TY - JOUR
T1 - A stochastic optimal control approach for power management in plug-in hybrid electric vehicles
AU - Moura, Scott Jason
AU - Fathy, Hosam K.
AU - Callaway, Duncan S.
AU - Stein, Jeffrey L.
N1 - Funding Information:
Manuscript received April 02, 2009; revised January 29, 2010. Manuscript received in final form February 16, 2010. First published March 29, 2010; current version published April 15, 2011. Recommended by Associate Editor R. Raja-mani. This work was supported in part by the University of Michigan Rackham Merit Fellowship and National Science Foundation Graduate Research Fellowship.
Funding Information:
Mr. Moura was a recipient of the National Science Foundation Graduate Research Fellowship, Univer-sity of Michigan Rackham Merit Fellowship, and College of Engineering Distinguished Leadership Award. He has also been nominated for the Best Student Paper Award at the 2009 ASME Dynamic Systems and Control Conference.
PY - 2011/5
Y1 - 2011/5
N2 - 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.
AB - 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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U2 - 10.1109/TCST.2010.2043736
DO - 10.1109/TCST.2010.2043736
M3 - Article
AN - SCOPUS:79955467872
SN - 1063-6536
VL - 19
SP - 545
EP - 555
JO - IEEE Transactions on Control Systems Technology
JF - IEEE Transactions on Control Systems Technology
IS - 3
M1 - 5439900
ER -