A Fundamental Framework for Health-Conscious Optimal Control in Battery Energy Systems, with Application to Lithium-ion Batteries

  • Fathy, Hosam Kadry (PI)

Project: Research project

Project Details

Description

Abstract

1130796

Hosam Fathy

Penn State University

Research Objectives: This proposal addresses the fundamental problem of optimally controlling battery systems for performance, efficiency, and health. The proposed research will use electrochemistry-based models for optimal battery management, with application to health-conscious battery charging, grid energy storage, and hybrid underwater vehicles.

Scientific Merit: The proposed research will add three original contributions to the literature. First, it will furnish a novel framework for combined order and index reduction in electrochemistry-based battery models, thereby making these models more conducive to optimal control. Second, it will use boundary control theory to optimize battery charging/discharging for long-term health. Third, it will address the optimal power and thermal management of a battery pack as a single integrated problem. Together, these contributions have the transformative potential to bridge the current gap between the electrochemistry and control technologies.

Broader Impact: The proposed research make a major contribution to battery energy storage and power management. The research discoveries will furnish two new courses on energy system modeling and optimal power management, and support two students in a lab with a solid record of recruiting and training outstanding underrepresented minority students. The PI will disseminate this research to the electrochemistry and control communities ? as well as existing industrial collaborators ? through an edited textbook and web-based seminar series. Finally, the research will enable the PI to incorporate a stronger battery energy storage components into existing toy kits for K-12 student education and outreach.

StatusFinished
Effective start/end date9/1/118/31/14

Funding

  • National Science Foundation: $355,000.00

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