Variable time domain model prediction energy management method for plug-in hybrid electric vehicle

Abstract

The invention discloses a variable time domain model prediction energy management method for a plug-in hybrid electric vehicle, and belongs to the field of plug-in hybrid electric vehicle energy management. The method mainly comprises the following steps: defining variables in a fuzzy controller, carrying out fuzzy processing on model parameters, defining a fuzzy control rule, and completing the construction of the fuzzy controller; obtaining related input parameters of the fuzzy controller at the current moment, and outputting a predicted time domain increment delta Np through the fuzzy controller; and superposing an initial predicted time domain Np initial and the predicted time domain increment delta Np, updating the predicted time domain Np and acting on an MPC controller, thereby realizing prediction control energy management of the parallel hybrid power vehicle variable time domain model. The problem that the traditional MPC adopting a fixed predicted time domain is difficult toadapt to the working condition change can be effectively solved, the control effect of an energy management strategy is effectively improved, and the fuel economy of the vehicle is further improved.

Description

technical field [0001] The invention belongs to the field of energy management of plug-in hybrid electric vehicles, in particular to a method for predicting energy management of plug-in hybrid electric vehicles with a time-varying domain model. Background technique [0002] The rapid development of the automobile industry has brought convenience to people, but it has also polluted the environment and caused resource shortages. The development of new energy vehicle technology is one of the effective ways to solve these problems, so hybrid vehicles are gradually developed. Compared with traditional hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) have the advantages of being able to connect to an external 220V socket power supply and equipped with large-capacity power batteries to ensure long-term battery life. Focus on the development. PHEV has dual energy sources. In order to better allocate energy sources to reduce fuel consumption, the formulation ...

AI Technical Summary

Problems solved by technology

The energy management strategy based on global optimization can achieve the global optimal solution, but the global operating conditions need to be known, and the calculation time is long; the energy management strategy based on instantaneous optimization has good online application potential and is widely used in the energy of hybrid vehicles. In the design of management strategies, especially model predictive control methods

[0004] The traditional model predictive control methods all use a fixed prediction time domain length, which is determined by researchers relying on experience or experiments, which has poor robustness, is difficult to adapt to changes in working conditions, and is difficult to ensure optimal fuel consumption. economy

Due to the uncertainty and diversity of driver behavior and the complexity of road and weather conditions in the actual driving process of the car, the difficulty of adjusting the control parameters of the model predictive controller is greatly increased.

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