Optimal control of temperature and fuel consumption for soaking pits in a steel plant-a distributed parameter approach

2007 ◽  
Vol 9 (4) ◽  
pp. 417-442 ◽  
Author(s):  
D. R. Yang ◽  
F. Y. Wang ◽  
K. S. Chang ◽  
Won-Kyoo Lee
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Steel Plant ◽  
Distributed Parameter ◽  
Parameter Approach

scholarly journals Optimal Control for a Hydraulic Recuperation System Using Endoreversible Thermodynamics

2021 ◽  
Vol 11 (11) ◽  
pp. 5001
Author(s):  
Robin Masser ◽  
Karl Heinz Hoffmann
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Energy Savings ◽  
Combustion Engine ◽  
Mechanical Energy ◽  
Hydraulic Systems ◽  
Commercial Vehicles ◽  
Hybrid Drive ◽  
Environmental Considerations ◽  
Onboard System

Energy savings in the traffic sector are of considerable importance for economic and environmental considerations. Recuperation of mechanical energy in commercial vehicles can contribute to this goal. One promising technology rests on hydraulic systems, in particular for trucks which use such system also for other purposes such as lifting cargo or operating a crane. In this work the potential for energy savings is analyzed for commercial vehicles with tipper bodies, as these already have a hydraulic onboard system. The recuperation system is modeled based on endoreversible thermodynamics, thus providing a framework in which realistic driving data can be incorporated. We further used dissipative engine setups for modeling both the hydraulic and combustion engine of the hybrid drive train in order to include realistic efficiency maps. As a result, reduction in fuel consumption of up to 26% as compared to a simple baseline recuperation strategy can be achieved with an optimized recuperation 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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