Optimization on control strategy for CO2-based dual-cooling thermal management system in electric vehicles

The thermal management of electric vehicles (EVs) faces a critical challenge in simultaneously maintaining cabin comfort and ensuring battery safety. To tackle this issue, an adaptive control strategy for a CO2 transcritical dual-cooling system is proposed, underpinned by a multiphysics battery model validated experimentally. The model integrates electrochemical, thermal, and aging dynamics, predicting voltage and temperature with high accuracy (maximum errors of 4.2 % and 6.5 %, respectively). Systematic optimization identified a coolant flow rate of 25 L/min to minimize battery temperature difference (ΔT ≤ 0.5 °C) and a 15 % expansion valve opening to balance Coefficient of Performance (COP) with cooling capacity. Dynamic vapor quality regulation at the chiller outlet enhanced system COP by 46.5 % (from 1.29 to 1.89) and reduced optimal discharge pressure by 2.1 %. Compared to a fixed-valve strategy, the variable approach shortened battery cooling time by 38.7 % (from 595 s to 429 s) and increased COP by 3.7 %. The dual-cooling mode reduced battery aging by 10 % but raised energy consumption by 46.4 % versus cabin-only cooling, slightly compromising thermal comfort (Predicted Mean Vote (PMV) = 1.15 vs. target 0.5) and prolonging cabin temperature stabilization by 225 s. At 38 °C ambient temperature, dual-cooling cut driving range by 35 %, with cabin thermal load contributing 77.2 % to the total loss. Under high-speed driving, battery cooling dominated efficiency loss (37.4 %). These findings underscore the essential role of adaptive control in balancing battery durability, cabin comfort, and energy efficiency in next-generation EV thermal systems.