Journal
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 19, Issue 3, Pages 545-555Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2010.2043736
Keywords
Dynamic programming; Markov process; plug-in hybrid electric vehicles (PHEV); power management; powertrain control; powertrain modeling
Funding
- University of Michigan
- National Science Foundation
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This paper examines the problem of optimally splitting driver power demand among the different actuators (i.e., the engine and electric machines) in a plug-in hybrid electric vehicle (PHEV). Existing studies focus mostly on optimizing PHEV power management for fuel economy, subject to charge sustenance constraints, over individual drive cycles. This paper adds three original contributions to this literature. First, it uses stochastic dynamic programming to optimize PHEV power management over a distribution of drive cycles, rather than a single cycle. Second, it explicitly trades off fuel and electricity usage in a PHEV, thereby systematically exploring the potential benefits of controlled charge depletion over aggressive charge depletion followed by charge sustenance. Finally, it examines the impact of variations in relative fuel-to-electricity pricing on optimal PHEV power management. The paper focuses on a single-mode power-split PHEV configuration for mid-size sedans, but its approach is extendible to other configurations and sizes as well.
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