Abstract
With a growing amount of battery applications in today’s world, there is a large interest into the methods of detecting, estimating, and analyzing the battery degradation. Consequently, many different health detection and estimation methods and techniques have been proposed. This is also the case of the incremental capacity analysis (ICA) 1 method, which receives a significant interest in the Lithium-ion (Li-ion) batteries research and development fields. The method offers the possibility to analyze the ageing processes (e.g. loss of lithium inventory, loss of active material and kinetic changes) of Li-ion batteries and also has the potential to be implemented into a battery management system 2. However, what is the suitability of this method for emerging battery technologies, such as Lithium-Sulfur (Li-S)? Li-S batteries differ in many aspects from Li-ion batteries, as for example discussed in 3, fact which in some cases prevents a straightforward transfer of the methods and approaches to be applied on them. Already at the method applicability, the first difference and challenge can be spotted by comparing the charging and discharging voltage profiles of the Li-ion and Li-S batteries, as illustrated in Figure 1. In the case of the Li-ion batteries, the curves are strictly monotonous, while the typical Li-S voltage discharging curve has a ‘dip’ between the high- and low- voltage plateaus. Moreover, the Li-S charging curve can be monotonous or it can have a ‘bump’ (high internal resistance) at the beginning of the charging phase, as shown in Figure 2, according to the charging conditions and the previous history. Furthermore, the two chemistries are driven by different mechanisms. The Li-ion batteries work based upon an intercalation mechanism, where the ions travel directly between the electrodes. On the other hand, the Li-S batteries belong to the “solution chemistries”, where reduction and oxidation reactions of several stages of polysulfide species take place during charging and discharging 4. Therefore, analyzing the incremental capacity (IC) curves should be done carefully by considering the aforementioned differences. In this work, the IC curves were derived based on the approach presented in 2, where the battery voltage profile is divided into smaller voltage intervals, which are used to count the capacity increase. However, if it would be applied directly, the change of trend in the voltage would not be reflected and the change of the capacity, in the area marked by grey in Figure 2, would be computed wrongly and assigned to a different voltage value. Therefore, we propose at first to split the voltage curves into monotonic parts, as illustrated by the critical points A, B, C and D in Figure 2. These monotonous parts are evaluated separately to obtain appropriate dQ/dV values and later on they are composed together. Accordingly, the ICA technique is applied to the charging and discharging voltage profiles of the Li-S battery at various temperatures and by different currents to see the trends and understand their behavior, an example of the IC curves is shown in Figure 3. This methodology is further used to identify and assess the ageing mechanisms in Li-S batteries during both calendar and cycle ageing conditions. Moreover, the suitability of the ICA applied to the Li-S batteries for state-of-health estimation is explored. 1. M. Dubarry, V. Svoboda, R. Hwu, and B. Yann Liaw, Electrochem. Solid-State Lett., 9, A454–A457 (2006). 2. X. Han, M. Ouyang, L. Lu, J. Li, Y. Zheng, and Z. Li, J. Power Sources, 251, 38–54 (2014). 3. K. Propp, M. Marinescu, D. J. Auger, L. O’Neill, A. Fotouhi, K. Somasundaram, G. J. Offer, G. Minton, S. Longo, M. Wild, and V. Knap, J. Power Sources, 328, 289–299 (2016). 4. M. Wild, L. O’Neill, T. Zhang, R. Purkayastha, G. Minton, M. Marinescu, and G. J. Offer, Energy Environ. Sci. (2015). Figure 1
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