Used EV batteries can be utilized as 2nd-life energy storage systems for stationary applications. From an economic point of view, disassembly, characterization, and sorting of modules and reassembly should be avoided, and EV batteries are integrated unaltered into the storage system. However, aged batteries vary in power- and energy content and electrical characteristic (e.g., different states-of-health), which would cause unequal and uncontrollable power-sharing if connected in parallel. Within the research project UnABESA, a flexible architecture was proposed and successfully developed and validated to control the power of each battery pack in a multi-pack system individually. Fig. 1 shows the UnABESA architecture with three energy storage strings, as it was set up for the prototype system.
The UnABESA architecture introduces additional degrees of freedom, as the power for the battery packs can be chosen freely as long as the sum equals the required total system power. This, in turn, requires power flow control (PFC) algorithms for a successful operation.
OPFC can be optimized with respect to different, potentially concurring, target indicators. The Hyper Space Exploration (HSE) was applied as a process and toolbox for evaluation and multi-criteria optimization of PFC algorithms concerning the target indicators performance, efficiency, and battery lifetime. Different state-of-the-art and a novel PFC algorithm were compared for a large set of use case variations of two applications, namely frequency containment reserve and peak shaving. Fig. 2 shows exemplary results for the novel OPFC algorithm for different parameterization of the OPFC (left side) and the results of the HSE analysis for a large set of use case and design variations and OPFC parameters.