Online condition monitoring of lithium-ion and lead acid batteries for renewable energy applications

Master Thesis


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Electrochemical Impedance Spectroscopy (EIS) has been largely employed for the study of reaction kinetics and condition monitoring of batteries during different operational conditions, such as: Temperature, State of Charge (SoC) and State of Health (SoH) etc. The EIS plot translates to the impedance profile of a battery and is fitted to an Equivalent Electric Circuit (EEC) that model the physicochemical processes occurring in the batteries. To precisely monitor the condition of the batteries, Kramers-Kronig relation: linearity, stability and causality as well as the appropriate perturbation amplitude applied during EIS should be adhered to. Regardless of the accuracy of EIS, its lengthy acquisition time makes it impracticable for online measurement. Different broadband signals have been proposed in literature to shorten EIS measurement time, with different researchers favouring one technique over the other. Nonetheless, broadband signals applied to characterize a battery must be reasonably accurate, with little effect on the systems instrumentation. The major objective of this study is to explore the differences in the internal chemistries of the lithium-ion and lead acid batteries and to reduce the time associated with their condition monitoring using EIS. In this regard, this study firstly queries the methodology for EIS experiments, by investigating the optimum perturbation amplitude for EIS measurement on both the lead acid and lithium-ion batteries. Secondly, this study utilizes electrochemical equations to predict the dynamics and operational conditions associated with batteries. It also investigates the effect of different operational conditions on the lead acid and lithium-ion batteries after EEC parameters have been extracted from EIS measurements. Furthermore, different broadband excitation techniques for rapid diagnostics are explored. An online condition monitoring system is implemented through the utilization of a DC-DC converter that is used to interface the battery with the load. The online system is applied alongside the different broadband signals. The deviation in the broadband impedance spectroscopy result is compared against the Frequency Response Analyzer (FRA) to determine the most suitable technique for battery state estimation. Based on the comparisons, the adoption of a novel technique – Chirp Broadband Signal Excitation (CBSE) is proposed for online condition monitoring of batteries, as it has the advantage of being faster and precise at the most important frequency decade of the impedance spectrum of batteries.