Lithium-ion batteries have been widely used in many important applications. However, there are still many challenges facing lithium-ion batteries, one of them being degradation. Battery degradation is a complex problem, which involves many electrochemical side reactions in anode, electrolyte, and cathode. Operating conditions affect degradation significantly and therefore the battery lifetime. It is of extreme importance to achieve accurate predictions of the remaining battery lifetime under various operating conditions. This is essential for the battery management system to ensure reliable operation and timely maintenance and is also critical for battery second-life applications. After introducing the degradation mechanisms, this paper provides a timely and comprehensive review of the battery lifetime prognostic technologies with a focus on recent advances in model-based, data-driven, and hybrid approaches. The details, advantages, and limitations of these approaches are presented, analyzed, and compared. Future trends are presented, and key challenges and opportunities are discussed.

A physics-based side-reaction coupled electrochemical model for capacity fade of a graphite/LiMn 2 O 4 cell is developed by including the key degradation mechanisms in both anode and cathode. The side reactions considered in this study include 1) solid electrolyte interphase (SEI) growth and manganese deposition on the anode and 2) manganese dissolution, electrolyte oxidation and salt decomposition on the cathode. Our study reveals three stages of capacity fade upon long term cycling: acceleration, stabilization, and saturation. In the acceleration stage, capacity fade is due mainly to the cyclable lithium loss induced by the anode SEI growth. In the stabilization stage, the anode SEI growth slows down as it gets thicker, the cathode Mn dissolution-induced capacity loss outpaces cyclable lithium loss, and the cathode becomes more intercalated at the end of discharge. In the saturation stage, cathode capacity degrades further and becomes the limiting factor, the cyclable lithium is shifted to the anode and the cathode reaches end-of-discharge saturation due to the severe cathode capacity fade. This study shows that the cyclable lithium loss and the cathode capacity loss are the two major contributors to the cell capacity fade, and the interaction between them determines the cell capacity.Energy security and climate change challenges provide a strong impetus for the development of electric vehicles (EV) and hybrid electric vehicles (HEV). 1,2 Lithium ion batteries are one of the most important components of the EVs and HEVs. One of the most important topics is the degradation, or aging process, of the cells during operation. A substantial amount of work has gone into understanding capacity fade through experiments and theoretical/numerical studies. Ramadass et al. 3 carried out a complete capacity fade analysis for the Sony 18650 cells after hundreds of cycles. They divided the capacity fade into rate capability loss as well as primary and secondary active material losses. However, they proposed no model to quantitatively explain the capacity fade due to different mechanisms. Safari et al. 4 proposed a multimodal physics-based aging model to predict the capacity fade for Li-ion batteries. They assumed that capacity fade stems mainly from solid electrolyte interphase (SEI) growth on the anode, and that lithium ion consumption during SEI growth was the main contributor to cycling degradation. Zhang et al. 5 developed a single-particle model which they calibrated against the cycling data to study the parameter trajectories. They suggested that there were probably different stages of capacity fade in the lithium ion battery. However, they proposed no degradation model to quantitatively study the degradation process.The studies above have attempted to elucidate capacity fade by focusing on specific mechanisms, not by regarding all the key mechanisms together. Because each mechanism is coupled to each other, it is important to consider all of them and their interactions simultaneously. In this way, the whole life of a ba...

In this study, a phase-field model is developed to simulate the microstructure morphology evolution that occurs during solid electrolyte interphase (SEI) growth. Compared with other simulation methodologies, the phase-field method has been widely applied in the solidification modeling that has great relevance to SEI formation. The developed model can simulate SEI structure and morphology evolution, and can predict SEI thickness growth rate. X-ray photoelectron spectroscopy (XPS) experiments are performed to confirm the major SEI species as LiF, Li 2 O, ROLi, and ROCO 2 Li. Transmission electron microscopy (TEM) experiment is performed to present the SEI layer structures. The experiments reduce the complexity of the model development and provide validation to some extent. Fick's law and mass balance are applied to investigate lithium-ion concentration distributions and diffusion coefficients in different types of SEI layers predicted by the phase-field simulations. Simulation results show that lithium-ion diffusion coefficients between 298 K and 318 K are 1. 340-7.328 Lithium-ion batteries (LIBs) are widely used in many applications, such as cell phones, electric vehicles (EVs), and other energy storage modules. However, LIBs suffer from severe performance degradation due to undesired chemical reactions, 1 ageing, 2,3 corrosion, 4-6 compromised structural integrity, 7,8 and thermal runaway. 9-11 The degradation occurs during both calendar and cycling lifespans, and reduces the longevity of LIBs. Recently, much attention has been focused on LIB material decomposition, 12 e.g., the formation and growth of new components [13][14][15][16][17][18][19] due to undesired side reactions. 1,20 The main degradation mechanisms in LIBs vary with different active materials, 2 however, it is well known that a carbonaceous lithium-intercalation electrode in contact with electrolyte solution becomes covered by a passivation layer called a solid electrolyte interphase (SEI). While SEI can prevent the exfoliation of graphite materials and inhibit further electrolyte decomposition.21 SEI layer growth can also cause battery capacity fade and increase cell internal resistance. 17,[22][23][24][25][26] Therefore, the study of SEI plays a key role in battery degradation and other related performance improvement research. Many studies have been published in SEI computational and experimental studies, including but not limited to. [27][28][29][30] Many researchers have investigated SEI in LIBs in terms of structure, 7,8,29,31-33 formation and composition, 20,22,27 and thickness growth prediction and measurement. 15,16,34,35 SEI is believed to have a multilayered structure: a compact layer of inorganic components (e.g., LiF, Li 2 O) close to graphite electrode followed by a porous organic layer (e.g., ROLi, ROCO 2 Li) close to the electrolyte solution phase. 22,29,[31][32][33] The composition of SEI depends on the electrode materials and electrolyte composition.27 Broussely et al. investigated the mechanism of lithium loss in LIBs during ...

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