Multivariate analysis of diesel engine performance: Integrating PCA and TOPSIS for comprehensive evaluation and ranking of operating parameters

Abstract. This study presents a comprehensive analysis of diesel engine performance through the integration of Principal Component Analysis (PCA) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The aim is to evaluate and rank various operating parameters influencing diesel engine performance, including BTE, specific fuel consumption, and emissions levels. Through PCA, underlying patterns and relationships among these parameters are identified, reducing the dimensionality of the dataset while retaining essential information. Subsequently, TOPSIS methodology is employed to determine the relative importance of each parameter and rank diesel engine configurations or operating conditions based on their performance. By combining these techniques, this study provides a robust framework for decision-making in diesel engine optimization and design, offering insights into the most influential factors driving engine performance and emissions.