Name
Abstract | ||
|---|---|---|
In this work, a new rule-based control strategy is developed for the energy management of parallel hybrid electric vehicles (HEVs): the torque-leveling threshold-changing strategy (TTS). In contrast to the commonly used electric assist control strategy (EACS) designed based on the load following approach, the TTS proposes and applies a new fundamental concept of torque leveling. This mechanism operates the engine with a constant torque when the engine is active, thus ensuring the engine works at an efficient operating point. The TTS additionally adopts the threshold-changing mechanism to operate the HEV in a charge-sustaining manner. To show its effectiveness, the TTS is implemented to a through-the-road (TTR) HEV and benchmarked against two conventional control strategies: the dynamic programming (DP) and the EACS. In addition, to facilitate real-time application, an adaptive version of the TTS is also developed, which updates the parameters in TTS online by using pattern recognition techniques with a feedback controller. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IECON.2018.8591385 | IECON 2018 - 44TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY |
Keywords | Field | DocType |
Parallel hybrid electric vehicle, heuristic control strategy, pattern recognition | Dynamic programming,Energy management,Heuristic,Torque,Feedback controller,Control theory,Operating point,Control engineering,Load following power plant,Engineering,State of charge | Conference |
ISSN | Citations | PageRank |
1553-572X | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| xuefang li | 1 | 18 | 2.74 |
| Arghavan Nazemi | 2 | 0 | 0.34 |
| Simos A. Evangelou | 3 | 7 | 10.22 |