中南大学学报（英文版）
中南大學學報（英文版）
중남대학학보（영문판）
Journal of Central South University
2015年
12期
4687-4692
,共6页
翟禹嘉%孙研%钱科军%LEE Sang-hyuk
翟禹嘉%孫研%錢科軍%LEE Sang-hyuk
적우가%손연%전과군%LEE Sang-hyuk
neural network%spark-ignition engine%dynamical system modeling%system identification%multi-input and mult-output (MIMO) control system
Lookup table is widely used in automotive industry for the design of engine control units (ECU). Together with a proportional-integral controller, a feed-forward and feedback control scheme is often adopted for automotive engine management system (EMS). Usually, an ECU has a structure of multi-input and single-output (MISO). Therefore, if there are multiple objectives proposed in EMS, there would be corresponding numbers of ECUs that need to be designed. In this situation, huge efforts and time were spent on calibration. In this work, a multi-input and multi-out (MIMO) approach based on model predictive control (MPC) was presented for the automatic cruise system of automotive engine. The results show that the tracking of engine speed command and the regulation of air/fuel ratio (AFR) can be achieved simultaneously under the new scheme. The mean absolute error (MAE) for engine speed control is 0.037, and the MAE for air fuel ratio is 0.069.
