05 Fakultät Informatik, Elektrotechnik und Informationstechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6

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Open Access
Analytic free-energy expression for the 2D-Ising model and perspectives for battery modeling
(2023) Markthaler, Daniel; Birke, Kai Peter
Although originally developed to describe the magnetic behavior of matter, the Ising model represents one of the most widely used physical models, with applications in almost all scientific areas. Even after 100 years, the model still poses challenges and is the subject of active research. In this work, we address the question of whether it is possible to describe the free energy A of a finite-size 2D-Ising model of arbitrary size, based on a couple of analytically solvable 1D-Ising chains. The presented novel approach is based on rigorous statistical-thermodynamic principles and involves modeling the free energy contribution of an added inter-chain bond DAbond(b, N) as function of inverse temperature b and lattice size N. The identified simple analytic expression for DAbond is fitted to exact results of a series of finite-size quadratic N N-systems and enables straightforward and instantaneous calculation of thermodynamic quantities of interest, such as free energy and heat capacity for systems of an arbitrary size. This approach is not only interesting from a fundamental perspective with respect to the possible transfer to a 3D-Ising model, but also from an application-driven viewpoint in the context of (Li-ion) batteries where it could be applied to describe intercalation mechanisms.
Open Access
Design, properties, and manufacturing of cylindrical Li-ion battery cells : a generic overview
(2023) Baazouzi, Sabri; Feistel, Niklas; Wanner, Johannes; Landwehr, Inga; Fill, Alexander; Birke, Kai Peter
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.
Open Access
Feasible energy density pushes of Li-metal vs. Li-ion cells
(2021) Karabelli, Duygu; Birke, Kai Peter
Li-metal batteries are attracting a lot of attention nowadays. However, they are merely an attempt to enhance energy densities by employing a negative Li-metal electrode. Usually, when a Li-metal cell is charged, a certain amount of sacrificial lithium must be added, because irreversible losses per cycle add up much more unfavourably compared to conventional Li-ion cells. When liquid electrolytes instead of solid ones are used, additional electrolyte must also be added because both the lithium of the positive electrode and the liquid electrolyte are consumed during each cycle. Solid electrolytes may present a clever solution to the issue of saving sacrificial lithium and electrolyte, but their additional intrinsic weight and volume must be considered. This poses the important question of if and how much energy density can be gained in realistic scenarios if a switch from Li-ion to rechargeable Li-metal cells is anticipated. This paper calculates various scenarios assuming typical losses per cycle and reveals future e-mobility as a potential application of Li-metal cells. The paper discusses the trade-off if, considering only the push for energy density, liquid electrolytes can become a feasible option in large Li-metal batteries vs. the solid-state approach. This also includes the important aspect of cost.
Open Access
Hybrid modeling of lithium-ion battery : physics-informed neural network for battery state estimation
(2023) Singh, Soumya; Ebongue, Yvonne Eboumbou; Rezaei, Shahed; Birke, Kai Peter
Accurate forecasting of the lifetime and degradation mechanisms of lithium-ion batteries is crucial for their optimization, management, and safety while preventing latent failures. However, the typical state estimations are challenging due to complex and dynamic cell parameters and wide variations in usage conditions. Physics-based models need a tradeoff between accuracy and complexity due to vast parameter requirements, while machine-learning models require large training datasets and may fail when generalized to unseen scenarios. To address this issue, this paper aims to integrate the physics-based battery model and the machine learning model to leverage their respective strengths. This is achieved by applying the deep learning framework called physics-informed neural networks (PINN) to electrochemical battery modeling. The state of charge and state of health of lithium-ion cells are predicted by integrating the partial differential equation of Fick’s law of diffusion from a single particle model into the neural network training process. The results indicate that PINN can estimate the state of charge with a root mean square error in the range of 0.014% to 0.2%, while the state of health has a range of 1.1% to 2.3%, even with limited training data. Compared to conventional approaches, PINN is less complex while still incorporating the laws of physics into the training process, resulting in adequate predictions, even for unseen situations.
Open Access
Implementation of battery Digital Twin : approach, functionalities and benefits
(2021) Singh, Soumya; Weeber, Max; Birke, Kai Peter
The concept of Digital Twin (DT) is widely explored in literature for different application fields because it promises to reduce design time, enable design and operation optimization, improve after-sales services and reduce overall expenses. While the perceived benefits strongly encourage the use of DT, in the battery industry a consistent implementation approach and quantitative assessment of adapting a battery DT is missing. This paper is a part of an ongoing study that investigates the DT functionalities and quantifies the DT-attributes across the life cycles phases of a battery system. The critical question is whether battery DT is a practical and realistic solution to meeting the growing challenges of the battery industry, such as degradation evaluation, usage optimization, manufacturing inconsistencies or second-life application possibility. Within the scope of this paper, a consistent approach of DT implementation for battery cells is presented, and the main functions of the approach are tested on a Doyle-Fuller-Newman model. In essence, a battery DT can offer improved representation, performance estimation, and behavioral predictions based on real-world data along with the integration of battery life cycle attributes. Hence, this paper identifies the efforts for implementing a battery DT and provides the quantification attribute for future academic or industrial research.
Open Access
Investigation of the influence of electrode surface structures on wettability after electrolyte filling based on experiments and a lattice Boltzmann simulation
(2023) Wanner, Johannes; Birke, Kai Peter
The filling of the electrolyte and the subsequent wetting of the electrodes is a quality-critical and time-intensive process in manufacturing of lithium-ion batteries. The exact influencing factors are the subject of research through experiments and simulation tools. Previous studies have demonstrated that wetting occurs mainly in the transition between the materials but leads to gas entrapments. Therefore, this paper investigates the influence of the electrode surface structures, situated between anode and separator, on the wetting progress, through experimental capillary wetting and simulated with a lattice Boltzmann simulation. The results show that the simulations can identify the exact pore size distribution and determine the wetting rates of the entire materials. Furthermore, the experiments reveal a negative correlation between fast wetting and rougher surface properties. This enables a more precise determination of the wetting phenomena in lithium-ion cell manufacturing.
Open Access
Multi-method model for the investigation of disassembly scenarios for electric vehicle batteries
(2023) Baazouzi, Sabri; Grimm, Julian; Birke, Kai Peter
Disassembly is a pivotal technology to enable the circularity of electric vehicle batteries through the application of circular economy strategies to extend the life cycle of battery components through solutions such as remanufacturng, repurposing, and efficient recycling, ultimately reintegrating gained materials into the production of new battery systems. This paper aims to develop a multi-method self-configuring simulation model to investigate disassembly scenarios, taking into account battery design as well as the configuration and layout of the disassembly station. We demonstrate the developed model in a case study using a Mercedes-Benz battery and the automated disassembly station of the DeMoBat project at Fraunhofer IPA. Furthermore, we introduce two disassembly scenarios: component-oriented and accessibility-oriented disassembly. These scenarios are compared using the simulation model to determine several indicators, including the frequency of tool change, the number and distribution of robot routes, tool utilization, and disassembly time.
Open Access
Optimization of disassembly strategies for electric vehicle batteries
(2021) Baazouzi, Sabri; Rist, Felix Paul; Weeber, Max; Birke, Kai Peter
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.
Open Access
Proof of concept : the GREENcell : a lithium cell with a F-, Ni- and Co-Free cathode and stabilized in-situ LiAl alloy anode
(2023) Schad, Kathrin; Welti, Dominic; Birke, Kai Peter
Given the rising upscaling trend in lithium-ion battery (LiB) production, there is a growing emphasis on the environmental and economic impacts alongside the high energy density demands. The cost and environmental impact of battery production primarily arise from the critical elements Ni, Co, and F. This drives the exploration of Ni-free and Co-free cathode alternatives such as LiMn 2O 4 (LMO) and LiFePO 4 (LFP). However, the absence of Ni and Co results in reduced capacity and insufficient cyclic stability, particularly in the case of LMO due to Mn dissolution. To compensate for both low cathode capacitance and low cycle stability, we propose the GREENcell, a lithium cell combining a F-free polyisobutene (PIB) binder-based LMO cathode with a stabilized in -situ LiAL alloy anode. A LiAl alloy anode with the chemical composition of LiAl already shows a theoretical capacity of 993 Ah·kg−1. Therefore, it promises extraordinarily higher energy densities compared to a commercial graphite anode with a capacity of 372 Ah·kg−1. Following an iterative development process, different optimization strategies, especially those targeting the stability of the Al-based anode, were evaluated. During Al foil selection, foil purity and thickness could be identified as two of the dominant influencing parameters. A pressed-in stainless steel mesh provides both mechanical stability to the anode and facilitates alloy formation by breaking up the Al oxide layer beforehand. Additionally, a binder-stabilized Al oxide or silicate layer is pre-coated on the Al surface, posing as a SEI-precursor and ensuring a uniform liquid electrolyte distribution at the phase boundary. Employing a commercially available Si-containing Al alloy mitigated the mechanical degradation of the anode, yielding a favorable impact on long-term stability. The applicability of the novel optimized GREENcell is demonstrated using laboratory coin cells with LMO and LFP as the cathode. As a result, the functionality of the GREENcell was demonstrated for the first time, and thanks to the anode stabilization strategies, a capacity retention of >70% after 200 was achieved, representing an increase of 32.6% compared to the initial Al foil.
Open Access
Sodium-based batteries : in search of the best compromise between sustainability and maximization of electric performance
(2020) Karabelli, Duygu; Singh, Soumya; Kiemel, Steffen; Koller, Jan; Konarov, Aishuak; Stubhan, Frank; Miehe, Robert; Weeber, Max; Bakenov, Zhumabay; Birke, Kai Peter
Till 2020 the predominant key success factors of battery development have been overwhelmingly energy density, power density, lifetime, safety, and costs per kWh. That is why there is a high expectation on energy storage systems such as lithium-air (Li-O2) and lithium-sulfur (Li-S) systems, especially for mobile applications. These systems have high theoretical specific energy densities compared to conventional Li-ion systems. If the challenges such as practical implementation, low energy efficiency, and cycle life are handled, these systems could provide an interesting energy source for EVs. However, various raw materials are increasingly under critical discussion. Though only 3 wt% of metallic lithium is present in a modern Li-ion cell, absolute high amounts of lithium demand will rise due to the fast-growing market for traction and stationary batteries. Moreover, many lithium sources are not available without compromising environmental aspects. Therefore, there is a growing focus on alternative technologies such as Na-ion and Zn-ion batteries. On a view of Na-ion batteries, especially the combination with carbons derived from food waste as negative electrodes may generate a promising overall cost structure, though energy densities are not as favorable as for Li-ion batteries. Within the scope of this work, the future potential of sodium-based batteries will be discussed in view of sustainability and abundance vs. maximization of electric performance. The major directions of cathode materials development are reviewed and the tendency towards designing high-performance systems is discussed. This paper provides an outlook on the potential of sodium-based batteries in the future battery market of mobile and stationary applications.
Open Access
Tackling xEV battery chemistry in view of raw material supply shortfalls
(2020) Karabelli, Duygu; Kiemel, Steffen; Singh, Soumya; Koller, Jan; Ehrenberger, Simone; Miehe, Robert; Weeber, Max; Birke, Kai Peter
The growing number of Electric Vehicles poses a serious challenge at the end-of-life for battery manufacturers and recyclers. Manufacturers need access to strategic or critical materials for the production of a battery system. Recycling of end-of-life electric vehicle batteries may ensure a constant supply of critical materials, thereby closing the material cycle in the context of a circular economy. However, the resource-use per cell and thus its chemistry is constantly changing, due to supply disruption or sharply rising costs of certain raw materials along with higher performance expectations from electric vehicle-batteries. It is vital to further explore the nickel-rich cathodes, as they promise to overcome the resource and cost problems. With this study, we aim to analyze the expected development of dominant cell chemistries of Lithium-Ion Batteries until 2030, followed by an analysis of the raw materials availability. This is accomplished with the help of research studies and additional experts’ survey which defines the scenarios to estimate the battery chemistry evolution and the effect it has on a circular economy. In our results, we will discuss the annual demand for global e-mobility by 2030 and the impact of Nickel-Manganese-Cobalt based cathode chemistries on a sustainable economy. Estimations beyond 2030 are subject to high uncertainty due to the potential market penetration of innovative technologies that are currently under research (e.g. solid-state Lithium-Ion and/or sodium-based batteries).
Open Access
User-friendly, requirement-based assistance for production workforce using an asset administration shell design
(2020) Al Assadi, Anwar; Fries, Christian; Fechter, Manuel; Maschler, Benjamin; Ewert, Daniel; Schnauffer, Hans-Georg; Zürn, Michael; Reichenbach, Matthias
Future production methods like cyber physical production systems (CPPS), flexibly linked assembly structures and the matrix production are characterized by highly flexible and reconfigurable cyber physical work cells. This leads to frequent job changes and shifting work environments. The resulting complexity within production increases the risk of process failures and therefore requires longer job qualification times for workers, challenging the overall efficiency of production. During operation, cyber physical work cells generate data, which are specific to the individual process and worker. Based on the asset administration shell for Industry 4.0, this paper develops an administration shell for the production workforce, which contains personal data (e.g. qualification level, language skills, machine access, preferred display and interaction settings). Using worker and process specific data as well as personal data, allows supporting, training and instating workers according to their individual capabilities. This matching of machine requirements and worker skills serves to optimize the allocation of workers to workstations regarding the ergonomic workplace setup and the machine efficiency. This paper concludes with a user-friendly, intuitive design approach for a personalized machine user interface. The presented use-cases are developed and tested at the ARENA2036 (Active Research Environment for the Next Generation of Automobiles) research campus.