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 Modeling and experimental investigation of the interaction between pressure-dependent aging and pressure development due to the aging of lithium-ion cells(2023) Avdyli, Arber; Fill, Alexander; Birke, Kai PeterIn order to meet the increasing demands of the battery in terms of range, safety and performance, it is necessary to ensure optimal operation conditions of a lithium-ion cell. In this thesis, the influence of mechanical boundary conditions on the cell is investigated theoretically and experimentally. First, fundamental equations are derived that lead to coupled models that can be parameterized based on specific cell measurements and predict the pressure evolution due to capacity aging and vice versa. The model is used to derive optimal operating points of the cell, which can be considered in the module design.Item Open Access Impedance based temperature estimation of lithium ion cells using artificial neural networks(2021) Ströbel, Marco; Pross-Brakhage, Julia; Kopp, Mike; Birke, Kai PeterItem Open Access Pressure characteristics and chemical potentials of constrained LiFePO4/C6 cells(2018) Singer, Jan Patrick; Kropp, Timo; Kuehnemund, Martin; Birke, Kai PeterConstraining lithium-ion cells increases the cyclic lifetime. However, depending on an expected volume expansion during charge and discharge cycling, defining the optimal constraining pressure range is not straightforward. In this study, we investigate a lithium iron phosphate/graphite pouch cell at four initial constraining pressure levels. As a function of C-Rate, the thermodynamic principle of the non-monotonic pressure curve during full charge and discharge cycles is evaluated. Using the rubber balloon model to calculate the chemical potential of lithium iron phosphate and discussing the relationship between the chemical potential and pressure, we illustrate the pressure curve qualitatively. By applying differential pressure analysis, we evaluate the resulting pressure curves of a single graphite stage. Approaching a fundamental understanding of reduced cycling lifetime of full cells with unknown material composition, we allocate the stages and stage transitions of graphite as well as the phase transition of lithium iron phosphate. Local extreme values in the differential pressure analysis indicate phase and stage transitions. These values can identify critical operating conditions that should be considered for defining the optimum initial constraining pressure range.Item Open Access Non-uniform circumferential expansion of cylindrical Li-ion cells - the potato effect(2021) Hemmerling, Jessica; Guhathakurta, Jajnabalkya; Dettinger, Falk; Fill, Alexander; Birke, Kai PeterThis paper presents the non-uniform change in cell thickness of cylindrical Lithium (Li)-ion cells due to the change of State of Charge (SoC). Using optical measurement methods, with the aid of a laser light band micrometer, the expansion and contraction are determined over a complete charge and discharge cycle. The cell is rotated around its own axis by an angle of α=10° in each step, so that the different positions can be compared with each other over the circumference. The experimental data show that, contrary to the assumption based on the physical properties of electrode growth due to lithium intercalation in the graphite, the cell does not expand uniformly. Depending on the position and orientation of the cell coil, there are different zones of expansion and contraction. In order to confirm the non-uniform expansion around the circumference of the cell in 3D, X-ray computed tomography (CT) scans of the cells are performed at low and at high SoC. Comparison of the high resolution 3D reconstructed volumes clearly visualizes a sinusoidal pattern for non-uniform expansion. From the 3D volume, it can be confirmed that the thickness variation does not vary significantly over the height of the battery cell due to the observed mechanisms. However, a slight decrease in the volume change towards the poles of the battery cells due to the higher stiffness can be monitored.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 A high frequency alternating current heater using the advantages of a damped oscillation circuit for low voltage Li-ion batteries(2024) Oehl, Joachim; Gleiter, Andreas; Manka, Daniel; Fill, Alexander; Birke, Kai PeterIn many cases, batteries used in light e-mobility vehicles such as e-bikes and e-scooters do not have an active thermal management system. This poses a challenge when these batteries are stored in sub-zero temperatures and need to be charged. In such cases, it becomes necessary to move the batteries to a warmer location and allow them to acclimatize before charging. However, this is not always feasible, especially for batteries installed permanently in vehicles. In this work, we present an internal high-frequency AC heater for a 48 V battery, which is used for light electric vehicles of EU vehicle classes L1e and L3e-A1 for a power supply of up to 11 kW. We have taken advantage of the features of a damped oscillating circuit to improve the performance of the heater. Additionally, only a small inductor was added to the main current path through a cable with three windings. Furthermore, as the power electronics of the heater is part of the battery main switch, fewer additional parts inside the battery are required and therefore a cost and space reduction compared to other heaters is possible. For the chosen setup we reached a heating rate of up to 2.13 K min -1 and it was possible to raise the battery temperature from -10 °C to 10 °C using only 3.1% of its own usable capacity.Item Open Access Comparison of aqueous- and non-aqueous-based binder polymers and the mixing ratios for Zn//MnO2 batteries with mildly acidic aqueous electrolytes(2021) Fitz, Oliver; Ingenhoven, Stefan; Bischoff, Christian; Gentischer, Harald; Birke, Kai Peter; Saracsan, Dragos; Biro, DanielConsidering the literature for aqueous rechargeable Zn//MnO2 batteries with acidic electrolytes using the doctor blade coating of the active material (AM), carbon black (CB), and binder polymer (BP) for the positive electrode fabrication, different binder types with (non-)aqueous solvents were introduced so far. Furthermore, in most of the cases, relatively high passive material (CB+BP) shares ~30 wt% were applied. The first part of this work focuses on different selected BPs: polyacrylonitrile (PAN), carboxymethyl cellulose (CMC), styrene butadiene rubber (SBR), cellulose acetate (CA), and nitrile butadiene rubber (NBR). They were used together with (non-)aqueous solvents: DI-water, methyl ethyl ketone (MEK), and dimethyl sulfoxide (DMSO). By performing mechanical, electrochemical and optical characterizations, a better overall performance of the BPs using aqueous solvents was found in aqueous 2 M ZnSO4 + 0.1 M MnSO4 electrolyte (i.e., BP LA133: 150 mAh·g-1 and 189 mWh·g-1 @ 160 mA·g-1). The second part focuses on the mixing ratio of the electrode components, aiming at the decrease of the commonly used passive material share of ~30 wt% for an industrial-oriented electrode fabrication, while still maintaining the electrochemical performance. Here, the absolute CB share and the CB/BP ratio are found to be important parameters for an application-oriented electrode fabrication (i.e., high energy/power applications).Item 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 PeterAccurate 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.Item Open Access Feasible energy density pushes of Li-metal vs. Li-ion cells(2021) Karabelli, Duygu; Birke, Kai PeterLi-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.