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, which belongs to the field of plug-in hybrid electric vehicle energy management. The method comprises the following steps of constructing a fuzzy logic controller, determining a track of a battery state of charge reference SOCr, solving a local optimal solution in the determined prediction time domain length Np by using a model prediction control method and taking fuel consumption as an optimization target, and updating a vehicle state, obtaining a predicted time domain increment deltaNp through a fuzzy logic controller according to the deviation deltaSOC between the actual power battery state of charge SOC and the battery state of charge reference SOCr and the model prediction control single-step calculation time Tc, superposing the predicted time domain increment deltaNp with the initial predicted time domain Npinitial, and updating the predicted time domainlength Np. By adopting the method, the problem that the traditional MPC adopting a fixed predicted time domain is difficult to adapt 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 (Plug-inHybridElectric Vehicle, PHEV) has the advantages of being able to connect to an external 220V socket power supply and equipped with a large-capacity power battery to ensure long-term battery life. develop. PHEV has dual energy sources. In order to better allocate energy sources to reduce fuel consumption, the...

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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