A multi-input and multi-output design on automotive engine management system
来源期刊：中南大学学报(英文版)2015年第12期
论文作者：ZHAI Yu-jia SUN Yan QIAN Ke-jun LEE Sang-hyuk
文章页码：4687 - 4692
Key words：neural network; spark-ignition engine; dynamical system modeling; system identification; multi-input and mult-output (MIMO) control system
Abstract: 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.
ZHAI Yu-jia(翟禹嘉)1, 2, SUN Yan(孙研)2, 3, QIAN Ke-jun(钱科军)4, LEE Sang-hyuk1, 2
(1. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China;
2. Centre for Smart Grid and Information Convergence, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China;
3. International Business School Suzhou, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China;
4. Suzhou Power Supply Company, Suzhou 215123, China)
Abstract: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.
Key words:neural network; spark-ignition engine; dynamical system modeling; system identification; multi-input and mult-output (MIMO) control system
