Advanced Battery Diagnostics: Decode the Information in Electrode Swelling

Ongoing project that started in 2017.

The project plan is to fuse existing electrical and thermal measurements, with novel mechanical measurements to estimate the state and health of not only the cells in a battery module but also the state of the individual electrodes. This approach, enabling nonconventional electrode-state-specific power limits at their maximum and safe utilization, allows us to operate closer to the physical limits for discharging at high temperatures and charging under cold conditions.

Unmanned vehicles require accurate and robust diagnostic techniques for assessing the state of their energy storage in order to be best utilized given the vehicle mission and constraints. Batteries are critically important for the situational awareness of autonomous ground vehicles, powering critical monitoring, communication and protection equipment. Degradation of Li-ion battery is the result of a number of physical and chemical mechanisms that take place at various components of the cell i.e. the electrolyte, the separator, the current collectors, and more importantly the individual electrodes. Important types of degradation are parasitic reactions such as Solid Electrolyte Interphase (SEI) growth and lithium plating that consumes the reversible lithium during cycling leading to capacity fade. This is a well-studied and modeled degradation, since it causes a simultaneous increase in resistance. Thus it is easier to identify with real-time dynamic excitation.

Another important and not well studied mechanism is the Loss of Active Material (LAM) or Loss of Cyclable Lithium (LCL) when the active material of the electrode is no longer available for insertion and extraction of lithium. Batteries in ground vehicles are stored for many days (sometimes months) under elevated temperature conditions with many LAM and LCL aging mechanisms. The aging from these mechanisms is very hard to identify since it requires a full charge-discharge operation at low c-rate; a condition that is highly unusual in most applications. Thus estimating reliably and fast (at switch-on) their state of health (SOH) and state of Power (SOP) is of paramount importance.

Publications:

• Suhak Lee, Peyman Mohtat, Jason B. Siegel, and Anna G. Stefanopoulou, “Beyond Estimating Battery State of Health: Identifiability of Individual Electrode Capacity and Utilization,” ACC 2018.

Publications from PIs’ related work:

• P Mohtat, F Nezampasandarbabi, S Mohan, JB Siegel, AG Stefanopoulou, “On identifying the aging mechanisms in li-ion batteries using two points measurements,” American Control Conference (ACC), 2017.
• NA Samad, B Wang, JB Siegel, AG Stefanopoulou, “Parameterization of Battery Electrothermal Models Coupled With Finite Element Flow Models for Cooling,” Journal of Dynamic Systems, Measurement, and Control 139 (7), 071003, 2017
• M Zhang, J Du, L Liu, A Stefanopoulou, J Siegel, L Lu, X He, X Xie, “Internal Short Circuit Trigger Method for Lithium-Ion Battery Based on Shape Memory Alloy,” Journal of The Electrochemical Society 164 (13), A3038-A3044, 2017
• M Zhang, L Liu, A Stefanopoulou, J Siegel, L Lu, X He, M Ouyang, “Fusing Phenomenon of Lithium-Ion Battery Internal Short Circuit,” Journal of The Electrochemical Society 164 (12), A2738-A2745, 2017.