Engineering topics

Jansen, Andy

Publications and source records attributed to Jansen, Andy.

3 records

DOE OSTI2020

Electrochemical Model Assessment of Strategies for Fast Charge

The United States Department of Energy (DOE) has identified extreme fast charging (XFC) as a critical challenge that must be overcome in order to achieve widespread adoption of electric vehicles. DOE’s eXtreme Fast Charge and Cell Evaluation (XCEL) program seeks to reduce charge time to 10-15 minutes for a 200+ Wh/kg Li-ion battery. This presentation for DOE’s Vehicle Technologies Program Annual Merit Review summarizes the XCEL team’s work developing electrochemical models to interpret data and applying them to identify best strategies to achieve fast charge. Strategies include advanced electrode architectures, elevated temperature charging, novel charge protocols, advanced electrolytes, thermal management and suppression of heterogeneities that cause early onset of the damaging Li plating side reaction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2017

Computational Design of Batteries from Materials to Systems

Computer models are helping to accelerate the design and validation of next generation batteries and provide valuable insights not possible through experimental testing alone. Validated 3-D physics-based models exist for predicting electrochemical performance, thermal and mechanical response of cells and packs under normal and abuse scenarios. The talk describes present efforts to make the models better suited for engineering design, including improving their computation speed, developing faster processes for model parameter identification including under aging, and predicting the performance of a proposed electrode material recipe a priori using microstructure models.

25 ENERGY STORAGE↗

DOE OSTI2017

Microstructure Characterization and Modeling for Improved Electrode Design

This presentation describes research work led by NREL with team members from Argonne National Laboratory and Texas A&M University in microstructure analysis, modeling and validation under DOE's Computer-Aided Engineering of Batteries (CAEBAT) program. The goal of the project is to close the gaps between CAEBAT models and materials research by creating predictive models that can be used for electrode design.

33 ADVANCED PROPULSION SYSTEMS↗