Quest Journals Journal of Research in Mechanical Engineering Volume 8 ~ Issue 1 (2022) pp: 12-23 ISSN(Online) : 2321-8185 www.questjournals.org *Corresponding Author: Mohamed I. Amin 12 | Page Research Paper Sensitivity Study of Indicated Mean Pressure to Working Cycle Parameters in Spark Ignition Engines Mohamed I. Amin 1 , and Waleed Neseem 2 1,2 (Mechanical Power Department, Military Technical College, Cairo, Egypt.) Corresponding Author: Mohamed I. Amin, ABSTRACT: Increasing power to weight ratio is a main target for all engine designers. One of the most important parameters that assess the engine output power is the indicated mean pressure (IMP). The purpose of this work is to investigate the effect of working cycle parameters on IMP and how it is sensitive to these parameters’ changes. It is shown that IMP is a function of five working cycl e parameters namely pressure at the end of suction stroke(S), compression polytropic exponent (n), compression ratio (ε), Pressure rise ratio (λ), and expansion polytropic exponent (m). The analysis indicated that change of IMP is highly sensitive to expansion polytropic exponent change (m) more than other controlling parameters. Also, the sensitivity of IMP is not the same for wide ranges of other working cycle parameters change. By using regression, new correlations between IMP sensitivity and working cycle parameters have been introduced with lowest R 2 = 0.987 and error in a range of 7%. Such relations could be a useful tool for engine designers to increase IMP and power to weight ratio. KEYWORDS: Sensitivity Study, Indicated Mean Pressure, Internal Combustion Engines, and Spark Ignition Engines. Received 04 Jan, 2022; Revised 13 Jan, 2022; Accepted 15 Jan, 2022 © The author(s) 2022. Published with open access at www.questjournals.org I. INTRODUCTION Indicated mean pressure (IMP) is a parameter that measures the ability of engine to do work and it is independent on engine volume [1]. It expresses the work done by unit volume of engine and can be calculated by dividing the work done in one cycle by swept volume [2]. Previous works show that IMP is a function of many working cycle parameters, and as increasing of IMP means engine power to weight increase, it is convenient to determine which one of these working parameters has dominant effect on IMP. This encourages conducting a comprehensive sensitivity analysis of IMP to working cycle parameters. Sensitivity analysis is a technique which findings the dependence of a system output on a specific input to evaluate the hazardousness of a certain strategy, in other words, it is the investigation of a mathematical model or system output uncertainty due to different sources of uncertainty in its inputs [3]. Sensitivity analysis approaches can be classified to mathematical, statistical, and graphical [4]. Mat hematical methods assess sensitivity of a model output to a series of an input. These methods do not focus on the variation in the output due to inputs variance, but they can measure the influence of variation of input range on the output [5]. Sometimes, mathematical methods can be useful in showing the most significant inputs [6]. Statistical methods model’s inputs are allocated probability distributions and considering the effect of change in inputs on the output distribution [7, 8]. Depending on the method, one or more inputs are varied at a time. Statistical methods permit to detect the effect of interactions among many inputs. Graphical methods offer illustration of sensitivity in graph forms, charts, or surfaces, and usually used to give visual sign of how an output is affected by change in inputs [9]. There are different sensitivity methods which can be followed to investigate certain model or system. Nominal Range Sensitivity or local sensitivity analysis estimates the effect of individual input variation over a reasonable range on model outputs, while keeping all other inputs at constant values [10]. The change in the model output due to the change in the input variable is concerned to the sensitivity of the model to that specific input variable [5]. Nominal range sensitivity analysis is a relatively simple method that is easily to apply but interactions among inputs are difficult to get [4]. Automatic Differentiation Technique (AD) is a technique for estimating local sensitivities for large models by calculating first-order partial derivatives of outputs with respect to small changes in the inputs [4, 11-