Journal
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 20, Issue 6, Pages 1490-1505Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2011.2168820
Keywords
Dynamic programming; fuel economy; hybrid electric vehicle; powertrain control; supervisory control
Funding
- National Science Foundation
- NDSEG
- NSF-GRFP
- Ford Motor Company
Ask authors/readers for more resources
Hybrid vehicle fuel economy performance is highly sensitive to the energy management strategy used to regulate power flow among the various energy sources and sinks. Optimal non-causal solutions are easy to determine if the drive cycle is known a priori. It is very challenging to design causal controllers that yield good fuel economy for a range of possible driver behavior. Additional challenges come in the form of constraints on powertrain activity, such as shifting and starting the engine, which are commonly called drivability metrics and can adversely affect fuel economy. In this paper, drivability restrictions are included in a shortest path stochastic dynamic programming (SP-SDP) formulation of the real-time energy management problem for a prototype vehicle, where the drive cycle is modeled as a stationary, finite-state Markov chain. When the SP-SDP controllers are evaluated with a high-fidelity vehicle simulator over standard government drive cycles, and compared to a baseline industrial controller, they are shown to improve fuel economy more than 11% for equivalent levels of drivability. In addition, the explicit tradeoff between fuel economy and drivability is quantified for the SP-SDP controllers.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available