DISTURBANCE REJECTION MODEL PREDICTIVE CONTROL FOR RENEWABLE ENERGY VEHICLE CHARGING RECTIFIER

Zhang Jianwei; Cao Qiaosen; Chang Haichen; Tian Guizhen; Liu Guangchen

doi:10.19912/j.0254-0096.tynxb.2022-1478

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (1) : 545-551. DOI: 10.19912/j.0254-0096.tynxb.2022-1478

DISTURBANCE REJECTION MODEL PREDICTIVE CONTROL FOR RENEWABLE ENERGY VEHICLE CHARGING RECTIFIER

Zhang Jianwei^1,2, Cao Qiaosen¹, Chang Haichen³, Tian Guizhen^1,2, Liu Guangchen^1,2

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Abstract

This paper focuses on the model predictive charging control strategy for renewable energy vehicle charging （G2V） rectifier. The traditional model predictive control （MPC） algorithm requires accurate system model parameters. Therefore, if the model parameters used in the controller are inaccurate, the performance may deteriorate, affecting the charging control performance of the rectifier. To address this issue, the MPC based on the extended state observer （ESO） for G2V charging rectifier is proposed. The parameter mismatch is regarded as the extended disturbance term and estimated by the extended state observer （ESO）. The proposed method only utilizes system input and output data and does not need accurate system parameters. When there exists a parameter mismatch, it can be regarded as a disturbance and be estimated by ESO, thus achieving an accurate estimation of the predicted current. Therefore, the robustness of the controller against the parameter mismatch is enhanced. Simulation and experimental results verify the feasibility and effectiveness of the proposed MPC based on ESO.

Key words

model predictive control / renewable energy vehicles / disturbance rejection / robustness / extended state observer / model parameters mismatch

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Zhang Jianwei, Cao Qiaosen, Chang Haichen, Tian Guizhen, Liu Guangchen. DISTURBANCE REJECTION MODEL PREDICTIVE CONTROL FOR RENEWABLE ENERGY VEHICLE CHARGING RECTIFIER[J]. Acta Energiae Solaris Sinica. 2024, 45(1): 545-551 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1478

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