An experimental-based artificial neural network performance study of common rail direct injection engine run on plastic pyrolysis oil

Figures & data

Figure 1. Experimental set up for plastic pyrolysis oil

Table 1. Fuel properties

Property	PPO	Diesel
Density (kg/m^3)	835.5	840
Kinematic viscosity (cSt)	2.52	2
Flash point (^oC)	40	50
Fire point (^oC)	43	56
Calorific value (kJ/kg)	40248	44500
Cloud point(^oC)	-	2
Pour point (^oC)	-	−16
Cetane number	46	55

Table 2. Properties of blended fuels

Blends	PPO: Diesel 70:30
Properties
Density (kg/m^3)	830
Kinematic viscosity (cSt)	2.4
Flash point (°C)	45
Fire point (°C)	52
Calorificvalue (kJ/kg)	40,671
Cetane number	47

Figure 2. Schematic diagram of the CRDI experimental test rig

Table 3. Specifications of CI engine

Make and model	Kirloskar, TV1
Engine type	Single cylinder four stroke direct injection diesel engine
Orientation	Vertical
Ignition system	Compression Ignition
Bore x Stroke	87.5 mm x 110 mm
Displacement volume	660 cc
Compression ratio	17.5: 1
Arrangement of valves	Overhead
Combustion chamber	Open Chamber (Direct injection)
Rated power	5.2 KW @1500 RPM
Cooling Medium	Water cooled
Air measuring manometer
Made	MX 201
Type	U- Type
Range	100 – 0 – 100 mm
Eddy current dynamometer
Model	AG – 10
Type	Eddy current
Maximum	7.5 (kW at 1500–3000 RPM)
Flow	Water must flow through Dynamometer during the use
Dynamometer arm length	0.180 m
Uel measuring unit range	0–50 ml

Table 4. Uncertainties for the present investigation

Measured variable	Accuracy (±)
Load (N)	0.1
Engine speed (rpm)	1
Temperature, (^oC)	1
Fuel consumption (g)	0.1
Measured variable	Uncertainty (%)
HC	±1.2
CO	±2.5
NOx	±2.3
Smoke	±2.0
Calculated parameters	Uncertainty (%)
BTE (%)	±1.2
HRR (J/^oCA)	±1.3

Table 5. Specification of Exhaust Gas analyser

Type	DELTA 1600 S
Object of measurement	Carbon Monoxide (CO), Carbon dioxide(CO2) and Hydrocarbon (HC)
Range of measurement	HC = 0 to 2000ppm as C2H4 CO = 0 to 10% CO2 = 0 to 16 % O2 = 0 to 21% NOX = 0 to 5000 ppm (as Nitric Oxide)
Accuracy	HC = ± 30 ppm HC CO = ± 0.2% CO CO2 = ± 1% CO2 O2 = ± 0.2% O2 NOX = ± 10% ppm NO
Resolution	HC = 1 ppm CO = 0.01% Vol CO2 = 0.1% Vol O2 = 0.01% Vol NOX = 1 ppm
Warm up time	10 min (self-controlled) at 20^o C
Speed of Response Time	Within 15 sec. for 90% response
Sampling	Directly sampled from tail pipe
Power source	100 to 240 V AC/50 HZ
Weight	800 g
Size	800 mm x 210 mm x 50 mm

Table 6. Specifications of Smoke Meter

Type	HARTRIDGE SMOKEMETER-4
Object of measurement	Smoke
Measuring range opacity	0–100%
Accuracy	± 2% relative
Resolution	0.1%
Smoke length	0.43 m
Ambient Temperature Range	−5 ^o C to +45^o C
Warm up time	10 min (self-controlled) at 20^o C
Speed of Response Time	Within 15 sec. for 90% response
Sampling	Directly sampled from tail pipe
Power supply	100 to 240 V AC/50 HZ
Size	100 mm x 210 mm x 50 mm

Table 7. Experimental data for modelling of ANN

Trial no.	Parameter settings			Characteristics
	IT (t) (^obTDC)	IOP (p) (Bar)	EGR (e) (%)	BTE (%)	Smoke (HSU)	HC (ppm)	NOx (ppm)	Pmax (bar)	HRR (J/^0CA)
1	15	800	15	28	53	51	600	69	66
2	15	800	20	27.5	56	54	502	67.5	64
3	15	800	25	26.92	63	58	403	65	60
4	15	900	15	28.5	50	49	620	72	68
5	15	900	20	28	54	52	520	70	66
6	15	900	25	27.4	60	56	421	67	63
7	15	1000	15	28.3	52	50	608	70	67
8	15	1000	20	27.8	55	53	510	68	65
9	15	1000	25	27.1	62	57	411	66	62
10	10	800	15	28.5	50	46	622	72	68
11	10	800	20	28	53	49	515	70	66
12	10	800	25	27.4	58	54	410	67	62
13	10	900	15	29.2	47	42	650	74	70
14	10	900	20	28.6	50	46	540	72	68
15	10	900	25	28	55	51	428	69	65
16	10	1000	15	28.8	49	45	630	73	69
17	10	1000	20	28.3	52	48	526	71	67
18	10	1000	25	27.7	56	53	414	69	64
19	5	800	15	28.1	52	50	605	70	67
20	5	800	20	27.6	55	53	507	68	65
21	5	800	25	27.0	62	57	408	66	61
22	5	900	15	28.6	49	48	625	73	69
23	5	900	20	28.1	53	51	524	71	67
24	5	900	25	27.5	59	55	425	67.5	64
25	5	1000	15	28.14	51	49	612	71	68
26	5	1000	20	27.91	53	52	515	69	66
27	5	1000	25	27.1	60	56	416	67	63

Table 8. Network developed for MATLAB

MATLAB
Topology	3 inputs 5 outputs and 2 hidden layers with 9 hidden neurons in each layer
Data	Training Subject: 70% randomly selected observation data
	Test Subject: 30% randomly selected observation data
Activation	Log-sigmoid
Training algorithm	Feed Forward Back-Propagation
Loss function	Minimum MSE
Stopping criteria	Stop the network training when the variation error starts increasing

Table 9. Fraction of variance [R²], RMSE and MAPE values

Parameters	R^2	RMSE	MAPE (%)
BTE	0.99938	1.024	0.8
HC	0.99567	0.899	1.1
NOx	0.99862	0.725	0.45
PP	0.99999	0.135	0.61
HRR	0.99999	0.239	0.72

Figure 3. Architecture of the proposed ANN

Figure 4. (a) Variation of BTE with IT and EGR (b) Correlation coefficient for BTE

Figure 5. (a) Variation of HC with IT and EGR (b) Correlation coefficient for HC

Figure 6. (a) Variation of NOx with IT and EGR (b) Correlation coefficient for NO_x

Table 10. Comparison of results with current emission regulation

Emissions	CO gms/Kwhr	HC gms/Kwhr	NOx gms/Kwhr	PM gms/Kwhr
BS-IV	1.5	0.96	3.5	0.02
Expt. Results	1.4	0.977	3.6	0.02

Figure 7. (a) Variation of PP with IT and EGR (b) Correlation coefficient for PP

Figure 8. (a) Variation of HRR with IT and EGR. (b) Correlation coefficient for HRR

Table

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