Session: 09-01-01: Electrochemical Energy Storage and Conversion Systems I

Paper Number: 166245

Investigating Li-Ion Batteries Lifecycle Performance Using Real-Time Dynamic Load Cyclic Testing 

Electrochemical energy storage systems will play a crucial role in driving the transition to a low- carbon economy. The demand for battery technologies has grown significantly, particularly for Lithium-Ion Batteries (LIBs), which are the most widely used battery systems due to their broad applications in sectors such as electric vehicles and grid storage. As global adoption of renewable energy sources continues to accelerate, LIBs are essential for mitigating the instability associated with the intermittent nature of renewable energy sources. However, their efficiency and longevity in real-world applications are hindered by degradation processes.

The loading conditions under which Li-ion batteries operate profoundly impact their lifecycle. To investigate such impacts, previous studies considered idealized lab conditions with simplified loading profiles, due to the challenges with testing under realistic dynamic conditions. On the other hand, in numerous real-world applications LIBs are subject to dynamic loads. Laboratory simulations considering steady-state constant current, constant voltage (CC-CV) profiles may therefore fail in characterizing LIB performance in those realistic cases, as the validity of testing real-world systems under ideal experimental conditions is still unknown. Therefore, there is a need for experimental studies to assess LIBs performance under realistic, dynamic profiles. 

We overcome these limitations of idealized experimental studies by using a state-of-the-art Power-Hardware-in-the-Loop (PHIL) system. PHIL can replicate complex scenarios and control conditions in real-time experimental settings, enabling testing high-power devices with different simulated scenarios in a more flexible and safer environment than traditional testing methods. To obtain a deeper insight into battery degradation phenomena in real-world applications, we perform battery-aging experiments under dynamic operation. Our PHIL system is obtained using a top-notch OPAL-RT real-time simulator that executes real-time conditions of fast dynamics.

To determine the impact of load control on cells’ life cycle, we reproduced two realistic dynamic loading scenarios adapted from standard drive cycling test profiles for electrical vehicles. In our first dynamic load scenario we discharged cells under a standard drive cycling profile scaled based on the chemistry of the tested battery. Our second scenario consists of a Ramp Rate Limited (RRL) profile to smooth sudden power fluctuations and ensure stability. Changes in capacity, resistance, and electrochemical properties are then reported for both dynamic load scenarios. Incremental Capacity Analysis (ICA) and Electrochemical Impendence Spectroscopy (EIS) are implemented to assess the health of the system during the dynamic load cyclic testing. The comparison of our tests results for the original and RRL dynamic loading indicates that battery performance is greatly impacted by the ramp rate control on the dynamic load profile. These results can aid the development of more robust electrochemical systems by ensuring effective methods for dynamic load control of these systems.

Presenting Author: Efat Mohammadi University of Memphis

Presenting Author Biography: Efat Mohammadi is a PhD candidate in Mechanical Engineering at the University of Memphis (U.S.A.), conducting research in the Energy System Control and Optimization (ESCO) Lab under the supervision of Dr. Alexander J. Headley.
Her research focuses on longevity, efficiency, and real-world performance of electrochemical energy storage systems, such as li-ion batteries and PEM water electrolyzers. Specifically, her work addresses a critical gap in understanding electrochemical systems degradation under realistic operating conditions. She is developing methodologies to isolate and analyze the real-time relationships between operational factors and degradation, with the goal of optimizing system control. This approach aims to enhance system performance and reliability through the application of advanced control techniques.

Authors:

Efat Mohammadi University of Memphis
Alexander Headley University of Memphis