Electrochemical models: methods and applications for safer lithium-ion battery operation

Abstract

Emphasis on clean energy has led to a widespread focus on lithium-ion batteries. However, a major obstacle is their degradation with several cycles or calendar aging. Battery management systems rely on an essential model-based algorithm to protect the battery from operating outside the safety limit. Thus, this work attempts to answer important research questions on battery models: Are physics-based electrochemical models (EM) robust enough to identify internal cell degradation and abnormal battery behavior? How are the structural simplifications and mathematical order reductions imposed on the EMs and what are their trade-offs? How to apply simplified EM for safer and more efficient battery operation? What are the prospects and obstacles to employing EM-based algorithms in the future? This paper presents a detailed analysis of EM from a modeling and application perspective and introduces battery operating mechanisms, typical failures, and their effects. Followed by an analysis of full order EM (Pseudo 2-Dimensional), and further classification into simpler and advanced reduced order models. The study demonstrates the gaps in theoretical understanding and their implementation for real-time battery operations such as in thermal management, energy utilization, and fault diagnosis and prognosis.

From Atoms to Wheels: The Role of Multi-Scale Modeling in the Future of Transportation Electrification

“…Many researchers effectively use microstructure modeling to answer performance questions and link to the manufacturing processes typically seen in battery plants, namely mixing, coating, and drying, 31 and simulations at this length scale have exponentially improved over the past few years due to the increases in computational power available in many industries. Meso-scale.-Perhaps the most researched length scale in the VE domain, as evidenced by the number of modeling methods 32 and approaches reported in literature, meso-scale modeling captures the linkage between material properties, electrode and cell design, and provides outputs that can be scaled to the system level. One of the most popular models to drive virtual design is that of Newman 7,8 and colleagues.…”

Determination of Fast Battery-Charging Profiles Using an Electrochemical Model and a Direct Optimal Control Approach

“…References [34,35] provide a comprehensive evaluation of mathematical models for lithium-ion and nickel-based batteries. The most comprehensive mathematical model widely used in battery simulations is the Doyle-Fuller-Newman model [29,[36][37][38], well known in the literature by its acronym DFN ' [39], is developed using the Maxwell-Stefan equations for the transport of ions in concentrated electrolytes. Fick's law describes the diffusion of lithium ions in the negative and positive electrodes.…”

Ageing of High Energy Density Automotive Li-ion Batteries: The Effect of Temperature and State-of-Charge

“…Battery ageing studies are complex due to the interrelation of multiscale processes, requiring multiple techniques for a profound analysis and often interpretations can be often challenging due to technical limitations [18]. Most of the ageing studies are focused on cell, electrode, or material levels [19] and the challenge to distinguish individual ageing processes has motivated the classification of ageing mechanisms into three major ageing modes: loss of lithium inventory (LLI), loss of active material (LAM), and loss of electric conductivity also known as resistance increase (RI) [20][21][22][23][24]. LLI refers to processes that result in a loss of lithium ions available to participate in the redox process, such as the formation of the solid-electrolyte interphase (SEI), while LAM covers processes that involve loss or changes resulting in the lower electrochemical activity of the host material, including transition metal dissolution, irreversible phase transition, and particle disconnection as a result of particle cracking.…”