Improving the Stability and Fuel Economy for Belt-Starter Generator Mild HEV at Idle Speed Using Model Predict Control

摘要

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.