain at least one of driving durability data according to a driving state of a host vehicle or calendar aging data according to a parking state of the host vehicle, or any combination thereof ; (“The electric vehicle control device 52 is a computer device that controls the charging/discharging operation of t battery 51, and measures the voltage, current, and temperature of the battery 51 during charging/discharging of the battery 51 and records the same in a storage means 52a.” [0055], “the diagnostic analysis data may comprise operation characteristic accumulative information for the battery 51, and may include at least one selected from the group consisting of an accumulative operation time for each voltage section, an accumulative operation time for each current section, and an accumulative operation time for each temperature section for the battery 51 of the electric vehicle 50.” [0091], “when the electric vehicle 50 is parked, the battery service server 30 may collect the diagnostic analysis data about the battery 51 of the electric vehicle 50 through the network 40 from the communication device 20 separately installed in the parking place, and store the same in the database 60” [0101]), where this teaches obtaining the driving durability data including the voltage, current, and temperature of the battery, and the calendar aging data which includes the state of charge and the temperature of the battery over time including collecting data when the vehicle is parked. obtain degradation data of a battery of the host vehicle using at least some of the driving durability data or the calendar aging data, or the any combination thereof ; (“the battery service server 30 may determine the degree of degradation of the battery 51 by using the operation characteristic profile of the battery 51 included in the diagnostic analysis data, and record the degree of degradation in the diagnostic analysis data storage unit 62 of the database 60 to be matched with the model code of the electric vehicle 50 and/or the identification code of the electric vehicle 50 and/or the model code of the battery 51 and/or the identification code of the battery 51.” [0110]), in which the degradation data of a battery can be determined using the data collected from the battery. compare reference data identified based on a predetermined reference model with the degradation data to determine a degradation state of the battery ; (“the battery service server 30 determines whether the operation characteristic profile of the battery 51 is collected in a preset degradation estimation voltage section. To this end, the battery service server 30 may examine the voltage distribution of the voltage profile according to the change of SOC. If the determination is YES, the battery service server 30 may determine a charge capacity change amount by integrating the current data measured in the degradation estimation voltage section, and determine the ratio of the charge capacity change amount to a reference charge capacity change amount as the degree of degradation. The reference charge capacity change amount is a charge capacity change amount represented while the battery 51 in a BOL state is being charged in the degradation estimation voltage section, and the reference charge capacity change amount may be recorded in advance in the database 60 for each model of the battery” [0111]), where the collected battery data is compared to reference data. wherein the at least one instruction executed by the controller is configured to cause the vehicle battery control apparatus to determine a first calendar aging model based on concluding that an abandonment time before the host vehicle starts to drive is greater than a predetermined time ; (“In another example, the diagnostic analysis data may comprise operation characteristic accumulative information for the battery 51 and may include at least one selected from the group consisting of an accumulative operation time for each voltage section, an accumulative operation time for each current section, and an accumulative operation time for each temperature section for the battery 51 mounted to the electric vehicle 50.” [0079], “The database 60 includes a degradation look-up table storage unit 64. The degradation look-up table storage unit 64 is an information storage area in which voltage profile information according to SOC is recorded for each degree of degradation of the battery 51. The area in which the voltage profile information is stored for each degree of degradation is allocated to each battery assigned with the same battery model code. The degradation look-up table storage unit 64 may be defined in advance using data provided by a battery manufacturer and stored in the database 60.” [0082], “ when the electric vehicle 50 is parked, the battery service server 30 may collect the diagnostic analysis data about the battery 51 of the electric vehicle 50 through the network 40 from the communication device 20 separately installed in the parking place, and store the same in the database 60” [0101], “the battery service server 30 determines whether the operation characteristic profile of the battery 51 is collected in a preset degradation estimation voltage section. To this end, the battery service server 30 may examine the voltage distribution of the voltage profile according to the change of SOC. If the determination is YES, the battery service server 30 may determine a charge capacity change amount by integrating the current data measured in the degradation estimation voltage section, and determine the ratio of the charge capacity change amount to a reference charge capacity change amount as the degree of degradation.” [0111]) where the collected battery data from a battery during a period of time including when the vehicle is parked is compared to reference data from a reference model. The calendar aging data including the state of charge and the temperature of the battery is collected and stored, and can be compared database information, which can be used to determine the capacity and degradation of the battery. Kim does not teach concluding that an abandonment time before the host vehicle starts to drive is greater, less than, or equal to a predetermined time. However, Fujita teaches (“Left-at-high-charge-level duration rate D is one of the degrees of battery degradation which is defined by t/t 0 , where t represents the time period over which the secondary battery V1 is left unused in a state of a certain SOC (for example, 90%) or more, and t 0 represents the elapsed time from the date of manufacture of the battery to the present, and is a characteristic value in which the degree of battery degradation increases as left-at-high-charge-level duration rate D increases. The time period t over which the secondary battery V1 is left unused in a state of the certain SOC or more and the elapsed time t 0 from the date of manufacture of the battery to the present are read out from the memory of the battery controller V4 via the vehicle controller V5 .” [0028]), which shows comparing the time in which the battery is left unused to a time threshold, for example, determining when the vehicle battery is left unused is greater than a predetermined time. Thus, it would have been obvious to a person of ordinary skill in the art where the abandonment time is less than a time threshold in an attempt to provide an improved system or method, as a person with ordinary skill has good reason to pursue the known options within his or her technical grasp. It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Kim’s vehicle battery controller with Fujita’s abandonment time threshold in order to improve analyzing battery data (“to suppress both degradation of a battery and a decrease in the existence value of a vehicle.” see Fujita [0007]). With respect to claims 2 and 12 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 1 and 11. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 1 and 11. Kim further teaches: accumulate and store the driving durability data according to the driving state while driving in the memory, when the host vehicle starts to drive ; (“The electric vehicle control device 52 may record driving characteristic information of the electric vehicle 50 in the storage means 52a. The driving characteristic information includes a speed change profile and a driving distance accumulative profile of the electric vehicle 50. Optionally, the driving characteristic information may further include coordinate data for a moving path of the electric vehicle 50. The speed change profile includes a set of speed data (SOC k , Velocity k , t k ) according to the SOC of the battery 51. Here, velocity and t are a driving speed and a time stamp of the electric vehicle 50, respectively.” [0072], where driving durability data is recorded and stored when the vehicle is driving at different points in time, which would include the start of a trip. identify the degradation data of the battery, based on at least one of the calendar aging data according to the parking state, the calendar aging data being stored in the memory before the host vehicle starts to drive, or an existing calendar aging model, or any combination thereof ; (“In an example, the diagnostic analysis data includes at least one selected from the group consisting of a speed change profile, a driving distance accumulative profile, and a battery operation characteristic profile of the electric vehicle 50. The battery operation characteristic profile is latest charging characteristic information and includes voltage, current, and temperature change profile according to the SOC of the battery 51.” [0078], “The database 60 includes a degradation look-up table storage unit 64. The degradation look-up table storage unit 64 is an information storage area in which voltage profile information according to SOC is recorded for each degree of degradation of the battery 51. The area in which the voltage profile information is stored for each degree of degradation is allocated to each battery assigned with the same battery model code. The degradation look-up table storage unit 64 may be defined in advance using data provided by a battery manufacturer and stored in the database 60.” [0082], “the battery service server 30 may determine the degree of degradation of the battery 51 by using the operation characteristic profile of the battery 51 included in the diagnostic analysis data, and record the degree of degradation in the diagnostic analysis data storage unit 62 of the database 60 to be matched with the model code of the electric vehicle 50 and/or the identification code of the electric vehicle 50 and/or the model code of the battery 51 and/or the identification code of the battery 51.” [0110]), in which the degradation data of a battery can be determined using the data collected from the battery. With respect to claims 3 and 13 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 2 and 12. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 2 and 12. Kim further teaches: identify the degradation data of the battery based on at least one of the existing calendar aging model corresponding to an abandonment time period before the host vehicle starts to drive or the calendar aging data, or any combination thereof and store the first calendar aging model determined using the calendar aging data, the degradation data, and the existing calendar aging model in the memory, upon concluding that the abandonment time before the host vehicle starts to drive is greater than the predetermined time ; (“In another example, the diagnostic analysis data may comprise operation characteristic accumulative information for the battery 51 and may include at least one selected from the group consisting of an accumulative operation time for each voltage section, an accumulative operation time for each current section, and an accumulative operation time for each temperature section for the battery 51 mounted to the electric vehicle 50.” [0079], “ when the electric vehicle 50 is parked, the battery service server 30 may collect the diagnostic analysis data about the battery 51 of the electric vehicle 50 through the network 40 from the communication device 20 separately installed in the parking place, and store the same in the database 60” [0101], “the battery service server 30 determines whether the operation characteristic profile of the battery 51 is collected in a preset degradation estimation voltage section. To this end, the battery service server 30 may examine the voltage distribution of the voltage profile according to the change of SOC. If the determination is YES, the battery service server 30 may determine a charge capacity change amount by integrating the current data measured in the degradation estimation voltage section, and determine the ratio of the charge capacity change amount to a reference charge capacity change amount as the degree of degradation. The reference charge capacity change amount is a charge capacity change amount represented while the battery 51 in a BOL state is being charged in the degradation estimation voltage section, and the reference charge capacity change amount may be recorded in advance in the database 60 for each model of the battery ” [0111]), where the collected battery data from a battery during a period of time including when the vehicle is parked is compared to reference data from a reference model. determine and store the existing calendar aging model as the first calendar aging model in the memory, upon concluding that the abandonment time is less than or equal to the predetermined time ; (“In another example, the diagnostic analysis data may comprise operation characteristic accumulative information for the battery 51 and may include at least one selected from the group consisting of an accumulative operation time for each voltage section, an accumulative operation time for each current section, and an accumulative operation time for each temperature section for the battery 51 mounted to the electric vehicle 50.” [0079], “ when the electric vehicle 50 is parked, the battery service server 30 may collect the diagnostic analysis data about the battery 51 of the electric vehicle 50 through the network 40 from the communication device 20 separately installed in the parking place, and store the same in the database 60” [0101]) where the collected battery data from a battery during a period of time including when the vehicle is parked is compared to reference data from a reference model. Kim does not teach concluding that an abandonment time before the host vehicle starts to drive is greater, less than, or equal to a predetermined time. However, Fujita teaches (“Left-at-high-charge-level duration rate D is one of the degrees of battery degradation which is defined by t/t 0 , where t represents the time period over which the secondary battery V1 is left unused in a state of a certain SOC (for example, 90%) or more, and t 0 represents the elapsed time from the date of manufacture of the battery to the present, and is a characteristic value in which the degree of battery degradation increases as left-at-high-charge-level duration rate D increases. The time period t over which the secondary battery V1 is left unused in a state of the certain SOC or more and the elapsed time t 0 from the date of manufacture of the battery to the present are read out from the memory of the battery controller V4 via the vehicle controller V5 .” [0028]), which shows comparing the time in which the battery is left unused to a time threshold, for example, determining when the vehicle battery is left unused is greater than a predetermined time. Thus, it would have been obvious to a person of ordinary skill in the art where the abandonment time is less than a time threshold in an attempt to provide an improved system or method, as a person with ordinary skill has good reason to pursue the known options within his or her technical grasp. It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Kim’s vehicle battery controller with Fujita’s abandonment time threshold in order to improve analyzing battery data (“to suppress both degradation of a battery and a decrease in the existence value of a vehicle.” see Fujita [0007]). With respect to claims 4 and 14 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 1 and 11. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 1 and 11. Kim does not teach, but Fujita further teaches: wherein the calendar aging data includes at least one of an abandonment time until the host vehicle starts to drive, a state of charge (SOC) value of the battery at a time point when the host vehicle is abandoned, or a battery temperature at each of the time point when the host vehicle is abandoned and a time point when the host vehicle starts to drive, or any combination thereof ; (“The degradation degree calculation unit 11 receives history data about a usage state related to a factor responsible for degradation of the secondary battery V1, and calculates the degrees of battery degradation by using the history data about the usage state. Specifically, the degradation degree calculation unit 11 calculates quick charging frequency A, charge level frequency at the start of charging B, power consumption frequency C, and left-at-high-charge-level duration rate D, and also calculates a battery temperature at the start of charging, the relationship between an outside air temperature and a battery temperature, and a battery temperature at the start of driving .” [0023] “Left-at-high-charge-level duration rate D is one of the degrees of battery degradation which is defined by t/t 0 , where t represents the time period over which the secondary battery V1 is left unused in a state of a certain SOC (for example, 90%) or more , and t 0 represents the elapsed time from the date of manufacture of the battery to the present, and is a characteristic value in which the degree of battery degradation increases as left-at-high-charge-level duration rate D increases. The time period t over which the secondary battery V1 is left unused in a state of the certain SOC or more and the elapsed time t 0 from the date of manufacture of the battery to the present are read out from the memory of the battery controller V4 via the vehicle controller V5.” [0028]), where battery data includes a time in which the battery is left unused, a state of charge value, and temperature time points in which the battery is left unused and when the vehicle starts to drive. It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Kim’s vehicle battery controller with Fujita’s abandonment time threshold in order to improve analyzing battery data (“to suppress both degradation of a battery and a decrease in the existence value of a vehicle.” see Fujita [0007]). With respect to claims 5 and 15 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 1 and 11. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 1 and 11. Kim further teaches: accumulate and store the calendar aging data according to the parking state during abandonment in the memory, when the host vehicle ends driving and is powered off ; (“In another example, the diagnostic analysis data may comprise operation characteristic accumulative information for the battery 51 and may include at least one selected from the group consisting of an accumulative operation time for each voltage section, an accumulative operation time for each current section, and an accumulative operation time for each temperature section for the battery 51 mounted to the electric vehicle 50.” [0079], “ when the electric vehicle 50 is parked, the battery service server 30 may collect the diagnostic analysis data about the battery 51 of the electric vehicle 50 through the network 40 from the communication device 20 separately installed in the parking place, and store the same in the database 60” [0101]), where the battery data during different period of time including when the vehicle is off and not being driven is collected and stored. Thus, it would have been obvious to a person of ordinary skill in the art to collect battery information when the host vehicle ends driving in an attempt to provide an improved system or method, as a person with ordinary skill has good reason to pursue the known options within his or her technical grasp. In turn, because the product as claimed has the properties predicted by the prior art, it would have been obvious to make the system or product where the battery data is collected when the host vehicle ends driving and is powered off. identify the degradation data of the battery, based on at least one of the driving durability data according to the driving state, the driving durability data being stored in the memory before the host vehicle is powered off, or an existing driving durability model, or any combination thereof ; (“In an example, the diagnostic analysis data includes at least one selected from the group consisting of a speed change profile, a driving distance accumulative profile, and a battery operation characteristic profile of the electric vehicle 50. The battery operation characteristic profile is latest charging characteristic information and includes voltage, current, and temperature change profile according to the SOC of the battery 51.” [0078], “The database 60 includes a degradation look-up table storage unit 64. The degradation look-up table storage unit 64 is an information storage area in which voltage profile information according to SOC is recorded for each degree of degradation of the battery 51. The area in which the voltage profile information is stored for each degree of degradation is allocated to each battery assigned with the same battery model code. The degradation look-up table storage unit 64 may be defined in advance using data provided by a battery manufacturer and stored in the database 60.” [0082], “the battery service server 30 may determine the degree of degradation of the battery 51 by using the operation characteristic profile of the battery 51 included in the diagnostic analysis data, and record the degree of degradation in the diagnostic analysis data storage unit 62 of the database 60 to be matched with the model code of the electric vehicle 50 and/or the identification code of the electric vehicle 50 and/or the model code of the battery 51 and/or the identification code of the battery 51.” [0110]), in which the degradation data of a battery can be determined using the data collected from the battery. With respect to claims 6 and 16 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 5 and 15. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 5 and 15. Kim does not teach, but Fujita teaches: identify the degradation data of the battery based on at least one of the existing driving durability model identified in a driving period before the host vehicle is powered off or the driving durability data, or any combination thereof and store a first driving durability model identified using the driving durability data, the degradation data, and the existing driving durability model in the memory, upon concluding that energy used while driving before the host vehicle is powered off is greater than a specified amount ; (“Power consumption frequency C is one of the degrees of battery degradation which is defined by W×β, where W represents average output power of the secondary battery V1 during certain driving, such as one trip from when an ignition key is turned on to when the ignition key is turned off, and β represents a weight coefficient, and is a characteristic value in which the degree of battery degradation increases as power consumption frequency C increases. The weight coefficient β increases as the average output power W increases. The average output power W of the secondary battery V1 during one trip and the weight coefficient β are read out from the memory of the battery controller V4 via the vehicle controller V5.” [0027], “In step ST2, the degradation degree calculation unit 11 calculates degradation degrees, such as… power consumption frequency C… on the basis of the read usage history data about the secondary battery V1. In step ST3, the alternative suppression measure extraction unit 12 determines whether or not the individual calculation results of… power consumption frequency C… at the start of driving are lower than or equal to certain allowable values.” [0044]), where the degradation data of the battery can be determined when the energy used while driving, or power consumed while driving, before the host vehicle is powered off, is greater than a specified amount. determine and store the existing driving durability model as the first driving durability model in the memory, upon concluding that the energy is less than or equal to the specified amount ; (“In step ST2, the degradation degree calculation unit 11 calculates degradation degrees, such as quick charging frequency A, charge level frequency at the start of charging B, power consumption frequency C, left-at-high-charge-level duration rate D, the battery temperature at the start of charging, the relationship between an outside air temperature and a battery temperature, and the battery temperature at the start of driving, on the basis of the read usage history data about the secondary battery V1. In step ST3, the alternative suppression measure extraction unit 12 determines whether or not the individual calculation results of quick charging frequency A, charge level frequency at the start of charging B, power consumption frequency C, left-at-high-charge-level duration rate D, the battery temperature at the start of charging, the relationship between an outside air temperature and a battery temperature, and the battery temperature at the start of driving are lower than or equal to certain allowable values.” [0044]), where the degradation data of the battery can be determined when the energy used while driving, or power consumed while driving, before the host vehicle is powered off, is compared to a specified threshold. It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to have combined Kim’s vehicle battery controller with Fujita’s energy threshold in order to improve analyzing battery data (“to suppress both degradation of a battery and a decrease in the existence value of a vehicle.” see Fujita [0007]). With respect to claims 7 and 17 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 1 and 11. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 1 and 11. Kim further teaches: wherein the driving durability data includes at least one of energy used until the host vehicle is powered off, a current used while the host vehicle is driving, or an average battery temperature while the host vehicle is driving, or any combination thereof ; (“the battery service server 30 may analyze the accumulative operation time for each voltage section, the accumulative operation time for each current section, and the accumulative operation time for each temperature section of the battery 51 included in the diagnostic analysis data to generate frequency distribution for each voltage, current and temperature, and then record the same in the diagnostic analysis data storage unit 62 of the database 60 to be matched with the model code of the electric vehicle 50 and/or the identification code of the electric vehicle 50 and/or the model code of the battery 51 and/or the identification code of the battery 51.” [0102]), the current and temperature of the battery is collected over the time that the vehicle is being used. With respect to claims 8 and 18 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 1 and 11. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 1 and 11. Kim further teaches: determine the reference model based on reference durability data about at least one of a current, a temperature of the battery, or an SOC value, or any combination thereof, in response that the host vehicle ends driving and is powered off ; (“the battery service server 30 may analyze the accumulative operation time for each voltage section, the accumulative operation time for each current section, and the accumulative operation time for each temperature section of the battery 51 included in the diagnostic analysis data to generate frequency distribution for each voltage, current and temperature, and then record the same in the diagnostic analysis data storage unit 62 of the database 60 to be matched with the model code of the electric vehicle 50 and/or the identification code of the electric vehicle 50 and/or the model code of the battery 51 and/or the identification code of the battery 51.” [0102], where the durability data of the data can be matched to a reference model. compare the reference data identified by inputting at least one of at least a portion of the driving durability data or at least a portion of the calendar aging data, or any combination thereof to the reference model with the degradation data to identify the degradation state of the battery ; (“the battery service server 30 determines whether the operation characteristic profile of the battery 51 is collected in a preset degradation estimation voltage section. To this end, the battery service server 30 may examine the voltage distribution of the voltage profile according to the change of SOC. If the determination is YES, the battery service server 30 may determine a charge capacity change amount by integrating the current data measured in the degradation estimation voltage section, and determine the ratio of the charge capacity change amount to a reference charge capacity change amount as the degree of degradation. The reference charge capacity change amount is a charge capacity change amount represented while the battery 51 in a BOL state is being charged in the degradation estimation voltage section, and the reference charge capacity change amount may be recorded in advance in the database 60 for each model of the battery” [0111]), where the collected battery data during the different times of using the battery is compared to reference data from a reference model. With respect to claims 9 and 19 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 8 and 11. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 8 and 11. Kim further teaches: a display operatively connected to the controller , (“The user interface is a graphic user interface and may be provided through an integrated information display 53 of the electric vehicle 50. The integrated information display 53 is provided aside the driver’s seat in the electric vehicle 50, and is a computer display that manages the control of the electric vehicle 50 and displays various driving information of the electric vehicle 50.” [0177]) identify a score about a degradation degree of the battery, based on a difference between the reference data and the degradation data ; (“the database may include a data area in which voltage profile information defined for each battery model and each degree of degradation is stored, and the battery service server may be configured to identify a voltage profile with highest similarity to a voltage profile included in the diagnostic analysis data by referring to the voltage profile information of each degree of degradation corresponding to a battery model for which the diagnostic analysis data is collected, determine a degree of degradation corresponding to the identified voltage profile as a degree of degradation of the battery, and store the determined degree of degradation in the database.” [0019], “In one example, the battery service server 30 may calculate the remaining life of the battery 51 by referring to the degradation information on the battery 51 and output the same graphically through the battery management software.” [0187]), where the score for a degradation degree of the battery can be determined based from reference data. display at least one of a predetermined battery state notification corresponding to a magnitude of the score among a plurality of battery state notifications or a battery operation guide identified based on a battery usage history, or any combination thereof, using the display ; (“the information about the remaining life may be output from the integrated information display 53 of the electric vehicle 50 through the electric vehicle control device 52. The remaining life may be calculated by referring to a look-up table that defines the remaining life for each degree of degradation. The remaining life look-up table may be defined for each model of the electric vehicle 50 and/or each battery model and recorded in advance in the battery residual value storage unit 65 of the database 60.” [0187], “the battery service server 30 may analyze the driving information of the electric vehicle 50, calculate the remaining life of the battery under the condition that the user’s current driving habit is maintained, and transmit the same to the electric vehicle control device 52 through the network 40. Then, the electric vehicle control device 52 may display the remaining life information of the battery through the integrated information display 53 of the electric vehicle 50.” [0189]), where the determined battery state information is displayed. With respect to claims 10 and 20 , Kim and Fujita, as shown in the rejection above, discloses the limitations of claims 9 and 19. The combination of Kim and Fujita teaches vehicle battery control apparatus and method of claims 9 and 19. Kim further teaches: display the battery operation guide including at least one of a ratio between normal charge and quick charge, a ratio between normal driving and driving at rapid acceleration and deceleration, an amount of average charging of the battery while parked, or an average temperature of the battery while driving, or any combination thereof ; (“The driving habit may be analyzed using the speed change profile according to the SOC included in the diagnostic analysis data collected from the electric vehicle 50. As an example, the battery service server 50 may accumulatively count the number of sudden accelerations by analyzing the speed change profile according to the SOC, and classify the driving habit into a plurality of types according to the number of sudden accelerations .” [0190], “Then, the electric vehicle control device 52 may display the remaining life information of the battery 51 estimated for each type of driving habit through the integrated information display 53 of the electric vehicle 50. In addition, the battery management software may display the remaining life information of the battery 51 estimated for each type of driving habit through the display of the mobile communication terminal 90. The user of the electric vehicle 50 may be provided with the remaining life information of the battery 51 estimated from the current driving habit as well as the remaining life information of the battery 51 estimated from other driving habit types. Accordingly, it is possible to induce the user of the electric vehicle 50 to drive more economically.” [0191]), where a ratio between normal driving and driving at rapid acceleration and deceleration and other recorded battery data can be shown on the display. Conclusion 07-40 AIA Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL . See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Christine N Huynh whose telephone number is (571)272-9980. The examiner can normally be reached Monday - Friday 8 am - 4 pm. 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, Aniss Chad can be reached at (571)270-3832. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /CHRISTINE NGUYEN HUYNH/Examiner, Art Unit 3662 /ANISS CHAD/Supervisory Patent Examiner, Art Unit 3662 Application/Control Number: 18/783,021 Page 2 Art Unit: 3662 Application/Control Number: 18/783,021 Page 3 Art Unit: 3662 Application/Control Number: 18/783,021 Page 4 Art Unit: 3662 Application/Control Number: 18/783,021 Page 5 Art Unit: 3662 Application/Control Number: 18/783,021 Page 6 Art Unit: 3662 Application/Control Number: 18/783,021 Page 7 Art Unit: 3662 Application/Control Number: 18/783,021 Page 8 Art Unit: 3662 Application/Control Number: 18/783,021 Page 9 Art Unit: 3662 Application/Control Number: 18/783,021 Page 10 Art Unit: 3662 Application/Control Number: 18/783,021 Page 11 Art Unit: 3662 Application/Control Number: 18/783,021 Page 12 Art Unit: 3662 Application/Control Number: 18/783,021 Page 13 Art Unit: 3662 Application/Control Number: 18/783,021 Page 14 Art Unit: 3662 Application/Control Number: 18/783,021 Page 15 Art Unit: 3662 Application/Control Number: 18/783,021 Page 16 Art Unit: 3662 Application/Control Number: 18/783,021 Page 17 Art Unit: 3662 Application/Control Number: 18/783,021 Page 18 Art Unit: 3662 Application/Control Number: 18/783,021 Page 19 Art Unit: 3662 Application/Control Number: 18/783,021 Page 20 Art Unit: 3662 Application/Control Number: 18/783,021 Page 21 Art Unit: 3662 Application/Control Number: 18/783,021 Page 22 Art Unit: 3662 Application/Control Number: 18/783,021 Page 23 Art Unit: 3662 Application/Control Number: 18/783,021 Page 24 Art Unit: 3662 Application/Control Number: 18/783,021 Page 25 Art Unit: 3662 Application/Control Number: 18/783,021 Page 26 Art Unit: 3662 Application/Control Number: 18/783,021 Page 27 Art Unit: 3662 Application/Control Number: 18/783,021 Page 28 Art Unit: 3662 Application/Control Number: 18/783,021 Page 29 Art Unit: 3662 Application/Control Number: 18/783,021 Page 30 Art Unit: 3662
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