Look ahead based Supervisory control of a light duty Diesel engine
Paper in proceedings, 2018

With recent developments in autonomous cars, route based optimisation is closer to reality. Penetration of such connected cars technology provides potential for optimisation of fuel consumption. In this paper, look ahead prediction is used along with lumped parameter based models to develop a supervisory controller for a light duty diesel engine. A supervisory interface proposed in earlier works for a light duty diesel engine with LNT-SCR aftertreatment system is used. The supervisory controller is designed with the objective of non-interference of local controllers. However, the ability to influence the subsystem with a system objective is maintained. The look ahead prediction comprises of vehicle speed and load trajectory. A set of discrete control actions are evaluated for the complete powertrain to determine the optimal action with respect to equivalent fuel consumption. The use of the simple models along with discrete control actions has low computational effort. After a full factorial simulation of the discrete actions carried out on-line, the optimal supervisory control action is chosen by selecting the action with least fuel consumption. The simulation results utilising the proposed controller is analysed for fuel equivalent consumption saving potential.

Engine modelling and control

Subsystems and Intelligent Components

Author

Dhinesh Vilwanathan Velmurugan

Chalmers, Electrical Engineering, Signalbehandling och medicinsk teknik, Signal Processing

Daniel Lundberg

Volvo Cars

Tomas McKelvey

Chalmers, Electrical Engineering, Signalbehandling och medicinsk teknik, Signal Processing

5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling
Changchun, China,

MultiMEC- Multivariabla metoder för energieffektiv motorstyrning

VINNOVA, 2015-03-01 -- 2018-12-31.

Areas of Advance

Transport

Subject Categories

Vehicle Engineering

Control Engineering

DOI

10.1016/j.ifacol.2018.10.102

More information

Latest update

11/21/2018