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Energy generation with renewable sources demands energy storage coupling to maintain power quality in the electrical generation and supply for smart grids. Electrochemical energy storage in batteries has become the option due to compactivity, easy arrangement, economic factors and because it delivers nearly instant response both to input from the battery and output from the network to the battery. Among storage technologies, lead batteries offer a reliable, cost-effective solution which can be adapted for different types of energy storage applications (1-4). Predicting the lifetime of lead-acid batteries represents a challenge due to the irregularity of the cycling regime with charging and discharging intercepting each other constantly. To achieve better accuracy in the lifetime description it is desirable to combine performance and lifetime models. However, this is a complicated task due to different phenomena affecting lifetime such as corrosion, acid stratification, gassing, sulfation and sulfate crystal growth, and degradation of the active material (1, 3, 5-7) . One of the most representative models, presented by Schiffer and collaborators(7), based on the concept of ‘weighted Ah throughput’ used weighting factor to understand the full charge and partial state-of-charge cycling and its changes due to acid stratification, gassing, and high temperature. Corrosion effects are calculated based on battery voltage and temperature. Other models are based on equivalent circuit analysis. There are three type of electrical models such as: Thevenin, Impedance and Run-time based electrical models (8, 9). Thevenin’s model which uses a series resistor and an RC parallel network to predict battery response to transient load events at an specific state of charge (SOC), by assuming the open-circuit voltage is constant (9). The impedance model employs electrochemical impedance spectroscopy to obtain the AC-equivalent impedance model. However, the fitting process is difficult and only work for a fixed SOC and temperature setting. Runtime-based models use a complex circuit network to simulate battery runtime and DC voltage response for a constant discharge current. They can predict neither runtime nor voltage response for varying load currents accurately (9). However, most of these models are adjusted or obtaining from experimental data sets and are highly dependent on the parametrical adjustment to accurately describe the lifetime process. Moreover, phenomelogical description of process such as corrosion, gassing or sulfation are not quite understood under extreme temperature and operation conditions. The aim of this study is to combine electrochemical and electrical equations to describe the performance of lead-acid batteries. By combining Schiffer’s approach with Butler-Volmer type description of phenomena such as load current, corrosion processes and gassing, as function of temperature, we will gain insight and better description of ageing phenomena. Our proposed methodology can be summarized as: i) overpotential calculation based on experimental data, ii) load current calculation by using experimental overpotentials and Butler-Volmer equations as a function of temperature, iii) overpotential calculations such as corrosion and gassing with electrochemical models. Acknowledgement We gratefully acknowledge the support of the Universidad Nacional de Colombia - Sede Medellín with its 2018-2019 Research and Innovation project funding program for the project “Desarrollo de un simulador multiescala para estudio de procesos físico-químicos basado en teorías atómicas y moleculares Versión 2.0” References G. J. May, A. Davidson and B. Monahov, Journal of Energy Storage, 15, 145 (2018). S. Sundararagavan and E. Baker, Solar Energy, 86, 2707 (2012). J. Yang, C. Hu, H. Wang, K. Yang, B. Liu Jing and H. Yan, International Journal of Energy Research, 41, 336 (2016). Z. Zhou, M. Benbouzid, J. Frédéric Charpentier, F. Scuiller and T. Tang, Renewable and Sustainable Energy Reviews, 18, 390 (2013). A. Degla, M. Chikh, A. Chouder, F. Bouchafaa and A. Taallah, IET Renewable Power Generation, 12, 484 (2018). H. Hao, A Review of the Positive Electrode Additives in Lead-Acid Batteries, p. 2329 (2018). J. Schiffer, D. U. Sauer, H. Bindner, T. Cronin, P. Lundsager and R. Kaiser, Journal of Power Sources, 168, 66 (2007). C. Min and G. A. Rincon-Mora, IEEE Transactions on Energy Conversion, 21, 504 (2006). R. Dufo-López, J. M. Lujano-Rojas and J. L. Bernal-Agustín, Applied Energy, 115, 242 (2014). |
