modelling of an automotive air conditioning system using anfis

Predicted E d,tot
(kW)
Predicted W comp
(kW)
Predicted COP
Predicted Q evap
(kW)
Predicted T evap,ao
(K)
specific enthalpies of the moist air at the inlet and outlet
of the evaporator, and enthalpy of the condensate
leaving the evaporator, thus having several sources of
uncertainty. Consequently, the resulting high uncertainty
influences the training process, and causes a poorer
performance for the Q evap predictions.
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270
r = 0.968
MRE = 0.23%
RMSE = 0.83 K
R 2 = 0.9999
+2%
-2%
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Experimental T evap,ao
(K)
Figure 2. The ANFIS predictions for the air dry bulb
temperature at the evaporator outlet vs. experimental values.
8
7
6
r = 0.970
MRE = 4.48%
RMSE = 0.28 kW
R 2 = 0.9975
+10%
power is also not as good as those for T evap,ao . In fact, the
ANFIS yields even slightly poorer performance for
W comp predictions compared with that for Q evap ones, as
reported in Figure 4.
As shown in Figure 5, the ANFIS predictions for the
coefficient of performance result in a MRE of 3.86%, an r
value of 0.966 and an R 2 value of 0.9981. Because COP
depends on two parameters, namely the cooling capacity
load and compressor power, it has several uncertainty
sources involved in the evaluation of these parameters.
This leads to training of the proposed ANFIS using data
with high uncertainty, which in turn causes a relatively
poor statistical performance for the COP predictions.
Figure 6 shows that the ANFIS predictions for the total
rate of exergy destruction in the refrigeration circuit of the
system have a comparable accuracy with Q evap , W comp
and COP predictions. However, as seen Figure 7, the
ANFIS outstandingly predicts the compressor discharge
temperature with a MRE of 0.28%, an r value of 0.988
and an R 2 value of 0.9999. The excellent ANFIS
predictions for T dis are due to the high accuracy of the
temperature measurements performed in the experiments.
The discharge temperature is an indicator of the
compressor durability. The possibility of the thermal
destruction of the compressor oil increases with rising
discharge temperature.
5
4
-10%
3.5
3
r = 0.966
MRE = 3.86%
RMSE = 0.11
R 2 = 0.9981
+10%
3
3 4 5 6 7 8
Experimental Q evap
(kW)
Figure 3. The ANFIS predictions for the cooling capacity vs.
experimental values.
2.5
2
-10%
3,5
3
2,5
r = 0.969
MRE = 5.28%
RMSE = 0.15 kW
R 2 = 0.9957
+10%
1.5
1.5 2 2.5 3 3.5
Experimental COP
Figure 5. The ANFIS predictions for the coefficient of
performance vs. experimental values.
3.5
r = 0.973
2
1,5
-10%
3
2.5
MRE = 4.96%
RMSE = 0.14 kW
R 2 = 0.9962
+10%
1 1.5 2 2.5 3 3.5
Experimental W comp
(kW)
Figure 4. The ANFIS predictions for the compressor power
vs. experimental values.
2
1.5
-10%
Because the evaluation of the compressor power
requires the refrigerant mass flow rate and enthalpies of
the refrigerant at the evaporator inlet and outlet, the
accuracy of the ANFIS predictions for the compressor
1.5 2 2.5 3 3.5
Experimental E d,tot
(kW)
Figure 6. The ANFIS predictions for the total rate of exergy
destruction in the refrigeration circuit of the refrigeration
system vs. experimental values.
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