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Volumn 2, Issue , 2011, Pages 279-286

Optimal energy management for a hybrid vehicle using neuro-dynamic programming to consider transient engine operation

Author keywords

Engine in the loop (EIL); Neuro dynamic programming (NDP); Numerical optimization; Online learning; Optimal control; Power management; Reinforcement learning; Series hydraulic hybrid; Transient diesel emissions

Indexed keywords

ENGINE-IN-THE-LOOP (EIL); HYDRAULIC HYBRIDS; NEURO-DYNAMIC PROGRAMMING; NUMERICAL OPTIMIZATIONS; ONLINE LEARNING; OPTIMAL CONTROLS; POWER MANAGEMENTS; TRANSIENT DIESEL EMISSIONS;

EID: 84881467500     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/DSCC2011-6138     Document Type: Conference Paper
Times cited : (28)

References (21)
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  • 7
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  • 8
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    • Johri, R.1    Filipi, Z.2
  • 9
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    • Tate, E.D.1    Grizzle, J.W.2    Peng, H.3
  • 13
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    • Self-learning neural controller for hybrid power management using neuro-dynamic programming
    • Johri, R. and Filipi, Z., 2011, "Self-Learning Neural controller for Hybrid Power Management using Neuro-Dynamic Programming," SAE Technical Paper 2011-24-0081.
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    • Johri, R.1    Filipi, Z.2
  • 14
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    • Hydraulic hybrid propulsion for heavy vehicles: Combining the simulation and engine-in-the-loop techniques to maximize the fuel economy and emission benefits
    • Filipi, Z and Kim, Y J, 2010, "Hydraulic Hybrid Propulsion for Heavy Vehicles: Combining the Simulation and Engine-In-the-Loop Techniques to Maximize the Fuel Economy and Emission Benefits," Oil & Gas Science & Technology, 65(1), pp. 155-178.
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  • 15
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  • 17
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.