Online Identification of Power Required for Self-Sustainability of the Battery in Hybrid Electric Vehicles [electronic resource]
Model Identification; Hybrid Electric Vehicles; Power Management Control; Stochastic Control; Fuel Economy.
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Online Access |
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| Format: | Government Document Electronic eBook |
| Language: | English |
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Oak Ridge, Tenn. : Oak Ridge, Tenn. :
Oak Ridge National Laboratory. ; distributed by the Office of Scientific and Technical Information, U.S. Department of Energy,
2014.
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| 245 | 0 | 0 | |a Online Identification of Power Required for Self-Sustainability of the Battery in Hybrid Electric Vehicles |h [electronic resource] |
| 260 | |a Oak Ridge, Tenn. : |b Oak Ridge National Laboratory. ; |a Oak Ridge, Tenn. : |b distributed by the Office of Scientific and Technical Information, U.S. Department of Energy, |c 2014. | ||
| 336 | |a text |b txt |2 rdacontent. | ||
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| 500 | |a Published through SciTech Connect. | ||
| 500 | |a 01/01/2014. | ||
| 500 | |a ASME 2014 Internal Combustion Engine Division Fall Technical Conference, Columbus, IN, IN, USA, 20141019, 20141022. | ||
| 500 | |a Malikopoulos, Andreas. | ||
| 520 | 3 | |a Hybrid electric vehicles have shown great potential for enhancing fuel economy and reducing emissions. Deriving a power management control policy to distribute the power demanded by the driver optimally to the available subsystems (e.g., the internal combustion engine, motor, generator, and battery) has been a challenging control problem. One of the main aspects of the power management control algorithms is concerned with the self-sustainability of the electrical path, which must be guaranteed for the entire driving cycle. This paper considers the problem of identifying online the power required by the battery to maintain the state of charge within a range of the target value. An algorithm is presented that realizes how much power the engine needs to provide to the battery so that self-sustainability of the electrical path is maintained. | |
| 520 | 0 | |a Model Identification; Hybrid Electric Vehicles; Power Management Control; Stochastic Control; Fuel Economy. | |
| 536 | |b DE-AC05-00OR22725. | ||
| 710 | 2 | |a Oak Ridge National Laboratory. |4 res. | |
| 710 | 1 | |a United States. |b Department of Energy. |b Office of Scientific and Technical Information. |4 dst. | |
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