Smart battery systems - from cell to pack

The global shift toward sustainable energy systems is demanding significant advancements in electrification and energy storage technologies. Batteries are one of the main enablers of this transition and plays an important role in diverse applications ranging from renewable energy integration to maritime propulsion. This thesis presents a comprehensive investigation into the role of batteries in electrification, bridging the gap between cell level modeling and large-scale energy storage systems. Through a multidisciplinary approach, the research advances understanding and innovation in battery modeling, system integration and battery analytics.

The study is the development of cell-level models to predict battery performance and degradation under certain operating conditions. Using computational techniques and state-of-the-art deep learning algorithms, the thesis introduces new methodologies to improve test time for battery packs and down to cell level tests. These models are validated through experimental data and are planned to be applied to an artificial intelligence (AI) driven battery management systems through a Eurostar project (AIBMS). This is expected to enable more efficient utilization and extended lifespans of battery systems.

Furthermore a new framework for state of health has been analyzed and introduced, which combine battery data from electrochemical impedance spectroscopy with the mathematical transformation Markov transition field and uses a convolutional neural network algorithm to classify the cell state of health (SoH).

The work also addresses the integration of energy storage with photovoltaic (PV) systems, a step toward increasing renewable energy adoption. By combining system-level simulations and real-world case studies, the thesis analysis and highlights the economical optimization of the introduction of a maritime second-life battery energy storage into a local PV plant.

A distinctive focus of the research is on maritime electrification which is a sector undergoing rapid transformation especially in Denmark. Batteries are emerging as a viable alternative to traditional fossil fuel-based propulsion systems for ships. One example is the Danish E-ferry Ellen which is the ship worked on in parts of this thesis. The thesis explores the potential of a second-life application for the battery pack from Ellen and evaluates the state of the cell after the first life application. Through detailed testing and data collection it offers recommendations for the design and deployment of energy storage systems tailored for the second-life use of these cells.

By integrating cell level insights with system level applications, the research provides a holistic framework for advancing battery technologies in areas of electrification. The findings contribute to a deeper understanding of the intersection between battery performance, system integration, and sector-specific requirements, enabling more reliable and sustainable energy solutions across industries. During the Ph.D. study the built up of a new research group has been ongoing and a substantial amount of resources has been allocated for this purpose. A total amount of 7.472.000 DKK has been secured from funding applications and further 14.257.000 DKK are planned or submitted. A new battery laboratory is also being built and some of the test and data collection for the thesis has been conducted in this lab.