Review of Artificial Intelligent Algorithms for Engine Performance, Control, and Diagnosis

This paper reviews the artificial intelligent algorithms in engine management. study provides a clear image of current state affairs for past 15 years and fresh insights improvements future directions field The scope this comprises three main aspects to be discussed, namely, performance, control, diagnosis. first is associated with need control basic characteristics that prove working properly, emission fuel economy. Engine refers ability identify fulfill requirements derived from emissions, durability. In part, hybrid electric vehicle (HEV) application transient operations are discussed. Lastly, diagnosis entails assessment techniques can used problems solve them accordingly. misfire detection, knock intake system leakage will evaluated. neural network provide efficient results terms economy as easily achievable. However, when it comes diagnosis, fuzzy logic rule its strong robustness networks limited efficiency due complex nature processes presence big data, instance, HEVs control. That has brought forward usage reinforcement learning novel machine recent maximize highlighted following part. PRISMA methodology was justify reference selection review.