from chemistry to pack
AION Engineering INC For years, battery engineers have relied on the Single-Particle Model with Electrolyte (SPME) as the industry standard for cell simulation. SPME operates on a convenient mathematical simplification: it collapses the entire complex, porous electrode into a single representative particle. At low C-rates, this volume-averaged macroscopic assumption holds. But when a cell is … Read more
AION Engineering INC In battery continuum modelling, few parameters are as universally accepted—and as fundamentally flawed for modern cells—as a Bruggeman exponent of 1.5. While it is widely understood that tortuosity and porosity are distinct structural metrics, the industry consistently defaults to this idealized constant to bridge the gap between them. To understand why modern … Read more
AION Engineering INC When you open the datasheet of a lithium-ion cell, one of the first values to catch your eye is the internal resistance. Typically, it sits there as a single, proud number: ACIR: 15 mOhm. Many engineers look at this number, validate the “quality” of the cell, and integrate it into their vehicle … Read more
AION Engineering INC In lithium-ion batteries, electrode performance is governed not only by material chemistry but by the three-dimensional microstructure formed by particles, pores, binder, and conductive additives. Before production begins, this microstructure already defines how ions and electrons will move through the electrode. Once manufacturing starts, many of these structural characteristics can no longer … Read more
Parameter identification of a battery Equivalent Circuit Model (ECM) using Particle Swarm Optimization (PSO). The ECM includes a series resistance R0, an RC branch with R1 and C1, and a polynomial OCV-SOC relationship. The equations that describe the Equivalent Circuit Model (ECM) are given: The flow diagram takes you through the parameter optimization process. The … Read more
Authors: Antonio Garcia Martinez, Carlos Micó, Imad Elkourchi, and Jaime Martín CALBET (CALorimetric Battery Energy Tool) is an in-house thermodynamic model developed at CMT – Clean Mobility & Thermofluids, Universitat Politècnica de València (UPV) to analyze the thermal runaway (TR) behavior of lithium-ion cells under accelerating rate calorimetry (ARC) conditions. The model has been designed to provide a fast, robust, and … Read more
Most lithium-ion cells are rated to operate from –40 to 80 °C, yet few ever experience the extremes for more than a few minutes. In real-world operation, temperature tends to converge within a much narrower band. This is typically between 30 and 50 °C. That reality should guide how battery models are trained if they are to … Read more
Authors: Ionworks For several decades, the Doyle-Fuller-Newman model has been the cornerstone of computational battery modeling, design, and optimization. Since the model was developed based on an assumption of Fickian diffusion in the solid active material particles, the equilibrium state in a DFN model is an electrode of compositionally homogeneous particles. While this is appropriate … Read more
Authors: Marcus Tuchel, Prof. Emma Kendrick School of Metallurgy and Materials, University of Birmingham, Elms Rd, Birmingham B15 2SE Abstract Methodology Extrapolated OCV Li ion diffusion coefficient Conclusions and Future Work References Research Bio Marcus Tuchel is a PhD student in the Birmingham Energy Materials Group, under the supervision of Prof. Emma Kendrick and Prof. … Read more
This post is a compilation of three separate case-studies covering battery cell design and construction. The data and analysis for these case-studies was carried out using the Faraday Institutions CAMS model. CAMS was designed to rapidly assess the potential energy density of different cell chemistries and cell formats. The model can also be used as … Read more