Identifying Parameters for Aging-Adaptive Battery Management

Abstract: The modern transportation system is largely based on fossil fuels. To reduce this reliance on oil and gas and thereby drastically reduce emissions, a transition to renewable power sources is necessary. Lithium-ion batteries are the most established candidate for electromobility applications, with suitable energy and power densities. However, their limited lifetime is often further reduced by inadequate battery utilization. Battery usage is overseen by the battery management system relying on different models to determine for instance the charging procedure or estimate the state of charge. Degradation affects internal rate-determining processes and precise battery management is only possible if the used model resolves the battery-internal states and accounts for their changes. In this thesis, I therefore investigate if suitable adjustments to usage can prolong battery lifetime. To achieve such aging-adaptive battery management, the online diagnosis of degradation is paramount. A novel method for the identification of electrochemical parameters relying on optimal experiment design is presented. The operando identification of electrochemical parameters is demonstrated using an established physics-based model and improved accuracy of the model and the estimated parameter set is shown. The method is then utilized to estimate parameter changes in a cycling study on commercial cells, highlighting how beginning-of-life estimates quickly become obsolete. Identified parameter estimates correlate with post-mortem analysis and therefore offer meaningful insight into battery degradation. The information content in real-world driving patterns is investigated for three distinct heavy-duty vehicle types. We show that it is possible to gain meaningful insight into battery degradation from such driving data alone but the information content heavily depends on usage type. Finally, the benefit of the proposed aging-adaptive battery management is demonstrated for fast charging of automotive prototype cells.