Abstract
In this paper we present models and optimization algorithms to rapidly compute the fuel-optimal energy management strategies of a hybrid electric powertrain for a given driving cycle. Specifically, we first identify a mixed-integer model of the system, including the engine on/off signal. Thereafter, by carefully relaxing the fuel-optimal control problem to a linear program, we devise an iterative algorithm to rapidly compute the minimum-fuel energy management strategies. We validate our approach by comparing its solution with the globally optimal one obtained solving the mixed-integer linear problem and demonstrate its effectiveness by assessing the impact of different battery charge targets on the achievable fuel consumption. Numerical results show that the proposed algorithm can assess fuel-optimal control strategies in a few seconds, paving the way for extensive parameter studies and real-time implementations.
| Original language | English |
|---|---|
| Pages (from-to) | 134-140 |
| Number of pages | 7 |
| Journal | IFAC-PapersOnLine |
| Volume | 52 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2019 |
| Externally published | Yes |
| Event | 9th IFAC International Symposium on Advances in Automotive Control, AAC 2019 - Orléans, France Duration: 24 Jun 2019 → 27 Jun 2019 Conference number: 9 https://aac19.sciencesconf.org/ http://www.ifac-control.org/events/advances-in-automotive-control-9th-aac-2019 |
Bibliographical note
Part of special issue:9th IFAC Symposium on Advances in Automotive Control AAC 2019: Orléans, France, 23–27 June 2019
Keywords
- Hybrid vehicles
- convex optimization
- energy management
- linear programming
- mixed-integer optimal control
- supervisory control