PMP-principle-based dual-state adaptive control method of plug-in hybrid power system

Abstract

The invention relates to a PMP-principle-based dual-state adaptive control method of a plug-in hybrid power system. The PMP-principle-based dual-state adaptive control method mainly includes the following steps that S1, according to the data recorded by a vehicle-mounted GPS system and an actual operation scenario of a vehicle, a comprehensive working condition including the speed and a road slopeis constructed; S2, according to parameters of the whole vehicle, power parts and transmission parts, a longitudinal vehicle dynamics model and a control-oriented engine, motor and battery circuit model are established; S3, a battery capacity attenuation model considering calendar aging is constructed; S4, a pontryagin minimum principle is used for determining a reasonable compromise proposal between battery aging and energy consumption offline; S5, based on the pontryagin minimum principle, an adaptive control strategy is developed; S6, reference trajectories of battery states of charge andbattery aging states are planned; and S7, the dual-state adaptive control method is tested and corrected. According to the PMP-principle-based dual-state adaptive control method, a new idea is provided for the multi-objective adaptive control of the plug-in hybrid power system, so that the comprehensive operation cost of the vehicle is minimized.

Description

technical field [0001] The invention belongs to the field of new energy vehicles and relates to a two-state self-adaptive control method for a plug-in hybrid power system based on the PMP principle. Background technique [0002] Cars are already an indispensable tool for people to travel. With the increase in the number of cars, it has brought greater pressure on the energy that was originally in short supply. Automobile emissions have become the largest source of pollution in various countries. CO and NO emitted from automobiles x And some particulate emissions have had a very bad impact on the environment on which people live. Under the dual pressure of energy crisis and environmental pollution, research on new energy vehicles has become an urgent task at present. [0003] Plug-in hybrid electric vehicle (PHEV) can combine the advantages of hybrid electric vehicle and pure electric vehicle, and has become the most popular new energy vehicle product at present, but the ex...

AI Technical Summary

Problems solved by technology

The rule-based strategy is mainly determined based on engineering experience. It is simple to implement and fast to calculate, so it is widely used. However, due to the limitations of engineering experience, the potential of power system energy saving and emission reduction cannot be fully utilized, and there is no way to ensure that the battery works in an optimal operating state. ; Although model predictive control is an advanced control method recognized by the industry, the power system of PHEV is a complex nonlinear system, which makes it difficult to implement model predictive control and often cannot meet the time response requirements of the system; the equivalent fuel consumption is the smallest The strategy can make up for the deficiency of the rule-based strategy to a certain extent, and has the characteristics of small amount of calculation and obvious optimization effect, and has been valued by major car companies and research institutions. However, this method can only be optimized for a single goal (such as economy), unable to optimize multi-objective collaboratively

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