Dynamic programming applied to investigate energy management strategies for a plug-In HEV1

22nd International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exposition, EVS 2006

Volumn , Issue , 2006, Pages 1035-1046

  O'Keefe, Michael Patrick ^a   Markel, Tony ^a  

^a NATIONAL RENEWABLE ENERGY LABORATORY   (United States)

Author keywords

Dynamic programming; Energy efficiency; Hybrid strategy; Modeling; Plug in hybrid

Indexed keywords

BATTERY ELECTRIC VEHICLES; ENERGY MANAGEMENT STRATEGIES; HYBRID STRATEGIES; HYBRID-ELECTRIC VEHICLES; NEAR-OPTIMAL CONTROL; OPTIMIZATION ALGORITHMS; PLUG-IN HYBRID ELECTRIC VEHICLES; PLUG-IN HYBRIDS;

ALGORITHMS; CONTROL SYSTEM SYNTHESIS; ELECTRIC VEHICLES; ENERGY EFFICIENCY; FUEL CELLS; FUEL ECONOMY; GASOLINE; HYBRID VEHICLES; MODELS;

DYNAMIC PROGRAMMING;

EID: 84880480476     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Bertsekas, Dimitri P., Dynamic Programming and Optimal Control, Athens Scientific, 2000.
2. Lin, Chan-Chiao; Peng, Huei; and Grizzle, Jessy W., Control System Development for an Advanced- Technology Medium-Duty Hybrid Electric Truck, Society of Automotive Engineers 2003-01-3369, 2003.
3. Simpson, Andrew, Cost-Benefit Analysis of Plug-in Hybrid Electric Vehicle Technology, EVS-22, 2006.
4. Python Programming Language, http://www.python.org.
5. Numeric Python and Scientific Python, http://www.scipy.org.
6. Matplotlib Python Extension, http://matplotlib.sourceforge.net.