showing 2 related works from this author
Adaptive control of hybrid vehicle depending on driving cycle analysis
2013
The most adapted energy management in hybrid electric vehicles depends on the current driving situation. This paper describes a novel control strategy based on driving cycle recognition. A Driving Cycle Recognition Algorithm (DCRA) is firstly presented. It allows recognition between three driving modes: urban, suburban and highway. A real-time control strategy is then defined based on fuzzy logic using DCRA. Results are presented and compared to fuzzy logic controllers parametrized for urban or highway cycles.
Autonomy estimation for EV based on road planning software
2014
A methodology to estimate the energy consumption of an electric vehicle is presented. An approach to create a driving cycle based on data extracted from road planning software is developped; it is used to forecast the total cycle energy consumption. Results are compared to the ones obtained from the corresponding actual driving cycle. The influence of road elevation is taken into. Results match with regard to vehicle velocities, power demand and estimated energy consumption, with a maximum error of 10%. It can thus be concluded that road planning-based energy consumption estimation can be a useful tool by providing accurate information to drivers.