Path-forecasting for HEV optimal energy management (POEM)
| Autor: | Anthony Mark Phillips, Ming L. Kuang, Johannes Geir Kristinsson, Yanan Zhao |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Engineering Mathematical optimization business.product_category Optimization problem business.industry Energy management 020302 automobile design & engineering Control engineering 02 engineering and technology Dynamic programming 020901 industrial engineering & automation 0203 mechanical engineering Robustness (computer science) Electric vehicle Battery state of charge Fuel efficiency Vehicle control business |
| Zdroj: | ACC |
| DOI: | 10.1109/acc.2016.7525131 |
| Popis: | This paper studies a control strategy using path-forecasting for Hybrid Electric Vehicle (HEV) optimal energy management (POEM). In the previous work, a receding horizon control (RHC) approach was developed to solve a dynamic programming (DP) formulated optimization problem where preview information of an intended route is utilized to schedule battery state of charge (SoC) usage profile along the route for optimal fuel economy of HEVs. This paper presents our recent work that further developed POEM strategy with refined route segmentation rules and fuel consumption estimation. The work also contains the development of a simulation platform integrating POEM strategy with a production level vehicle control strategy, fuel economy evaluation of POEM under different driving cycles, and the robustness study of the POEM strategy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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