Selecting Optimal Combination of Operating Parameters of VCR Diesel Engine Adopting AHP

Objective: To select the optimal combination of Variable compression ratio (VCR) diesel engine operating parameters using Sesbania aculeate biodiesel. Method/Statistical Analysis: The Analytical Hierarchy Process(AHP)approach is a mathematical approach used to find the optimal combination of VCR diesel engine operating parameters and the best blend of Sesbania aculeata biodiesel. Findings: It provides the alternatives and also the visualization of various criteria and their interrelations. The alternatives are ranked by measuring the criteria and their relative importance. The permanent concept helps for the better appreciation of criteria and considers the problem selection as it contains possible criteria components and their relative importance. It was found that the optimal combination of 100% load, 17.5 compression ratio and SAOME20 blend is the optimal combination of operating parameters of the VCR diesel engine. Novelty/Improvement: The best combination of operating parameters can be found systematically and logically using AHP.


Introduction
It has been proven for many years that alternative fuels can fulfil the demand of energy as the petroleum based fuels are depleting day by day. In the present days, alternative fuels have become a very potential source of energy. Generally diesel engines have a high compression ratio.The fuel injected at high compression ratio (CR), the ignition take place before an adequate air-fuel mixture is formed and leads to heterogeneous combustion. The result shows, the formation NO x because of the insufficient oxygen. When the compression ratio reduced, the temperature and pressure are reduced and leads in reduction of NO x -soot emission. The engine best performance can be obtained by the optimal combination of operating parameters. The parameters like load, injection timing, compression ratio and injection pressure influence the engine performance.
In 1 the multi attribute decision making methods are proposed in conjunction with real time requirements. In 2-3 the different techniques were extensively applied to numerous diverse decision making problems.
In 4 , the Analytical Hierarchy Process (AHP) was proposed. In 5 , a number of functional characteristics make AHP a useful methodology. In 6 , the vital characteristics of AHP included the ability to handle decision situations involving subjective judgements, multiple decision makers and the ability to provide measures of consistency of preferences. In 7 , the AHP can efficiently deal with the objective or subjective attributes. In 8 , AHP adopted for selection of materials for drinking water. In 9 , AHP adapted to selection of manufacturing technologies. In 10 , adapted AHP in modelling a team and in turn selection of a team leader.
The aim of this study is to select the optimum combination of operating parameters such as fuel blend, load and compression ratio to get the better performance of the diesel engine using AHP.
have been installed to the engine to measure various parameters such as fuel consumption, air consumption, and speed. Also a 5 gas analyser is attached to the test rig for emission measurement. Standard operating procedure has been followed to conduct performance and emission test using diesel and blends of S.aculeata biodiesel are SAOME10 (10% S.aculeata biodiesel + 90% diesel), SAOME20 (20% S.aculeata biodiesel + 80% diesel), SAOME30 (30% S.aculeata biodiesel + 70% diesel) and SAOME40 (40% S.aculeata biodiesel + 60% diesel).

Methodology of AHP
The step wise procedure of AHP approach is given below:

Step 1: Attributes Matrix
The attributes matrix consist of alternatives, attributes and their relative importance 11 . In in this approach the blends of S.aculeata biodiesel, load and compression ratio are considered as alternatives. BSFC, BTE, NO x , HC, CO, CO 2 and Smoke are the attributes. The decision matrix of given problem which having 60 experiments shown in Table 1.

Step 2: Normalization of Decision Matrix
The Normalization process used for makes all the attributes values in to non-dimensional. The procedure of the normalization as given. d ij = c ij /max j (c ij ); when the j th attribute is found to be beneficial (1) d ij = min j (c ij )/c ij ; when the j th attribute is found to be non beneficial.
The decision matrix with normalized values shows in Table 2.
In this study, The BTE is beneficial and BSFC.NO X , CO, HC, smoke and CO 2 are non beneficial.

Step 3: Relative Importance Values for Attributes
Using AHP 11 , the decision makers analyses the attributes and assign the relative importance values (off diagonal element. The pair wise comparison matrix N, as shown in eq. (3) is formed with p ij and p ji where p ij = 1 when i = j and p ji = 1/p ij .  Table 3 shows the scale for pair wise comparison. The pair wise comparison matrix shown in this study shown in eq. (4), the judgment of relative importance values of attribute is obtained by the consistency check 11 . The consistency ratio should be less than 0.1 as per the decision making method. The consistency ratio was found for the Pair wise comparison matrix shown in eq. (4) is 0.052.

Step 4: Matrix for Attributes of Alternatives
The attributes matrix of each alternative is formed with help of normalized values as diagonal and off diagonal elements is taken from eq. (4) and this matrix is represented as R in eq. (5).    Two attribute are equal importance 1 1 One attribute is moderately important than that of other 2 ½ One attribute is strongly important than the other 3 1/3 One attribute is very strongly important than the other 4 ¼ One attribute is exactly important than the other 5 1/5 A computer program was generated to simplify the Per(C) calculation Step 6: Rank of Alternative By using the step 5 calculates the index scores for all the 60 experiments and sorts either in ascending or descending order. The alternative with higher index score is ranked as higher from the alternatives.
The index score for alternative 1 is presented. The alternative selection attribute matrix is given as (step 4), The alternative selection attribute matrix is shown in eq. (6). . Step

5: Permanent of Alternative Selection Attribute Matrix
The permanent function (Per C) or determinant also called index score and is calculated as follows.   R =  0 119  3  2  3  2  4  3  0 33 0 378  2  2  2  3  2  0 50 0 50 0 706  3  2  4 The calculated index score of experiment no.1 is 27 as shown in eq. (8). Likewise, the index scores for all given experiments are calculated and tabulated to rank them and are shown in Table 4.

Conclusion
The general procedure of the uniqueness of the decision making AHP approach by using the number of selection of qualitative and quantitative attributes the combination of optimal operating parameters of VCR diesel engine were found to be combination of 100% load, 17.5 compression ratio and SAOME20 blend.