Title :
Fuzzy control to improve high-voltage battery power and engine speed control in a hybrid electric vehicle
Author :
Syed, Fazal U. ; Kuang, Ming ; Czubay, John ; Smith, Matt ; Ying, Hao
Author_Institution :
Sustainable Mobility Technol. & Hybrid Programs, Ford Motor Co., Dearborn, MI, USA
Abstract :
With the recent emphasis on developing more environmentally friendly and fuel-efficient vehicles, Ford Motor Company developed a full hybrid electric vehicle (HEV) with a power-split hybrid powertrain consisting of an integrated motor and a generator. The power-split hybrid consists of two powertrains; an engine and an electric drive system. This powertrain provides a great potential to improve fuel economy in part due to its ability to operate engine at efficient regions independent of the vehicle speed. The engine speed determination in such a system depends on the desired high voltage (HV) battery power and the driver demand (driver torque/power request). Clearly, in order to control HV battery power to a desired power, a sophisticated controls system is essential which controls engine power to achieve the desired HV battery power. The desired engine power in turn determines the desired engine speed. It is essential that engine speed operation is smooth and stable with an acceptable response. Use of a classical proportional-integral (PI) based control system to control HV battery power is limited due to the nonlinear behavior of the powertrain, and results either in an undesired engine speed stability behavior under certain driving conditions or degraded response time. This paper presents a new nonlinear controls scheme based on a fuzzy controller to resolve the undesired engine speed behavior while achieving desired engine speed response and improved high-voltage battery power controls. Simulations are conducted with this controller and results show that the proposed fuzzy controller improves HV battery power controls and thereby the engine speed behavior and response time (e.g., no overshoots, improved settling time, and uncompromised rise time).
Keywords :
PI control; battery powered vehicles; electric drives; fuzzy control; hybrid electric vehicles; machine control; nonlinear control systems; power control; power transmission (mechanical); velocity control; engine speed behavior; engine speed control; engine speed response time; fuzzy controller simulation; high voltage battery power control; hybrid electric vehicle; nonlinear fuzzy control; power-split hybrid powertrain; Batteries; Control systems; Engines; Fuzzy control; Hybrid electric vehicles; Mechanical power transmission; Nonlinear control systems; Pi control; Proportional control; Velocity control;
Conference_Titel :
Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American
Print_ISBN :
0-7803-9187-X
DOI :
10.1109/NAFIPS.2005.1548559