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Modeling and Simulation of a Commercial Lithium-Ion Battery with Charge Cycle Predictions

doi: 10.3390/su142114035
The analysis of the behavior of lithium-ion batteries has gained considerable interest in recent years. There are different alternatives for the analysis of this behavior; however, depending on the type of modeling, there are application and optimization restrictions. In this work, a hybrid model has been made that is capable of predicting the characteristics of a lithium-ion battery. As a novelty, the simplification, at the same time, facilitates the sampling of parameters for their prompt selection for optimization. A new model open to the user is proposed, which has proven to be efficient in simulation time. For example, one hour simulates it in 5 min, providing information detailing how these parameters, State of Health (SOH), Open Circuit Voltage (VOC), State of charge (SOC), and Number of charge and discharge cycles, in the face of temperature variations and charge and discharge cycles. Opening the possibility of optimizing the parameters with different techniques to estimate the performance and dynamics in the face of temperature change and charge and discharge cycles. A model based on linear regressions, manufacturer characteristics, and integrating equations in the electrical model of electrochemical phenomena is proposed.
- University of Guadalajara Mexico
- University of Guadalajara Mexico
- Universidad Tecnologica de Tlaxcala Mexico
- Universidad Tecnologica de Tlaxcala Mexico
batteries, Environmental effects of industries and plants, hybrid model, TJ807-830, modeling, simulation, TD194-195, Renewable energy sources, Environmental sciences, GE1-350, modeling; simulation; batteries; hybrid model
batteries, Environmental effects of industries and plants, hybrid model, TJ807-830, modeling, simulation, TD194-195, Renewable energy sources, Environmental sciences, GE1-350, modeling; simulation; batteries; hybrid model
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).4 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
