Electrode manufacturing is an important part of the cost of lithium-ion batteries (LIBs). It accounts for at least 20 to 40% of the total pack costs. The process is broken down into steps and involves various parameters that need to be controlled and monitored during each step. This article aims to address the research gap regarding a holistic approach to the manufacturing process. To achieve this, a tracking and tracing system is used to analyze the interdependencies among different process parameters. In addition, a Delphi method is used to validate the results.
Electrode materials play a vital role in the performance of the battery cell. In particular, the physical properties of the electrode depend on its topology and structure. The use of intelligent electrodes can improve the efficiency of energy storage devices. Several research efforts have been dedicated to improving electrode materials for better battery cells. However, significant cost reduction remains a major challenge as we approach theoretical density limits.
Currently, electrode manufacturing is carried out using an expert-based approach. More than 50 publications have been published about this topic. While this literature does offer a comprehensive overview of the various electrode parameters, most of them are based on a single expert-based approach. In this paper, we develop a digitalization approach to support the implementation of this technology. Moreover, we demonstrate that this strategy is able to produce a scalable, cost-efficient approach.
The article provides a detailed description of the various methods and approaches that were developed to ensure the transferability of the technology. It also includes the development of a DSM, which can be used for the analysis of the interdependencies between different process parameters.
The first step is the identification of the relevant parameters. These are the input and output parameters for each process step. A prioritization scheme was used to categorize the 120 parameters into two categories. For each parameter, a minimum and a maximum value were used to normalize the results. After that, the number of bilateral interdependencies was quantified. Finally, the DSM was used to analyze the resulting data and to suggest potential data-driven solutions for the electrode manufacturing process.
The electrode surface is a product parameter that is influenced by several factors such as the calendering process, agglomeration of small particles, and the stability of the slurry. Calendering, for example, improves the flatness of the surface. Additionally, the camber effect in calendering has been observed to affect the quality of the electrode surface.
Moreover, the slurry stability directly affects the coating process performance. Large particles in the slurry tend to sediment, affecting the uniformity of the slurry. Therefore, the slurry should be designed to minimize the amount of large particles and increase the density of the active material. Furthermore, it is recommended that the slurry is enriched with a binder, which can provide stronger particle links.
Various studies have been conducted to improve the properties of the electrode slurry. This can be done by changing the quantity of conductive agents and adjusting the amount of binder. As a result, an even distribution of conductive agent is achieved, thereby ensuring the optimal conductivity of the electrode.
English
Write a Message