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: 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: 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: A network-based diagnosis server for monitoring and diagnosing a system, the server being remote from the system it is observing, comprises a sensor for generating signals indicative of a characteristic of a component of the system, a network-interfaced sensor agent coupled to the sensor for receiving signals therefrom, a broker module coupled to the network for sending signals to and receiving signals from the sensor agent, a handler application connected to the broker module for transmitting signals to and receiving signals therefrom, a reasoner application in communication with the handler application for processing, and responding to signals received from the handler application, wherein the sensor agent, broker module, handler application, and reasoner applications operate simultaneously relative to each other, such that the present invention diagnosis server performs continuous monitoring and diagnosing of said components of the system in real time.

Abstract: A network-based diagnosis server for monitoring and diagnosing a system, the server being remote from the system it is observing, comprises a sensor for generating signals indicative of a characteristic of a component of the system, a network-interfaced sensor agent coupled to the sensor for receiving signals therefrom, a broker module coupled to the network for sending signals to and receiving signals from the sensor agent, a handler application connected to the broker module for transmitting signals to and receiving signals therefrom, a reasoner application in communication with the handler application for processing, and responding to signals received from the handler application, wherein the sensor agent, broker module, handler application, and reasoner applications operate simultaneously relative to each other, such that the present invention diagnosis server performs continuous monitoring and diagnosing of said components of the system in real time.