Framework for integrated plant and control optimization of electro-thermal systems: An energy storage system case study

Advances in power density, energy storage technology, and thermal management are crucial to increased electrification of vehicles, especially those with high ramp rate loads. To meet these demands, a systems-minded design approach is needed, capable of simultaneously optimizing multi-domain system dynamics including control. This work provides a framework for simultaneous plant and control design leveraging a graph-based modeling tool for multi-domain dynamics. The graph-based modeling tool captures system-level dynamics spanning multiple energy domains. This tool facilitates control design by providing a state-space-like set of dynamic equations that describe the system???s behavior and are computationally inexpensive to simulate. Modular, scalable graph-based models enable design optimization for both plant and controller design. To demonstrate an application of the framework, a hybrid electro-thermal energy storage system is described to provide a power-dense energy storage solution for classes of future electrified vehicles with high ramp rate power demands. Heuristic controllers protect energy storage elements while meeting reference signal commands. Sizing and control parameters of the energy storage system are optimized using the graph-based optimization framework. Simultaneous optimization of both components and control parameters demonstrate significant reductions in size while retaining a high level of performance, leading to improvements in power density.

Automated summary

This study provides a framework for simultaneous plant and control design using a graph-based modeling tool for multi-domain dynamics. Optimizing the size and control parameters of the energy storage system can significantly improve power density.