ABSTRACT:

Idle speed control is a landmark application of feedback control in automotive vehicles that continues to be of significant interest to automotive industry practitioners, since improved idle performance and robustness translate into better fuel economy, emissions and drivability. In this paper, we develop a model predictive control (MPC) strategy for regulating the engine speed to the idle speed set-point by actuating the electronic throttle and the spark timing. The MPC controller coordinates the two actuators according to a specified cost function, while explicitly taking into account constraints on the control and requirements on the acceptable engine speed range, e.g., to avoid engine stalls. Following a process proposed here for the implementation of MPC in automotive applications, an MPC controller is obtained with excellent performance and robustness as demonstrated in actual vehicle tests. In particular, the MPC controller performs better than an existing baseline controller in the vehicle, is robust to changes in operating conditions, and to different types of disturbances. It is also shown that the MPC computational complexity is well within the capability of production electronic control unit and that the improved performance achieved by the MPC controller can translate into fuel economy improvements.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE :Sentence Vector Model Based on Implicit Word Vector Expression - 2018ABSTRACT:Word vector and topic model can help retrieve data semantically. However, there still are several problems: 1) antonyms share high similarity
PROJECT TITLE :Research on Kano Model Based on Online Comment Data Mining - 2018ABSTRACT:The opinion mining and also the sentiment analysis of the network comment are the key points of the text analysis. By excavating the comment
PROJECT TITLE :A Generative Model for Sparse Hyperparameter Determination - 2018ABSTRACT:Sparse autoencoder is an unsupervised feature extractor and has been widely used in the machine learning and knowledge mining community.
PROJECT TITLE :Phase Transitions and a Model Order Selection Criterion for Spectral Graph Clustering - 2018ABSTRACT:One in every of the longstanding open issues in spectral graph clustering (SGC) is the thus-called model order
PROJECT TITLE :On Distributed Linear Estimation With Observation Model Uncertainties - 2018ABSTRACT:We contemplate distributed estimation of a Gaussian supply during a heterogenous bandwidth constrained sensor network, where the

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry