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Conference paper

Research on cascaded bidirectional DC-DC converter based on model predictive control

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1Hubei Key Laboratory for High-efficiency Utilisation of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Nanli Road, Hubei 430068, China

Published
28 February 2019
Pages
346-354
Received
28 February 2019
DOI
10.65582/set.2018.102
Access
Open access, © 2018 Copyright WSSET
Download PDF9 pages · 787 KB

Abstract

The traditional double closed loop PID control method of bidirectional Buck/Boost DC-DC converter is more mature and has better control effect, but the process of setting up PI parameters is rather tedious. The power prediction control based on the model predictive control (MPC) thought is simple and the controller is easy to realise. But the large amount of computation in the control process leads to slower response of the system. Therefore, traditional PID control or power predictive control is difficult to achieve good performance for cascaded bidirectional DC-DC converters. In this paper, a model predictive control method based on reference power is proposed, which takes the duty ratio as input and has weight factor. This method has the advantages of simple and intuitive control process and good control effect. Through the establishment of the system model, the calculation of the reference power, the evaluation of the performance index and the optimisation of the switching state, the performance of the system is optimised, which makes the converter have a faster response speed and a smaller voltage overshoot. In view of the above control methods, a simulation model is built to verify the results. The results show that compared with the traditional PID control method and power prediction control method, the proposed method can improve the dynamic and static performance of the system. The results verify the effectiveness of the proposed control method.

Keywords. Bidirectional DC-DC converter; model predictive control; PID control; duty cycle

© 2018 Copyright WSSET

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