DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This communication is a first office action, non-final rejection on the merits. Claims 1-20, as originally filed, are currently pending and have been considered below.
Claim Rejections - 35 USC § 103
3. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
4. Claims 1-5, 7-15 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over John et al. ( WO-2021-005942) in view of Furr et al. ( WO-2020-260623) in view of Ryu (WO-2021-141255).
As Per Claim 1, John et al. ( John) teaches, a system for controlling battery consumption in an electric aircraft (100), ( via an aircraft 100 through controller 101 determining the battery consumption, and the remaining battery level, Page 20, para 6, Fig.3) the system comprising: a monitor unit (109) configured to compile operating data for at least one battery module in a battery pack of the electric aircraft; (via battery monitoring unit 109, page 11, para 6-7, Fig.3)); and a computing device coupled to the monitor unit, ( via processor 101, Page 12 4th para – Page 13, 1st para, Fig.3))
However, John does not explicitly teach, computing device is configured to: generate a digital twin of the at least one battery pack module; simulate, via the digital twin, a degradation of the at least one battery pack module based on the operating data for the at least one battery module; and predict a future performance of the at least one battery pack module based on the simulated degradation of the at least one battery pack module.
In a related field of Art, Furr et al. ( Furr) teaches, battery monitoring system wherein, computing device is configured to: generate a digital twin of the at least one battery pack module; ( via a battery management system 100 comprising a data aggregation and management module 108 that implements a BLIS service 110 and maintains a battery database ( [0039], Fig.1),.. using the data gathered by the BLIS service as inputs to generate a digital twin for a given battery cell, module, or pack. , [0067]-0068]). .. “the BLIS service may use a digital twin to predict a failure and trigger dispatch of a battery pack based on the predicted failure”[0090], see [0039], [0067-0068], [0090-0091], Fig.1).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings ( battery management system 100, module 108, BLIS 110 and database 112) of Furr and configure with the system of John in order to the BLIS service able to predict the failure of a battery through the digital twin simulation, identify a compatible module in inventory, dispatch it to the local service station. Motivation to combine the two teachings is, to predict battery failure (i.e., an added safety feature to enhance safety of the battery, and avoiding catastrophic failures).
However, John in view of Furr does not explicitly teach, simulate, via the digital twin, a degradation of the at least one battery pack module based on the operating data for the at least one battery module; and predict a future performance of the at least one battery pack module based on the simulated degradation of the at least one battery pack module.
In a related field of Art , Ryu discloses, a simulation system and data distribution method , wherein, simulate, via the digital twin, a degradation of the at least one battery pack module based on the operating data for the at least one battery module; and predict a future performance of the at least one battery pack module based on the simulated degradation of the at least one battery pack module (( via simulation system using a software simulation method predicting degree of degradation of battery, See Page 2, pare 3-5; Page 5 last para -Page 6 last para , Fig. 1).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr and Ryu before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings (software simulation system composed of MBD( model based design), and IoT device) of Ryu and configure with the system of John in order to execute a simulation for predicting the deterioration of the lifespan of a battery pack for an electric vehicle.
Motivation to combine the two teachings is, to predict battery degradation (i.e., an added safety feature to determine the battery warranty period ).
As per Claim 2, John as modified by Furr and Ryu teaches the limitation of Claim 1. However, John in view of Furr and Ryu teaches, the system further comprising updating the digital twin based on a difference between an actual performance of the at least one battery pack module and the predicted future performance. ( Furr : see [0068-0069], [0090-0091], Fig.1).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings ( battery management system 100, module 108, BLIS 110 and database 112) of Furr and configure with the system of John in order to predict the failure of a battery through the digital twin simulation. Motivation to combine the two teachings is, to predict battery failure (i.e., an added safety feature to enhance safety of the battery, and avoiding catastrophic failures).
As per Claim 3, John as modified by Furr and Ryu teaches the limitation of Claim 1. However, John in view of Furr and Ryu teaches, wherein updating the digital twin is further based on a difference between an actual voltage of the at least one battery pack module and a predetermined voltage threshold. (Furr :[0039]).
(See rationale supporting obviousness and motivation to combine, of claim 2 above).
As per Claim 4, John as modified by Furr and Ryu teaches the limitation of Claim 1. However, John in view of Furr and Ryu teaches, wherein the monitor unit includes a plurality of sensors each configured to monitor a respective one of a plurality of battery modules in the battery pack of the electric aircraft, ( Furr : via “The WBMS nodes comprise a battery and a sensor. In some embodiments, the sensor is integrated with the battery. In some embodiments, the sensor is attached to the battery, for example taking the form of a dongle”, [0024], [0033],[0035] Fig.2-4)
…“The dongle 307 may include a sensor configured to sense a condition of the battery pack 305. For example, the dongle may include a sensor configured to sense voltage, current, state of charge, temperature chemical composition, or any other condition of the battery pack for which it is desired to collect data”, [0033])…
“BLIS 110 may maintain digital twins of the monitored batteries, may serve as a marketplace for batteries”, [0068], [0033],[0035] Fig.2-4) and wherein the computing device is configured to generate the digital twin based on a difference between a voltage measured in each of the plurality of sensors and at least one voltage threshold ( Furr: via “The dongle 307 may include a sensor configured to sense a condition of the battery pack 305. For example, the dongle may include a sensor configured to sense voltage, current, state of charge, temperature chemical composition, or any other condition of the battery pack for which it is desired to collect data”,[0037]), [0068] [0069]). (See rationale supporting obviousness and motivation to combine, of claim 2 above).
As per Claim 5, John as modified by Furr and Ryu teaches the limitation of Claim 4. However, John in view of Furr and Ryu teaches, wherein the computing device is further configured to classify the at least one battery module ( Furr : via “machine learning (ML) techniques are used to classify batteries into different groups”, [0056]). based on an amount of the difference between the voltage measured in each of the plurality of sensors and the at least one voltage threshold. (Furr : via [0068] [0069]). (See rationale supporting obviousness and motivation to combine, of claim 2 above).
As per Claim 7, John as modified by Furr and Ryu teaches the limitation of Claim 1. However, John in view of Furr and Ryu teaches, wherein the computing device is further configured to generate a plurality of digital twins each corresponding to a respective one of a plurality of battery modules in the battery pack of the electric aircraft (Furr : [0005][0006]). (See rationale supporting obviousness and motivation to combine, of claim 2 above).
As per Claim 8, John as modified by Furr and Ryu teaches the limitation of Claim 7. However, John in view of Furr and Ryu teaches, wherein the computing device is in communication with a battery management system (BMS) configured to record each of the plurality of digital twins. ( Furr : via a battery management system 100 comprising a data aggregation and management module 108 that implements a BLIS service 110 and maintains a battery database ( [0039], Fig.1),.. using the data gathered by the BLIS service as inputs to generate a digital twin for a given battery cell, module, or pack. , [0067]-0068]). .. “the BLIS service may use a digital twin to predict a failure and trigger dispatch of a battery pack based on the predicted failure”[0090], see [0039], [0067-0068], [0090-0091], Fig.1). (See rationale supporting obviousness and motivation to combine, of claim 2 above).
As per Claim 9, John as modified by Furr and Ryu teaches the limitation of Claim 1. However, John in view of Furr and Ryu teaches, wherein the computing device is further configured to generate the digital twin with a machine learning model and a degradation training set from a previous set of battery pack data correlated to another digital twin. (Furr : [0055-0057]). (See rationale supporting obviousness and motivation to combine, of claim 2 above).
As per Claim 10, John as modified by Furr and Ryu teaches the limitation of Claim 1. However, John in view of Furr and Ryu teaches, wherein the computing device is further configured to predict a heat generation of the battery pack based on the simulated degradation of the at least one battery pack module. ( Furr : via “temperature may be datestamped” [0039], [0068]). (See rationale supporting obviousness and motivation to combine, of claim 2 above).
As Per Claim 11, John et al. ( John) teaches, a method for controlling battery consumption in an electric aircraft, ( via controller 101 of aircraft 100 determining the battery consumption, and the remaining battery level, Page 20, para 6, processor 101, Page 12 4th para – Page 13, 1st para, Fig.3)).
However, John does not explicitly teach, generating a digital twin of at least one battery pack module in a battery pack of the electric aircraft via a computing device;
simulating, via the digital twin, a degradation of the at least one battery pack module based on operating data for the at least one battery module; and predicting a future performance of the at least one battery pack module based on the simulated degradation of the at least one battery pack module.
In a related field of Art, Furr et al. ( Furr) teaches, battery monitoring system wherein, generating a digital twin of at least one battery pack module in a battery pack of the electric aircraft via a computing device;( via a battery management system 100 comprising a data aggregation and management module 108 that implements a BLIS service 110 and maintains a battery database ( [0039], Fig.1),.. using the data gathered by the BLIS service as inputs to generate a digital twin for a given battery cell, module, or pack. , [0067]-0068]). .. “the BLIS service may use a digital twin to predict a failure and trigger dispatch of a battery pack based on the predicted failure”[0090], see [0039], [0067-0068], [0090-0091], Fig.1).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings ( battery management system 100, module 108, BLIS 110 and database 112) of Furr and configure with the system of John in order to the BLIS service able to predict the failure of a battery through the digital twin simulation, identify a compatible module in inventory, dispatch it to the local service station. Motivation to combine the two teachings is, to predict battery failure (i.e., an added safety feature to enhance safety of the battery, and avoiding catastrophic failures).
However, John in view of Furr does not explicitly teach, simulating, via the digital twin, a degradation of the at least one battery pack module based on operating data for the at least one battery module; and predicting a future performance of the at least one battery pack module based on the simulated degradation of the at least one battery pack module.
In a related field of Art , Ryu discloses, a simulation system and data distribution method , wherein, simulating, via the digital twin, a degradation of the at least one battery pack module based on operating data for the at least one battery module; and
predicting a future performance of the at least one battery pack module based on the simulated degradation of the at least one battery pack module ( via simulation system using a software simulation method predicting degree of degradation of battery, See Page 2, pare 3-5; Page 5 last para -Page 6 last para , Fig. 1).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr and Ryu before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings (software simulation system composed of MBD( model based design), and IoT device) of Ryu and configure with the system of John in order to execute a simulation for predicting the deterioration of the lifespan of a battery pack for an electric vehicle. Motivation to combine the two teachings is, to predict battery degradation (i.e., an added safety feature to determine the battery warranty period ).
As per Claim 12, John as modified by Furr and Ryu teaches the limitation of Claim 11. However, John in view of Furr and Ryu teaches, updating the digital twin based on a difference between an actual performance of the at least one battery pack module and the predicted future performance. ( Furr : see [0068-0069], [0090-0091], Fig.1).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings ( battery management system 100, module 108, BLIS 110 and database 112) of Furr and configure with the system of John in order to predict the failure of a battery through the digital twin simulation. Motivation to combine the two teachings is, to predict battery failure (i.e., an added safety feature to enhance safety of the battery, and avoiding catastrophic failures).
As per Claim 13, John as modified by Furr and Ryu teaches the limitation of Claim 11. However, John in view of Furr and Ryu teaches, wherein updating the digital twin is further based on a difference between an actual voltage of the at least one battery pack module and a predetermined voltage threshold. (Furr :[0039]). (See rationale supporting obviousness and motivation to combine, of claim 12 above).
As per Claim 14, John as modified by Furr and Ryu teaches the limitation of Claim 11. However, John in view of Furr and Ryu teaches, monitoring a voltage of each of a plurality of the battery modules in the battery pack of the electric aircraft, ( Furr : via “The WBMS nodes comprise a battery and a sensor. In some embodiments, the sensor is integrated with the battery. In some embodiments, the sensor is attached to the battery, for example taking the form of a dongle”, [0024],
…“The dongle 307 may include a sensor configured to sense a condition of the battery pack 305. For example, the dongle may include a sensor configured to sense voltage, current, state of charge, temperature chemical composition, or any other condition of the battery pack for which it is desired to collect data”, [0033])…“BLIS 110 may maintain digital twins of the monitored batteries, may serve as a marketplace for batteries”, [0068], [0033],[0035] Fig.2-4), and wherein the computing device is configured to generate the digital twin based on a difference between each monitored voltage and at least one voltage threshold ( Furr: via “The dongle 307 may include a sensor configured to sense a condition of the battery pack 305. For example, the dongle may include a sensor configured to sense voltage, current, state of charge, temperature chemical composition, or any other condition of the battery pack for which it is desired to collect data”,[0037]), [0068] [0069]). (See rationale supporting obviousness and motivation to combine, of claim 12 above).
As per Claim 15, John as modified by Furr and Ryu teaches the limitation of Claim 14. However, John in view of Furr and Ryu teaches, wherein the computing device is further configured to classify each of the plurality of battery modules ( Furr : via “machine learning (ML) techniques are used to classify batteries into different groups”, [0056]) based on the difference between each monitored voltage and the at least one voltage threshold (Furr : via [0068] [0069]). (See rationale supporting obviousness and motivation to combine, of claim 12 above).
As per Claim 17, John as modified by Furr and Ryu teaches the limitation of Claim 11. However, John in view of Furr and Ryu teaches, wherein generating the digital twin includes generating, via the computing device, a plurality of digital twins each corresponding to a respective one of a plurality of battery modules in the battery pack of the electric aircraft (Furr : [0005][0006]). (See rationale supporting obviousness and motivation to combine, of claim 12 above).
As per Claim 18, John as modified by Furr and Ryu teaches the limitation of Claim 11. However, John in view of Furr and Ryu teaches, wherein the digital twin is generated via a machine learning model and a degradation training set from a previous set of battery pack data correlated to another digital twin (Furr : “The analysis may be done using machine learning algorithms executed by the BLIS service 110”, [0057], [0055-0057]). (See rationale supporting obviousness and motivation to combine, of claim 12 above).
As per Claim 19, John as modified by Furr and Ryu teaches the limitation of Claim 18. However, John in view of Furr and Ryu teaches, wherein the degradation training set includes a battery degradation estimation for the previous set of battery pack data. (Ryu : page 3, last 2 paragraphs).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr and Ryu before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings (software simulation system composed of MBD( model based design), and IoT device) of Ryu and configure with the system of John in order to execute a simulation for predicting the deterioration of the lifespan of a battery pack for an electric vehicle. Motivation to combine the two teachings is, to predict battery degradation (i.e., an added safety feature to determine the battery warranty period).
As per Claim 20, John as modified by Furr and Ryu teaches the limitation of Claim 11. However, John in view of Furr and Ryu teaches, predicting a heat generation of the battery pack based on the simulated degradation of the at least one battery pack module ( Furr : via “temperature may be datestamped” [0039], [0068]). (See rationale supporting obviousness and motivation to combine, of claim 12 above).
5. Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over John et al. ( WO-2021-005942) in view of Furr et al. ( WO-2020-260623) in view of Ryu
(WO-2021-141255) in view of Nagasubramanian ( USP 5,989,748).
As per Claim 6, John as modified by Furr and Ryu teaches the limitation of Claim 1. However, John in view of Furr and Ryu does not explicitly teach, wherein the operating data includes electrochemical data.
In a related field of art Nagasubramanian teaches, lithium/lithium batteries, wherein the operating data includes electrochemical data ( via lithium/lithium ion batteries with cyanoethylated additives (Col. 1, lines 10-15) … operating data including “electrochemical and thermodynamic data now indicate that lithium/lithium ion batteries may well be used as power sources in electric vehicles”, [col.6, lines 45-47]).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr and Ryu and Nagasubramanian before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings (lithium/lithium ion batteries ) of Nagasubramanian configure with the system of John in order to monitor the battery operating condition by using electrochemical data to predict battery degradation. Motivation to combine the two teachings is, to miniature batteries (i.e., light power source aircraft).
As per Claim 16, John as modified by Furr and Ryu teaches the limitation of Claim 11. However, John in view of Furr and Ryu does not explicitly teach, wherein the operating data includes electrochemical data.
In a related field of art Nagasubramanian teaches, lithium/lithium batteries, wherein the operating data includes electrochemical data ( via lithium/lithium ion batteries with cyanoethylated additives (Col. 1, lines 10-15) … operating data including “electrochemical and thermodynamic data now indicate that lithium/lithium ion batteries may well be used as power sources in electric vehicles”, [col.6, lines 45-47]).
It would have been obvious to one of ordinary skill in the art, having the teachings of John and Furr and Ryu and Nagasubramanian before him before the effective filing date of the claimed invention to modify the systems of John to include the teachings (lithium/lithium ion batteries ) of Nagasubramanian configure with the system of John in order to monitor the battery operating condition by using electrochemical data to predict battery degradation. Motivation to combine the two teachings is, to miniature batteries (i.e., light power source aircraft).
Conclusion
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/MUHAMMAD SHAFI/Primary Examiner, Art Unit 3666C