@inproceedings{9a4e328fe50141058e1f83198f30a7a6,
title = "Optimization of dynamic battery paramter characterization experiments via differential evolution",
abstract = "Characterization is important for making models match reality and allowing for quick and accurate measurements of parameters. In this paper we present a method for designing dynamic battery experiments using an evolutionary algorithm that directly generates Pareto fronts via differential evolution. This optimization creates current trajectories for multiple objectives, namely, maximizing Fisher information gathered while minimizing battery damage. An estimator is used on simulated battery experiments to verify the improvements associated with these trajectories. This exercise illustrates the experimental trade-offs between gathering parameter information and causing battery degradation. The procedure in this paper is widely applicable as both the battery model and parameter's of interest can be substituted as needed.",
author = "Joel Forman and Jeffrey Stein and Hosam Fathy",
year = "2013",
doi = "10.1109/acc.2013.6579945",
language = "English (US)",
isbn = "9781479901777",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "867--874",
booktitle = "2013 American Control Conference, ACC 2013",
address = "United States",
note = "2013 1st American Control Conference, ACC 2013 ; Conference date: 17-06-2013 Through 19-06-2013",
}