Sungjea Park

Extremely fast charging (XFC) of high-energy-density lithium-ion batteries is fundamentally constrained by the intrinsic waveform characteristics of conventional variable-current profiles (VCPs), limiting further reductions in charging time while maintaining electro-thermal safety. In the present study, a computational electro-thermally constrained optimization framework is developed in which a square-wave VCP is reformulated using a finite Fourier series to improve XFC performance. An electro-thermal numerical model is employed to evaluate the charging behavior of the resulting Fourier series-based square wave (F-square wave) with the number of harmonic terms ranging from N = 1 to 100. The optimal charging performance is achieved at N = 10, reducing the charging time from 940 to 878 s (6.6%) and satisfying the U.S. DOE 15-min XFC target (900 s). The performance enhancement originates from two complementary effects: the Gibbs overshoot, which locally increases the charging current near the allowable current limit, and the finite-series approximation, which smooths the current transition before and after the waveform discontinuity. Rather than treating the Gibbs overshoot associated with Fourier approximation as an undesirable numerical artifact, this study demonstrates that it can be computationally exploited as a controlled perturbation to accelerate charging while maintaining electro-thermal safety. Although the Fourier perturbation slightly increases the terminal voltage risk near the waveform discontinuity, all electrical and thermal constraints remain satisfied throughout the charging process. These findings demonstrate that finite Fourier perturbation provides an effective computational design strategy for overcoming the intrinsic waveform limitations of discontinuous charging profiles and advancing electro-thermally constrained XFC of lithium-ion batteries.

Conventional physics‐based fuel cell models have faced limitation in explaining the through‐plane liquid water distributions observed by state‐of‐the‐art imaging techniques. To elucidate these experimental findings, we advance a temperature‐dependent phase separation model (TDPSM) framework by introducing separate liquid transport equations for each porous constituent. The proposed theoretical framework incorporates relative hydrophobicity at overlapping interfaces and employs a volume‐averaging scheme to reveal the physics underlying optical liquid visualization. A novel validation approach is proposed, enabling simultaneous prediction of through‐plane liquid profiles and conventional polarization curves with strong agreement to experimental data. Extensive numerical simulations comparing water transport scenarios with and without a microporous layer (MPL) integrate previously fragmented experimental findings on the MPL’s dual role. The study also presents water management strategies for two operating regimes: (i) low‐temperature high‐humidity (LTHH), where liquid flooding dominates, and (ii) high‐temperature low‐humidity (HTLH), where membrane dehydration presents an emerging industrial challenge. Under LTHH conditions, a hydrophobicity order of catalyst layer (CL) > MPL > gas diffusion layer (GDL) establishes an interfacial liquid pump that enables effective liquid removal. In contrast, under HTLH operation, a more hydrophobic MPL relative to the CL (MPL > CL) forms an interfacial barrier that sustains reliable membrane water retention. Overall, this theoretical framework redefines water management as a synergistic outcome of relative hydrophobic characteristics between adjacent porous layers, rather than as properties of isolated components.