Coolant Flow Rate is Critical
In EVs, power for operating the TMS comes from energy extracted from the battery. Reducing the energy requirement for the TMS reduces its drain on the battery, therefore optimizing coolant flow rate is essential. The STAR-CCM+ model revealed that more heat is stored in the battery pack in lower coolant flow velocity conditions, indicating in turn that at lower flow velocities, less heat is transferred into the coolant. Temperature rise less than doubled when flow velocity was halved.
In most battery packs, maximum temperature variation is limited to 3 K along the direction of the flow stream. The experimental model easily met the 3 K limit, and could effectively cool the pack even at very low flow velocities. It was found that temperature rise in the battery pack using the experimental TMS is on the same order as graphene-augmented, phase change material (PCM)-based thermal management systems reported in research literature. Although such PCM-based TMSs are also compact, this new TMS does not require novel materials such as graphene, and can therefore be produced at lower cost.
Overcoming Contact Resistance
Contact resistance at the solid-state interfaces has proven a major source of problems in large battery pack designs. In this TMS model, thermal contact resistance at the conduction element channel and cell conduction element interfaces were found to be the largest hindrance, resulting in temperature discontinuities, as shown in Figure 4. However, it was found that contact resistance could be reduced by use of thermal interface material at the solid-solid interfaces, which greatly improved thermal performance.
Because large Li-ion battery packs must operate at high-discharge-rate conditions in EVs and HEVs, heat generation becomes a critical factor to address. Even at high discharge rates and low-flow-velocity conditions, the experimental TMS kept maximum temperature rise within the acceptable industry range of 7 K, yielding excellent thermal performance. The TMS was found to cool the battery pack effectively even at low coolant flow rates.
Using the CFD-based TMS functional model created with STAR-CCM+ and Battery Design Studio, a close agreement between simulations and experimental measurements was achieved, validating the model against experiment with greater than 90 percent accuracy. Representative battery packs constructed using the symmetry of the total pack were successfully simulated, together with the TMS, to compensate for the high computational cost.
Methodologies determined through this research can be implemented in onboard battery management systems to reduce the number of sensors, reduce temperature non-uniformity, and simplify control systems. The ability of this novel compact TMS to work effectively and safely under stringent conditions makes it a suitable candidate for large Li-ion battery packs used in EVs.
This article was written by Suman Basu, Next Generation Research, Samsung R&D Institute India, Bangalore. For more information on the Siemens PLM Software products used in this application, visit here .