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Fuel economy optimization of power split hybrid vehicles: A rapid dynamic programming approach
- Source :
- Energy. 166:929-938
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Fuel economy of hybrid vehicles is affected by their powertrain configurations, powertrain parameters, and energy management strategies. It is most beneficial to optimizing all the three factors simultaneously. However, when the design search space is large, an exhaustive, optimal control strategy, such as dynamic programming (DP), is too computationally expensive. Hence, a faster optimization method with higher computational efficiency and acceptable accuracy is required. Based on the DP approach, an approximate optimization method, called rapid dynamic programming (Rapid-DP), is developed and discussed in this paper. This method effectively reduces the decision-making time (the time can be reduced by a factor of 700, compared to the DP approach) for optimal control. The optimization processes and results are described and then compared with the original DP and PEARS + methods under two different driving cycles: FTP72 and HWFET. In conjunction with particle swarm optimization (PSO), the rapid-DP is leveraged, for the first time, to optimize key powertrain parameters for power split hybrid electric vehicles. Based on two power-split hybrids: Toyota Prius and Prius++, the joint optimization approach is exploited to examine vehicular fuel savings attributed to synergistic parameters optimization and operating-mode increase. The multi-mode configuration with optimal component parameters is demonstrated to be most fuel-efficient, with 6.56% and 3.15% fuel reductions under FTP72 and HWFET cycles, respectively, with respect to the original Prius 2010.
- Subjects :
- Powertrain
Computer science
Energy management
020209 energy
Mechanical Engineering
Particle swarm optimization
02 engineering and technology
Building and Construction
Optimal control
Pollution
Industrial and Manufacturing Engineering
Dynamic programming
General Energy
020401 chemical engineering
Economy
Power split
Component (UML)
0202 electrical engineering, electronic engineering, information engineering
Key (cryptography)
0204 chemical engineering
Electrical and Electronic Engineering
Civil and Structural Engineering
Subjects
Details
- ISSN :
- 03605442
- Volume :
- 166
- Database :
- OpenAIRE
- Journal :
- Energy
- Accession number :
- edsair.doi...........705e0db3637b55fb2720ce1c1db04b04