Electrochemical impedance spectroscopy (EIS) techniques for the evaluation of the state of health (SOH) of batteries

Electrochemical energy storage has become important in the last years to improve the energetic efficiency of stationary and hybrid energy production systems. It becomes important the monitoring of the state of the battery to know online the energy content, to avoid dangerous operating conditions and to extend the useful life of the batteries. The energy content of the batteries can be evaluated through the knowledge of the State of Charge (SOC) and the State of Health (SOH). In literature several methods already exist to evaluate the SOC with precision, but the SOH is a parameter difficult to evaluate. Indeed the batteries, also belonging to the same technology, have different ageing phenomena. There is lack of methods and results to evaluate the SOH of the batteries online, while they are operative. The target of this work is the identification of the SOH through innovative techniques based on Electrochemical Impedance Spectroscopy (EIS). Compared to other methods, EIS is a powerful diagnostic tool to study the physical and chemical properties of any electrochemical system, allowing the possibility to study physical parameters for the monitoring of the batteries. A combination of theory, experimental and simulation tools have been therefore individuated to determine the SOH. The tested electrochemical cells are nickel-metal hydride (NiMH) of 1.3 Ah, 1.2 V and lithium polymer (LiPO) of 1.05 Ah, 3.7 V of nominal capacity and voltage respectively. To reach the goal, we have defined an experimental test procedure to accelerate the ageing of the cells, in order to study the ageing phenomena and to acquire experimental data. The impedance spectra (IS) from the EIS have been acquired at different SOC and SOH. Through a fitting procedure performed on the acquired IS, we have extracted the parameters of an equivalent circuit model. The information extracted by the IS and the parameters extracted by the model have been used to build some diagnostic diagrams, that in the following have been interpreted through the formalism of the Theory of Evidence (ToE) to determine the SOH. Combining the points obtained by the IS at different SOC and SOH, the ToE can improve the estimation of the SOH iteratively, a great advantage compared to the classic Theory of Probability. After the achievement of the goal and making sure that the IS provide information about the SOH of the batteries, a prototype has been realized to acquire online the IS. In the future the prototype can be integrated in a battery management system (BMS) to improve the estimation of the SOC and to evaluated accurately the SOH.