In this study a complete cell-level electrical equivalent circuit model (ECM) of energy and power lithium-ion cells with 3 different chemistries and multiple temperatures (−5 °C to 45 °C) is developed and validated under different dynamic load profiles. The chemistries under investigation are Nickel Manganese Cobalt 20 Ah (high energy), Lithium Iron Phosphate 14 Ah (high power) and Lithium Titanate Oxide 5 Ah (high power), providing a range of different cell characteristics and capacities. An updated workflow for the development of the ECM model is presented which includes extended versions of previous characterization and parameterization procedures used to populate a 2nd Order Thévenin ECM topology. The model is able to use two types of charge estimations, the extended coulomb counting and the extended Kalman filter techniques. The accuracy of the simulation in all three chemistries is increased through this improved characterization and optimization procedures. The “Initial State of Charge value”, “Capacity Value”, “Internal Resistance value” and the “Open Circuit Voltage” are included inside the complete model and have shown to affect greatly the accuracy of the simulations, specifically when the extended coulomb counting technique is implemented. The State of Health (SoH) level the validation profile was characterize in combination with the total time the simulation is performed have shown to affect also the accuracy of the simulation. The complete developed model is able to be combined with thermal and ageing models of lithium-ion cells. Combining this with the extended database of validated simulations for the different chemistries and temperatures, provides a suitable model to be extended to pack-level models of battery packs.
Original languageEnglish
Pages (from-to)133-146
Number of pages14
JournalInternational Journal of Electrical Power & Energy Systems
Volume98
Issue numberJune 2018
DOIs
Publication statusPublished - 14 Dec 2017

    Research areas

  • Dynamic load profiles, ECM parameterization, Electric modelling, Equivalent circuit models, Lithium-ion batteries, Simulation platform

ID: 35771545