Lithium-Ion (Li-ion) batteries are widely used in electric and hybrid electric vehicles for energy storage. However, a Li-ion battery’s lifespan and performance is reduced if it’s overheated during operation. To maintain the battery’s temperature below established thresholds, the heat generated during charge/discharge must be removed and this requires an effective cooling system. This paper introduces a battery thermal management system (BTMS) based on a dynamic thermal-electric model of a cylindrical battery. The heat generation rate estimated by this model helps to actively control the air mass flow rate. A nonlinear back-stepping controller and a linear optimal controller are developed to identify the ideal cooling air temperature which stabilizes the battery core temperature. The simulation of two different operating scenarios and three control strategies has been conducted. Simulation results indicate that the proposed controllers can stabilize the battery core temperature with peak tracking errors smaller than 2.4°C by regulating the cooling air temperature and mass flow rate. Overall the controllers developed for the battery thermal management system show improvements in both temperature tracking and cooling system power conservation, in comparison to the classical controller. The next step in this study is to integrate these elements into a holistic cooling configuration with AC system compressor control to minimize the cooling power consumption.
- Dynamic Systems and Control Division
Cooling Air Temperature and Mass Flow Rate Control for Hybrid Electric Vehicle Battery Thermal Management
Tao, X(, & Wagner, J. "Cooling Air Temperature and Mass Flow Rate Control for Hybrid Electric Vehicle Battery Thermal Management." Proceedings of the ASME 2014 Dynamic Systems and Control Conference. Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. San Antonio, Texas, USA. October 22–24, 2014. V002T34A002. ASME. https://doi.org/10.1115/DSCC2014-6001
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