Predictive Controller Design for Automobile Climate System

Authors

1 Department of Electrical Engineering, Imam Khomeini International University, Qazvin, Iran

2 Mechanical Engineering, Azad University, Takestan, Iran

Abstract

Since the car is working in different climatic conditions, any Changes in temperature of the climatic conditions can affect various parts of the car. So it is necessary to optimize the energy consumption & keep the passengers in a suit & comfort state considering this kind of changes. The automotive air conditioning system is one of the largest ancillary loads in the passenger cars , with considerable effects on the vehicle fuel consumption .While most of the studies have represented linearized equations & simplified steady state matrixes , In the simulations of this paper, Nonlinear dynamic equations with using a model predictive controller and advanced control theory is designed for automotive air conditioning system.At the same time, a genetic algorithm technic which is a method of generation evaluation, is finding out the best answer in the whole problem space using a fitness function to select optimized inputs for sending to the plant. Also in this system a compressor capacity & fan flow rate has considered as two inputs to achieve the main objectives like minimizing the steady state error, system fast response, reduction of noise effects, minimizing of energy consumption and comforter of passengers.

Keywords

Main Subjects

References

[1] {Carey, 1998 #8}Iran Khodro, “Automotive Air Conditioning”, Winter, Tehran, Iran, (2012).
 
[2] Zhang., Q., and Canova., M., ”Sliding Mode Control of an Automotive Air Conditioning System”, American Control Conference,Washington DC, USA, June 17-19, (2013).
 
 
 
[3] Zhang., Q., and Canova., M.,”Output Feedback Control of Automotive Air Conditioning System using H∞ Technique”, International Journal of Refrigeration, ISSN 0140-7007, (2015).
 
[4] Daly Beng, Steven, BA (Hons), ”Automotive  Air Conditioning and Climate Control Systems”, Elsevier, Ltd, (2006).
 
 [5] Subramaniyan, A.S., and Pandian, S., ”A State Space Approach for the Dynamic Analysis of Automotive Air Conditioning System”, International Refrigeration and Air Conditioning Conference, Purdue University, USA, Jul 12-15, (2010).
 
[6] Shiming Deng.Qi Qi, ”Multivariable Control-oriented Modeling of a Direct Expansion (DX) Air Conditioning (A/C)System”, Hung Kong Polytechnic University, International Journal of Refrigeration, Vol. 31, pp. 841-849, (2008).
 
[7] Wang. Liuping, ”Model Predictive Control System Design and Implementation using MATLAB”, School of Electrical and Computer Engineering RMIT University Melbourne, VIC 3000 Australia, Springer, ISSN 1430-9491, (2009).
 
[8] Dasgupta, D., and Michalewicz, Z.,”Evolutionary Algorithms in Engineering Applications”, Springer Science & Business Media, (2013).
 
[9] Sanaye, S., and Dehghandokht, M., ”Temperature Control of a Cabin in an Automobile using Thermal Modeling and Fuzzy Controller”, Applied Energy Vol. 97, pp. 860–868, (2012).
 
[10] Khayyam, H., ”Adaptive Intelligent Control of Vehicle Air Conditioning System”, Applied Thermal  Engineering Vol. 51, pp. 1154-1161, (2013).
 
[11] Zhang, Q., Fiorentini, L., and Canova, M., ”H∞  Robust Control of an Automotive Air Conditioning System”, American Control Conference, Portland, Oregon, USA, June 4-6, (2014).
 
[12] Rasmusen, B., and Allene, A., ”Gain Scheduled Control of an Air Conditioning System using the Youla Parameterization”, Control Systems Technology, IEEE Transactions on, Vol. 18, No. 5, pp. 1216-1225, (2010).
 
[13] Sotomayor, P.O., and Alberto Reis Parise, J., ”Characterization and Simulation of an Open Piston Compressor  for Application on Automotive Air Conditioning Systems Operating with R-134a”, International Journal of Refrigeration, Vol. 53, pp. 1-31, (2015).
 
 
[14] Miranda, Á.G., and Chen, T.S., ”Feasibility Study of a Green Energy Powered Thermoelectric Chip Based Air Aonditioner for Electric Vehicles”, National Tsing Hua University, Vol. 59, pp. 633-641, (2013).
 
[15] Kamar, H.M., and Robiah, A., ”Artificial Neural Networks for Automotive Air Conditioning Systems”, Applied Thermal Engineering, Vol. 50, pp. 63-70, (2013).
 
[16] Chin Chiu, Ch., and Tsai Nan, Ch., ”Near-optimal Order-reduced Control for A/C  System of EVs (Electric Vehicles)”, Energy, Vol. 66, pp. 342-353, (2014).
 
[17] Preglej, A., and Rehrl, J., ”Energy-efficient Fuzzy Model Bases Multivariable Predictive Control of a HVAC System”, Energy & Buildings Vol. 82, pp. 520-533, (2014).
 
[18] Yang, Y., and Wu. Min-Der, ”Temperature Control of the Four-zone Split Inverter Air Conditioners using LMI Expression Based on LQR for Mixed H2/H∞”, Applied Energy Vol. 113, pp. 912–923, (2014).
 
[19]  Khaki Sedigh, A., ”Modern Control System”, 5th Edition, University of Tehran, (2009).
 
[20] Borrelli, F., and Bemporad, A., ”Predictive Control for Linear and Hybrid Systems”, MPC Course Material, Berkeley, October 19, (2015).
 
[21] Zheng, Tao., ”Advance Model Predictive Control”, Intech University, Croatia, (2011).
 
[22] Fayazbakhsh, M.A., and Bahrami, M., ”Comprehensive Modeling of Vehicle Air Conditioning Loads using Heat Balance Method”, Simon Fraser University, USA, http://www.Sae.org, (2013).
 
[23] Ling.Qian, J., and Hwang, Y., ”Thermodynamics Cycle Analysis and Numerical Modeling of Thermoelastic Cooling Systems”, International Journal of Refrigeration, University of Maryland, USA, April, (2015).
 
[24] Chiang, Ng.B, and Mat Darus. I.Z, ”Dynamic Modelling of an Automotive Variable Speed Air Conditioning System using Nonlinear Autoregressive Exogenous Neural Networks”, Applied Thermal Engineering, Vol. 73, pp. 1253-1267, (2014).
 
[25] Iranian Sanden Industries,”Engineering Department Archieve”, http://www.Sanden.ir.
 
[26] Majzoobi, Gh.,”Advanance Numerical Calculations Methods”, 5th Edition, Hamedan Bu Ali Sina University,  (2012).
 
[27] Van Wylen, and Poosti, B., ”Fundamentals of Thermodynamics”, 6th Edition, Sharif University,(2013).
Iranian Journal of Mechanical Engineering Transactions of ISME
Volume 21, Issue 1 - Serial Number 54
System Dynamics and Solid Mechanics
June 2019
Pages 151-175

Files

History

  • Receive Date: 29 November 2017
  • Revise Date: 28 April 2018
  • Accept Date: 09 June 2018

Share

How to cite

Statistics