Hybrid car energy-saving prediction control method based on road gradient information

Abstract

The invention relates to a hybrid car energy-saving prediction control method based on road gradient information. The method comprises the steps of acquiring real road position information, altitude and terrain information by virtue of a google map as system input, and establishing a real road gradient model; establishing a system dynamics model, and decoupling the system dynamics model to obtain an independent three-degree-of-freedom system model; embedding the real road gradient model to a hybrid car dynamics state space model to obtain a system mathematic model; realizing a control method by adopting a model prediction control theory, solving an optimum control problem by utilizing a numerical value simulation solution, adjusting and optimizing the energy flow of the hybrid car in an online mode according to the real car driving condition to obtain the optimum performance of a hybrid car system, adopting a planetary gear mechanism as an electronic stepless speed changer, enabling an engine to work at an optimum work site, and predicting a target storage battery charge state by utilizing road gradient information. The energy flow of the hybrid car is online adjusted, so that a purpose of saving energy and reducing emission can be realized.

Description

technical field [0001] The invention relates to an energy-saving predictive control method for a hybrid electric vehicle based on road slope information, in particular to a real-time optimal control method for a hybrid electric vehicle. Background technique [0002] The increasingly severe global energy and environmental situation, especially the huge impact of the international financial crisis on the automobile industry, has pushed countries around the world to accelerate the strategic transformation of the automobile industry. In order to develop more energy-saving and environment-friendly automobiles and solve the above two problems, hybrid electric vehicles have been industrialized at present. Compared with traditional vehicles, hybrid vehicles have the redundancy of battery and fuel dual system drive. Using this redundancy, the operating point of the driving device can be adjusted to the optimal position, so as to achieve the goal of energy saving and emission reductio...

AI Technical Summary

Problems solved by technology

The traditional global optimal control algorithm dynamic programming and Pontryagin minimum principle control methods cannot achieve real-time optimal control because they need to know all future working conditions in advance.

Traditional rule-based control strategies fail to maximize efficiency

General feed-forward control (assuming a constant vehicle speed pattern) cannot achieve real-time optimal

The traditional instantaneous optimal control parameters are too affected by changes in future vehicle operating conditions and cannot meet the control performance

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