Abstract
In this paper, the fuel economy is chosen as the optimization target of a Plug-in hybrid electric bus (PHEB). The optimization mathematical model of PHEB powertrain parameters is established, which is based on optimal energy management strategy, and the energy management strategy of this model is formulated by dynamic programming (DP) algorithm. Firstly, PHEB fuel economy is chosen as the objective function of parameter optimization. Then, combinatorial optimization algorithm is designed by Multi-Island genetic algorithm (MIGA) and Sequential Quadratic Programming-NLPQL. MIGA is used for global optimization firstly, and the NLPQL is used for local optimization. Finally, experiments results prove that PHEB fuel consumption per 100 km has reduced to 17.41 L diesel from 18.51 L diesel, and electricity consumption per 100 km remains the same level.
| Original language | English |
|---|---|
| Pages (from-to) | 2460-2465 |
| Number of pages | 6 |
| Journal | Energy Procedia |
| Volume | 105 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | 8th International Conference on Applied Energy, ICAE 2016 - Beijing, China Duration: 8 Oct 2016 → 11 Oct 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Multi-Island genetic algorithm
- Parameters optimization
- Plug-in Hybrid electric bus
- Sequential Quadratic Programming-NLPQL
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