Optimized alternating-flow direct refrigerant cooling for lithium-ion batteries: Mitigating localized dry-out under extreme operational boundaries

Thermal management of Lithium-ion (Li-ion) batteries under extreme operational boundaries remains a critical challenge for high-power electric vehicles. While Direct Refrigerant Cooling (DRC) offers superior latent heat absorption, standard unidirectional Static-Flow (S-Flow) architectures frequently suffer from severe downstream dry-out and condenser saturation under dynamic thermal loads. Although recent advancements have introduced flow-reversal mitigation, their validation has been strictly confined to nominal operating envelopes, leaving the critical thermodynamic failure mechanisms under real-world extremes entirely unquantified. To bridge this critical knowledge gap, this study develops a robust transient one-dimensional numerical framework to evaluate an Integrated Thermal Management System (ITMS) featuring an intelligent Optimized Alternating-Flow (Opt-A-Flow) logic under previously unmapped extreme boundary conditions. Under a severe 50.0 °C ambient soak, the thermal performance of the S-Flow architecture substantially deteriorates; the convective heat transfer coefficient deteriorates by 57.6%, and the system Coefficient of Performance (COP) reduces to an unsustainable 0.94. Similarly, under a 5.0 °C low-ambient 4C fast-charging protocol, unmitigated internal ohmic heating overpowers the unidirectional flow, inducing a unsafe maximum temperature difference ( Δ T ) of 18.5 °C. The targeted Opt-A-Flow mitigation mechanism successfully resolves these multi-physics failures. By dynamically injecting two-phase refrigerant to break condenser saturation limits, the optimized logic strictly bounds the maximum battery temperature ( T max ) to 34.8 °C and tightly compresses the spatial Δ T to a highly uniform 3.8 °C under the 50.0 °C boundary. Furthermore, by preventing the compressor from stalling, the architecture achieves a fully recovered terminal COP of 1.65, demonstrating the energetic and thermal advantages of the Opt-A-Flow framework under extreme operational envelopes.