05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Analytic free-energy expression for the 2D-Ising model and perspectives for battery modeling(2023) Markthaler, Daniel; Birke, Kai PeterAlthough 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.Item Open Access Cycling of double-layered graphite anodes in pouch-cells(2022) Müller, Daniel; Fill, Alexander; Birke, Kai PeterIncremental improvement to the current state-of-the-art lithium-ion technology, for example regarding the physical or electrochemical design, can bridge the gap until the next generation of cells are ready to take Li-ions place. Previously designed two-layered porosity-graded graphite anodes, together with LixNi0.6Mn0.2Co0.2O2 cathodes, were analysed in small pouch-cells with a capacity of around 1 Ah. For comparison, custom-made reference cells with the average properties of two-layered anodes were tested. Ten cells of each type were examined in total. Each cell pair, consisting of one double-layer and one single-layer (reference) cell, underwent the same test procedure. Besides regular charge and discharge cycles, electrochemical impedance spectroscopy, incremental capacity analysis, differential voltage analysis and current-pulse measurement are used to identify the differences in ageing behaviour between the two cell types. The results show similar behaviour and properties at beginning-of-life, but an astonishing improvement in capacity retention for the double-layer cells regardless of the cycling conditions. Additionally, the lifetime of the single-layer cells was strongly influenced by the cycling conditions, and the double-layer cells showed less difference in ageing behaviour.Item Open Access Optimization of disassembly strategies for electric vehicle batteries(2021) Baazouzi, Sabri; Rist, Felix Paul; Weeber, Max; Birke, Kai PeterVarious 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.Item Open Access The influence of micro-structured anode current collectors in combination with highly concentrated electrolyte on the Coulombic efficiency of in-situ deposited Li-metal electrodes with different counter electrodes(2020) Heim, Fabian; Kreher, Tina; Birke, Kai PeterThis paper compares and combines two common methods to improve the cycle performance of lithium metal (Li) electrodes. One technique is to establish a micro-structured current collector by chemical separation of a copper/zinc alloy. Furthermore, the use of a highly concentrated ether-based electrolyte is applied as a second approach for improving the cycling behavior. The influence of the two measures compared with a planar current collector and a 1 M concentrated carbonate-based electrolyte, as well as the combination of the methods, are investigated in test cells both with Li and lithium nickel cobalt manganese oxide (NCM) as counter electrodes. In all cases Li is in-situ plated onto the micro-structured current collectors respectively a planar copper foil without presence of any excess Li before first deposition. In experiments with Li counter electrodes, the effect of a structured current collector is not visible whereas the influence of the electrolyte can be observed. With NCM counter electrodes and carbonate-based electrolyte structured current collectors can improve Coulombic efficiency. The confirmation of this outcome in experiments with highly concentrated ether-based electrolyte is challenging due to high deviations. However, these results indicate, that improvements in Coulombic efficiency achieved by structuring the current collector’s surface and using ether-based electrolyte do not necessarily add up, if both methods are combined in one cell.Item Open Access Multi-method model for the investigation of disassembly scenarios for electric vehicle batteries(2023) Baazouzi, Sabri; Grimm, Julian; Birke, Kai PeterDisassembly 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.Item Open Access Artificial feature extraction for estimating state-of-temperature in lithium-ion-cells using various long short-term memory architectures(2022) Kopp, Mike; Ströbel, Marco; Fill, Alexander; Pross-Brakhage, Julia; Birke, Kai PeterThe temperature in each cell of a battery system should be monitored to correctly track aging behavior and ensure safety requirements. To eliminate the need for additional hardware components, a software based prediction model is needed to track the temperature behavior. This study looks at machine learning algorithms that learn physical behavior of non-linear systems based on sample data. Here, it is shown how to improve the prediction accuracy using a new method called “artificial feature extraction” compared to classical time series approaches. We show its effectiveness on tracking the temperature behavior of a Li-ion cell with limited training data at one defined ambient temperature. A custom measuring system was created capable of tracking the cell temperature, by installing a temperature sensor into the cell wrap instead of attaching it to the cell housing. Additionally, a custom early stopping algorithm was developed to eliminate the need for further hyperparameters. This study manifests that artificially training sub models that extract features with high accuracy aids models in predicting more complex physical behavior. On average, the prediction accuracy has been improved by ΔTcell=0.01 °C for the training data and by ΔTcell=0.007 °C for the validation data compared to the base model. In the field of electrical energy storage systems, this could reduce costs, increase safety and improve knowledge about the aging progress in an individual cell to sort out for second life applications.Item 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 PeterGiven 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.Item Open Access Novel approach to ensure safe power supply for safety-relevant consumers(2022) Braun, Lars; Le, Minh; Motz, Jürgen; Birke, Kai PeterThe 12 V powernet in vehicles must fulfill certain safety requirements due to the safety demand of consumers. A potential risk is undervoltage for a safety-relevant consumer, which leads to its fault. Therefore, a novel approach is presented in this study, which can predict the minimum terminal voltage for consumers. This consists of diagnostics of the wiring harness and of the lead-acid battery as well as predefined consumer currents. Using simulation, first the beginning of a drive cycle is simulated to determine the state of the powernet, and afterwards a critical driving maneuver is simulated to validate the predicted minimum terminal voltage. It demonstrates that the novel approach is able to predict a fault due to undervoltage. In addition to fulfilling safety requirements, the novel approach could be used to achieve additional availability and miniaturization of powernet components compared to the state of the art.Item Open Access Towards high efficiency CO2 utilization by glow discharge plasma(2021) Renninger, Stephan; Rößner, Paul; Stein, Jan; Lambarth, Maike; Birke, Kai PeterPlasma technology reaches rapidly increasing efficiency in catalytic applications. One such application is the splitting reaction of CO2 to oxygen and carbon monoxide. This reaction could be a cornerstone of power-to-X processes that utilize electricity to produce value-added compounds such as chemicals and fuels. However, it poses problems in practice due to its highly endothermal nature and challenging selectivity. In this communication a glow discharge plasma reactor is presented that achieves high energy efficiency in the CO2 splitting reaction. To achieve this, a magnetic field is used to increase the discharge volume. Combined with laminar gas flow, this leads to even energy distribution in the working gas. Thus, the reactor achieves very high energy efficiency of up to 45% while also reaching high CO2 conversion efficiency. These results are briefly explained and then compared to other plasma technologies. Lastly, cutting edge energy efficiencies of competing technologies such as CO2 electrolysis are discussed in comparison.Item Open Access A novel long short-term memory approach for online state-of-health identification in lithium-ion battery cells(2024) Kopp, Mike; Fill, Alexander; Ströbel, Marco; Birke, Kai PeterRevolutionary and cost-effective state estimation techniques are crucial for advancing lithium-ion battery technology, especially in mobile applications. Accurate prediction of battery state-of-health (SoH) enhances state-of-charge estimation while providing valuable insights into performance, second-life utility, and safety. While recent machine learning developments show promise in SoH estimation, this paper addresses two challenges. First, many existing approaches depend on predefined charge/discharge cycles with constant current/constant voltage profiles, which limits their suitability for real-world scenarios. Second, pure time series forecasting methods require prior knowledge of the battery’s lifespan in order to formulate predictions within the time series. Our novel hybrid approach overcomes these limitations by classifying the current aging state of the cell rather than tracking the SoH. This is accomplished by analyzing current pulses filtered from authentic drive cycles. Our innovative solution employs a Long Short-Term Memory-based neural network for SoH prediction based on residual capacity, making it well suited for online electric vehicle applications. By overcoming these challenges, our hybrid approach emerges as a reliable alternative for precise SoH estimation in electric vehicle batteries, marking a significant advancement in machine learning-based SoH estimation.