Dynamic Programming-based Optimization of Control Variables of an Extended Range Electric Vehicle
SAE paper #2013-01-1481, 2013 SAE World Congress, Detroit, MI2013A dynamic programming-based algorithm is developed and used for off-line optimization of range extended electric vehicle power train control variables over standardized certification driving cycles. The aim is to minimize the fuel consumption subject to battery state-of-charge constraints and physical limits of different power train variables. The control variables to be optimized include engine torque and electric machine speed, as well as a variable that selects the power train operating mode. The optimization results are presented for four characteristic certification driving cycles and characteristic vehicle operating regimes including electric driving during charge depleting mode, hybrid driving during charge sustaining mode, and combined/blended regime. fuel consumption; electric drives; railway vehicles and equipment; optimization; standardization; certification; batteries
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SAE paper #2013-01-1481, 2013 SAE World Congress, Detroit, MI
2013
Cited by 20
▾
-
[3] An Optimized Real-Time Energy Management Strategy for the Power-Split Hybrid Electric Vehicles🔗IEEE Transactions on Control Systems Technology, 2019
-
[4] Challenges of micro/mild hybridisation for construction machinery and applicability in UK🔗Renewable & Sustainable Energy Reviews, 2018
-
[5] An energy management of plug-in hybrid electric vehicles based on driver behavior and road information🔗Journal of Intelligent & Fuzzy Systems, 2017
-
[10] Study on energy management strategy based on DP for range extended electric bus in Chinese driving cycles🔗IEEE Transportation Electrification Conference and Expo, Asia-Pacific, 2014
-
[14] On smoothing HEV/EREV supervisory control action using an extended ECMS approach🔗2013 World Electric Vehicle Symposium and Exhibition (EVS27), 2013