Rising fuel prices, pollutant emissions and an increasing concern for global warming has initiated a development process within the automotive industry towards electrified powertrains. Due to the high cost of electric buffer capacity plug-in hybrid electric vehicles (PHEVs), rather than battery electric vehicles, are expected to be the viable electrified option during the foreseeable future, at least for vehicles that frequently travel longer distances.
One of the control problems in the PHEV energy management system is how to optimally discharge the battery when the length of a trip exceeds the all electric range (AER). Rather than using the trivial charge depleting charge sustaining (CDCS) strategy, i.e. to operate as an electric vehicle until the battery is depleted and then proceed in charge sustaining operation as a conventional hybrid electric vehicle, it is possible to improve powertrain efficiency if the battery is discharged gradually throughout the trip. A gradual discharge lowers the average discharge current, thereby lowering the resistive losses that are quadratic in current. However, to find a suitable discharge rate some a priori information regarding the future trip is required.
The main research topic in the project concerns how a priori information regarding the future trip can be acquired and utilized to improve PHEV energy efficiency. The research covers aspects such as quasi static powertrain modeling, convex optimization and optimal control techniques such as Dynamic Programming.
Examples of topics that have been investigated are:
- Recognition of commuting routes from logged driving data
- How route recognition techniques can be used by the energy management system to improve energy efficiency
- Optimal discharge strategies for PHEVs when the trip length prediction is uncertain
- How uncertain estimates of the battery state of charge affects the optimal energy management of PHEVs and HEVs
The research is carried out within Swedish Hybrid Vehicle Centre (SHC).
Read an interview with researcher Viktor Larsson, on fuel optimal control (SHC).