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Local inhomogeneous electrode utilization in recent lithium-ion batteries tends to increase due to larger sizes and/or higher densication, which poses a challenge for accurate, model-based monitoring. Pseudo-two dimensional (p2D) physicochemical models (PCM) can oer such locality via calculating local potentials and concentrations through the thickness of the electrode stack and are numerically reduced for implementation in a microcontroller in this work. Finite dierence method combined with solid-diusion approximations and orthogonal collocation reformulation are applied to generate three MATLAB-and three microcontroller-suitable C-code p2D-PCMs, which are experimentally validated towards constant current charge/discharge and driving cycle loads on a high-energy NMC-811/SiC-18650 lithium-ion battery. Benchmarking to an equivalent circuit model reveals similar mean cell voltage errors below 20 mV for the driving cycle. Reducing spatial elements reveals errors below 1 % for local (i.e. concentrations/potentials) and global

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One approach to influence the current flow through the battery pack is to implement switching circuits. Two switching elements are necessary for each cell-stage to be bypassed or activated. This allows active load management. Thus the utilisation of the battery pack can be maximised in every situation. Adaptive control algorithms allow several kinds of operating strategies. Furthermore, dynamic output voltage can be generated to serve the best output for the downstream voltage level. A battery pack with an additional connection at its central point allows the generation of sine-shaped output voltages. As consequence of individual load management, different types of batteries or even different kinds of energy storages can be interconnected to built serial hybrid electrical energy storages. This novel approach allows precisely tailored battery packs for each application to enhance performance and energy supply.