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Energy conservation for refrigeration systems by means of hybrid fuzzy adaptive control techniques

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Abstract

Most vapour compression refrigeration systems still operate under on–off control, although it is well known that the application of any other control method could result in improved COP. For that purpose, the present paper experimentally studies the use of adaptive fuzzy hybrid control and design of experiments techniques, as well as the application of the response surface methodology, in a 5-ton vapour compression system with a variable speed compressor and an electronic expansion valve. Evaporation temperature and evaporator overall conductance were found to be the most relevant input parameters to the fuzzy hybrid control system, where the optimal trajectory was sought without taking into account the elapsed time. Results have shown that the knowledge of the most relevant parameter of the system allowed for the control system to seek high COP zones. It has been found that this type of technique does not jeopardize the control performance, which remains robust.

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Abbreviations

A:

Scheme of the control related to the number of steps of the EEV

B:

Scheme of the control related to the compressor speed

COP:

Coefficient of performance (–)

e(k):

Inlet error of the adaptive fuzzy PI control (A)

ea(k):

Accumulated inlet error of the fuzzy PI control (A)

∆e(k):

Change in inlet error of the adaptive fuzzy PD control (B)

∆e :

Mean absolute change in inlet error of the adaptive fuzzy PD control (B)

f e(k):

Estimated frequency (Hz)

f r(k):

Real frequency (Hz)

FREQ:

Frequency of compressor (Hz)

IAE:

Integral of the absolute error value

ITAE:

Integral of the absolute error value time weighted

k :

Refer to instant of time

KKv :

Adaptive mechanism of internal factor of the adaptive fuzzy PD control (B)

k pc :

Gain of the fuzzy PI control (A)

Kv :

Sensibility scale factor of the adaptive fuzzy PD control (B)

N:

Negative set of the adaptive fuzzy PD control (B)

\(\dot{m}_{r22}\) :

Refrigerant mass flow rate (kg/s)

NEEV:

Number of steps of the electronic expansion valve (–)

R :

Positive set of the adaptive fuzzy PD control (B)

\(P_{1}\) :

Compressor suction pressure (kPa)

\(P_{2}\) :

Compressor discharge pressure (kPa)

\(P_{3}\) :

Condensation pressure (kPa)

\(P_{4}\) :

Pressure measured downstream the electronic expansion valve (kPa)

\(\dot{Q}_{{\text{ev}}}\) :

Cooling capacity (kW)

∆t:

Period of time (s)

t a :

Settlement time period (s)

\(T_{{\text{cd}}}\) :

Condensation temperature (°C)

\(T_{{\text{ev}}}\) :

Evaporation temperature (°C)

\(T_{1}\) :

Refrigerant temperature at the evaporator outlet (°C)

\(T_{5}\) :

Water temperature at the evaporator outlet (°C)

\(T_{8}\) :

Water temperature at the evaporator inlet (°C)

\(\Delta T_{{\text{sc}}}\) :

Degree of subcooling (°C)

\(\Delta T_{{\text{sh}}}\) :

Degree of superheat (°C)

UA :

Heat exchanger conductance (kW/m2 K)

U c :

Output signal of the fuzzy adaptive PD controller (B)

U k :

Output signal of the fuzzy PI controller (A)

U 2 :

Output signal to the actuator of the fuzzy PI controller (A)

|Uc|:

Mean absolute exit signal of the fuzzy adaptive PI control (B)

u(e):

Pertinence function inlet error of the adaptive fuzzy PI control (A)

u(ea):

Pertinence function inlet error accumulated of the adaptive fuzzy PI control

UA :

Heat exchanger overall conductance (kW/K)

\(\dot{W}\) :

Power consumption (kW)

Z:

Zero set of the adaptive fuzzy PD control (B)

CCF:

Central composite design—face centred

DOE:

Design of experiments

EEV:

Electronic expansion valve

FET:

Field effect transistor

LN:

Mean large negative

LP:

Large positive

MN:

Medium negative

MP:

Medium positive

MSR:

Methodology of response surface

N:

Negative

P:

Positive

PID:

Proportional integral derivative controller

PLC:

Programmable logic controller

QQR:

Optimal lineal quadratic control

SISO:

Traditional control for one entrance and one exit

SN:

Small negative

SP:

Small positive

TXV:

Thermostatic expansion valve

Z, ZO:

Zero

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Acknowledgments

The authors gratefully acknowledge the support of CNPq, CAPES, FAPERJ and FAPEMIG.

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Authors and Affiliations

  1. School of Mechanical Engineering, Federal University of Uberlandia, Av. Joao Naves de Avila, 2121, Santa Monica, Uberlandia, MG, 38400-902, Brazil

    Enio Pedone Bandarra Filho & Oscar Saul Hernandez Mendoza

  2. Engineering Department, Universidad Francisco de Paula Santander, Avenida Gran Colombia No. 12E-96, San Jose de Cucuta, NS, Colombia

    Francisco Ernesto Moreno Garcia

  3. Department of Mechanical Engineering, Pontifícia Universidade Católica do Rio de Janeiro, Rua Marques de Sao Vicente, 225, Gavea, Rio de Janeiro, RJ, 22451-900, Brazil

    Jose Alberto Reis Parise

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  1. Enio Pedone Bandarra Filho
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  2. Oscar Saul Hernandez Mendoza
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  3. Francisco Ernesto Moreno Garcia
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  4. Jose Alberto Reis Parise
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Correspondence to Enio Pedone Bandarra Filho.

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Technical Editor: Francis HR Franca.

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Bandarra Filho, E.P., Hernandez Mendoza, O.S., Moreno Garcia, F.E. et al. Energy conservation for refrigeration systems by means of hybrid fuzzy adaptive control techniques. J Braz. Soc. Mech. Sci. Eng. 38, 1753–1766 (2016). https://doi.org/10.1007/s40430-016-0538-2

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