Search Results for author:
Found 6 papers, 3 papers with code
Accounting for the Effects of Probabilistic Uncertainty During Fast Charging of Lithium-ion Batteries
Our results demonstrate that uncertainty in ambient temperature results in violations of constraints on the voltage and temperature.
Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging
Tuning parameters in model predictive control (MPC) presents significant challenges, particularly when there is a notable discrepancy between the controller's predictions and the actual behavior of the closed-loop plant.
Cycle Life Prediction for Lithium-ion Batteries: Machine Learning and More
Prediction of battery cycle life and estimation of aging states is important to accelerate battery R&D, testing, and to further the understanding of how batteries degrade.
Interpretation of High-Dimensional Linear Regression: Effects of Nullspace and Regularization Demonstrated on Battery Data
We developed an optimization formulation to compare regression coefficients and coefficients obtained by physical engineering knowledge to understand which part of the coefficient differences are close to the nullspace.
Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra
Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data.
Latent Variable Method Demonstrator -- Software for Understanding Multivariate Data Analytics Algorithms
The ever-increasing quantity of multivariate process data is driving a need for skilled engineers to analyze, interpret, and build models from such data.
