A neurofuzzy-controlled power management strategy for a series hybrid electric vehicle. (August 2014) - Chindamo, Daniel; Economou, John T; Gadola, Marco; Knowles, Kevin
This paper focuses on the design of the power management strategy as the key factor in improving the performance in terms of the efficiency, the range and the fuel consumption for a small-scale series hybrid electric vehicle. A complex hybrid vehicle system is considered, and a practically realisable and traceable neurofuzzy strategy for improving the vehicle efficiency is introduced. The method results in extending the vehicle's range while deciding when to switch the internal-combustion engine on or off as a function of the state of charge of the battery and the electrical power produced from the generator. Consequently, the speed of the internal-combustion engine (i.e. the current produced) is determined as a function of the driving conditions. Suitable tests were performed in order to verify the effectiveness of the proposed strategy; the verification tests were carried out using a consolidated model which also includes real-world experimental vehicle data. The results show that, by using the proposed power management strategy, a good compromise between the efficiency, the range and the fuel consumption can be obtained in many practically useful driving conditions.