System-Level Model and Stochastic Optimal Control for a PEM Fuel Cell Hybrid Vehicle

[+] Author and Article Information
Chan-Chiao Lin1

Department of Mechanical Engineering, University of Michigan, G041 Lay Automotive Laboratory, Ann Arbor, MI 48109-2133chancl@umich.edu

Min-Joong Kim

Department of Mechanical Engineering, University of Michigan, G041 Lay Automotive Laboratory, Ann Arbor, MI 48109-2133minjoong@umich.edu

Huei Peng

Department of Mechanical Engineering, University of Michigan, G041 Lay Automotive Laboratory, Ann Arbor, MI 48109-2133hpeng@umich.edu

Jessy W. Grizzle

Department of Electrical Engineering and Computer Science, University of Michigan, 4221 EECS Building, 1301 Beal Avenue, Ann Arbor, MI 48109-2122grizzle@umich.edu


Corresponding author.

J. Dyn. Sys., Meas., Control 128(4), 878-890 (Apr 16, 2006) (13 pages) doi:10.1115/1.2362785 History: Received November 06, 2004; Revised April 16, 2006

System-level modeling and control strategy development for a fuel cell hybrid vehicle (FCHV) are presented in this paper. A reduced-order fuel cell model is created to accurately predict the fuel cell system efficiency while retaining dynamic effects of important variables. The fuel cell system model is then integrated with a DC/DC converter, a Li-ion battery, an electric drive, and tire/vehicle dynamics to form an FCHV. In order to optimize the power management strategy of the FCHV, we develop a stochastic design approach based on the Markov chain modeling and stochastic dynamic programming (SDP). The driver demand is modeled as a Markov process to represent the future uncertainty under diverse driving conditions. The infinite-horizon SDP solution generates a stationary state-feedback control policy to achieve optimal power management between the fuel cell system and battery. Simulation results over different driving cycles are presented to demonstrate the effectiveness of the proposed stochastic approach.

Copyright © 2006 by American Society of Mechanical Engineers
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Figure 15

Simulation results of SDP control over UDDS cycle

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Figure 16

Power distribution trajectories by using SDP control strategy

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Figure 1

Block diagram of the reduced-order fuel cell system (arrow directions represent computation flows)

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Figure 2

Simulation setup for comparison of different fuel cell system models

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Figure 3

Simulation validation results: pressures and flow rates

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Figure 4

Simulation validation results: voltage and compressor power

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Figure 5

Fuel cell power levels as a function of stack current

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Figure 6

Fuel cell net current versus fuel cell stack current

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Figure 7

Fuel cell stack efficiency and fuel cell system efficiency

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Figure 8

Schematic of the fuel cell hybrid propulsion system

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Figure 9

FCHV simulation model in SIMULINK

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Figure 10

Block diagram of the DC/DC converter

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Figure 11

Resistance battery model

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Figure 12

Power management problem for the fuel cell hybrid vehicle

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Figure 13

Four representative driving cycles for constructing the Markov chain model

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Figure 14

Stochastic optimal control problem for power management

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Figure 17

Simulation comparison of the rule-based control and SDP control




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