Technoeconomic Analysis of Chemical and Electrochemical Technologies

Technoeconomic Analysis of Chemical and Electrochemical Technologies

Technoeconomic analysis (TEA) is the translation and interpretation of a technical process or product with respect to its figures of merit. Figures of merit for a technical process are broad and include both raw material and process requirements – e.g., utilities, capital investment, and land. Figures of merit for a product are set by the characteristics of the design – e.g., mass, volume, cost, power, etc. TEA analysis is valuable for determining supply chain requirements, identifying the potential of alternative technologies, setting R&D priorities, tracking R&D progress, identifying bottlenecks & cost drivers, and evaluating/projecting product cost.

The TEA team within the Electrochemical Energy Storage (EES) theme (department) is engaged in the development of TEA models and analyses. The model development benefits from data and insights gained from theoretical and experimental developments within EES. The team reciprocates with analyses to quantify the merits of new materials and energy storage concepts.

The team is primarily supported by the U.S. Department of Energy (USDOE’s Vehicle Technologies Office), the U.S. Environmental Protection Agency (USEPA), and the National Highway and Traffic Safety Administration (NHTSA). The team also works with industry sponsors, often as a member of government-funded projects. The team’s main software product, the Battery Performance and Cost (BatPaC) model, is widely used by start-up and corporate developers of lithium-ion batteries, academic institutions, and policymakers.

Our team conducts TEA by combining experimental/simulation data, physics-based models, and product specs to determine performance metrics.

Research Areas

The Battery Performance and Cost Model (BatPaC)

The Battery Performance and Cost (BatPaC) model receives high visibility because it is very detailed in its presentation of the battery design and cost structure, it is used by many government agencies, academia, and commercial entities, and because it is shared with battery researchers at no cost. The BatPaC model is a tool based on Microsoft® Office Excel spreadsheets that has been developed at Argonne for estimating the performance and manufacturing cost of lithium-ion batteries for electric-drive vehicles, including hybrid-electrics (HEV), plug-in hybrids (PHEV) and pure electrics (EV). The code has a range of default inputs for all parameters, which can also be overridden by the user. For example, BatPaC has pre-built libraries of electrode couples, pack configurations, and vehicle power/energy requirements. BatPaC is supported by several rigorous models that provide data, insights, and parameter/price estimates.

A full description of the model can be found in the manual. Please see contact information on the right panel of this webpage for a free copy of BatPaC. 

A video tutorial explaining Argonne National Laboratory’s Battery Performance and Cost (BatPaC) Model v5.1 recorded on November 13, 2023. The video includes the following sections: BatPaC introduction, In-tool overview, Demonstration on how to add a new material, and questions.

 

Physics-Based Modeling

The team also develops physics-based, continuum-level models to better understand real-world performance and product design. These models can be zero to three-dimensional in space and can simulate electrochemical, thermal, and mechanical behavior expected throughout the life of the technology. Some examples include the use of these models to study:

  • the influence of thermal and electrical design on the lifetime of lithium-ion battery modules
  • the fast charge ability and limitations of lithium-ion batteries under electrochemical and thermal control
  • the mechanical behavior of silicon electrodes in lithium-ion batteries
  • the processes controlling dynamic charge acceptance and discharge capacity in lead batteries
Chemical Engineering Process Modeling

Process modeling is a key capability of the team and is used to understand the manufacturing of batteries and their precursor materials. The team develops process models for understanding the individual steps in battery manufacturing – e.g., solvent drying/recovery and dry room operation. Process models of key components are also used to identify critical materials and potential bottlenecks in the supply chain – e.g. cathode active material (CAM), lithium salt (LiF6), and lithium-metal production for batteries.

Research Tools

The team has developed and uses the following technoeconomic and physics-based models to support their internal and collaborative research efforts. Only BatPaC is made available to researchers at no cost. Please see contact information on the right panel of this webpage for interest in collaboration. These models include:

  1. The Battery Performance and Cost Model (BatPaC), see above (assumes stiff pouch cells)
  2. The Battery Performance and Cost Model for cylindrical cells (BatPaC-Cylindrical)*
  3. Thermal/electrochemical model of lithium-ion pouch cells under dynamic cooling conditions*
  4. Electrical/thermal/electrochemical/degradation model of modules containing lithium-ion cylindrical cells*
  5. Electrochemical models for lead batteries*
  6. Process model for the synthesis of layered oxide cathode active materials (NMCxyz, NCA, single crystal, polycrystalline)*
  7. Process model for the synthesis of lithium iron phosphate (LFP) and lithium manganese iron phosphate (LMFP)*
  8. Model of the solvent drying process during coating of lithium-ion battery electrodes*
  9. Process model for the recovery of solvents used in the coating of lithium-ion battery electrodes*
  10. Process model for the dry room used in lithium-ion battery production*
  11. Process model for LiPF6 production*

    *denotes models that can be leveraged through collaborative research projects
     

Government Performance and Results Act (GPRA)

The USDOE’s Vehicle Technology Office (VTO) conducts an annual evaluation of the cost of automotive lithium-ion batteries by considering the state-of-the-art parameter values achieved through its funded R&D portfolio. This analysis is conducted with the BatPaC model and is used as a tracking tool as part of the agency’s Government Performance and Results Act (GPRA) obligations.

Past Contributors

Staff: Paul A. Nelson, Kevin G. Gallagher, Dennis W. Dees, David C. Robertson
Postdocs:Naresh Susarla, Juhyun Song, Hong-Keun Kim, Zhe Liu, Abhas Deva
Undergraduate Students:Sai Varanasi, Joshua Miao, Victoria Kulaga

Publications