Model predictive control-based power management strategy for two-mode power-split HEVs

The power management strategy is a key technique of power-split HEVs (PSHEV). The rule-based control strategy which is applied usually and easily implemented can’t achieve the optimal state of the power distribution. The normal optimization strategies are depending on the driving cycles and have lots of numerical calculation such as the dynamic programming, or can’t enhance the fuel economy much more remarkably limited by the short sight decision such as the equal fuel consumption minimum strategy. The Model Predictive Control (MPC)-based power management strategy with the fuel economy as the chief objective is proposed for a two-mode PSHEV. Some state variables of the powertrain and the vehicle are predicted by the predictive model. The real-time optimization with infinite horizon is used for the optimal decision. The predictive model including the battery state and the output torque provides the priori knowledge for the optimal calculation. The optimization problem is converted to a linear quadratic optimal control problem for enhancing the solution efficiency which can be calculated real-time. The MPC controller is tested by the system simulation for validating the optimization effect in the condition of NEDC driving cycle. The battery SOC is remained near the balance value and the fuel economy is enhanced. The engine is operating in the optimal economy zone and the 100km fuel consumption is decreased by 13.4% comparing with the rule-based control strategy. The feasibility of the MPC-based power management strategy is validated by the controller design and the system simulation. The power management strategy can enhance the fuel economy effectively and has been proved that it is a potential real-time optimization method for the power distribution of the PSHEV.