Model-Based Energy Consumption Optimization of a Twin Battery Concept Combining Liquid and Solid-State Electrolyte Cells

The majority of powertrain types considered important contributors to achieving the CO₂ targets in the transportation sector employ a battery as an energy storage device. The need for batteries is hence expected to grow drastically with increasing market share of CO₂-optimized powertrain concepts. The resulting huge pressure on the development of future electrochemical energy storage systems necessitates the application of advanced methodologies enabling a fast and cost-efficient concept definition and optimization process. This paper presents a model-based methodology for the optimization of BEV thermal management concept layouts and operation strategies targeting minimized energy consumption. Starting at the vehicle level, the proposed methodology combines appropriate representations of all primary powertrain components with 1D cooling and refrigerant circuit models and focuses on their interaction with the battery chemistry. To this end, the battery cells are thermally modeled in 3D, complemented by a P2D electro-physicochemical approach. Thanks to online coupling the cell representation with the 1D powertrain and thermal management models, heat transfer and cell temperatures can be calculated as a function of the boundary conditions at each simulation step. The model-based methodology is subsequently employed for the optimization of a novel Twin Battery concept combining sodium-ion and solid-state lithium-ion battery cells. The approach enables the cost-efficient adaption of both thermal management layout and operation strategy, resulting in reduced energy input and shorter time required for reaching operation temperature of the solid-state cells. Ultimately, a minimization of the overall powertrain energy consumption can be achieved while ensuring chemistry-specific optimal temperature levels and hence reduced battery aging.