Title :
A Torque Control Strategy with Charge Buffer for Parallel Hybrid Electric Vehicle
Author :
Huang, Xi ; Tan, Ying ; He, Xingui
Author_Institution :
Dept. of Machine Intell., Peking Univ., Beijing, China
Abstract :
As a new kind of vehicles with low fuel cost and low emission, hybrid electric vehicle (HEV) has been given more and more attention in recent years. The key technique in the HEV is the optimal control strategy for the best performance. This paper proposed a new torque control strategy with charge buffer (TCSCB) to control the two power sources of the HEV. The TCSCB is based on the control of engine torque which make the control strategy easily distribute the output power to the engine and motor. In this control strategy, the real time optimization based on the engine efficiency map increases engine efficiency observably. The charge buffer reduces the dramatic fluctuation of the engine torque to improve the fuel economy. The prediction engine torque based on the neural network improves the control performance by the future information greatly. The simulation results showed the TCSCB could reach a higher fuel economy and lower emission compared to the current control strategies. In order to optimize the control performances, the parameters in the TCSCB were also discussed in details.
Keywords :
engines; hybrid electric vehicles; neural nets; optimal control; power control; torque control; charge buffer; engine efficiency map; engine torque; fuel economy; neural network; optimal control strategy; parallel hybrid electric vehicle; torque control; Artificial neural networks; Engines; Hybrid electric vehicles; Power capacitors; System-on-a-chip; Thyristors; Torque;
Conference_Titel :
Vehicular Technology Conference Fall (VTC 2010-Fall), 2010 IEEE 72nd
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4244-3573-9
Electronic_ISBN :
1090-3038
DOI :
10.1109/VETECF.2010.5594436