CT Measurements - To Characterize Batteries

摘要

Urban e-mobility is on the rise: Cars as well as bikes, buses and trains are being progressively electrified. Main advantages of this technology are decreasing emissions and noise pollution in the cities. However, the public perception of e-mobility is still negatively influenced by issues such as the low range of electric cars and safety concerns. To raise the interest and the field of application, the lifetime and full exploit of the batteries energy density has to be maximized. The range of the vehicles must be calculated in advance. Therefore, battery models are needed to predict the battery capacity over lifetime. In the literature, different types of battery models are described: on the one hand, there are impedance-based models, which are parameterized by the charge discharge characteristics of the used battery cell.. On the other hand, there are physical-chemical battery models, which use specific physical and chemical battery data as input parameters. These models are differentiate by accuracy and time. This work focus on the physical-chemical models, to generate a better understanding of batteries and their internal reactions. The main advantage of these models is that the model itself is universal just the input parameters have to be adjusted to the used cell. Physical-chemical battery models consist of two parts: the specific cell model and the aging model. For a precise aging forecast, an accurate battery model is needed. The battery mode 1 itself describes the externally measurable electrical behaviour of the cell as result of the current flow on the basis of the underlying internal processes of the battery. These processes such as diffusion and interfacial charge transfer have to be understood in detail and described mathematically. The input parameters for those correlations have to be identified in material analyses on cell level, as for example, the geometric parameters, the conductivity, electrode porosity, diffusion parameters, .. M. Ecker et al 2015 for example published a complete parameter set of one special battery for such a model. However, such methods have several disadvantages: For example, the well known GITT (galvanostatic intermittent titration technique) method is often used for the detection of time constants for diffusion processes. Due to the graphite plateaus, this method is not applicable to graphite anodes. Another example is the electrode porosity and the change in porosity due to the solid electrolyte interface. In many cases, the porosity is measured with the mercury porosimeter which is known for exhibiting side-reactions which metals such as copper and aluminum. Due to known inaccuracies and lengthy procedures in common measurement approaches, new methods are developed and utilized in this work in order to conduct a parameter extraction for a physical-chemical battery model of a commercial electric vehicle. CT measurements are used to investigate the electrodes and get an insight view in the material structure. In other faculties CT measurements are well known. Here, this method is also used to calculate the porosity of the anode. These measurements were performed at cells with different states-of-health. This allows us to correlate the data sets over aging to the operating conditions and thus to identify important aging factors. One main output is a better understanding of the development of the cover layer of the electrode and its influence on cell aging. The SEI growth (solid electrolyte interface) is one known main aging effect of lithium-ion batteries, which has to be understood in detail to develop a good aging formula, which in turn is needed for the modelling. The CT measurement results shown here give new insights in the electrode structures during aging. This approach shows that methods of other disciplines might have a high impact on our field of research, if they are adopted properly.