No abstract

Various studies show that electrification, integrated into a circular economy, is crucial to reach sustainable mobility solutions. In this context, the circular use of electric vehicle batteries (EVBs) is particularly relevant because of the resource intensity during manufacturing. After reaching the end-of-life phase, EVBs can be subjected to various circular economy strategies, all of which require the previous disassembly. Today, disassembly is carried out manually and represents a bottleneck process. At the same time, extremely high return volumes have been forecast for the next few years, and manual disassembly is associated with safety risks. That is why automated disassembly is identified as being a key enabler of highly efficient circularity. However, several challenges need to be addressed to ensure secure, economic, and ecological disassembly processes. One of these is ensuring that optimal disassembly strategies are determined, considering the uncertainties during disassembly. This paper introduces our design for an adaptive disassembly planner with an integrated disassembly strategy optimizer. Furthermore, we present our optimization method for obtaining optimal disassembly strategies as a combination of three decisions: (1) the optimal disassembly sequence, (2) the optimal disassembly depth, and (3) the optimal circular economy strategy at the component level. Finally, we apply the proposed method to derive optimal disassembly strategies for one selected battery system for two condition scenarios. The results show that the optimization of disassembly strategies must also be used as a tool in the design phase of battery systems to boost the disassembly automation and thus contribute to achieving profitable circular economy solutions for EVBs.

Battery cells are the main components of a battery system for electric vehicle batteries. Depending on the manufacturer, three different cell formats are used in the automotive sector (pouch, prismatic, and cylindrical). In the last 3 years, cylindrical cells have gained strong relevance and popularity among automotive manufacturers, mainly driven by innovative cell designs, such as the Tesla tabless design. This paper investigates 19 Li-ion cylindrical battery cells from four cell manufacturers in four formats (18650, 20700, 21700, and 4680). We aim to systematically capture the design features, such as tab design and quality parameters, such as manufacturing tolerances and generically describe cylindrical cells. We identified the basic designs and assigned example cells to them. In addition, we show a comprehensive definition of a tabless design considering the current and heat transport paths. Our findings show that the Tesla 4680 design is quasi-tabless. In addition, we found that 25% of the cathode and 30% of the anode are not notched, resulting in long electrical and thermal transport paths. Based on CT and post-mortem analyses, we show that jelly rolls can be approximated very well with the Archimedean spiral. Furthermore, we compare the gravimetric and volumetric energy density, the impedance, and the heating behavior at the surface and in the center of the jelly rolls. From the generic description, we present and discuss production processes focusing on format and design flexible manufacturing of jelly rolls.

No abstract

In the coming decades, the number of end-of-life (EoL) traction battery systems will increase sharply. The disassembly of the system to the battery module is necessary to recycle the battery modules or to be able to use them for further second-life applications. These different recovery paths are important pathways to archive a circular battery supply chain. So far, little knowledge about the disassembling of EoL batteries exists. Based on a disassembly experiment of a plug-in hybrid battery system, we present results regarding the battery set-up, including their fasteners, the necessary disassembly steps, and the sequence. Upon the experimental data, we assess the disassembly duration of the battery system under uncertainty with a fuzzy logic approach. The results indicate that a disassembling time of about 22 min is expected for the battery system in the field study if one worker conducts the process. An estimation for disassembling costs per battery system is performed for a plant in Germany. Depending on the plant capacity, the disassembling to battery module level is associated with costs between EUR 80 and 100 per battery system.