Authors

J. Radtke, L. Peis, M. Shahafve, A. Arakkal, S. Shetty, Capgemini, Munich; J. Meyer-Schwickerath, W. Zaghloul, STABL Energy GmbH, Munich; N. Bajcinca, B. Manesh, M. Al Khatib, RPTU, Kaiserslautern

Year

2026

Print Info

Production/Publication ÖVK

Summary

Electric vehicles (EVs) provide substantial potential for grid‑supportive services through bidirectional charging (BDL). However, the associated increase in cyclic load accelerates battery degradation, while conventional EV architectures lack mechanisms to actively manage aging at module level. The MultiLOAD project addresses this challenge by integrating a Modular Multilevel Converter (MMC) topology with a state‑of‑health (SOH)‑aware battery management and control strategy. The MMC enables dynamic insertion and bypass of battery modules, allowing flexible allocation of electrical stress and eliminating the need for a conventional on‑board charger.
To enable predictive and degradation‑aware operation, a cell characterization campaign was conducted, including electrical modelling via equivalent‑circuit models (ECM) and aging studies under varying depth‑of‑discharge (DOD), C‑rates, and state‑of‑charge (SOC) conditions. These results provide the basis for analytical parameter functions and semi‑empirical aging models used within a model‑predictive control (MPC) framework.
The proposed two‑layer MPC allocates discrete load‑factor levels to individual modules, prioritizing healthier modules while protecting aged ones. The control strategy incorporates experimentally derived battery‑friendly cycling patterns and is validated through a hierarchical approach combining Model‑in‑the‑Loop (MiL), Hardware‑in‑the‑Loop (HiL), and Power‑Hardware‑in‑the‑Loop (P-HiL) testing.
The initial results demonstrate that SOH‑based load distribution can reduce stress on degraded modules, ensure functional MMC operation, and improve the long‑term aging trajectory compared to classical SOC‑based control. These findings underline the potential of MMC‑based architectures to enable resource‑efficient, grid‑supportive EV operation.

ISBN

978-3-9504969-5-6

DOI

https://doi.org/10.62626/zu1i-hadn Copy link

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