Kraus, H., Ackerl, M., Karoshi, P., Fabian, J. et al., "A New Approach to an Adaptive and Predictive Operation Strategy for PHEVs," SAE Technical Paper 2015-01-1222, 2015, doi:10.4271/2015-01-1222.
These days a new generation of hybrid electric vehicles (HEV) are penetrating the global vehicle market - the plug-in hybrid electric vehicles (PHEVs). Compared to conventional HEVs, PHEVs have additional significant potential. They are able to improve fuel efficiency and reduce local emissions due to higher battery capacities, and they can be recharged from external outlets. Energy management has a major impact on the PHEVs performance. In this publication, an innovative operation strategy for PHEVs is presented. This is due to the fact that both increasing fuel efficiency and enhancing the vehicle's longitudinal performance requires a fine balance between the consumption of fossil and electric energy. The new operation strategy combines advanced predictive and adaptive algorithms.In contrast to the charge-sustaining strategy of HEVs, the charge-depleting mode for PHEVs is more appropriate. Moreover, the highest efficiency is obtained when the state of charge (SOC) of the battery is near the lower limit at the end of the trip. However, especially for distances longer than the all-electric range (AER), a simple charge-depleting and afterwards charge-sustaining mode is not necessarily the most efficient. A blended operation strategy using future traffic information is more suitable for improving overall fuel consumption. However, without any prior knowledge of the driver's behaviour, it is hardly possible to provide the instantaneous desired vehicle power at the right time, for example, during overtaking. Consequently, the proposed operation strategy combines different data sources in order to predict the future power demand and adapt to different driving styles.