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An Optimization-Oriented Supervisory Controller Design for Hybrid Fuel Cell Electrified Vehicles

[+] Author Affiliations
Kai Wu, Jing Sun

University of Michigan, Ann Arbor, MI

Milos Milacic, Alhadi Albousefi, Ming Kuang

Ford Motor Company, Dearborn, MI

Paper No. DSCC2018-8995, pp. V001T09A003; 10 pages
doi:10.1115/DSCC2018-8995
From:
  • ASME 2018 Dynamic Systems and Control Conference
  • Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare
  • Atlanta, Georgia, USA, September 30–October 3, 2018
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5189-0
  • Copyright © 2018 by ASME

abstract

In this paper, an optimization-oriented supervisory controller based on Pontryagin’s Minimum Principle (PMP) is established to develop an on-road energy management strategy for hybrid fuel cell vehicles. A method to estimate initial co-state value based on average power is proposed and demonstrated, which makes the offline PMP algorithm feasible for on board implementation. Furthermore, the proposed adaptive PMP (A-PMP) maintains charge-sustaining performance using readily available driving information, such as the total travel time. The A-PMP is evaluated on a high fidelity Ford fuel cell electrified vehicle powertrain with an experimentally validated fuel cell stack model. Comparing to the default baseline energy management method, the A-PMP provides better fuel economy performance. The simulation results show up to 1.1% miles per gallon gasoline equivalent (MPGe) improvement for Highway Fuel Economy Test (HWFET), 2.1% for Urban Dynamometer Driving Schedule (UDDS), and 7.0% for EPA Federal Test Procedure (FTP-75).

Copyright © 2018 by ASME

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