Hierarchical Model Predictive Control for Parallel Hybrid Electrical Vehicles

Abstract

One purpose of the control strategy for a parallel hybrid electric vehicle (PHEV) is to control the state of charge (SOC) of the battery to achieve a maximum powertrain efficiency. Because of the nonlinearity of the powertrain, the control strategy should implement nonlinear optimization in real time. This paper presents a new hierarchical optimal control design to execute real-time optimization on the basis of a model predictive control concept. The proposed control architecture suggests a two-layer control subjected to the related constraints according to the changing rate of different parameters. The prime controller optimizes the best trajectory of the state of charge according to the load detected by a load prediction module, while the second controller will apply the output signal from the prime controller along with the signal from the prediction module and the driver inputs to control the powertrain. Additionally, a new methodology to predict the future load imposed on the wheels is introduced. Through simulation and experiment results, it is shown that the proposed prediction control can effectively reduce fuel consumption and exhaust emission.

Multivariable integral linear quadratic Gaussian robust control of islanded microgrid to mitigate voltage oscillation for improving transient response

“…The slow control loop response and low bandwidth limits the use of these controllers. Hierarchical control method has been developed to ensure the better voltage and frequency regulation of islanded MG . The controller is operated in three stages e.g., primary, secondary and tertiary level of control.…”

Enhancing dynamic operation optimization feasibility for constrained model predictive control systems

“…The hierarchical control system distinguished by time-scale is presented in [20], where the overall convergence properties are established. The application of the proposed model predictive control strategy for parallel hybrid electric vehicles is presented in [21]. A economically optimal process control strategy is proposed in [22], where a dynamic economic optimization problem is solved firstly and the model predictive controller tracks the trajectory with the optimal action.…”

“…Asymptotic convergence of the closed-loop system to the optimal trajectory can be guaranteed, if the model predictive controller is designed appropriately. Nevertheless, the stability of the literatures [20][21][22], which adopts hierarchical control framework, have not been established. The terminal equality constraint has been applied in [11] without stability analysis, which is extremely restrictive compared to the single-layered MPC with the adoption of terminal invariant set constraints.…”

Economic model predictive control for the operation optimization of water distribution networks with risks

“…Benefit from the abilities to handle problems with multivariable and constraints, MPC has been widely applied to many different systems [9][10][11][12][13][14][15][16][17] including WDNs [18]. Besides, for different specific problems, various types of MPC controllers have been studied, such as distributed MPC [19,20], self-stiggered MPC [21], robust MPC [22] and so on.…”