Name
Abstract | ||
|---|---|---|
The air conditioning system is one of the largest ancillary loads on passenger cars, with considerable effects on the fuel consumption. In this scenario, the optimization and control of the A/C system actuators has an important role in reducing the parasitic load of the A/C compressor. This paper presents an application of sliding mode control to an automotive air conditioning system, with the objective of regulating the superheat temperature and cooling capacity by using the compressor speed and expansion valve position inputs. A nonlinear, physical A/C system model was considered as the starting point to operate Model Order Reduction, with the objective of obtaining a simple model for control design. Then, an error feedback sliding mode regulation problem is solved to design a local controller tracking desired trajectories by the compressor speed and expansion valve position. The simulation results obtained show that the controller is robust to external disturbances such as variations in the air speed or temperature. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ACC.2013.6580738 | ACC |
Keywords | Field | DocType |
compressor speed,expansion valve position inputs,control design,compressors,a/c system actuator optimization,cooling,control system synthesis,robust control,automobiles,fuel consumption,automotive air conditioning system,feedback,parasitic load,sliding mode control,trajectory control,model order reduction,actuators,a/c compressor,superheat temperature regulation,local controller,a/c system actuator control,fuel economy,valves,air conditioning,passenger cars,cooling capacity,variable structure systems,nonlinear physical a/c system model,error feedback sliding mode regulation problem,atmospheric modeling,mathematical model,refrigerants,system identification | Air conditioning,Automotive engineering,Control theory,Control theory,Computer science,Control engineering,Gas compressor,Parasitic load,Thermal expansion valve,Robust control,Cooling capacity,Sliding mode control | Conference |
ISSN | ISBN | Citations |
0743-1619 | 978-1-4799-0177-7 | 1 |
PageRank | References | Authors |
0.42 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Quansheng Zhang | 1 | 2 | 1.15 |
| Marcello Canova | 2 | 52 | 10.30 |
| Giorgio Rizzoni | 3 | 258 | 56.95 |