دانلود رایگان مقاله روش جدید حالت سلامت تشخیصی برای باتری لیتیوم-یون در سرویس

Abstract

The development of improved State-of-Health (SoH) diagnostic methods is a current research topic for battery-powered applications. For instance, the current rapid development of Electric Vehicles (EV) creates a strong demand for an accurate and reliable on-board SoH indicator during operation. Such an indicator is a key parameter required to optimize battery energy management and to track the degradation of the system performance. The electrochemical impedance spectrum (EIS) of an electrochemical system is a powerful lab-based diagnostic technique, usually measured using a frequency response analyzer. In this paper, we present an innovative diagnostic technique based on analysis of free voltage and current signals to give a so called “quasi-electrochemical impedance spectrum” (QEIS) and demonstrate its application on a Li-ion battery during a real EV duty cycle. It is worth noting that in our technique no additional signal is applied to the cell, since the current flowing into cells during use on-board is directly processed in the data treatment step. Commercial batteries (1.4 Ah cylindrical LiFePO4/graphite cell) were selected in this study to validate the diagnostic method in the framework of an applied case study related to an electric school bus demonstrator. In order to study the capability of QEIS measurements as a diagnostic tool for SoH of Li-ion cells, a test procedure including ageing phases has been defined to characterise Li-ion cells before and during ageing. Voltage and current signals were treated by Fast Fourier Transform (FFT) in order to determine the QEIS spectra of Li-ion cells under study. Then, SoH prediction algorithms have been obtained from a mathematical analysis of the impedance parameters sensitive to SoH.

4. Conclusions

In this study, a new in operando method for estimating the SoH of a Li-ion battery was assessed on a commercial module. The method uses the real current and voltage values of the module during an in-use load cycling scenario as input data to calculate an impedance spectrum, so-called QEIS, which could be fitted to an electrical equivalent circuit model. SoH prediction algorithms have been obtained from a mathematical analysis of the model parameters. This method has been applied to ageing data collected from two modules undergoing different ageing protocols over 7 months. QEIS spectra calculated using our method were fitted to an electrical equivalent circuit model. It was found that the ohmic resistance (R0) and capacitance (C1) parameters of the model evolved monotonically with capacity fade of the battery, for the two different ageing protocols under consideration. By combining the two parameters an indicator of battery SoH was obtained, measurable using only the free output signals of the battery (current and voltage). This correlation could further be applied to other Li-ion battery systems, provided there is a similar ageing mechanism triggered. This method is a promising solution for an embedded system to monitor battery SoH and also for lifetime prediction. To be used for another Li-ion technology it is however necessary to process to a measurement campaign in order to evaluate adapted fitted parameters of other battery chemistries.