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 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 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 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 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 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 PeterBattery 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.Item Open Access Cycle tests on the influence of different charging currents : a case study on different commercial, cylindrical lithium ion cells(2023) Parschau, Anke; Degler, David; Fill, Alexander; Birke, Kai Peter; Allmendinger, FrankOn the way to a Precise Battery, the generation of measurement results and findings based on them play an important role. Although cycle life tests are time-consuming and expensive, they can provide support and important information. Especially in the current topic of accelerating the charging process, it is important to know how different charging currents affect different cell types. The CC CV charging method is still the most common, widely used method. Therefore, long-term cycle tests are carried out in this work in order to clarify the influence of different charging currents, as recommended by the cell manufacturers. Common high-energy and high-power cylindrical lithium ion cells are investigated and compared. In addition to the influence of the charging protocol on the aging, charging time and heating, the effects on the dispersion of the cells as well as the effects on the constant current and the constant voltage part of the charging process are considered. From the results it can be seen how different the investigated cells behave in response to increased charging currents. Even supposedly similar cells show significant differences in aging behavior.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.Item Open Access How cell design affects the aging behavior : comparing electrode-individual aging processes of high-energy and high-power lithium-ion batteries using high precision coulometry(2023) Jagfeld, Sebastian Michael Peter; Birke, Kai Peter; Fill, Alexander; Keil, PeterThe aging behavior of lithium-ion batteries is crucial for the development of electric vehicles and many other battery-powered devices. The cells can be generally classified into two types: high-energy (HE) and high-power (HP) cells. The cell type used depends on the field of application. As these cells differ in their electrical behavior, this work investigates whether both cell types also show different aging behavior. More precisely, the occurring capacity loss and internal side reactions are analyzed via the charge throughput. For comparison, aging tests are carried out with a high-precision battery tester, allowing the application of High Precision Coulometry (HPC). This enables early detection of aging effects and also allows us to break down the capacity loss into electrode-individual processes. A total of two sub-studies are performed: (1) a cyclic study focusing on lithium plating; and (2) an accelerated calendar aging study. It is found that HE cells exhibit stronger cyclic aging effects (lithium plating) and HP cells exhibit stronger calendar aging effects. The higher lithium plating can be explained by the higher diffusion resistance of the lithium ions within the electrodes of HE Cell. The higher calendar aging fits to the larger electrode surfaces of the HP cell. These results give deep insights into the proceeding aging in a novel way and are interesting for the selection of the appropriate cell type in the context of battery development. In a next step, the measured capacity losses could also be used for a simple parameterization of battery aging models.