A Stochastic Optimal Control Approach for Power Management in Plug-In Hybrid Electric Vehicles

• Published in: IEEE transactions on control systems technology Vol. 19; no. 3; pp. 545 - 555
• Main Authors: Moura, S J, Fathy, H K, Callaway, D S, Stein, J L
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.2011; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Applied sciences; Charge; Computer science; control theory; systems; Constraint optimization; Control theory. Systems; Depletion; Drives; Dynamic programming; Electric charge; Electric machines; Electric power generation; Electric vehicles; Energy; Energy management; Energy. Thermal use of fuels; Engines; Engines and turbines; Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc; Exact sciences and technology; Hybrid electric vehicles; Hybrid vehicles; Management; Markov process; Mechanical engineering. Machine design; Optimal control; Optimization; plug-in hybrid electric vehicles (PHEV); Power demand; power management; Power system management; powertrain control; powertrain modeling; Shafts, couplings, clutches, brakes; Stochastic processes; Stochasticity; Studies; Markov process; Motor car; powertrain control; Fuel consumption; Modeling; Optimization; Pricing; Fuel economy; power management; powertrain modeling; Motor fuel consumption; Dynamic programming; Actuator; Hybrid vehicle; Mechanical drive; plug-in hybrid electric vehicles (PHEV); Stochastic programming; Power divider; Electrical network; Power control; Electric machine; Optimal control; Fuel; Stochastic control; Energy management
• ISSN: 1063-6536; 1558-0865
• DOI: 10.1109/TCST.2010.2043736

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.