Conceptual Design of Solid-State Li-Battery for Urban Air Mobility

The negative impact of internal combustion engines on the environment is a major concern in metropolitan areas due to the continued rapid growth and high overall level in the number of vehicles, population, and traffic congestion. Electric vertical take-off and landing (eVTOL) aircraft promises a new era for urban regional transportation and air mobility to address the challenges mentioned above. Nonetheless, providing electrical energy storage systems, like batteries, is one of the key issues with such aircraft. Here, the non-flammable technology of all-solid-state Li batteries with high theoretical gravimetric energy is an attractive option. Modelling allows for a knowledge-driven assessment of the potential of this technology. We here used a combination of a pseudo-2-dimensional cell model with a microstructure surrogate model approach to acquire a better understanding of the effect of the cathode microstructure on the internal process limitations. This model is incorporated into a global optimisation algorithm to predict optimum battery size with respect to the dynamic load demand of eVTOL. When carbon black and active materials are premixed, the battery performs better than when solid electrolyte and active materials are premixed, particularly for low amounts of carbon black in the cathode combination, i.e., 5%. Further, results indicate that future electrification of transportation powertrains would necessitate optimising the composition and distribution of electrode components to fulfil the high demands for power and energy density. By enhancing transport through the microstructure and improving the material\u27s intrinsic conductivity, it is possible to significantly increase the effective diffusivity and conductivity of ASSB, and hence the mission range

Unveiling the interaction of reactions and phase transition during thermal abuse of Li-ion batteries

Safety considerations have always accompanied the development of new battery chemistries; this holds especially for the Li-ion battery with its highly reactive components. An overall assessment and decrease of risks of catastrophic failures such as during thermal runaway, requires an in-depth and quantitative understanding of the ongoing processes and their interaction. This can be provided by predictive mathematical models. Thus, we developed a thermal runaway model that focuses on rigorous modelling of thermodynamic properties and reactions of each component within a Li-ion battery. Moreover, the presented model considers vapour–liquid equilibria of a binary solvent mixture for the first time. Simulations show a fragile equilibrium between endothermic and exothermic reactions, such as LiPF$_{6}$ and LEDC decomposition, in the early phases of self-heating. Further, an autocatalytic cycle involving the production of HF and the SEI component Li$_{2}$CO$_{3}$ could be revealed. Additionally, the unpredictability of the thermal runaway could be directly correlated to availability of LEDC or contaminants such as water. Also, solvent boiling can have a significant influence on the self-heating phase of a Li-ion battery, due to its endothermic nature. Further analysis revealed that the rising pressure, stemming from gassing reactions, can suppress solvent boiling until the thermal runaway occurs

Comparison of methodologies to estimate state-of-health of commercial Li-ion cells from electrochemical frequency response data

Various impedance-based and nonlinear frequency response-based methods for determining the state-of-health (SOH) of commercial lithium-ion cells are evaluated. Frequency response-based measurements provide a spectral representation of dynamics of underlying physicochemical processes in the cell, giving evidence about its internal physical state. The investigated methods can be carried out more rapidly than controlled full discharge and thus constitute prospectively more efficient measurement procedures to determine the SOH of aged lithium-ion cells. We systematically investigate direct use of electrochemical impedance spectroscopy (EIS) data, equivalent circuit fits to EIS, distribution of relaxation times analysis on EIS, and nonlinear frequency response analysis. SOH prediction models are developed by correlating key parameters of each method with conventional capacity measurement (i.e., current integration). The practical feasibility, reliability and uncertainty of each of the established SOH models are considered: all models show average RMS error in the range 0.75%–1.5% SOH units, attributable principally to cell-to-cell variation. Methods based on processed data (equivalent circuit, distribution of relaxation times) are more experimentally and numerically demanding but show lower average uncertainties and may offer more flexibility for future application

Disorders of Consciousness

Disorders of Consciousness are a big challenge for the entire process of rehabilitation: assessment, diagnosis, pharmacological, and rehabilitation programs, including conventional treatments and the use of new technologies