Browse Publications Technical Papers 2021-26-0409

Engine Friction Optimization Approach using Multibody Simulations 2021-26-0409

From April 2020 BS 6 phase 1 legislation has come into place in India. Further in the coming years from 2022 CAFÉ norms will be implemented targeting 122 g/km CO2 fleet emissions. Also, from year 2023 onwards BS 6 phase 2 emission legislation with RDE cycle will be in place. With the expensive exhaust after-treatment system needed for meeting BS 6 norms, the Diesel powertrain based vehicles cost has increased further creating even further price difference to it’s Gasoline fuel variants. Additionally, the price difference between Diesel and Gasoline fuel is always reducing. These reasons have changed the buying pattern of passenger cars in India, with vehicle powered by engine<1.5 L displacements have gradually shifted predominantly to Gasoline powertrain. The impact of this will further stress the fleet CO2 emissions for manufacturers. Apart from new technologies being considered for reducing CO2, optimization of engine friction has always been on the top of the list to improve efficiency and fuel economy. This paper outlines the application of advanced simulation methodology for the optimization of engine friction. For this study the most selling 1.4 L Gasoline engine from the Indian market was selected. The work highlights on how to identify the friction optimization potential for the selected engine using the new simulation methodology developed. The method includes building and calibrating multi-body simulation (MBS) models using subsystem level measurement or database information and split the friction shares of the engine subsystems and components using physical friction modeling approaches. The simulation approach is capable to model the friction for new components or system developments. The simulation models have been validated to test data showing excellent correlation. We shift the necessity of hardware friction testing and hardware iterations more towards a frontloading approach using CAE methods.


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