Optimal control of intelligent vehicle longitudinal dynamics via hybrid model predictive control

2019 ◽  
Vol 112 ◽  
pp. 190-200 ◽  
Author(s):  
Xiaoqiang Sun ◽  
Yingfeng Cai ◽  
Shaohua Wang ◽  
Xing Xu ◽  
Long Chen
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Hybrid Model ◽  
Predictive Control ◽  
Intelligent Vehicle ◽  
Longitudinal Dynamics

scholarly journals Hybrid Model Predictive Control of a Variable Displacement Engine Mode Management

2020 ◽  
Vol 53 (2) ◽  
pp. 14047-14054
Author(s):  
Pawel Majecki ◽  
Michael J. Grimble ◽  
Ibrahim Haskara ◽  
Chen-Fang Chang
Keyword(s):  
Model Predictive Control ◽  
Hybrid Model ◽  
Predictive Control ◽  
Variable Displacement

scholarly journals Shipboard Power Management for Failure Mode Using the Hybrid MPC Approach

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2915
Author(s):  
Xiuyan Peng ◽  
Bo Wang ◽  
Lanyong Zhang ◽  
Peng Su
Keyword(s):  
Model Predictive Control ◽  
Power Systems ◽  
Power Management ◽  
Failure Mode ◽  
Hybrid Model ◽  
Predictive Control ◽  
Minimum Principle ◽  
Management Control ◽  
Shipboard Power ◽  
Two Stages

Shipboard integrated power systems, the key technology of ship electrification, call for effective failure mode power management control strategy to achieve the safe and reliable operation in dynamic reconfiguration. Considering switch reconfiguration with system dynamics and power balance restoration after reconfiguration, in this paper, the optimization objective function of optimal management for ship failure mode is established as a hybrid model predictive control problem from the perspective of hybrid system. To meet the needs for fast computation, a hierarchical hybrid model predictive control algorithm is proposed, which divides the original optimization problem into two stages, and reduces the computation complexity by relaxing constraints and the minimum principle. By applying to a real-time simulator in two scenarios, the results verify the effectivity of the proposed method.

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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