Optimizing the Microstructure and Processing Parameters for Lithium‐Ion Battery Cathodes: A Use Case Scenario with a Digital Manufacturing Platform

Abstract

With increasing electrification in the automotive field, lithium‐ion batteries are rapidly becoming an inseparable part of everyday life. To meet the various governmental goals regarding CO2 emissions, it has become imperative to rapidly optimize the manufacturing process to produce high‐quality batteries at the least possible emissions and cost. Model‐based methods provide a simple and efficient view on complex processes and on identifying best‐case scenarios for production, since they require minimal material and time expenditure. In the authors’ recently published work, by Thomitzek et al., a digital modeling framework is initially described. It uniquely combines process chain and battery cell models. Herein, this digital framework is utilized to set up a numerical optimization routine. The routine helps to identify the best possible microstructure parameters in an NMC 622 cathode to maximize the resulting discharge volumetric energy density. Furthermore, the minimal energy expenditure for processing is determined. With the findings herein, an inexpensive method for identifying optimal battery manufacturing scenarios is presented, with the goal of producing high‐quality battery cells at the lowest cost. The provided model framework and optimization routine is easily adaptable for other battery types and manufacturing lines.

Possibilities and challenges of cathode materials for Zn-ion batteries

“…Techniques such as solvothermal, hydrothermal, and chemical vapour deposition are being explored to synthesise cathode materials with controlled nanostructures. 49 (b). In situ characterization.…”

Techno-Economic and Sustainable Challenges for EV Adoption in India: Analysis of the Impact of EV Usage Patterns and Policy Recommendations for Facilitating Seamless Integration

“…The literature provides insights into the development of strategies, optimization techniques, and cost analysis models [75] to reduce the manufacturing cost of EVs: a) Investigate methods to reduce the cost of manufacturing [76] and materials for the batteries. b) Cost savings [77] can be derived by implementing advanced manufacturing technologies [78] and increasing the scale of production. c) Explore approaches to stimulate the expansion of the used EV market [79], enhancing accessibility for a wider consumer base through the provision of affordable options.…”

Digitalization Platform for Sustainable Battery Cell Production: Coupling of Process, Production, and Product Models

“…The input and output parameters of each simulation are stored in the data storage module, being available to be used in further models or by different analysis functions. These analyses include, for example, robust optimization [24] or identification of production tolerances. [25] As shown in Figure 1, parameters provide the connection between models and modules.…”

“…[11,13] Starting from the battery cell model, it also enables the definition of process parameters based on the desired battery cell performance. [24] Due to the strictly interlinked processes and the parameter interdependencies, variations in process parameters lead to impacts on the entire process chain, altering the material and energy flows. Via the coupling of the process and production-oriented models, it is possible to analyze the interactions between process and production levels, such as the effect of different process configurations on the energy demand per produced cell.…”