Electrochemical models at different scales and varying levels of complexity have been used to study the evolution of the anode surface in lithium metal batteries. This includes continuum, mesoscale (phase-field approaches), and multiscale models. Thermodynamics-based equations have been used to study phase changes in lithium batteries using phase-field approaches. However, grid convergence studies and the effect of additional parameters needed to simulate these models are not well-documented in the literature. In this paper, using a motivating example of a moving boundary model in one- and two-dimensions, we show how one can formulate phase-field models, implement algorithms for the same and analyze the results. An open-access code with no restrictions is provided as well. The article concludes with some thoughts on the computational efficiency of phase-field models for simulating dendritic growth.
Current research involving applying stack pressure to lithium-pouch cells has shown both performance and lifetime benefits. Fixtures are used to mimic this at the cell level and conventionally prescribe a constant displacement onto the cell. This increases stack pressure but also causes pressure to vary. Despite this, applying an initial stack pressure improves cell conductivity, as well as cell lifetime [1, 2]. In this paper, a fixture was designed that applies constant pressure to the cell independent of displacement. Thefixture uses pneumatics to apply a constant stack pressure independent of elastic andplastic swelling. Cells constrained by the constant pressure fixture (CPF) fixture anda conventional fixture (MBPF) were evaluated using a Hybrid Pulse Power Characterization (HPPC) test, to measure internal resistance and maximum deliverable power. Multiple stack pressures were applied to investigate differences in pressure variation and performance between constant pressure and constant displacement, while all tests were additionally compared to control tests with no applied stack pressure. The CPF reduced pressure variation during charging and discharging. revealing the performance effects of maintaining uniform pressure. Applying constant stack pressure reduced the discharge impedance and improved discharged power of the tested cell but did not improve charge performance. Additionally, all constraining methods reported lower internal resistance with maximum current compared to 50% maximum current. Discharge performance benefits from constant pressure could influence pack design to improve vehicle performance.
Real-time battery modelling advancements have quickly become a requirement as the adoption of battery electric vehicles (BEVs) has rapidly increased. In this paper an open-source, improved discrete realisation algorithm, implemented in Julia for creation and simulation of reduced-order, real-time capable physics-based models is presented. This work reduces the Doyle-Fuller-Newman electrochemical model into continuousform transfer functions and introduces a computationally informed discrete realisation algorithm (CI-DRA) to generate the reduced-order models. Further improvements in conventional offline model creation are obtained as well as achieving in-vehicle capable model creation for ARM based computing architectures. Furthermore, a sensitivity analysis on the resultant computational time is completed as well as experimental validation of a worldwide harmonised light vehicle test procedure (WLTP) for a LG Chem. M50 21700 parameterisation. A performance comparison to the conventional Matlab implemented discrete realisation algorithm (DRA) is completed showcasing a mean computational time improvement of 88%. Finally, an ARM based compilation is investigated for in-vehicle model generation and shows a modest performance reduction of 43% when compared to the x86 implementation while still generating accurate models within 5.5 seconds.
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