Abstract: Systems and methods for analyzing physical characteristics of a battery include arrangements of two or more transducers coupled to the battery. A control module controls one or more of the two or more transducers to transmit acoustic signals through at least a portion of the battery, and one or more of the two or more transducers to receive response acoustic signals. Distribution of physical properties of the battery is determined based at least on the transmitted acoustic signals and the response acoustic signals.

Abstract: Systems, techniques, and computer-implemented processes for calibration of transducers used for acoustic signal-based analysis are disclosed. In one aspect, a calibration method includes capturing a plurality of signals for a plurality of channels, each of the plurality of channels being associated with a pair of transducers formed of a transmitting transducer and a receiving transducer; and for each of the plurality of channels, determining a corresponding peak intensity for a corresponding signal of the plurality of signals; normalizing the corresponding signal based at least on the corresponding peak intensity to yield a corresponding normalized signal; and applying a time-shift to the normalized signal.

Abstract: Systems and methods for acoustic signal based analysis, include obtaining acoustic response signal data of at least a portion of a battery cell, the acoustic response signal data comprising waveforms generated by transmitting one or more acoustic excitation signals into at least the portion of the battery cell and recording response vibration signals to the one or more acoustic excitation signals. One or more metrics are determined from at least the acoustic response signal data, the one or more metrics being determined based on correlation of the one or more metrics to one or more characteristics of battery cells and a reference model is generated from the one or more metrics. A test battery can be evaluated using the reference model. Actionable insights or recommendations can be generated based on the evaluation. The reference model can also be updated based on the evaluation.

Abstract: One or more aspects of the present disclosure are directed to fixturing mechanisms for placement of battery cells inside an ultrasonic testing system. The disclosed fixturing mechanisms enable accurate and predictable loading, placement, and unloading of battery cells inside ultrasonic testing systems allowing all faces of battery cells of different types (e.g., pouch cells, prismatic cells, cylindrical cells, etc.) to have sufficient exposure to transmission and reception of acoustic signals. This fixturing mechanism furthers the goal of providing a robustly designed ultrasonic test system and producing accurate inspection results for batteries.

Abstract: Aspects of the present disclosure are directed to a suite of testing apparatuses and non-destructive, acoustic inspection methods for scanning and inspecting batteries to determine and characterize various physical phenomena in these batteries. In one aspect, a rastering system for non-invasive and acoustic inspection of battery cells includes a holder for placing a battery cell inside the system for the acoustic inspection, at least one transducer configured to perform acoustic measurements on the battery cell, and a controller configured with inspection parameters for performing the acoustic measurements, the inspection parameters being dynamic and interchangeable depending on at least one or more of a shape, a size, and a form factor of the battery cell.

Abstract: The present disclosure are directed to techniques for defect detection and identification inside batteries. In one aspect, a non-invasive method of identifying and labeling defects in a battery cell includes transmitting acoustic signals through a battery cell via one or more first transducers, receiving response signals in response to the acoustic signals at one or more second transducers, determining whether at least one feature of interest exists in the battery cell based on analyzing the response signals, performing an identification and labeling process on the at least one feature of interest to determine at least one defect in the battery cell, and outputting a result of the identification and labeling process.

Abstract: Systems and techniques for measuring process characteristics including electrolyte distribution in a battery cell. A non-destructive method for analyzing a battery cell includes determining acoustic features at two or more locations of the battery cell, the acoustic features based on one or more of acoustic signals travelling through at least one or more portions of the battery cell during one or more points in time or responses to the acoustic signals obtained during one or more points in time, wherein the one or more points in time correspond to one or more stages of electrolyte distribution in the battery cell. One or more characteristics of the battery cell are determined based on the acoustic features at the two or more locations of the battery cell.

Abstract: Systems and techniques for measuring process characteristics including electrolyte distribution in a battery cell. A non-destructive method for analyzing a battery cell includes determining acoustic features at two or more locations of the battery cell, the acoustic features based on one or more of acoustic signals travelling through at least one or more portions of the battery cell during one or more points in time or responses to the acoustic signals obtained during one or more points in time, wherein the one or more points in time correspond to one or more stages of electrolyte distribution in the battery cell. One or more characteristics of the battery cell are determined based on the acoustic features at the two or more locations of the battery cell.

Abstract: Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.

Abstract: Systems, techniques, and computer-implemented processes for acoustic signal based improvements to one or more process steps in the manufacture of battery cells. Information gathered based on an acoustic signal based analysis in one process step can be used in one or more other process steps using any suitable combination of feedback and/or feedforward of the acoustic signal based analysis. Such feedback and/or feedforward can improve the overall quality of battery cells produced using the manufacturing process, efficiency/cost of the manufacturing process, improvement in yield/reduction in wastage of the battery cells produced using the manufacturing process and/or improvements in individual process steps.

Abstract: Systems and methods for testing a component, such as a battery, of a host device include transmitting one or more input acoustic signals into at least a portion of the host device, through input transducers coupled to the host device. One or more response signals generated in response to the one or more input acoustic signals are detected through recording transducers coupled to the host device. The one or more response signals are stored and compared with reference signals or datasets. One or more physical characteristics of the component or battery are analyzed based on the comparison.

Abstract: Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.

Abstract: Systems, methods, and computer-readable media are provided for controlling a battery manufacturing process. For instance, signal based analysis that can include audio signal analysis can be performed during a first process step of a battery manufacturing process. Based on the signal based analysis, at least one adjustment can be determined for a second process step of the battery manufacturing process. Information associated with the at least one adjustment can be provided to the second process step.

Abstract: Systems, techniques, and computer-implemented processes are provided for acoustic signal based analysis of thin-films, electrode coatings, and other components of batteries. Data analytics on signals obtained by ultrasound excitation of materials is used to analyze electrode coating parameters, analyzing separators, and other battery components. Using the disclosed techniques in battery manufacturing and production can lead to reduction in wastage of damaged/scrapped battery cells and shorten production time.

Abstract: Systems and methods for battery testing including a holder system. The holder system is designed to couple one or more transducers to a battery under test, wherein the one or more transducers are configured for electrochemical-acoustic signal interrogation (EASI) of the battery. The holder system includes at least one arm to house at least one transducer to be coupled to the battery, and a pressure applying device to apply pressure to the at least one transducer, and to control pressure between the at least one transducer and the battery. The holder system is also configured to determine the pressure between the at least one transducer and the battery and adjust the pressure applied to the at least one transducer based on the determined pressure.

Abstract: Systems and methods for acoustic signal based analysis, include obtaining acoustic response signal data of at least a portion of a battery cell, the acoustic response signal data comprising waveforms generated by transmitting one or more acoustic excitation signals into at least the portion of the battery cell and recording response vibration signals to the one or more acoustic excitation signals. One or more metrics are determined from at least the acoustic response signal data, the one or more metrics being determined based on correlation of the one or more metrics to one or more characteristics of battery cells and a reference model is generated from the one or more metrics. A test battery can be evaluated using the reference model. Actionable insights or recommendations can be generated based on the evaluation. The reference model can also be updated based on the evaluation.

Abstract: Systems and methods for measuring temperature characteristics of a battery include one or more transducers coupled to the battery for transmitting and/or receiving sound waves through at least a portion of the battery. A temperature measurement unit is provided to determine a time-of-flight of sound waves through at least the portion of the battery based on transmitted and received sound waves through at least the portion of the battery, and to determine temperature characteristics of at least the portion of the battery based on the time-of-flight.

Abstract: Systems and methods for analyzing physical characteristics of a battery include arrangements of two or more transducers coupled to the battery. A control module controls one or more of the two or more transducers to transmit acoustic signals through at least a portion of the battery, and one or more of the two or more transducers to receive response acoustic signals. Distribution of physical properties of the battery is determined based at least on the transmitted acoustic signals and the response acoustic signals.

Abstract: Systems and techniques for measuring process characteristics including electrolyte distribution in a battery cell. A non-destructive method for analyzing a battery cell includes determining acoustic features at two or more locations of the battery cell, the acoustic features based on one or more of acoustic signals travelling through at least one or more portions of the battery cell during one or more points in time or responses to the acoustic signals obtained during one or more points in time, wherein the one or more points in time correspond to one or more stages of electrolyte distribution in the battery cell. One or more characteristics of the battery cell are determined based on the acoustic features at the two or more locations of the battery cell.

Abstract: Systems and methods of determining physical conditions of a battery, such as state of charge (SOC), state of health (SOH), quality of construction, defect, or failure state include driving two or more acoustic signals of two or more amplitudes, each acoustic signal having two or more frequencies, into the battery and detecting vibrations generated in the battery based on the two or more acoustic signals. Nonlinear response characteristics of the battery for the two or more acoustic signals are determined from the detected vibrations. The physical conditions of the battery are determined based at least in part on the nonlinear response characteristics, using nonlinear acoustic resonance spectroscopy (NARS) or nonlinear resonant ultrasound spectroscopy (NRUS).