In this paper, advanced equivalent circuit models (ECMs) were developed to model large format and high energy nickel manganese cobalt (NMC) lithium-ion 20 Ah battery cells. Different temperatures conditions, cell characterization test (Normal and Advanced Tests), ECM topologies (1st and 2nd Order Thévenin model), state of charge (SoC) estimation techniques (Coulomb counting and extended Kalman filtering) and validation profiles (dynamic discharge pulse test (DDPT) and world harmonized light vehicle profiles) have been incorporated in the analysis. A concise state-of-the-art of different lithium-ion battery models existing in the academia and industry is presented providing information about model classification and information about electrical models. Moreover, an overview of the different steps and information needed to be able to create an ECM model is provided. A comparison between begin of life (BoL) and aged (95%, 90% state of health) ECM parameters (internal resistance (R_o), polarization resistance (R_p), activation resistance (R_p2) and time constants (τ) is presented. By comparing the BoL to the aged parameters an overview of the behavior of the parameters is introduced and provides the appropriate platform for future research in electrical modeling of battery cells covering the ageing aspect. Based on the BoL parameters 1st and 2nd order models were developed for a range of temperatures (15 °C, 25 °C, 35 °C, 45 °C). The highest impact to the accuracy of the model (validation results) is the temperature condition that the model was developed. The 1st and 2nd order Thévenin models and the change from normal to advanced characterization datasets, while they affect the accuracy of the model they mostly help in dealing with high and low SoC linearity problems. The 2nd order Thévenin model with advanced characterization parameters and extended Kalman filtering SoC estimation technique is the most efficient and dynamically correct ECM model developed.

Lithium-ion battery (LIB) technology further enabled the information revolution by powering smartphones and tablets, allowing these devices an unprecedented performance against reasonable cost. Currently, this battery technology is on the verge of carrying the revolution in road transport and energy storage of renewable energy. However, to fully succeed in the latter, a number of hurdles still need to be taken. Battery performance and lifetime constitute a bottleneck for electric vehicles as well as stationary electric energy storage systems to penetrate the market. Electrochemical battery models are one of the engineering tools which could be used to enhance their performance. These models can help us optimize the cell design and the battery management system. In this study, we evaluate the ability of the Porous Electrode Theory (PET) to predict the effect of changing positive electrode density in the overall performance of Li-ion battery cells. It can be concluded that Porous Electrode Theory (PET) is capable of predicting the difference in cell performance due to a changing positive electrode density.

This paper examines the impact of the characterisation technique considered for the determination of the $L{i}^{+}$ solid state diffusion coefficient in uncycled as in cycled Nickel Manganese Cobalt oxide (NMC) electrodes. As major characterisation techniques, Cyclic Voltammetry (CV), Galvanostatic Intermittent Titration Technique (GITT) and Electrochemical Impedance Spectroscopy (EIS) were systematically investigated. $L{i}^{+}$ diffusion coefficients during the lithiation process of the uncycled and cycled electrodes determined by CV at 3.71 V are shown to be equal to $3.48\times {10}^{-10}$ cm ${}^2$ ·s ${}^{-1}$ and $1.56\times {10}^{-10}$ cm ${}^2$ ·s ${}^{-1}$ , respectively. The dependency of the $L{i}^{+}$ diffusion with the lithium content in the electrodes is further studied in this paper with GITT and EIS. Diffusion coefficients calculated by GITT and EIS characterisations are shown to be in the range between $1.76\times {10}^{-15}$ cm ${}^2$ ·s ${}^{-1}$ and $4.06\times {10}^{-12}$ cm ${}^2$ ·s ${}^{-1}$ , while demonstrating the same decreasing trend with the lithiation process of the electrodes. For both electrode types, diffusion coefficients calculated by CV show greater values compared to those determined by GITT and EIS. With ageing, CV and EIS techniques lead to diffusion coefficients in the electrodes at 3.71 V that are decreasing, in contrast to GITT for which results indicate increasing diffusion coefficient. After long-term cycling, ratios of the diffusion coefficients determined by GITT compared to CV become more significant with an increase about 1 order of magnitude, while no significant variation is seen between the diffusion coefficients calculated from EIS in comparison to CV.