Practical model-based control for low emission and low cost diesel engines

Grant number: LP160100650 | Funding period: 2016 - 2020



This project aims to develop and implement robust multivariable model predictive control algorithms for low emission and low cost diesel engines that reduce calibration effort. Legislative and increasing consumer requirements demand better control approaches than have been deployed in production vehicles to date, and motivate the use of model based techniques to meet performance and emissions specifications. However, current model-based controllers amplify the calibration effort and increase development costs as the tuning parameters are not related to time domain specifications. The anticipated outcome is new model based control architectures that improve diesel engine operation and reduce ..

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University of Melbourne Researchers