Cloud Based Framework for OBD-II System Diagnosis Using Recursive Least Square Parametric Estimation

Cloud computing technologies are embodied with automotive sector copiously. It aids in using data and computing services to manage information, communication, and computing, through Internet-based apps and online digital services. A cloud computing-based framework is suitable for developing and deploying simulation models to study, analyse and optimise the vehicle performance. The framework proves functional in collecting vehicle data, processing and then using them for datadriven or model-based development to deliver a complete software solution. Server-less cloud computing technologies with storage and function triggers form the architecture. The paper outlines a data-driven model of a Three-Way Catalyst (TWC) to test the cloud framework as an end-to-end solution. The model estimates a metric to quantify the oxygen storage capacity of the TWC over the air. This metric is an online adaptive gain, estimated through system diagnosis using the Recursive Least Squares method. This is followed by a Decision Tree Classification algorithm to classify these metrics according to their useful life. Thus, realising TWC health diagnostics.