Related papers: State-of-charge Estimation of a Li-ion Battery usi…
Li-Ion Solid-State Electrolytes (Li-SSEs) are a promising solution that resolves the critical issues of conventional Li-Ion Batteries (LIBs) such as poor ionic conductivity, interfacial instability, and dendrites growth. In this study, a…
A data-driven solution is provided for the fast-charging problem of lithium-ion batteries with multiple safety and aging constraints. The proposed method optimizes the charging current based on the observed history of measurable battery…
The impedance of a Li-ion battery contains information about its state of charge (SOC), state of health (SOH) and remaining useful life (RUL). Commonly, electrochemical impedance spectroscopy (EIS) is used as a nonparametric data-driven…
This paper is the second part of a series of papers about empirical approaches to open circuit voltage (OCV) modeling and its performance comparison in lithium-ion batteries. The first part of the series introduced various sources of…
Lithium ion batteries are widely used in many applications. Battery management systems control their optimal use and charging and predict when the battery will cease to deliver the required output on a planned duty or driving cycle. Such…
We investigate the modeling and simulation of ionic transport and charge conservation in lithium-ion batteries (LIBs) at the microscale. It is a multiphysics problem that involves a wide range of time scales. The associated computational…
Estimating the State of Health (SOH) of batteries is crucial for ensuring the reliable operation of battery systems. Since there is no practical way to instantaneously measure it at run time, a model is required for its estimation.…
Accurately predicting the state-of-health (SOH) and remaining useful life (RUL) of lithium-ion batteries is crucial for ensuring the safe and efficient operation of electric vehicles while minimizing associated risks. However, current deep…
Batteries are a key enabling technology for the decarbonization of transport and energy sectors. The safe and reliable operation of batteries is crucial for battery-powered systems. In this direction, the development of accurate and robust…
In recent years there has been a major interest in developing all solid state batteries, for the sake of safety (issues due to toxic and flammable organic liquid electrolytes are well known) as well as of high energy density…
Fast-charging of lithium-ion batteries is essential for electric vehicle adoption, but aggressive charging can accelerate its degradation and create safety risks. This study investigates a control framework that coordinates charging current…
Accurate identification of lithium-ion (Li-ion) battery parameters is essential for managing and predicting battery behavior. However, existing discrete-time methods hinder the estimation of physical parameters and face the fast-slow…
Diverse usage patterns induce complex and variable aging behaviors in lithium-ion batteries, complicating accurate health diagnosis and prognosis. Separate diagnostic cycles are often used to untangle the battery's current state of health…
Recent years have seen a rapidly escalating demand for battery technologies capable of storing more energy, charging more quickly and having longer usable lifetimes, driven largely by increased electrification of transport and by grid-scale…
Accurate prediction of lithium-ion battery lifespan is vital for ensuring operational reliability and reducing maintenance costs in applications like electric vehicles and smart grids. This study presents a hybrid learning framework for…
One of the most crucial challenges faced by the Li-ion battery community concerns the search for the minimum time charging without irreversibly damaging the cells. This can fall into solving large-scale nonlinear optimal control problems…
In recent years, the use of lithium-ion batteries has greatly expanded into products from many industrial sectors, e.g. cars, power tools or medical devices. An early prediction and robust understanding of battery faults could therefore…
This paper is the third part of a series of papers about empirical approaches to open circuit voltage (OCV) modeling of lithium-ion batteries. The first part of the series proposed models to quantify various sources of uncertainties in the…
Higher energy density and longer lifetime are the requirements for next-generation lithium-ion batteries. A promising anode material is silicon, which offers high specific capacity, but its significant volume change during lithiation and…
Cell inconsistency within a lithium-ion battery system poses a significant challenge in maximizing the system operational time. This study presents an optimization-driven active balancing method to minimize the effects of cell inconsistency…