Title :
An Intelligent Control Strategy in a Parallel Hybrid Vehicle
Author_Institution :
Amirkabir Univ., Tehran
Abstract :
This paper presents a design procedure for an adaptive power management control strategy based on a driving cycle recognition algorithm. The design goal of the control strategy is to minimize fuel consumption and engine-out NOx, HC and CD emissions on a set of diversified driving schedules. Seven facility-specific drive cycles are considered to represent different driving scenarios. For each facility-specific drive cycle, the fuel economy and emission are optimized and obtained proper split between the two energy sources (engine and electric motor). A driving pattern recognition algorithm is subsequently developed and used to classify the current driving cycle in to one of the facility-specific drive cycles; thus, the most appropriate control algorithm is adaptively selected. This control scheme was tested on a typical driving cycle and was found to work satisfactorily.
Keywords :
adaptive control; fuel economy; fuzzy control; hybrid electric vehicles; neurocontrollers; CO emission; HC emission; adaptive power management control; driving cycle recognition algorithm; driving schedule; electric motor; engine motor; engine-out NOx emission; facility-specific drive cycle; fuel consumption minimization; fuel economy; fuzzy rule base; intelligent control; neural network; parallel hybrid vehicle; torque distribution; Adaptive control; Algorithm design and analysis; Electric motors; Energy management; Engines; Fuel economy; Intelligent control; Pattern recognition; Programmable control; Vehicles; Hybrid vehicle; drive cycle; fuzzy rule base; neural network; torque distribution;
Conference_Titel :
Electric and Hybrid Vehicles, 2006. ICEHV '06. IEEE Conference on
Conference_Location :
Pune
Print_ISBN :
0-7803-9793-2
DOI :
10.1109/ICEHV.2006.352272