Abstract
This study explores the electrochemical and thermal dynamics of a lithium-ion battery pack
through simulations of charge-discharge cycles using Ansys Fluent. The battery pack
comprises two interconnected cells, analyzed to assess factors impacting performance, such
as voltage fluctuation, heat generation, and overall thermal behavior. Components like
electrodes, electrolytes, and separators play critical roles in influencing key parameters such
as energy density, power density, and cycle life. The study leverages these factors to provide
insights into the battery's behavior under realistic operational conditions, with a focus on
applications that demand high efficiency and reliability, such as electric vehicles and
renewable energy systems.
The charge-discharge cycle is modeled with a series of specific load conditions, including
constant power discharge at 400 W, charging at a 1C rate, high-rate discharges at 5C and 3C,
and additional charging at 6 A. These load profiles are structured to reflect real-world energy
demands, allowing for detailed analysis of how the battery’s voltage and temperature evolve
throughout each phase. For instance, during a 5C discharge phase, the voltage shows a sharp
drop due to the high current draw, indicating rapid energy depletion. In contrast, charging
phases see the voltage rise steadily, approaching the upper limit of the battery's operating
range. These voltage dynamics highlight the battery's energy response under various power
conditions and emphasize the impact of high-C discharges on performance.
Thermal behavior is analyzed in tandem with electrochemical performance, providing a dual
perspective on how these batteries function. The simulation shows that temperature begins
around 305 K and rises with each discharge phase, peaking at approximately 315 K during
high-power discharges. Temperature fluctuates throughout the cycle, with gradual cooling
during charging phases and increased heating during discharges. These temperature
variations are influenced by load conditions and atmospheric factors, such as ambient
temperature, and they have a direct impact on the battery’s efficiency, safety, and longevity.
High-C discharges, in particular, contribute to significant heat generation, which could
potentially accelerate wear on battery components if left unmanaged.
The model employs the empirical Nernst-Planck equation for electrochemistry, enabling
precise evaluations of current efficiency and potential distribution within the cells. This
equation supports a more accurate representation of the battery’s internal electrochemical
environment, which is crucial for understanding how current flows and how energy is
transferred within the pack. By capturing these aspects, the model provides a realistic
depiction of the battery's operational challenges and potential optimization areas.
This research offers valuable insights for enhancing lithium-ion battery designs, contributing
to improvements in energy density, power output, and thermal management. The results
underscore the importance of optimizing load schedules, charging protocols, and thermal
regulation to achieve high performance and longevity in applications like electric vehicles
and renewable energy storage. Overall, this project enhances the understanding of lithium-ion
battery systems, supporting innovations in battery technology to meet the increasing demand
for efficient, durable, and safe energy storage solutions.
