Fast summation transformation for battery impedance identification

A battery is an important subsystem for electrical energy storage in many military, space and commercial applications. Consequently, in-situ diagnostics for state-of-health estimation of the battery is also critical for enhancing the overall applications' reliability. Montana Tech, in collaboration with the Idaho National Laboratory (INL) and Qualtech Systems Inc. (QSI), has been working towards the development of advanced techniques for in-situ and real time estimation of a battery's impedance spectrum. INL has shown that the shift of a batteries impedance spectrum strongly correlates to the health of the battery [1].