Abstract: Energy storage cell impedance testing devices, circuits, and related methods are disclosed. An energy storage cell impedance measuring device includes a sum of sinusoids (SOS) current excitation circuit including differential current sources configured to isolate a ground terminal of the differential current sources from a positive terminal and a negative terminal of an energy storage cell. A method includes applying an SOS signal comprising a sum of sinusoidal current signals to the energy storage cell with the SOS current excitation circuit, each of the sinusoidal current signals oscillating at a different one of a plurality of different frequencies. The method also includes measuring an electrical signal at a positive terminal and a negative terminal of the energy storage cell, and computing an impedance of the energy storage cell at each of the plurality of different frequencies using the measured electrical signal.

Abstract: Battery impedance testing devices, circuits, systems, and related methods are disclosed. An impedance measurement device includes a current driver configured to generate an excitation current signal to be applied to a test battery responsive to a control signal, and a processor operably coupled with the current driver. The processor is configured to generate the control signal during an auto-ranging mode and a measuring mode. The auto-ranging mode applies the excitation current signal to the test battery over a plurality of different amplitudes to measure a response to the excitation current signal at each amplitude. The measuring mode applies the excitation current signal to the test battery for an amplitude responsive to the results of the auto-ranging mode. Improved sensitivity and resolution may be achieved for low impedance batteries with a rapid measurement time.

Abstract: Energy storage cell impedance testing devices, circuits, and related methods are disclosed. An energy storage cell impedance measuring device includes a sum of sinusoids (SOS) current excitation circuit including differential current sources configured to isolate a ground terminal of the differential current sources from a positive terminal and a negative terminal of an energy storage cell. A method includes applying an SOS signal comprising a sum of sinusoidal current signals to the energy storage cell with the SOS current excitation circuit, each of the sinusoidal current signals oscillating at a different one of a plurality of different frequencies. The method also includes measuring an electrical signal at a positive terminal and a negative terminal of the energy storage cell, and computing an impedance of the energy storage cell at each of the plurality of different frequencies using the measured electrical signal.

Abstract: Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. A time profile of this sampled signal has a duration that is a few periods of the lowest frequency. A voltage response of the battery, average deleted, is an impedance of the battery in a time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time profile by rectifying relative to sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

Abstract: Real-time battery impedance spectra are acquired by stimulating a battery or battery system with a signal generated as a sum of sine signals at related frequencies. An impedance measurement device can be used to interface between the battery system and a host computer for generating the signals. The impedance measurement device may be calibrated to adapt the response signal to more closely match other impedance measurement techniques. The impedance measurement device may be adapted to operate at mid-range voltages of about 50 volts and high-range voltages up to about 300 volts.

Abstract: Electrochemical Impedance Spectrum data are used to predict pulse performance of an energy storage device. The impedance spectrum may be obtained in-situ. A simulation waveform includes a pulse wave with a period greater than or equal to the lowest frequency used in the impedance measurement. Fourier series coefficients of the pulse train can be obtained. The number of harmonic constituents in the Fourier series are selected so as to appropriately resolve the response, but the maximum frequency should be less than or equal to the highest frequency used in the impedance measurement. Using a current pulse as an example, the Fourier coefficients of the pulse are multiplied by the impedance spectrum at corresponding frequencies to obtain Fourier coefficients of the voltage response to the desired pulse. The Fourier coefficients of the response are then summed and reassembled to obtain the overall time domain estimate of the voltage using the Fourier series analysis.

Abstract: Estimating impedance of energy storage devices includes generating input signals at various frequencies with a frequency step factor therebetween. An excitation time record (ETR) is generated to include a summation of the input signals and a deviation matrix of coefficients is generated relative to the excitation time record to determine crosstalk between the input signals. An energy storage device is stimulated with the ETR and simultaneously a response time record (RTR) is captured that is indicative of a response of the energy storage device to the ETR. The deviation matrix is applied to the RTR to determine an in-phase component and a quadrature component of an impedance of the energy storage device at each of the different frequencies with the crosstalk between the input signals substantially removed. This approach enables rapid impedance spectra measurements that can be completed within one period of the lowest frequency or less.

Abstract: Methods of rapidly measuring an impedance spectrum of an energy storage device in-situ over a limited number of logarithmically distributed frequencies are described. An energy storage device is excited with a known input signal, and a response is measured to ascertain the impedance spectrum. An excitation signal is a limited time duration sum-of-sines consisting of a select number of frequencies. In one embodiment, magnitude and phase of each frequency of interest within the sum-of-sines is identified when the selected frequencies and sample rate are logarithmic integer steps greater than two. This technique requires a measurement with a duration of one period of the lowest frequency. In another embodiment, where selected frequencies are distributed in octave steps, the impedance spectrum can be determined using a captured time record that is reduced to a half-period of the lowest frequency.

Abstract: Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. A time profile of this sampled signal has a duration that is a few periods of the lowest frequency. A voltage response of the battery, average deleted, is an impedance of the battery in a time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time profile by rectifying relative to sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

Abstract: Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. The time profile of this signal has a duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time record by rectifying relative to the sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

Abstract: Estimating impedance of energy storage devices includes generating input signals at various frequencies with a frequency step factor therebetween. An excitation time record (ETR) is generated to include a summation of the input signals and a deviation matrix of coefficients is generated relative to the excitation time record to determine crosstalk between the input signals. An energy storage device is stimulated with the ETR and simultaneously a response time record (RTR) is captured that is indicative of a response of the energy storage device to the ETR. The deviation matrix is applied to the RTR to determine an in-phase component and a quadrature component of an impedance of the energy storage device at each of the different frequencies with the crosstalk between the input signals substantially removed. This approach enables rapid impedance spectra measurements that can be completed within one period of the lowest frequency or less.

Abstract: An impedance analysis system for characterizing an energy storage device (ESD) includes a signal vector assembler to generate a signal vector from a composition of one or more waveforms and a signal generator for generating a stimulus signal responsive to the signal vector. A signal measurement device measures a response signal indicative of a response of the ESD substantially simultaneously with when the stimulus signal is applied to the energy storage device. A load variation monitor monitors load variations on the energy storage device due to operational circuitry coupled thereto. An analyzer is operably coupled to the response signal and analyzes the response signal relative to the signal vector to determine an impedance of the energy storage device.

Abstract: Electrochemical Impedance Spectrum (EIS) data are used directly to predict the pulse performance of an energy storage device. The impedance spectrum of the EIS is obtained in-situ using pre-existing techniques. A simulation waveform is configured such that the period of the pulse is greater than or equal to the lowest frequency of the impedance measurement. If the pulse is assumed to be periodic for analysis purposes, the complex Fourier series coefficients can be obtained. The number of harmonic constituents are selected so as to appropriately resolve the response, but the maximum frequency should be less than or equal to the highest frequency of the impedance measurement. In some cases, the measured frequencies of the impedance spectrum do not match the corresponding harmonic components of the simulated pulse wave. This is resolved by estimating the impedance measurements at the desired frequencies using linear interpolation, cubic spline fits, or other comparable methods.

Abstract: Methods of rapidly measuring the impedance spectrum of an energy storage device in-situ over a limited number of logarithmically distributed frequencies are described. An energy storage device is excited with a known input signal, and the response is measured to ascertain the impedance spectrum. The excitation signal is a limited time duration sum-of-sines consisting of a select number of frequencies. In one embodiment, magnitude and phase of each of frequency of interest within the sum-of-sines is identified when the selected frequencies and sample rate are logarithmic integer steps greater than two. This technique requires a measurement with a duration of one period of the lowest frequency. In another embodiment, where the selected frequencies are distributed in octave steps, the impedance spectrum can be determined using a captured time record that is reduced to a half-period of the lowest frequency.

Abstract: Disclosed are methods and apparatuses for determining an impedance of an energy-output device using a random noise stimulus applied to the energy-output device. A random noise signal is generated and converted to a random noise stimulus as a current source correlated to the random noise signal. A bias-reduced response of the energy-output device to the random noise stimulus is generated by comparing a voltage at the energy-output device terminal to an average voltage signal. The random noise stimulus and bias-reduced response may be periodically sampled to generate a time-varying current stimulus and a time-varying voltage response, which may be correlated to generate an autocorrelated stimulus, an autocorrelated response, and a cross-correlated response. Finally, the autocorrelated stimulus, the autocorrelated response, and the cross-correlated response may be combined to determine at least one of impedance amplitude, impedance phase, and complex impedance.