scholarly journals Optimal control of marine propulsion diesel engine during transient loading operation

2008 ◽  
Author(s):  
Γιώργος Παπαλάμπρου
Keyword(s):  
Optimal Control ◽  
Diesel Engine ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Transient Loading ◽  
Marine Propulsion

Η μείωση των εκπομπών καπνού και η βελτίωση απόκρισης φορτίου σε ένα ναυτικό υπερτροφοδοτούμενο κινητήρα Diesel, σε μεταβατική λειτουργία που περιλαμβάνει απότομες αυξήσεις στο φορτίο, αποτέλεσαν το αντικείμενο αυτής της εργασίας. Χρησιμοποιήθηκε σύστημα ελέγχου με μοντέλο πρόβλεψης (Model Predictive Control-MPC), σε ένα σύστημα εξωτερικής παροχής παροχής πεπιεσμένου αέρα απευθείας στο δοχείο αέρα. Ταυτόχρονα, στόχος ήταν η αποφυγή πάλμωσης του συμπιεστή του υπερπληρωτή, ανάντι του δοχείου αέρα.

Integrated Load-Split Scheme for Hybrid Ship Propulsion Considering Transient Propeller Load and Environmental Disturbance

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Nikolaos Planakis ◽  
George Papalambrou ◽  
Nikolaos Kyrtatos
Keyword(s):  
Diesel Engine ◽  
Model Predictive Control ◽  
Real Time ◽  
Predictive Control ◽  
Engine Performance ◽  
Hybrid Plant ◽  
Environmental Disturbance ◽  
Time Operation ◽  
Marine Propulsion ◽  
Real Time Operation

Abstract This work addresses the design and experimental implementation in real-time of an integrated predictive load-split management system for the transient and fluctuating propeller load sharing. Control-oriented modeling of the power system was performed based on experimental data gathered from the hybrid plant and on first principles for the diesel engine behavior and battery charging. Propulsion plant and environmental disturbance models are developed to simulate realistic marine load application. A nonlinear model predictive control (NMPC) scheme is proposed for the optimal transient power-split problem of a hybrid diesel-electric marine propulsion plant. The NMPC scheme directly controls the torque output of the diesel engine and the electric motor/generator ensuring that certain constraints concerning the system overloading are met, avoiding fast accelerations and load fluctuations of the diesel engine that affect engine performance. To achieve offset-free model predictive control (MPC) control, an observer is developed to provide the propeller law parameter to the NMPC for load estimation. The control system was experimentally tested in real-time operation. Results showed that controller rejected load disturbances and maintained the desired rotational speed of the powertrain as well as the desirable state of charge (SOC) in battery within the power plant limits, achieving smooth power transitions and mitigation of power fluctuations of the diesel engine.

An Economic Model Predictive Control Approach for Wind Power Smoothing and Tower Load Mitigation

2018 ◽  
Author(s):  
Mohamed M. Alhneaish ◽  
Mohamed L. Shaltout ◽  
Sayed M. Metwalli
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Model Predictive Control ◽  
Wind Power ◽  
Predictive Control ◽  
Economic Model ◽  
Control Algorithm ◽  
Fatigue Load ◽  
Economic Model Predictive Control ◽  
Control Framework

An economic model predictive control framework is presented in this study for an integrated wind turbine and flywheel energy storage system. The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a standard wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is studied. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load at the cost of a minimal reduction of the wind energy harvested.

Direct Optimal Control and Model Predictive Control

2017 ◽  
pp. 263-382 ◽  
Author(s):  
Mario Zanon ◽  
Andrea Boccia ◽  
Vryan Gil S. Palma ◽  
Sonja Parenti ◽  
Ilaria Xausa
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Direct Optimal Control

scholarly journals Sensitivity Analysis of the Battery Model for Model Predictive Control: Implementable to a Plug-In Hybrid Electric Vehicle

2018 ◽  
Vol 9 (4) ◽  
pp. 45 ◽  
Author(s):  
Nicolas Sockeel ◽  
Jian Shi ◽  
Masood Shahverdi ◽  
Michael Mazzola
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Predictive Control ◽  
Hybrid Electric Vehicle ◽  
Control Solution ◽  
Current Time ◽  
Battery Model ◽  
Hybrid Electric

Developing an efficient online predictive modeling system (PMS) is a major issue in the field of electrified vehicles as it can help reduce fuel consumption, greenhouse gasses (GHG) emission, but also the aging of power-train components, such as the battery. For this manuscript, a model predictive control (MPC) has been considered as PMS. This control design has been defined as an optimization problem that uses the projected system behaviors over a finite prediction horizon to determine the optimal control solution for the current time instant. In this manuscript, the MPC controller intents to diminish simultaneously the battery aging and the equivalent fuel consumption. The main contribution of this manuscript is to evaluate numerically the impacts of the vehicle battery model on the MPC optimal control solution when the plug hybrid electric vehicle (PHEV) is in the battery charge sustaining mode. Results show that the higher fidelity model improves the capability of accurately predicting the battery aging.

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