Evaluating Hybridization Potential Using Load Profile Metrics: A Rule-of-Thumb Approach

Hybrid battery systems, which combine high-energy and high-power cells, offer a promising solution for electrifying heavy-duty applications by balancing energy density, power capability, and cost. This paper presents a generic methodology for cost-optimal sizing of hybrid battery energy storage systems using a Mixed Integer Nonlinear Programming framework. A large-scale simulation study involving 10,000 load profiles replicating applications varying from road transportation to sea-going vessels is used to derive practical “rules of thumb” that guide when hybridization is beneficial, offering significant reductions in cost, weight, and volume compared to monotype battery configurations. Sensitivity analyses further validate the robustness of the method across varying cell costs and C-rates, making it applicable to a wide range of battery chemistries and use cases.