Over the last few decades, a broad range of battery technologies have been examined at Argonne for transportation applications. Today the focus is on lithium-ion batteries for hybrid electric (HEV), plug-in hybrid electric (PHEV), and full electric vehicle (EV) applications. Lithium-ion batteries have become the front-runner among rechargeable battery technologies because of their high energy storage and power densities. However, the wide acceptance of electric vehicles has been slow due in large part to the challenges facing the Li-ion family of chemistries: high cell and pack costs, safety concerns, limited cell life, and poor performance at temperatures below 0 degrees C. Research to overcome these limitations is being conducted on advanced lithium-ion cells at Argonne, where modeling plays a key role in their advancement.
Argonne offers a full range of battery modeling capabilities, including:
- Electrochemical transport modeling designed to examine the complex phenomena occurring inside individual cells
- Interactive cell, battery module, and pack design modeling capable of predicting precise overall and component weight and dimensions, as well as performance and manufacturing cost characteristics.
It is extremely difficult, if not impossible, to follow all the complex interactions of individual cell phenomena in an electrochemical system that is on the order of the size of a human hair using a strictly experimental approach. Modeling supports battery research efforts through:
- Interpreting experimental results
- Identifying performance limiting phenomena
- Predicting the impact of new materials and components
- Assisting in cost and performance optimization
- Suggesting advanced designs for specialized applications.
Electrochemical modeling utilizes a set of coupled non-linear differential equations to describe the pertinent transport, thermodynamic, and kinetic phenomena occurring in the cell. The set of equations are solved to obtain a detailed description of the current, potential, and concentration distributions in the cell (i.e., between the current collectors). It is relatively straight forward to translate the distributions to easily measurable quantities such as cell current and voltage, thus connecting microscopic quantities and variables, such as electrode and interfacial microstructure to fundamental electrochemical studies and cell performance.
The primary objective of the electrochemical modeling effort has been to associate changes that are seen in the post-test diagnostic studies of test cells with their loss of electrochemical performance. In this manner the modeling studies are being used to link analytical and electrochemical experimental efforts and to serve as a guide for future studies. In addition to giving unique insights into cell operation and degradation mechanisms, electrochemical modeling has tremendous predictive capability for optimization of lithium-ion cell performance.
Design and Cost Modeling
Cell, battery module, and pack design modeling are spreadsheet based simulations that determine the impedance behavior, available capacity, and thermal effects for general and specific designs. Typically, small lab cell experimental electrochemical studies on a perspective battery technology form the basis for specific simulations. The lab cell results are correlated to an equivalent circuit impedance model that predicts cell impedance as a function of the state of charge and the buildup of over-voltages during operation. Alternatively, the electrochemical model can be used to provide lab cell level performance results. The design model calculates power and energy, weight and volume of materials and components, as well as their thermal performance. The model is also capable of performing simulations on multiple battery designs for comparison and optimization.
The creation of BatPaC has been particularly useful for predicting the impact on overall battery size, weight, performance and cost of advanced materials and components developed in the laboratory. In a technology as dynamic as lithium-ion batteries, the ability to quickly access the potential impact of new materials from limited lab cell data has proven to be a tremendous tool to help guide the research and development effort at Argonne.