Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Machine Learning. According to news reporting originating from Perugia,Italy,by NewsR x correspondents,research stated,"In this study we define a comprehensive meth od for analyzing electrochemical impedance spectra of lithium batteries using eq uivalent circuit models,and for information extraction on state -of -charge and state -of -health from impedance data by means of machine learning methods. Est imation of circuit parameters typically implies a non -linear optimization probl em." Financial supporters for this research include European Union-Next Generation EU ,Mission Innovation program of Ministry of Environment and Energy Security (MAS E,ex-MITE) via the IEMAP project. Our news editors obtained a quote from the research from the University of Perug ia,"A detailed method for estimating initial values of the optimization algorit hm is described,emphasizing short computation times and efficient convergence t o global minimum. Parameters identifiability is investigated through an analysis of the injectivity of the model,Cramer-Rao lower bound,profile likelihood,an d sensitivity analysis. An exploratory data analysis is presented to estimate th e degree of correlation between impedance spectra (or circuit parameters) and ba ttery state -of -charge or state -of -health,prior to the implementation of any machine learning algorithm. A publicly available dataset of impedance spectra o f five lithium-polymer batteries is used to test the whole procedure."
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