Volume 67

Hybrid Nanofluid Spray Cooling Based Predictive Model Development for Advanced Thermal Management of Next Generation Electric Vehicles High-Power Electronics Muhammad Asim, Farooq Riaz Siddiqui, Sheheryar Khan, Hussain Sallar

Abstract

Electric vehicle (EV) powertrains predominantly rely on compact, high-density SiC/GaN power modules in traction inverters, on-board chargers, and DC-DC converters, where aggressive drive-cycle transients push local heat flux to 500-1000 W/cm2. These EV-specific duty constraints, tight packaging, weight/volume limits, and reliability under vibration, render conventional single-phase coolants inadequate. This study targets the EV high power electronics incorporating hybrid nanofluid spray cooling by developing a semi-analytical predictive framework for the heat-transfer coefficient (HTC) of hybrid nanofluids (HNFs) for high heat flux. The model embeds synergistic thermophysical effects such as effective conductivity, heat capacity, density/velocity ratios) and is validated against benchmark data for Al2O3-CNT, Al2O3-Ag, CNT-Ag, and GNP-Ag at mixing ratios 0.1-0.9 to 0.9-0.1 and fluxes 500 and 1000 W/cm2. The model achieves adjusted R2 = 94.5% (max R2 = 95.4%) and correctly ranks HNF chemistries for EV conditions; notably, CNT-Al2O3 (0.9-0.1) delivers the highest HTC enhancement among tested systems. By mapping HNF composition to HTC under different spray velocities, the model enables rapid coolant down-selection for EV modules to support miniaturization, lower junction temperatures, and efficiency gains. The contribution bridges material-level formulation and system-level EV thermal design, providing a tractable tool for EV thermal engineers to screen next-generation coolants for electrified drivetrains.

Keywords heat transfer coefficient, electronics cooling, semi-analytical model, hybrid nanofluid, electric vehicles, spray cooling