Hybrid vehicle fuel economy and drive quality are coupled through the “energy management” controller that regulates power flow among the various energy sources and sinks. This paper studies energy management controllers designed using shortest path stochastic dynamic programming (SP-SDP), a stochastic optimal control design method which can respect constraints on drivetrain activity while minimizing fuel consumption for an assumed distribution of driver power demand. The performance of SP-SDP controllers is evaluated through simulation on large numbers of real-world drive cycles and compared to a baseline industrial controller provided by a major auto manufacturer. On real-world driving data, the SP-SDP-based controllers yield 10% better fuel economy than the baseline industrial controller, for the same engine and gear activity. The SP-SDP controllers are further evaluated for robustness to the drive cycle statistics used in their design. Simplified drivability metrics introduced in previous work are validated on large real-world data sets.
Real-World Robustness for Hybrid Vehicle Optimal Energy Management Strategies Incorporating Drivability Metrics
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 12, 2013; final manuscript received May 3, 2014; published online August 8, 2014. Assoc. Editor: Shankar Coimbatore Subramanian.
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Opila, D. F., Wang, X., McGee, R., Brent Gillespie, R., Cook, J. A., and Grizzle, J. W. (August 8, 2014). "Real-World Robustness for Hybrid Vehicle Optimal Energy Management Strategies Incorporating Drivability Metrics." ASME. J. Dyn. Sys., Meas., Control. November 2014; 136(6): 061011. https://doi.org/10.1115/1.4027680
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