DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 09/24/2025 has been entered.
Response to Arguments
Applicant’s claim amendment of independent claim 31 overcome the 35 U.S.C. 112(b) rejection of claims 31-40 made previously.
Applicant’s claim amendment of claims independent of claims 31 and 41 overcome the 35 U.S.C. 103 rejection of claims 31-49 made previously.
Applicant's arguments filed on 09/24/2025 have been fully considered but they are not persuasive.
Applicant’s argument with regard to the 35 U.S.C. 103 rejection of claim 50 found in last paragraph on page 9 and paragraph 2 on page 10 which argues that an oscilloscope does not inherently has a display, and PC-based oscilloscopes does not include a display; and there is no teaching or suggestion in the applied references that a scan result would be received by controller 130 from processor 200 in Steingart ‘123.
It is respectfully disagreed.
Kaplan et al. (US 2013/0006570) teaches an oscilloscope having an associated display (e.g. figs. 1-2, [0012]).
In addition, claim 50 does not claim a display; therefore, teaching of a display is not required.
Therefore, a PC-based oscilloscope has an associated display, measurement data from the oscilloscope are being displayed on associated display of a PC that connected to the PC-based oscilloscope, and adding a display is obviously and logical thing to do because doing so allowing workers to view the scan result on the display remotely (e.g. motivated by fig. 1 and paragraph [0012] of Kaplan et al. (US 2013/0006570)).
As a result, the scan result is transmitted to the remote network service in order to allow the workers to view the scan result on the display remotely.
Applicant’s argument with regard to the 35 U.S.C. 103 rejection of claim 50 found in paragraph 3 on page 10 which argues that the rational advanced by the rejection amounts to impermissible hindsight because the relevant teaching are only found in Applicant’s disclosure rather than the cited references.
It is respectfully disagreed.
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
In this case, the motivation of having different workers may collaborate and share information to improving work efficiency does not come from Applicant’s disclosure, and enabling the scan result be view at different locations including local location and remote location is not found in Applicant’s disclosure, and enabling the scan result be view at remote location may be motivated by fig. 1 and paragraph [0012] of Kaplan et al. (US 2013/0006570).
Applicant’s argument with regard to the 35 U.S.C. 103 rejection of claim 40 found in first paragraphs on page 12 of applicant’s remarks which argues that nothing in the cited portions of Ladpli are seen to suggest that pressure should be applied to a battery during an ultrasonic scan as a small mechanical load exerted on the battery can result battery degradation or even short-circuiting; even a mechanical arm to apply pressure is well known, no evidence is provided to support that the mechanical arm to apply pressure, and such an arm would also support both the source and sensor used to perform the ultrasonic scan of the battery.
It is respectfully disagreed.
Ladpli also describe that “[0101] However, without an interlayer shear resistance of a battery core, thin battery layers can bend about their own individual neutral axis, and a structural contribution from the facesheets will be reduced. Therefore, MES Composites employ through-thickness polymer reinforcement pins, which extend through perforations in the electrode stack. The through-thickness reinforcement pins interlock the individual electrode layers, and mechanically link the two structural CFRP facesheets together (FIG. 13b). The interlocking pins allow load transfer between the two facesheets and inhibit the relative slipping between the adjacent electrode layers, allowing the entire laminate to be able to bend about a common neutral axis. This approach significantly increases the stiffness and strength of MES Composites over comparative Li-ion batteries” (e.g. fig. 13(b), [0101]).
Therefore, stiffness and strength the battery as taught by Lapli is significantly increase to handle higher pressure load caused by Load force as shown in fig. 13(b), so reducing risks of battery degradation or short-circuiting by external force.
Furthermore, Biswas et al. (US 2018/0123189) provide supports that a mechanical arm to apply pressure (e.g. figs. 4-5, [0051] and [0059], mechanical arms apply pressure to hole battery 402 as shown in fig. 4 that corresponds to battery 502(c) in fig. 5), and such an arm would also support both the source and sensor used to perform the ultrasonic scan of the battery (e.g. figs. 4-5, [0051] and [0059], mechanical arms apply pressure to hole battery 502c and also support transducer array head 408a-b for transmitting/receiving acoustic signals into/from battery 402 that corresponds to battery 502(c) in fig. 5).
Applicant’s argument with regard to the 35 U.S.C. 103 rejection of claim 43 found in last two paragraphs on page 12 of applicant’s remarks which argues that Ladpli fails suggest an open circuit voltage measurement.
It is respectfully disagreed.
As claimed in claim 43, last two lines claim 43 recites “the one or more opened circuit voltage and/or impedance measurement”, so either “the one or more opened circuit voltage” or “impedance measurement” is required to be taught.
Ladpli teaches a voltage sensor that is capable of obtaining at least one open circuit voltage measurement (e.g. fig. 14, cell voltage sensor capable of measuring an open circuit voltage of the battery supported by Biswas et al. (US 2018/0123189) provide support of measuring an open circuit voltage (e.g. Biswas, [0058])) and at least one impedance measurement of the battery during the ultrasonic scan (e.g. fig. 14, cell voltage & current sensor capable of measuring voltage and current of the battery during ultrasonic scan, and impedance measurement of the battery may be obtain based on the voltage and current measurements because impedance is calculated based on voltage divided by current).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, 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.
Claims 31-32, 34-39, 41-42 and 47-50 are rejected under 35 U.S.C. 103 as being unpatentable over Steingart et al. (US 2019/0064123), and further in view of Hsieh et al. (US 2018/0164383), Kaplan et al. (US 2013/0006570) and Matsumoto (JP 2014085328 A).
Regarding claims 31 and 41, Steingart teaches a battery testing apparatus (e.g. fig. 3, apparatus 100) comprising:
a control system (e.g. fig. 3, controller 130) configured to direct an ultrasonic scan of a battery (e.g. fig. 3, [0041], ultrasonic pulses from transducer 112 passes through battery 101);
a source configured to transmit one or more ultrasound signals into the battery for the ultrasonic scan (e.g. fig. 3, [0041], ultrasonic pulses from transduce 112 passes through battery 101, so transducer 112 is a source transducer); and
a sensor configured to detect one or more ultrasound signals reflected by or transmitted through the battery in response to the transmitted one or more ultrasound signals (e.g. fig. 3 and [0041], transducer 114 receives ultrasonic pulses passed through the battery 101, so transducer 114 is a sensor transducer); and
a remote network service comprising a processing system (e.g. figs. 3, [0041], processor means 200 has a processor, and processor means 200 may be at a remote location as described in paragraph [0047]),
wherein the control system is operatively coupled to the source and sensor and is configured to perform functions (e.g. fig. 3, controller 130 coupled to source transduce 112 and sensor transducer 114) comprising:
generating transmitted signal data for the transmitted one or more ultrasound signals (e.g. fig. 3, [0041], controller 130 sends control signal data to source transducer 112);
generating received signal data for the detected one or more ultrasound signals (e.g. fig. 3, [0041], controller 130 has a receiver means to receive signal data from sensor transducer 114); and
generating scan data for the ultrasonic scan based on the transmitted signal data and the received signal data (e.g. fig. 3, [0040]-[0041], filtered and/or converted data is generated based on the received signal data from sensor transducer 114); and
transmitting the generated scan data to the remote network service (e.g., fig. 3, [0040]-[0041], controller 130 transmits the filtered and/or converted data to processor means 200).
wherein the remote network service is configured to receive the scan data from the control system (e.g. fig. 3, [0040]-[0041], processor means 200 receives the filtered and/or converted data form controller 130) and to generate a scan result (e.g. [0041], determine state of charge (SOC), state of health (SOH), physical state and/or physical parameters of a tested battery) by:
computing a characteristic of the battery (e.g. e.g. [0041], determine state of charge (SOC), state of health (SOH), physical state and/or physical parameters of a tested battery).
wherein the remote network service is further configured to transmit data, to the control system (e.g. fig. 3, processor means 200 transmits data to controller means 130); and
wherein the control system is further configured to receive the transmission of the data from the remote network service (e.g. fig. 3, controller means 130 receives data from processor means 200).
In addition, Steingart also teaches receiving the scan result from the remote network service for display (e.g. [0048], a display unit or a printer receives the state of charge (SOC), state of health (SOH) and physical state information to present to a human operator from processor means 200).
However, Steingart is silent with regard to analyzing the scan data to quantify aspects of the transmitted signal data and the received signal data;
computing the characteristic of the scanned battery based at least in part on the quantified aspects; and
the transmission of the data being the scan result, including the computed characteristic of the battery.
Hsieh teaches analyzing scan data to quantify aspects of transmitted signal data and received signal data (e.g. figs. 1A-1B and 5A, [0060]-[0062], measured spectrum 112 is analyzed to determine shifts in resonance frequency f0 of input signal and response signal);
generate a scan result by computing a characteristic of a battery based at least in part on the quantified aspects (e.g. figs. 5A-5B, [0062], comparing different shits to reveal information about conditions of a battery); and
a control system has a display (e.g. fig. 1B, [0034], control unit 102 may comprise an oscilloscope and the oscilloscope has a display).
It would produce a predictive result of have adding a display to the control system of Steingart to display the scan result, including the computed characteristic of the battery, for the purpose of enabling the scan result be view at different locations including local location and remote location (e.g. motivated by fig. 1 and paragraph [0012] of Kaplan), so that different workers may collaborate and share information to improving work efficiency.
It would produce a predictable result of determining condition of the battery based on the transmitted signal data and the received signal data of Steignart by using the analyzing and computing steps taught by Hsieh, for the purpose of improving accuracy on determining conditions of the battery (e.g. [0007]) and detecting a broader scope of physical quality, defects and failure conditions in the battery (e.g. [0008]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Steignart by applying the teaching of Hsieh to explicitly include the steps of analyzing the scan data to quantify aspects of the transmitted signal data and the received signal data; and computing the characteristic of the scanned battery based at least in part on the quantified aspects; wherein the remote network system is further configured to transmit the scan result, including the computed characteristic of the battery, to the control system; and wherein the control system is further configured to receive the transmission of the scan result from the remote network service, for the purpose of improving accuracy on determining conditions of the battery (e.g. [0007]) and detecting a broader scope of physical quality, defects and failure conditions in the battery (e.g. [0008]) and/or enabling the scan result be view at different locations including local location and remote location, so that different workers may collaborate and share information to improving work efficiency.
However, combination of Steignart and Hsieh is silent with regard to a plurality of test platforms.
Matsumoto teaches a plurality of test platforms (e.g. figs. 5-6, test platforms 41 and 42), each test platform comprising:
a source configured to transmitted one or more ultrasound signals (e.g. figs. 5-6, paragraphs 18-19 of Description-of-Embodiments, “second ultrasonic sensors 41B and 42B are configured as sensors that transmit ultrasonic waves”), and
a sensor configured to detect one or more ultrasound signals transmitted through in response to the transmitted one or more ultrasound signal (e.g. figs. 5-6, paragraphs 18-19 of Description-of-Embodiments, “first ultrasonic sensors 41A and 42A of each of the actual measurement ultrasonic sensor groups 41 and 42 are configured as sensors that receive ultrasonic waves”).
The each test platform of the plurality of test platforms is capable of testing corresponding battery and corresponding scan data is capable of being transmitted and processed via the control system and the remote networked; therefore, it would produce a predictive result of having a plurality of test platforms to test corresponding a plurality of batteries, for the purpose of increasing test efficiency by testing multiple batteries in parallel by using corresponding test platforms.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Steignart, Hsieh, and Kaplan by applying the teaching of Matsumoto to have a plurality of test platforms to test corresponding a plurality of batteries, for the purpose of increasing test efficiency by testing multiple batteries in parallel by using corresponding test platforms.
Regarding claims 32 and 42, combination of Steignart, Hsieh, Kaplan, and Matsumoto teaches wherein the computed characteristic comprises is at least one of a state of charge (SOC) and a state of health (SOH) for the battery (e.g. Steignart, [0041] and [0048], determine state of charge (SOC), state of health (SOH), physical state and/or physical parameters of a tested battery).
Regarding claims 34 and 47, combination of Steignart, Hsieh, Kaplan, and Matsumoto teaches wherein, for at least one of the plurality of test platforms: the functions performed by the control system additionally include instructing the source to transmit the one or more ultrasound signals into the battery for the ultrasonic scan (e.g. fig. 3, controller 130 controls source transducer 112 transmits ultrasound pulses to battery 101) without the control system charging or discharging the battery during the ultrasonic scan (e.g. fig. 3, controller 130 does not charging or discharging the battery as shown in fig. 3), and
the sensor also detects the one or more ultrasound signals reflected by or transmitted through the battery (e.g. fig. 3, controller 130 controls sensor transducer 114 receives transmitted ultrasound pulses pass through battery 101) without the control system charging or discharging the battery during the ultrasonic scan (e.g. fig. 3, controller 130 does not charging or discharging the battery as shown in fig. 3).
Regarding claim 35, combination of Steignart, Hsieh, Kaplan, and Matsumoto teaches wherein the quantified aspects are changes in the received signal data as compared to the transmitted signal data in a time domain (e.g. Steignart, figs. 8-9, [0062], waveforms changed in time domain).
Regarding claim 36, combination of Steignart, Hsieh, Kaplan, and Matsumoto teaches wherein the quantified aspects are changes in the received signal data as compared to the transmitted signal data in a frequency domain (e.g. Steignart, fig. 5A, waveforms changed in frequency domain).
Regarding claim 37, combination of Steignart, Hsieh, Kaplan, and Matsumoto teaches wherein the quantified aspects include zero crossings and peak values and amplitudes of the transmitted signal data and the received signal data (e.g. Steignart, fig. 8 and [0062], zero crossings and peak values and amplitudes are parts of waveforms as show in fig. 8).
Regarding claims 38 and 48, combination of Steignart, Hsieh, Kaplan, and Matsumoto teaches wherein, for at least one of the plurality of test platforms, the source and the sensor are included in a same transducer placed against a side of the battery, and the source and the sensor are configured to operate in echo mode (e.g. Hsieh, fig. 8 and [0067], pulse-echo (reflection) mode where transduce need to have both a transmitter and receiver on a same transducer to work in the pulse-echo (reflection) mode).
Regarding claims 39 and 49, combination of Steignart, Hsieh, Kaplan, and Matsumoto teaches wherein, for at least one of the plurality of test platforms, the source and the sensor are placed on opposing sides of the battery and are configured to operate in through transmission mode (e.g. Hsieh, figs. 3 and 8A, [0067], transmission mode where transmitter of transducer 112 and receiver of transducer 114 are on opposing side).
Claims 33 and 45-46 are rejected under 35 U.S.C. 103 as being unpatentable over Steingart et al. (US 2019/0064123) in view of Hsieh et al. (US 2018/0164383), Kaplan et al. (US 2013/0006570) and Matsumoto (JP 2014085328 A), and further in view of Steingart et al. (US 2019/0072614).
Regarding claims 33 and 45-46, combination of Steingart_123, Hsieh, Kaplan, and Matsumoto is silent with regard to further comprising: one or more machine learning models that learn or predict mathematical relationships between known characteristics of other batteries and previously obtained quantified aspects of transmitted signal data and received signal data from scans of the other batteries,
wherein the remote network service computes the SOC and/or the SOH for the battery based at least in part on the quantified aspects by presenting the quantified aspects of the battery as input to the machine learning models to predict the SOC and/or the SOH.
However, Steingart_614 teaches one or more machine learning models that learn or predict mathematical relationships (e.g. fig. 4A and [0052], method 400 predicts SOC and SOH using machine learning techniques having training model 404 and predictive model 406) between known characteristics of other batteries and previously obtained quantified aspects of transmitted signal data and received signal data from scans of the other batteries (e.g. fig. 4A and [0053], each of battery a-n has known characteristics, acoustic dataset, reduced acoustic data set, etc. where acoustic dataset, reduced acoustic data set that may be obtained based on transmitted signal data and received signal data from scans),
wherein a computer computes the SOC and/or the SOH for the battery based at least in part on the quantified aspects by presenting the quantified aspects of the battery as input to the machine learning models to predict the SOC and/or the SOH (e.g. figs, 4A-4B, [0053]-[0054], generate predictions of SOC, SOH, etc. based on the inputs characteristics, acoustic dataset, reduced acoustic data set as inputs to the training model 404 and predictive model 406).
It would produce a predictable result by using the machine learning models as taught by Steingart_614 to provide the quantified aspects of the battery taught by combination of Steingart_123, Hsieh, and Matsumoto as input to the machine learning models to compute the SOC and/or the SOH, for the purpose of, using low-cost and high accuracy techniques which can directly measure the mechanical and physical states of the battery, to enhance determinations of SOC, SOH, and cell failure of the battery.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Steingart_123, Hsieh, Kaplan, and Matsumoto by applying the teaching of Steingart_614 to explicitly have further comprising: one or more machine learning models that learn or predict mathematical relationships between known characteristics of other batteries and previously obtained quantified aspects of transmitted signal data and received signal data from scans of the other batteries, wherein the remote network service computes the SOC and/or the SOH for the battery based at least in part on the quantified aspects by presenting the quantified aspects of the battery as input to the machine learning models to predict the SOC and/or the SOH, for the purpose of using low-cost and high accuracy techniques which can directly measure the mechanical and physical states of the battery, to enhance determinations of SOC, SOH, and cell failure of the battery.
Claims 40 and 43-44 are rejected under 35 U.S.C. 103 as being unpatentable over Steingart et al. (US 2019/0064123) in view of Hsieh et al. (US 2018/0164383), Kaplan et al. (US 2013/0006570), and Matsumoto (JP 2014085328 A), and further in view of Ladpli et al. (US 2019/0207274) and Biswas et al. (US 2018/0123189).
Regarding claims 40 and 43-44, combination of Steingart, Hsieh, Kaplan and Matsumoto is silent with regard to further comprising: an arm that supports at least one of the source and the sensor thereon and is configured to apply a pressure to the battery during the ultrasonic scan; a temperature sensor that obtains at least one temperature measurement of the battery during the ultrasonic scan; and a voltage sensor that obtains at least one open circuit voltage measurement and at least one impedance measurement of the battery during the ultrasonic scan;
wherein the remote network service analyzes the scan data in conjunction with the pressure applied to the battery, the temperature measurement, the open circuit voltage measurement, and the impedance measurement, to quantify aspects of the transmitted signal data and the received signal data.
However, Ladpli teaches a mechanical load applies a pressure to a battery (e.g. fig. 13, and [0099], it is obvious that a mechanical arm may be used to as mechanical load that supports at least one of the source and the sensor thereon and is configured to apply the pressure because it is more efficient and more accurate to apply a desire pressure by the mechanical arm controlled by a controller where Biswas et al. (US 2018/0123189) provide supports that a mechanical arm to apply pressure (e.g. Biswas, figs. 4-5, [0051] and [0059], mechanical arms apply pressure to hole battery 402 as shown in fig. 4 that corresponds to battery 502(c) in fig. 5), and such an arm would also support both the source and sensor used to perform the ultrasonic scan of the battery (e.g. Biswas, figs. 4-5, [0051] and [0059], mechanical arms apply pressure to hole battery 502c and also support transducer array head 408a-b for transmitting/receiving acoustic signals into/from battery 402 that corresponds to battery 502(c) in fig. 5)),
a strain and deformation sensor capable of detecting the pressure (e.g. fig. 14, strain and deformation sensor);
a temperature sensor that obtains at least one temperature measurement of the battery during an ultrasonic scan (e.g. fig. 14-15, temperature distribution sensor capable of measuring battery temperature during an ultrasonic scan); and
a voltage sensor that is capable of obtaining at least one open circuit voltage measurement (e.g. fig. 14, cell voltage sensor capable of measuring an open circuit voltage of the battery supported by Biswas et al. (US 2018/0123189) provide support of measuring an open circuit voltage (e.g. Biswas, [0058])) and at least one impedance measurement of the battery during the ultrasonic scan (e.g. fig. 14, cell voltage & current sensor capable of measuring voltage and current of the battery during ultrasonic scan, and impedance measurement of the battery may be obtain based on the voltage and current measurements because impedance is calculated based on voltage divided by current);
a device analyzes scan data in conjunction with the pressure applied to the battery, the temperature measurement, the open circuit voltage measurement, and the impedance measurement, to quantify aspects of the transmitted signal data and the received signal data (e.g. fig. 14, battery charge state and health are determined by Battery & Structural Health Monitoring using diagnostics & Damage detection model and physics-assisted data-driven battery SoC & SoC estimation model having inputs from ultrasonic signals sensor, strains & deformation sensor, temperature distribution sensor and cell voltage & current sensor).
It would produce a predicable result of determining the characteristic of the battery of Steingart, Hsieh, Kaplan, and Matsumoto by using the pressure applied to the battery, the temperature measurement, the open circuit voltage measurement, and the impedance measurement form their corresponding sensors and processing those measurements as taught by Ladpli and Biswas, for the purpose of achieving a cost effective way to determine the characteristics of the battery without needed to using laboratory equipment and electrochemical tool on-board that would also reduce complexity (e.g. Ladpli, [0048]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Steingart, Hsieh, Kaplan and Matsumoto by applying the teaching of Ladpli and Biswas to have further comprising: an arm that supports at least one of the source and the sensor thereon and is configured to apply a pressure to the battery during the ultrasonic scan; a temperature sensor that obtains at least one temperature measurement of the battery during the ultrasonic scan; and a voltage sensor that obtains at least one open circuit voltage measurement and at least one impedance measurement of the battery during the ultrasonic scan; wherein the remote network service analyzes the scan data in conjunction with the pressure applied to the battery, the temperature measurement, the open circuit voltage measurement, and the impedance measurement, to quantify aspects of the transmitted signal data and the received signal data, for the purpose of achieving a cost effective way to determine the characteristics of the battery without needed to using laboratory equipment and electrochemical tool on-board that would also reduce complexity (e.g. Ladpli, [0048]).
Claim 50 is rejected under 35 U.S.C. 103 as being unpatentable over Steingart et al. (US 2019/0064123), and further in view of Hsieh et al. (US 2018/0164383) and Kaplan et al. (US 2013/0006570).
Regarding claim 50, Steingart teaches a battery testing apparatus (e.g. fig. 3, apparatus 100) comprising:
a control system (e.g. fig. 3, controller 130) configured to direct an ultrasonic scan of a battery (e.g. fig. 3, [0041], ultrasonic pulses from transducer 112 passes through battery 101);
a source configured to transmit one or more ultrasound signals into the battery for the ultrasonic scan (e.g. fig. 3, [0041], ultrasonic pulses from transduce 112 passes through battery 101, so transducer 112 is a source transducer); and
a sensor configured to detect one or more ultrasound signals reflected by or transmitted through the battery in response to the transmitted one or more ultrasound signals (e.g. fig. 3 and [0041], transducer 114 receives ultrasonic pulses passed through the battery 101, so transducer 114 is a sensor transducer); and
wherein the control system is operatively coupled to the source and sensor and perform functions (e.g. fig. 3, controller 130 coupled to source transduce 112 and sensor transducer 114) comprising:
(a) generating transmitted signal data for the transmitted one or more ultrasound signals (e.g. fig. 3, [0041], controller 130 sends control signal data to source transducer 112);
(b) generating received signal data for the detected one or more ultrasound signals (e.g. fig. 3, [0041], controller 130 has a receiver means to receive signal data from sensor transducer 114); and
(c) generating scan data for the ultrasonic scan based on the transmitted signal data and the received signal data (e.g. fig. 3, [0040]-[0041], filtered and/or converted data is generated based on the received signal data from sensor transducer 114); and
(d) transmitting the generated scan data to a remote network service (e.g., fig. 3, [0040]-[0041], controller 130 transmits the filtered and/or converted data to processor means 200), the remote network service comprising a processing system (e.g. figs. 3, [0041], processor means 200 has a processor, and processor means 200 may be at a remote location as described in paragraph [0047]) and being configured to generate a scan result by:
wherein the remote network service is configured to receive the scan data from the control system (e.g. fig. 3, [0040]-[0041], processor means 200 receives the filtered and/or converted data form controller 130) and to generate a scan result (e.g. [0041], determine state of charge (SOC), state of health (SOH), physical state and/or physical parameters of a tested battery) by:
computing a characteristic of the battery (e.g. [0041], determine state of charge (SOC), state of health (SOH), physical state and/or physical parameters of a tested battery); and
(c) receiving the scan result from the remote network service (e.g. [0048], a display unit or a printer receives the state of charge (SOC), state of health (SOH) and physical state information to present to a human operator from processor means 200).
However, Steingart is silent with regard to analyzing the scan data to quantify aspects of the transmitted signal data and the received signal data, and
computing the characteristic of the battery based at least in part on the quantified aspects.
Hsieh teaches analyzing scan data to quantify aspects of transmitted signal data and received signal data (e.g. figs. 1A-1B and 5A, [0060]-[0062], measured spectrum 112 is analyzed to determine shifts in resonance frequency f0 of input signal and response signal);
generate a scan result by computing a characteristic of a battery based at least in part on the quantified aspects (e.g. figs. 5A-5B, [0062], comparing different shits to reveal information about conditions of a battery); and
a control system has a display (e.g. fig. 1B, [0034], control unit 102 may comprise an oscilloscope and the oscilloscope has a display).
It would produce a predictive result of have adding a display to the control system of Steingart to display the scan result, including the computed characteristic of the battery, for the purpose of enabling the scan result be view at different locations including local location and remote location (e.g. motivated by fig. 1 and paragraph [0012] of Kaplan), so that different workers may collaborate and share information to improving work efficiency.
It would produce a predictable result of determining condition of the battery based on the transmitted signal data and the received signal data of Steignart by using the analyzing and computing steps taught by Hsieh and Kaplan, for the purpose of improving accuracy on determining conditions of the battery (e.g. [0007]) and detecting a broader scope of physical quality, defects and failure conditions in the battery (e.g. [0008]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAIDONG ZHANG whose telephone number is (571)270-5815. The examiner can normally be reached M-F 8:00 AM - 5:00 PM.
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/HAIDONG ZHANG/Examiner, Art Unit 2858
/HUY Q PHAN/Supervisory Patent Examiner, Art Unit 2858