scholarly journals A Novel Nonlinear Optimal Control Approach for the Dynamic Process of a Hybrid Electric Vehicle Equipped with Electromechanical Transmission

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Changle Xiang ◽  
Donghao Zhang ◽  
Hailiang Zheng ◽  
Lijin Han ◽  
Kun Huang
Keyword(s):  
Optimal Control ◽  
Electric Vehicle ◽  
Dynamic Process ◽  
Hybrid Electric Vehicle ◽  
Nonlinear Optimal Control ◽  
Feasible Region ◽  
Control Variables ◽  
Control Approach ◽  
Hybrid Electric ◽  
Optimal Control Approach

Coordinatively controlling the engine and several motor/generators (MGs) during a dynamic process is a challenging problem because they are coupled together by the electromechanical transmission (EMT) system and all of them have strong nonlinear characteristics. We develop a novel nonlinear optimal control approach based on the multiobjective dynamic optimization model of the hybrid electric vehicle (HEV), which is equipped with an EMT system. In this approach, the current states of the components are obtained by using the state observation algorithm based on Kalman filtering; the future states of the components and the feasible region of the control variables are estimated by using the dynamic prediction algorithm based on the nonlinear model of the EMT system. Then, the control variables are achieved by using the optimal decision algorithm based on the hierarchical optimization and nonlinear programming, and the influence of the model error and the external disturbance are modified by using the feedback compensation algorithm. The simulation results illustrate the efficiency of the proposed control approach, and the test results verify its real-time performance.

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.

Optimal Control for Hybrid Electric Vehicle with Hydromechanical Transmission

2021 ◽  
Author(s):  
Aleksei V. Makarov ◽  
Valeriy G. Makarov ◽  
Tatiana V. Makarova ◽  
Vladislav V. Bataev
Keyword(s):  
Optimal Control ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric

A Nonlinear Optimal Control Approach for the Vertical Take-off and Landing Aircraft

2021 ◽  
pp. 2150012
Author(s):  
G. Rigatos
Keyword(s):  
Optimal Control ◽  
Control Method ◽  
Nonlinear Optimal Control ◽  
The Body ◽  
Algebraic Riccati Equation ◽  
Control Input ◽  
Time Step ◽  
Control Approach ◽  
Vtol Aircraft ◽  
Optimal Control Approach

The paper proposes a nonlinear optimal control approach for the model of the vertical take-off and landing (VTOL) aircraft. This aerial drone receives as control input a directed thrust, as well as forces acting on its wing tips. The latter forces are not perpendicular to the body axis of the drone but are tilted by a small angle. The dynamic model of the VTOL undergoes approximate linearization with the use of Taylor series expansion around a temporary operating point which is recomputed at each iteration of the control method. For the approximately linearized model, an H-infinity feedback controller is designed. The linearization procedure relies on the computation of the Jacobian matrices of the state-space model of the VTOL aircraft. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the aerial drone, under model uncertainties and external perturbations. For the computation of the controller’s feedback gains, an algebraic Riccati equation is solved at each time-step of the control method. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the VTOL aircraft, under moderate variations of the control inputs. The stability properties of the control scheme are proven through Lyapunov analysis.

A nonlinear optimal control approach for chaotic finance dynamics

2017 ◽  
Author(s):  
G. Rigatos ◽  
P. Siano ◽  
V. Loia ◽  
A. Tommasetti ◽  
O. Troisi
Keyword(s):  
Optimal Control ◽  
Nonlinear Optimal Control ◽  
Control Approach ◽  
Optimal Control Approach
Sign in / Sign up

Export Citation Format

Share Document