An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems

This paper presents an energy-saving controller for automotive air-conditioning/refrigeration (A/C-R) systems. With their extensive application in homes, industry, and vehicles, A/C-R systems are consuming considerable amounts of energy. The proposed controller consists of two different time-scale layers. The outer or the slow time-scale layer called a set-point optimizer is used to find the set points related to energy efficiency by using the steady state model; whereas, the inner or the fast time-scale layer is used to track the obtained set points. In the inner loop, thanks to its robustness, a sliding mode controller (SMC) is utilized to track the set point of the cargo temperature. The currently used on/off controller is presented and employed as a basis for comparison to the proposed controller. More importantly, the real experimental results under several disturbed scenarios are analysed to demonstrate how the proposed controller can improve performance while reducing the energy consumption by 9% comparing with the on/off controller. The controller is suitable for any type of A/C-R system even though it is applied to an automotive A/C-R system in this paper.

[1]  Yanjun Huang,et al.  Optimal energy-efficient predictive controllers in automotive air-conditioning/refrigeration systems , 2016 .

[2]  Yanjun Huang,et al.  A predictive power management controller for service vehicle anti-idling systems without a priori information , 2016 .

[3]  Alberto Leva,et al.  Adaptive relay-based control of household freezers with on-off actuators , 2010 .

[4]  Yong Chan Kim,et al.  Thermal comfort and energy saving in a vehicle compartment using a localized air-conditioning system , 2014 .

[5]  Yanjun Huang,et al.  A Supervisory Energy-Saving Controller for a Novel Anti-Idling System of Service Vehicles , 2017, IEEE/ASME Transactions on Mechatronics.

[6]  Kuo-Ming Chang,et al.  ADAPTIVE CONTROL FOR UNCERTAIN SYSTEMS WITH SECTOR-LIKE BOUNDED NONLINEAR INPUTS , 2002 .

[7]  Intan Zaurah Mat Darus,et al.  Application of adaptive neural predictive control for an automotive air conditioning system , 2014 .

[8]  Yanjun Huang,et al.  Model predictive control power management strategies for HEVs: A review , 2017 .

[9]  Robert Babuska,et al.  Fuzzy predictive control applied to an air-conditioning system , 1997 .

[10]  Nejat Olgac,et al.  Application of sliding mode control to swarms under conflict , 2011 .

[11]  Mignon Park,et al.  Fuzzy logic-based advanced on–off control for thermal comfort in residential buildings , 2015 .

[12]  John N. Lygouras,et al.  Variable structure TITO fuzzy-logic controller implementation for a solar air-conditioning system , 2008 .

[13]  Jakob Stoustrup,et al.  Adaptive MPC for a reefer container , 2015 .

[14]  Lars Finn Sloth Larsen,et al.  Non-linear and adaptive control of a refrigeration system , 2011 .

[15]  Yanjun Huang,et al.  A Comparative Study of the Energy-Saving Controllers for Automotive Air-Conditioning/Refrigeration Systems , 2017 .

[16]  Vadim I. Utkin,et al.  SLIDING MODE CONTROL FOR AUTOMOBILE AIR CONDITIONER , 2002 .

[17]  B. Saleh,et al.  Flow Control Methods in Refrigeration Systems: A Review , 2015 .

[18]  Siaw Kiang Chou,et al.  Achieving better energy-efficient air conditioning - A review of technologies and strategies , 2013 .

[19]  Xiang-Dong He,et al.  Dynamic modeling and multivariable control of vapor compression cycles in air conditioning systems , 1996 .

[20]  Yanjun Huang,et al.  Anti-Idling Systems for Service Vehicles with A/C-R Units: Modeling, Holistic Control, and Experiments , 2016 .

[21]  Darine Zambrano,et al.  Sliding mode predictive control of a solar air conditioning plant , 2009 .

[22]  Yanjun Huang,et al.  Modelling and optimal energy-saving control of automotive air-conditioning and refrigeration systems , 2017 .

[23]  H. Harry Asada,et al.  Multivariable control of vapor compression systems , 1998 .

[24]  Andrew G. Alleyne,et al.  Dynamic Modeling and Advanced Control of Air Conditioning and Refrigeration Systems , 2006 .

[25]  Bin Li,et al.  Optimal on–off control of refrigerated transport systems , 2010 .

[26]  Lars Finn Sloth Larsen,et al.  Model Based Control of Refrigeration Systems , 2006 .

[27]  M. Mohanraj,et al.  Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems—A review , 2012, Renewable and Sustainable Energy Reviews.

[28]  B. Egardt,et al.  Enhanced Sample Entropy-based Health Management of Li-ion Battery for Electrified Vehicles , 2014 .

[29]  Farrokh Janabi-Sharifi,et al.  Theory and applications of HVAC control systems – A review of model predictive control (MPC) , 2014 .

[30]  R. Decarlo,et al.  Variable structure control of nonlinear multivariable systems: a tutorial , 1988, Proc. IEEE.

[31]  Gongsheng Huang,et al.  Realization of robust nonlinear model predictive control by offline optimisation , 2008 .

[32]  Ming He,et al.  Multiple fuzzy model-based temperature predictive control for HVAC systems , 2005, Inf. Sci..