The thermal safety and longevity of lithium-ion batteries are critically constrained by excessive temperature rise and spatial thermal non-uniformity, particularly during high-rate discharges. Most existing numerical investigations rely on simplified heat generation models that fail to capture the spatiotemporal heterogeneity of electrochemical heat sources, leading to compromised predictive accuracy. To address this deficiency, this study develops a comprehensive three-dimensional electrochemical–thermal coupled framework, integrating the Newman pseudo-two-dimensional (P2D) electrochemical model with conjugate heat transfer and laminar flow dynamics. The predictive robustness of this framework is rigorously validated against experimental data across multiple discharge rates (3 C and 5 C). The validated model is then deployed to evaluate a water-cooled microchannel cold plate designed for prismatic LiMn2O4/graphite cells under a demanding 5 C discharge. A systematic parametric investigation is conducted to quantify the effects of ambient temperature (293–343 K), microchannel number (2–6), and coolant inlet velocity (0.1–0.6 m/s) on the maximum battery temperature (Tmax) and temperature difference (ΔT). Results demonstrate that the proposed system exhibits exceptional environmental robustness: over a 50 K ambient temperature span, Tmax increases by merely 2.0 K, remaining safely below the 323 K industry limit. Densifying the channel count from 2 to 6 further reduces Tmax by 1.55 K and narrows ΔT to 4.25 K, successfully satisfying the strict 5 K temperature uniformity standard. Furthermore, the thermal benefit of elevating inlet velocity exhibits a pronounced diminishing-return trend governed by the asymptotic reduction in bulk coolant temperature rise, dictating a critical trade-off against the quadratically escalating pumping power. Ultimately, these findings provide robust theoretical guidelines for the rational design of safe and energy-efficient battery thermal management systems.
Building similarity graph...
Analyzing shared references across papers
Loading...
Chuang Liu
Deng-Wei Yang
Cheng-Peng Ma
World Electric Vehicle Journal
Wuhan University
Hunan University of Technology
Building similarity graph...
Analyzing shared references across papers
Loading...
Liu et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69d895be6c1944d70ce06d47 — DOI: https://doi.org/10.3390/wevj17040196