43 citations · 195 across the 20 of their papers we have counts for
10 papers · 1 filter
Interpretation of High-Dimensional Regression Coefficients by Comparison with Linearized Compressing Features
Joachim Schaeffer, Jinwook Rhyu, Robin Droop +2
Linear regression is often deemed inherently interpretable; however, challenges arise for high-dimensional data. We focus on further understanding how linear regression approximate…
Systematic Feature Design for Cycle Life Prediction of Lithium-Ion Batteries During Formation
Jinwook Rhyu, Joachim Schaeffer, Michael L. Li +4
Optimization of the formation step in lithium-ion battery manufacturing is challenging due to limited physical understanding of solid electrolyte interphase formation and the long…
Safe Learning-Based Optimization of Model Predictive Control: Application to Battery Fast-Charging
Sebastian Hirt, Andreas Höhl, Johannes Pohlodek +4
Model predictive control (MPC) is a powerful tool for controlling complex nonlinear systems under constraints, but often struggles with model uncertainties and the design of suitab…
Mechanistic Modeling of Lipid Nanoparticle Formation for the Delivery of Nucleic Acid Therapeutics
Pavan K. Inguva, Saikat Mukherjee, Pierre J. Walker +13
Nucleic acids such as mRNA have emerged as a promising therapeutic modality with the capability of addressing a wide range of diseases. Lipid nanoparticles (LNPs) as a delivery pla…
Gaussian process-based online health monitoring and fault analysis of lithium-ion battery systems from field data
Joachim Schaeffer, Eric Lenz, Duncan Gulla +3
Health monitoring, fault analysis, and detection are critical for the safe and sustainable operation of battery systems. We apply Gaussian process resistance models on lithium iron…
Accounting for the Effects of Probabilistic Uncertainty During Fast Charging of Lithium-ion Batteries
Minsu Kim, Joachim Schaeffer, Marc D. Berliner +3
Batteries are nonlinear dynamical systems that can be modeled by Porous Electrode Theory models. The aim of optimal fast charging is to reduce the charging time while keeping batte…
Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging
Sebastian Hirt, Andreas Höhl, Joachim Schaeffer +3
Tuning parameters in model predictive control (MPC) presents significant challenges, particularly when there is a notable discrepancy between the controller's predictions and the a…
Cycle Life Prediction for Lithium-ion Batteries: Machine Learning and More
Joachim Schaeffer, Giacomo Galuppini, Jinwook Rhyu +4
Batteries are dynamic systems with complicated nonlinear aging, highly dependent on cell design, chemistry, manufacturing, and operational conditions. Prediction of battery cycle l…
Physics-based Modeling of Pulse and Relaxation of High-rate Li/CF-SVO batteries in Implantable Medical Devices
Qiaohao Liang, Giacomo Galuppini, Partha M. Gomadam +6
We present a physics-based model that accurately predicts the performance of Medtronic's implantable medical device battery lithium/carbon monofluoride (CF) - silver vanadium o…
LCEN: A Nonlinear, Interpretable Feature Selection and Machine Learning Algorithm
Pedro Seber, Richard D. Braatz
Interpretable models can have advantages over black-box models, and interpretability is essential for the application of machine learning in critical settings, such as aviation or…