Improving the stability and fuel economy for Belt-Starter Generator Mild HEV at idle speed using model predict control

Abstract

A multi-input single-output (MISO) controller using model predictive control is proposed for improving stability and fuel economy at idle speed for the Belt-Starter Generator (BSG) Mild Hybrid.Unlike the conventional algorithm which uses the electronic throttle control (ETC) and spark advance as actuators, ETC and torque of BSG are simultaneously employed as control inputs for maximum authority to maintain idle speed at desired value. The recursive least square technique is employed to identify the engine as a first-order MISO linear model. A nonlinear engine model established in Matlab/Simulink is used to evaluate the proposed and conventional algorithms. The proposed algorithm is also implemented on a V2 engine. Simulation results show that the proposed algorithm has less speed deviation than the conventional one under the presence of torque disturbances and model uncertainties. Since the spark timing can be kept at optimal condition, the fuel consumption of proposed algorithm is smaller than that of the conventional one.978-1-4799-5283-0/14/$31.00 ©2014 IEEE

Internal Combustion Engine Starting and Torque Boosting Control System Design with Vibration Active Damping Features for a P0 Mild Hybrid Vehicle Configuration

“…This may then be used as a basis for the development of the more advanced engine control strategies. These may include the model-predictive control-based idle speed control system [32], characterized by superior engine speed control performance, or a selforganizing fuzzy control system coupled with the equivalent consumption minimization strategy based on BSG utilization, which has shown about 15% fuel consumption reduction compared to the conventional automotive power train [33].…”