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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on October 30, 2023, November 26, 2024, and July 2, 2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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) 1, 2, 4, 5, 7, 10, 12 – 14, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Slepchenkov et al (US 2022/0219549 A1) (herein after Slepchenkov) in view of Wang et al (US 11,774,505 B1) (herein after Wang 505).
Regarding Claim 1, Slepchenkov discloses, 1. A system for monitoring an electrical equipment (Fig. 1A module-based energy system 100, ¶ 122 components of the vehicle), the system comprising: a sensor subsystem comprising a voltage sensor, a current sensor, and a temperature sensor (Fig. 2A, ¶ 133 monitor circuitry 208 configured to monitor (e.g., collect, sense, measure, and/or determine) one or more aspects of module 108 and/or the components thereof, such as voltage, current, temperature; Note: ¶ 125 FIGS. 2A-2B are block diagrams depicting additional example embodiments of system 100 with module 108 having a power converter 202, an energy buffer 204, and an energy source 20); a housing (Fig. 2C, housings 220, 222, 224) surrounding the sensor subsystem; a mounting interface (Fig. 2A, path 116) coupled to the housing and configured to couple to the electrical equipment, such that the sensor subsystem can detect signals associated with a battery (Fig. 4A, battery cell 402; Note: Fig 4A-D is part of Fig 2A-D ¶ 127 FIGS. 4A-4D are schematic diagrams depicting example embodiments of energy source 206) of the electrical equipment; a signal conditioning and communications subsystem (Fig. 2A, master control device (MCD) 112) coupled to the sensor subsystem within the housing and configured to receive a voltage signal stream, a current signal stream, and a temperature signal stream (Fig. 2A, ¶ 133 monitor (e.g., collect, sense, measure, and/or determine) one or more aspects of module 108 and/or the components thereof, such as voltage, current, temperature) from the sensor subsystem; —.
Slepchenkov fails to disclose, — and a processing subsystem coupled to the signal conditioning and communications subsystem and comprising a neural processing unit (NPU), the processing subsystem contained within the housing, and comprising non-transitory media storing instructions that, when executed, perform operations for: receiving data derived from the sensor subsystem; performing a set of transformation operations upon said data; identifying a set of unique signatures corresponding to states of a set of subcomponents of the battery, from the set of transformation operations; and returning an analysis comprising a recommended action for improving or maintaining proper performance of the battery, based upon the set of unique signatures.
In analogous art, Wang 505 discloses, — and a processing subsystem (Fig. 3, processor 60, a memory 61, an input apparatus 62 and an output apparatus 63) coupled to the signal conditioning and communications subsystem and comprising a neural processing unit (NPU) (Fig. 3. Col. 9. Ln. 18 processor 60, a memory 61, an input apparatus 62 and an output apparatus 63; Col. 8. Ln. 22 The neural network model based on deep learning), the processing subsystem contained within the housing, and comprising non-transitory media storing instructions that, when executed, perform operations for: receiving data derived from the sensor subsystem (Fig. 3. Col. 3. Ln. 63 sensor abnormality, real-time battery parameters); performing a set of transformation operations (Fig. 1. Col. 3. Ln. 66 multiple groups of feature data are calculated) upon said data; identifying a set of unique signatures (Fig. 1. Col. 4. Ln. 36 reflect the consistency of the single batteries) corresponding to states (Fig. 1. Col. 3. Ln. 36 safety state of a whole battery pack) of a set of subcomponents of the battery, from the set of transformation operations; and returning an analysis (Fig. 1. Col. 4. Ln. 21 classification result reflecting the consistency of each single battery) comprising a recommended action for improving or maintaining proper performance of the battery (Fig. 1. Col. 7. Ln. 47 a classification result of whether single battery consistency safety hazards exist), based upon the set of unique signatures.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov by combining the system disclosed by Slepchenkov with a system comprising: a processing subsystem coupled to the signal conditioning and communications subsystem and comprising a neural processing unit (NPU), the processing subsystem contained within the housing, and comprising non-transitory media storing instructions that, when executed, perform operations for: receiving data derived from the sensor subsystem; performing a set of transformation operations upon said data; identifying a set of unique signatures corresponding to states of a set of subcomponents of the battery, from the set of transformation operations; and returning an analysis comprising a recommended action for improving or maintaining proper performance of the battery, based upon the set of unique signatures; disclosed by Wang 505 for the benefit of using a fast calculation and high accuracy neural network to identify a battery hazard [Wang 505: Col. 2, Ln. 33: The neural network model based on deep learning is introduced inside and outside the traditional PCA algorithm in the whole process, which improves the accuracy of principal component analysis, reduces the interference of specific data values to principal component analysis results, also enhances the accuracy of consistency hazard identification, and fully exerts the advantages of fast calculation and high accuracy of the neural network model].
Regarding Claim 2, Slepchenkov in view of Wang 505 disclose the limitations of claim 1, which this claim depends on.
Slepchenkov further discloses, 2. The system of claim 1, wherein the electrical equipment comprises a vehicle (Fig. 1A ¶ 122 components of the vehicle).
Regarding Claim 4, Slepchenkov in view of Wang 505 disclose the limitations of claim 2, which this claim depends on.
Slepchenkov further discloses, 4. The system of claim 2, wherein the vehicle comprises an electric vehicle (Fig. 1A ¶ 122 components of the vehicle), wherein the analysis comprises a fault state (Fig. 1A, ¶ 118 module 108 indicates the presence of an actual or potential fault) in relation to an operational state of the electric vehicle, and wherein the recommended action comprises at least one of: stopping charging of the electric vehicle and re-positioning the electric vehicle (Fig. 23B, ¶ 291 inductive interface circuitry 2364).
Regarding Claim 5, Slepchenkov in view of Wang 505 disclose the limitations of claim 1, which this claim depends on.
Slepchenkov further discloses, 5. The system of claim 1, wherein said data comprises data derived only from the temperature signal stream (Fig. 2A, ¶ 133 monitor circuitry 208 configured to monitor (e.g., collect, sense, measure, and/or determine) one or more aspects of module 108 and/or the components thereof, such as temperature).
Regarding Claim 7, Slepchenkov in view of Wang 505 disclose the limitations of claim 1, which this claim depends on.
Slepchenkov fails to disclose, 7. The system of claim 1, wherein NPU comprises self-attention time-series transformer architecture comprising an encoder block comprising multi-head attention subarchitecture, and wherein the self-attention time-series transformer architecture of the NPU omits a decoder block.
Wang 505 further discloses, 7. The system of claim 1, wherein NPU comprises self-attention time-series transformer architecture (Fig. 1. Col. 3. Ln. 42 self-attention layer) comprising an encoder block comprising multi-head attention subarchitecture (Fig. 1. Col. 7. Ln. 42 trained multi-head), and wherein the self-attention time-series transformer architecture of the NPU omits a decoder block (Fig. 1. Col. 7. Ln. 41 series-connected; “series connected omits decode blocks”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the system disclosed by Slepchenkov and Wang 505 with a system wherein, NPU comprises self-attention time-series transformer architecture comprising an encoder block comprising multi-head attention subarchitecture, and wherein the self-attention time-series transformer architecture of the NPU omits a decoder block; disclosed by Wang 505 for the benefit of using a fast calculation and high accuracy neural network to identify a battery hazard [Wang 505: Col. 2, Ln. 33: The neural network model based on deep learning is introduced inside and outside the traditional PCA algorithm in the whole process, which improves the accuracy of principal component analysis, reduces the interference of specific data values to principal component analysis results, also enhances the accuracy of consistency hazard identification, and fully exerts the advantages of fast calculation and high accuracy of the neural network model].
Regarding Claim 10, Slepchenkov in view of Wang 505 disclose the limitations of claim 1, which this claim depends on.
Slepchenkov further discloses, 10. The system of claim 1, wherein the analysis includes a fault state indicating thermal runaway of the battery (Fig. 31A, ¶ 328 One or more thermal management systems can be utilized to circulate a heat transfer fluid, components with the greatest cooling requirements are cooled first), and wherein the recommended action comprises isolating the battery with a fireproof container (Fig. 31A, enclosure 3111).
Regarding Claim 12, Slepchenkov discloses,12. A method for monitoring an electrical equipment (Fig. 1A module-based energy system 100, ¶ methods, features and advantages of the subject matter described herein; ¶ 122 components of the vehicle), the method comprising: providing a mounting interface (Fig. 2A, path 116) between a sensor subsystem coupled to a signal processing subsystem (Fig. 2A, local control devices (LCDs) 114-1), and the electrical equipment, the sensor subsystem comprising a voltage sensor, a current sensor, and a temperature sensor (Fig. 2A, ¶ 133 monitor circuitry 208 configured to monitor (e.g., collect, sense, measure, and/or determine) one or more aspects of module 108 and/or the components thereof, such as voltage, current, temperature; Note: ¶ 125 FIGS. 2A-2B are block diagrams depicting additional example embodiments of system 100 with module 108 having a power converter 202, an energy buffer 204, and an energy source 20), and wherein providing the mounting interface comprises mounting the sensor subsystem to the electrical equipment, such that the voltage sensor, the current sensor, and the temperature sensor can detect signals from an output of a battery (Fig. 4A, battery cell 402; Note: Fig 4A-D is part of Fig 2A-D ¶ 127 FIGS. 4A-4D are schematic diagrams depicting example embodiments of energy source 206) of the electrical equipment; sampling a set of signal streams (Fig. 2A, ¶ 133 monitor circuitry 208 configured to monitor (e.g., collect, sense, measure, and/or determine) one or more aspects of module 108 and/or the components thereof) generated from the sensor subsystem during operation of the electrical equipment; —
Slepchenkov fails to disclose, — performing a set of transformation operations upon the set of signal streams wherein the set of transformation operations comprises operations applied by self-attention time-series transformer architecture; identifying a set of signatures corresponding to faults of a set of subcomponents of the battery from the set of transformation operations; and returning an analysis comprising a recommended action related to performance of the battery, based upon the set of signatures.
In analogous art, Wang 505 discloses, — performing a set of transformation operations (Fig. 1. Col. 3. Ln. 66 multiple groups of feature data are calculated) upon the set of signal streams wherein the set of transformation operations comprises operations applied by self-attention time-series transformer architecture (Fig. 1. Col. 3. Ln. 42 self-attention layer); identifying a set of signatures (Fig. 1. Col. 4. Ln. 36 reflect the consistency of the single batteries) corresponding to faults of a set of subcomponents of the battery from the set of transformation operations; and returning an analysis (Fig. 1. Col. 4. Ln. 21 classification result reflecting the consistency of each single battery) comprising a recommended action related to performance of the battery (Fig. 1. Col. 7. Ln. 47 a classification result of whether single battery consistency safety hazards exist), based upon the set of signatures.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov by combining the method performed by system disclosed by Slepchenkov with a method performed by a system comprising: — performing a set of transformation operations upon the set of signal streams wherein the set of transformation operations comprises operations applied by self-attention time-series transformer architecture; identifying a set of signatures corresponding to faults of a set of subcomponents of the battery from the set of transformation operations; and returning an analysis comprising a recommended action related to performance of the battery, based upon the set of signatures; disclosed by Wang 505 for the benefit of using a fast calculation and high accuracy neural network to identify a battery hazard [Wang 505: Col. 2, Ln. 33: The neural network model based on deep learning is introduced inside and outside the traditional PCA algorithm in the whole process, which improves the accuracy of principal component analysis, reduces the interference of specific data values to principal component analysis results, also enhances the accuracy of consistency hazard identification, and fully exerts the advantages of fast calculation and high accuracy of the neural network model].
Regarding Claim 13, Slepchenkov in view of Wang 505 disclose the limitations of claim 12, which this claim depends on.
Slepchenkov further discloses, 13. The method of claim 12, wherein the electrical equipment comprises an electric vehicle (Fig. 1A ¶ 122 components of the vehicle), and wherein analysis comprises detected faults (Fig. 2A, ¶ 117 with or without a fault) of the set of subcomponents of the battery and the electric vehicle, the set of subcomponents comprising: an energy management subcomponent (Fig. 2A, ¶ 125 a power converter 202), a thermal management subcomponent (Fig. 31A, ¶ 328 One or more thermal management systems), an inverter subcomponent ((Fig. 2A, ¶ 125 a power converter 202, inverter), an electric motor subcomponent (Fig. 2A, ¶ 111 control device 104 Motor Control Unit (MCU)), and a regenerative braking subcomponent (Fig. 2A, ¶ 153 Modules 108 ( e.g., regenerative braking),).
Regarding Claim 14, Slepchenkov in view of Wang 505 disclose the limitations of claim 13, which this claim depends on.
Slepchenkov further discloses, 14. The method of claim 13, wherein the recommended action comprises delivering energy stored within the battery to a grid (Fig. 1A, ¶ 106 Load 101 can be any type of load such as a motor or a grid) through a vehicle-to-grid (V2G) charging interface, in response to a demand event indicated in the analysis.
Regarding Claim 18, Slepchenkov in view of Wang 505 disclose the limitations of claim 12, which this claim depends on.
Slepchenkov further discloses, 18. The method of claim 12, wherein the electrical equipment comprises a transportation device (Fig. 1A, ¶ 122 components of the vehicle), and wherein the recommended action comprises at least one of: re-positioning the transportation device (Fig. 23B, ¶ 291 inductive interface circuitry 2364) and performing an emergency procedure for isolating the battery (Fig. 31A, enclosure 3111, ¶ 328 One or more thermal management systems can be utilized to circulate a heat transfer fluid, components with the greatest cooling requirements are cooled first).
Regarding Claim 19, Slepchenkov in view of Wang 505 disclose the limitations of claim 12, which this claim depends on.
Slepchenkov fails to disclose, 19. The method of claim 12, wherein the self-attention time-series transformer architecture comprises an encoder block comprising multi-head attention subarchitecture, wherein the self-attention time-series transformer architecture omits a decoder block.
Wang 505 further discloses, 19. The method of claim 12, wherein the self-attention time-series transformer architecture (Fig. 1. Col. 3. Ln. 42 self-attention layer) comprises an encoder block comprising multi-head attention subarchitecture (Fig. 1. Col. 7. Ln. 42 trained multi-head), wherein the self-attention time-series transformer architecture omits a decoder block (Fig. 1. Col. 7. Ln. 41 series-connected; “series connected omits decode blocks”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the method performed by the system disclosed by Slepchenkov and Wang 505 with a method performed by a system wherein, the self-attention time-series transformer architecture comprises an encoder block comprising multi-head attention subarchitecture, wherein the self-attention time-series transformer architecture omits a decoder block; disclosed by Wang 505 for the benefit of using a fast calculation and high accuracy neural network to identify a battery hazard [Wang 505: Col. 2, Ln. 33: The neural network model based on deep learning is introduced inside and outside the traditional PCA algorithm in the whole process, which improves the accuracy of principal component analysis, reduces the interference of specific data values to principal component analysis results, also enhances the accuracy of consistency hazard identification, and fully exerts the advantages of fast calculation and high accuracy of the neural network model].
Claim(s) 3, 6, 11, 15, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Slepchenkov et al (US 2022/0219549 A1) (herein after Slepchenkov) in view of Wang et al (US 11,774,505 B1) (herein after Wang 505), and further in view of Foland (US 2023/0206772 A1) (herein after Foland).
Regarding Claim 3, Slepchenkov in view of Wang 505 disclose the limitations of claim 2, which this claim depends on.
Slepchenkov and Wang 505 fail to disclose, 3. The system of claim 2, wherein the vehicle comprises an aircraft, wherein the analysis comprises a high temperature fault state in relation to a state of climb of the aerial vehicle, and wherein the recommended action comprises reducing a rate of climb of the aerial vehicle.
In analogous art, Foland discloses, 3. The system of claim 2, wherein the vehicle comprises an aircraft (Fig. 1, electric vehicle 108 may be an electric aircraft), wherein the analysis comprises a high temperature fault state (Fig. 1, ¶ 23 peak temperatures reached by battery pack 112; ¶ 28 "threshold temperature" is a specified temperature associated with a risk of harm to battery pack 112) in relation to a state of climb of the aerial vehicle (Fig. 1, ¶ 29 controller 104 may be configured to generate a revised flight plan 156 if temperature output 124 exceeds a threshold temperature), and wherein the recommended action comprises reducing a rate of climb (Fig. 5, ¶ 59 perform one or more aircraft maneuvers, turns, climbs, and/or descents; Note: Fig 5 is part of Fig 1; ¶ 51 In embodiments, flight controller 504 may be installed in an aircraft) of the aerial vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the system disclosed by Slepchenkov and Wang 505 with a system wherein, the vehicle comprises an aircraft, wherein the analysis comprises a high temperature fault state in relation to a state of climb of the aerial vehicle, and wherein the recommended action comprises reducing a rate of climb of the aerial vehicle; disclosed by Foland for the benefit of controlling aircraft flight in a safe manner based on predicted battery temperature [Foland: ¶ 17: In some embodiments, the controller may be configured to generate a revised flight plan if the predicted battery temperature exceeds the threshold temperature. Exemplary embodiments illustrating aspects of the present].
Regarding Claim 6, Slepchenkov in view of Wang 505 disclose the limitations of claim 1, which this claim depends on.
Slepchenkov further discloses, 6. The system of claim 1, wherein the current sensor comprises an inductive current sensor (Fig. 23B, ¶ 291 inductive interface circuitry 2364), —.
Slepchenkov and Wang 505 fail to disclose, — and wherein the temperature sensor comprises an optical temperature sensor, such that the sensor subsystem comprises non-contact sensors.
In analogous art, Foland discloses,— and wherein the temperature sensor comprises an optical temperature sensor (Fig. 1, ¶ 24 infrared sensors), such that the sensor subsystem comprises non-contact sensors (Fig. 1, ¶ 24 contactless sensor).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the system disclosed by Slepchenkov and Wang 505 with a sensor system wherein the temperature sensor comprises an optical temperature sensor, such that the sensor subsystem comprises non-contact sensors; disclosed by Foland for the benefit of controlling aircraft flight in a safe manner based on predicted battery temperature [Foland: ¶ 17: In some embodiments, the controller may be configured to generate a revised flight plan if the predicted battery temperature exceeds the threshold temperature. Exemplary embodiments illustrating aspects of the present].
Regarding Claim 11, Slepchenkov in view of Wang 505 disclose the limitations of claim 1, which this claim depends on.
Slepchenkov and Wang 505 fail to disclose, 11. The system of claim 1, returning the analysis comprises returning a set of fault states of at least one of the set of subcomponents of the battery, and wherein the set of subcomponents comprises a cell, an electrolyte, an anode, a cathode, a separator, and an interfacial subcomponent.
In analogous art, Foland discloses, 11. The system of claim 1, returning the analysis comprises returning a set of fault states (Fig. 2, ¶ 36 cell failure, malfunction of a battery cell) of at least one of the set of subcomponents of the battery, and wherein the set of subcomponents comprises a cell, an electrolyte (Fig. 2, ¶ 36 electrolytes), an anode, a cathode, a separator, and an interfacial subcomponent (Fig. 2, ¶ 36 electrical anomalies).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov in view of Wang 505 by combining the system disclosed by Slepchenkov in view of Wang 505 with a system wherein, returning the analysis comprises returning a set of fault states of at least one of the set of subcomponents of the battery, and wherein the set of subcomponents comprises a cell, an electrolyte, an anode, a cathode, a separator, and an interfacial subcomponent; disclosed by Foland for the benefit of controlling aircraft flight in a safe manner based on predicted battery temperature [Foland: ¶ 17: In some embodiments, the controller may be configured to generate a revised flight plan if the predicted battery temperature exceeds the threshold temperature. Exemplary embodiments illustrating aspects of the present].
Regarding Claim 15, Slepchenkov in view of Wang 505 disclose the limitations of claim 12, which this claim depends on.
Slepchenkov and Wang 505 fail to disclose, 15. The method of claim 12, wherein the electrical equipment comprises an aerial vehicle, wherein the analysis comprises a fault state in relation to an operational state of flight of the aerial vehicle, and wherein the recommended action comprises performing an emergency landing procedure.
In analogous art, Foland discloses, 15. The method of claim 12, wherein the electrical equipment comprises an aerial vehicle (Fig. 1, electric vehicle 108 may be an electric aircraft), wherein the analysis comprises a fault state (Fig. 1, ¶ 23 peak temperatures reached by battery pack 112; ¶ 28 "threshold temperature" is a specified temperature associated with a risk of harm to battery pack 112) in relation to an operational state of flight of the aerial vehicle (Fig. 1, ¶ 29 controller 104 may be configured to generate a revised flight plan 156 if temperature output 124 exceeds a threshold temperature), and wherein the recommended action comprises performing an emergency landing procedure (Fig. 5, ¶ 59 perform one or more aircraft maneuvers, turns, climbs, and/or descents; Note: Fig 5 is part of Fig 1; ¶ 51 In embodiments, flight controller 504 may be installed in an aircraft).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the method performed by the system disclosed by Slepchenkov and Wang 505 with a method performed by a system 15. The method of claim 12, wherein the electrical equipment comprises an aerial vehicle, wherein the analysis comprises a fault state in relation to an operational state of flight of the aerial vehicle, and wherein the recommended action comprises performing an emergency landing procedure; disclosed by Foland for the benefit of controlling aircraft flight in a safe manner based on predicted battery temperature [Foland: ¶ 17: In some embodiments, the controller may be configured to generate a revised flight plan if the predicted battery temperature exceeds the threshold temperature. Exemplary embodiments illustrating aspects of the present].
Regarding Claim 17, Slepchenkov in view of Wang 505 disclose the limitations of claim 12, which this claim depends on.
Slepchenkov and Wang 505 fail to disclose, 17. The method of claim 12, further comprising monitoring the set of subcomponents of the battery during manufacture of the battery, wherein the analysis indicated detection of a set of faults comprising one or more of: an electric fault state, an interfacial fault, an electrolyte preparation fault, and a delamination fault.
In analogous art, Foland discloses, 17. The method of claim 12, further comprising monitoring the set of subcomponents of the battery during manufacture of the battery, wherein the analysis indicated detection of a set of faults (Fig. 2, ¶ 36 cell failure, malfunction of a battery cell) comprising one or more of: an electric fault state (Fig. 2, ¶ 36 electrical anomalies), an interfacial fault, an electrolyte preparation fault (Fig. 2, ¶ 36 electrolytes), and a delamination fault (Fig. 2, ¶ 36 electrical anomalies).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the method performed by the system disclosed by Slepchenkov and Wang 505 with a method performed by a system wherein, returning the analysis comprises returning a set of fault states of at least one of the set of subcomponents of the battery, and wherein the set of subcomponents comprises a cell, an electrolyte, an anode, a cathode, a separator, and an interfacial subcomponent; disclosed by Foland for the benefit of controlling aircraft flight in a safe manner based on predicted battery temperature [Foland: ¶ 17: In some embodiments, the controller may be configured to generate a revised flight plan if the predicted battery temperature exceeds the threshold temperature. Exemplary embodiments illustrating aspects of the present].
Claim(s) 8 is rejected under 35 U.S.C. 103 as being unpatentable over Slepchenkov et al (US 2022/0219549 A1) (herein after Slepchenkov) in view of Wang et al (US 11,774,505 B1) (herein after Wang 505), and further in view of Wang (US 2024/0236862 A1) (herein after Wang 862).
Regarding Claim 8, Slepchenkov in view of Wang 505 disclose the limitations of claim 7, which this claim depends on.
Slepchenkov and Wang 505 fail to disclose, 8. The system of claim 7, wherein the NPU is an NPU with 1 trillions of operations per second (TOPS) capability with energy use performance of less than 1 picojoule per operation.
In analogous art, Wang 862 discloses, 8. The system of claim 7, wherein the NPU is an NPU with 1 trillions of operations per second (TOPS) capability with energy use performance of less than 1 picojoule per operation (Fig. 1, ¶ 31 stored energy device 140, e.g., bytes per picojoule).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the system disclosed by Slepchenkov and Wang 505 with a system wherein, the NPU is an NPU with 1 trillions of operations per second (TOPS) capability with energy use performance of less than 1 picojoule per operation; disclosed by Wang 862 for the benefit of partitioning the amount of energy stored in a battery to better manage and optimize energy usage [Wang 862: ¶ 8 the energy usage or consumption of the UE by determining a preferred partitioning of stored energy consumption at the UE during wireless data transfer between the UE and the base station ( e.g., a preferred partitioning of the amount or percentage of stored energy utilized by the UE for baseband signal processing with respect to the amount or percentage of energy utilized by the UE for radio interface signal processing), … thereby better managing (and in some cases, optimizing) stored energy usage and increasing battery life].
Claim(s) 9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Slepchenkov et al (US 2022/0219549 A1) (herein after Slepchenkov) in view of Wang et al (US 11,774,505 B1) (herein after Wang 505), and further in view of Bertness (US 2010/0262404 A1) (herein after Bertness).
Regarding Claim 9, Slepchenkov in view of Wang 505 disclose the limitations of claim 1, which this claim depends on.
Slepchenkov and Wang 505 fail to disclose, 9. The system of claim 1, wherein the electrical equipment comprises a transmission line, and wherein the recommended action comprises modulating at least one of a dynamic line rating and an effective transmission impedance of a power flow controller associated with the transmission line.
In analogous art, Bertness discloses, 9. The system of claim 1, wherein the electrical equipment comprises a transmission line (Fig. 1, Kelvin connection formed by connections 36A and 36B), and wherein the recommended action comprises modulating at least one of a dynamic line rating (Fig. 1, ¶ 29 dynamic parameters) and an effective transmission impedance (Fig. 1, ¶ 29 impedance) of a power flow controller associated with the transmission line.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the system disclosed by Slepchenkov and Wang 505 with a system wherein, the electrical equipment comprises a transmission line, and wherein the recommended action comprises modulating at least one of a dynamic line rating and an effective transmission impedance of a power flow controller associated with the transmission line; disclosed by Bertness for the benefit of adjusting battery charging to increase battery life and provide early detection of impeding battery failure [Bertness: ¶ 48 adjusted based upon the state of charge and/or the state of health … In general, this technique will improve vehicle reliability by reducing heat due to excessive IR losses, increasing battery life, providing early detection of impending battery failure].
Regarding Claim 16, Slepchenkov in view of Wang 505 disclose the limitations of claim 12, which this claim depends on.
Slepchenkov and Wang 505 fail to disclose, 16. The method of claim 12, wherein the electrical equipment comprises a transmission line, and wherein the recommended action comprises modulating at least one of a dynamic line rating and an effective transmission impedance of a power flow controller associated with the transmission line in response to an environmental condition encoded in the analysis.
In analogous art, Bertness discloses, 16. The method of claim 12, wherein the electrical equipment comprises a transmission line (Fig. 1, Kelvin connection formed by connections 36A and 36B), and wherein the recommended action comprises modulating at least one of a dynamic line rating (Fig. 1, ¶ 29 dynamic parameters) and an effective transmission impedance (Fig. 1, ¶ 29 impedance) of a power flow controller associated with the transmission line in response to an environmental condition encoded in the analysis.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the method performed by the system disclosed by Slepchenkov and Wang 505 with a method performed by a system wherein, the electrical equipment comprises a transmission line, and wherein the recommended action comprises modulating at least one of a dynamic line rating and an effective transmission impedance of a power flow controller associated with the transmission line; disclosed by Bertness for the benefit of adjusting battery charging to increase battery life and provide early detection of impeding battery failure [Bertness: ¶ 48 adjusted based upon the state of charge and/or the state of health … In general, this technique will improve vehicle reliability by reducing heat due to excessive IR losses, increasing battery life, providing early detection of impending battery failure].
Claim(s) 20 is rejected under 35 U.S.C. 103 as being unpatentable over Slepchenkov et al (US 2022/0219549 A1) (herein after Slepchenkov) in view of Wang et al (US 11,774,505 B1) (herein after Wang 505), and further in view of KOBAYASHI (US 2016/0109931 A1) (herein after Kobayashi).
Regarding Claim 20, Slepchenkov in view of Wang 505 disclose the limitations of claim 12, which this claim depends on.
Slepchenkov and Wang 505 fail to disclose, 20. The method of claim 12, further comprising executing the recommended action, wherein executing the recommended action comprises: transmitting information from the analysis, for observation through a mixed-reality device; receiving an input from a user of mixed reality device, the input configured to respond to at least one of a set of faults of the apparatus indicated in the analysis; and executing instructions for addressing the at least one fault of the set of faults, based upon the input, wherein the electrical equipment is positioned remote from the user.
In analogous art, Kobayashi discloses, 20. The method of claim 12, further comprising executing the recommended action, wherein executing the recommended action comprises: transmitting information from the analysis, for observation through a mixed-reality device (Fig. 1, ¶ 85 a virtual image which is displayed by the head mounted display 100); receiving an input from a user (Fig. 2, ¶ 107 input information acquisition unit 110 acquires a signal corresponding to an input operation from the user) of mixed reality device, the input configured to respond to at least one of a set of faults (Fig. 13, ¶ 400 the repair guide records checking items for specifying failure causes) of the apparatus indicated in the analysis; and executing instructions for addressing the at least one fault of the set of faults (Fig. 2, ¶ 131 power is supplied from the power supply unit 137 in response to an instruction from the control unit 140), based upon the input, wherein the electrical equipment is positioned remote (Fig. 13, ¶ 392 communication network 4 may be a wide communication line network which can connect remote locations to each other) from the user.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Slepchenkov and Wang 505 by combining the method performed by the system disclosed by Slepchenkov and Wang 505 with a method performed by a system further comprising, executing the recommended action, wherein executing the recommended action comprises: transmitting information from the analysis, for observation through a mixed-reality device; receiving an input from a user of mixed reality device, the input configured to respond to at least one of a set of faults of the apparatus indicated in the analysis; and executing instructions for addressing the at least one fault of the set of faults, based upon the input, wherein the electrical equipment is positioned remote from the user; disclosed by Kobayashi for the benefit of replacing a battery without stopping operation of the device [Kobayashi: ¶ 6 As advantage of some aspects of the invention is to enable a battery to be replaced without stopping an operation of a display apparatus which is driven with the battery.].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Gomez et al. (US 2021/0173376 A1) discloses, a system for monitoring an electrical equipment (Fig. 1A, ¶ 27 a system 100 for evaluating hydraulic apparatus events).
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/JOSEPH O. NYAMOGO/
Examiner
Art Unit 2858
/FARHANA A HOQUE/Primary Examiner, Art Unit 2858
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