Towards Real-Time Simulation of Flow Battery Models
For example, to meet power or voltage requirements, many redox flow batteries are stacked in series, parallel, or a combination of both. This can cause each cell to operate at different conditions (e.g., concentration, temperature, and potential). The battery energy storage system (BESS) responsible for managing the operation of the entire system will benefit from faster cell models that can predict the performance in real time to adjust for non-uniform conditions.
In the past, we have shown how mathematical reformulation techniques can be used to reduce the computational time for simulating Lithium-ion batteries without sacrificing accuracy(5,6). These algorithms enable direct adaption of physics based models in the battery management system (BMS). A physics based BMS provides more functionality (e.g., predicts life) and enables a smaller footprint by allowing for aggressive but safe operating protocols.
In this talk, we show how redox flow battery models can be reformulated for real-time analysis and optimization purposes. Both 1D and 2D models reported in the literature will be analyzed and reformulated(3,4,7-12). In our opinion, real-time physics based predictive models can play a critical role in BESS.
Electrochemical storage in redox flow batteries requires a flow of electrolyte, which is stored in tanks independent of the electrodes. The associated flow coupled diffusion and electrochemical reactions require a much different approach to modeling compared to lithium-ion batteries; however, spectral methods are general enough to be useful for reformulation of redox flow systems, though the form of the trial functions used may change.
The authors acknowledge financial support by the National Science Foundation under grant numbers CBET-0828002, and CBET-1008692, and funds from Sun Edison.
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