Fuel cell anode pressure dynamic matrix control method based on multi-model feedforward

Abstract

The invention discloses a fuel cell anode pressure dynamic matrix control method based on multi-model feedforward. A proton exchange membrane fuel cell is regarded as a three-input one-output multivariable object, object input includes a path of controlled quantity and two paths of disturbance quantities, a step response model of an output quantity to the controlled quantity and the disturbance quantities is identified at different steady-state operating condition points, and in control, an identification model for calculating a control increment and a corresponding DMC controller are switchedaccording to the actual operating condition of the fuel cell, thereby ensuring optimality of controlled quantity output. Compared with traditional predictive control, the method provided by the invention is applicable to a wider operating condition range, and disturbance is small during model switching. In addition, the method can also effectively suppress influence of a vent valve position and load current disturbance, control an anode pressure tracking set value, reduce differential pressure stress on the proton exchange membrane, prolong the service life of the proton exchange membrane, and ensure efficient, stable and safe operation of the fuel cell.

Description

technical field [0001] The invention relates to new energy automatic control technology, in particular to a fuel cell anode pressure dynamic matrix control method based on multi-model feedforward. Background technique [0002] With the continuous improvement of environmental protection and sustainable development requirements, the efficiency of traditional thermal power generation technology is limited by the Carnot cycle, and SO x and NO x Such by-products will cause environmental problems, but subject to high energy demand, the development of clean energy technology as a supplement is an effective way. The proton exchange membrane fuel cell technology directly converts the chemical energy in the fuel into electrical energy through electrochemical reactions. It has the characteristics of high energy conversion efficiency, high energy density, no pollution emission, low operating noise and low temperature, and is suitable for commercialization. promote. Most proton exchan...

AI Technical Summary

Problems solved by technology

However, since MPC is a model-based predictive control method, its control effect depends on the accuracy of the control model. When the dynamic characteristics of the controlled object are complex, the establishment of the control model requires a large amount of prior knowledge, regardless of the mechanism modeling or data identification. Difficulty

At the same time, the controller parameters of the MPC control strategy are often preset and will not be adjusted after being put into operation.

For proton exchange membrane fuel cells, when the exhaust valve position changes, the dynamic characteristics of the anode pressure will also change accordingly, and the effect of the fixed parameter controller will deteriorate, and even cause the system to oscillate

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