New Control Methodology for the Next Generation of Engine Management Systems

Completed

Energy Efficiency(Transport)
Not Energy Related
Fossil Fuels: Oil Gas and Coal(Oil and Gas, Oil and gas combustion)

Basic and strategic applied research

PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics)
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering)

Not Cross-cutting

Dr HM Xu
School of Mechanical Engineering
University of Birmingham

Standard

EPSRC

25 March 2013

24 September 2016

42 months

£563,195

Systems engineering

West Midlands

NC : Engineering

Dr HM Xu, School of Mechanical Engineering, University of Birmingham

Professor X Yao, School of Computer Science, University of Birmingham

Project Contact, Oxsensis1
Project Contact, TATA Motors Engineering Technical Centre
Project Contact, Jaguar Land Rover Limited
Project Contact, SAIC Motor UK Technical Centre Ltd
Project Contact, Shell Global Solutions UK

Despite of the fact that electrical cars are under development and have the potential to provide alternatives for short distance light duty transport, the internal combustion engine will continue to be the main power unit in vehicles for several decades to come. Compared with extensive research on combustion and after-treatment systems, little work has been completed with respect to engine system control optimisation, leaving considerable room to improve fuel economy and lower emissions. Current engine calibration process relies on deriving static tabular relationships and the corresponding values between each calibrated engine operating point, with closed-loop feedback control to adjust the settings accordingly for air-fuel ratio control in real engine operation so as to meet the performance targets and emissions legislation. Such a widely adopted method, however, is not efficient in achieving the best fuel economy of the vehicle due to the constraints in the time duration and cost of engine-bed based calibration. Environmental conditions changes, the time required for the closed-loop control to respond, cycle-by-cycle variations, and cylinder-to-cylinder variations make the current engine control impossible to handle the the optimisation of the engine functionalities.The development trend for future engines is towards an on-board intelligence for control and calibration and some research activities for the development of model based control systems are reported in literature. However, feasible strategies to control the engine operation cycle-by-cycle and cylinder-by-cylinder are not yet available.Expanding the work of the applicants in the related areas for many years, the overall Goal of this project is to use a combination of joint efforts from 3 research groups with expertise of engine technology, control technology and computing algorithm in order to develop and test a new engine control and calibration methodology with on-line intelligence built in. This overall goal will be achieved through realising the following objectives:(1) To develop a full real-time multi-cylinder engine model for cylinder-resolved-control purpose(2) To develop a novel engine control strategy involving optimization of control points and control point locations, and multi-objective evaluation of test cycle performance(3) To develop dynamic multi-objective evolutionary algorithms for online engine control optimization(4) To demonstrate the implementation of the engine control models initially on Hardware-in-the-Loop (HIL) dSPACE system and then further rapid prototyping on a test engine.(5) To compare the engine performance using the new techniques with traditional calibration and control approaches, and demonstrate improvements in terms of engine output, fuel consumption, and emissions.The new engine control methodology will be evaluated on a new Jaguar gasoline direct injection (GDI) engine model

10/07/12