Generally Vehicle Fuel Consumption Models are incapable of accurately predicting Fuel consumption for on road measurement, Most existing fuel consumption models are based on steady-state fuel mapping and these models cannot provide satisfactory predictions for vehicles operating under transient conditions. The objective is to characterize transient engine behaviour for fuel consumption modelling and use it for transient corrections to provide accurate and scalable fuel consumption prediction using on road driving cycle data which will enable to match or predict the output parameters such as fuel economy and the soot collected over the cycle.
B K Ramesh has done his graduation in Electronics and Communication Engineering. He has 25+ years Technology and management experience in Automotive, Robotics and Industrial Control and Communication Systems with leading companies like Bharat Electronics, Motorola, Dearborn Electronics. Currently he is the Co-Founder and Director of IntelliPredikt Technologies and is actively involved in developing Machine Learning based predictive applications for Automotive and Industrial domain.