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Model Predictive Controlled Dual Active Bridge Converter with Efficiency Optimization and Fast Dynamic Response

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Abstract

In this paper, combine hybrid modulation strategy and Model predictive control (MPC) for Dual active bridge (DAB) converter is presented to achieve high efficiency of wide load range and fast dynamic response for bidirectional power flow conversion. Through offline optimization of DAB converter at steady state, only one control variable is used to reduce computational burden, and without complex algorithm in the cost function for MPC strategy. In addition, based on the simpilified average mode of DAB converter, different predictive currents are derived. Besides, three scenarios of smooth mode transition for the hybrid control strategy is given in detail. Thus, fast dynamic response for mode transition and high efficiency for wide range is guaranteed by the proposed strategy. Finally, an experimental prototype of DAB converter is built and tested for verifying the steady state and fast transition with different operation modes performance.

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Abbreviations

DAB:

Dual active bridge

EV:

Electric vehicles

MVDC:

Medium voltage direct current grids

HVDC:

High voltage DC transmission

SPS:

Single phase shift

EPS:

Extended phase shift

DPS:

Dual phase shift

TPS:

Triple phase shift

RMS:

Root-mean-square

ZVS:

Zero voltage switching

PPL:

Pulsed power loads

PI:

Proportional-integral

OCFF:

Output current feedforward

VDPC:

Virtual direct power control

SMC:

Sliding mode control

FDM:

Fundamental duty modulation

MPC:

Model predictive control

d 1 , d 2 , d 3 :

The duty ratio between different bridge

fs :

Switching frequency of DAB converter

i HV1, i HV2 :

Averaging input and output current of H-bridge

C in , C out :

Input capacitor and output capacitor

i ac1 ,i ac2 :

Inductor current in H-bridge

v ac1 ,v ac2 :

Mid-point voltage in H-bridge

i co :

Output capacitor current

V in ,V o :

Input voltage and output voltage

d 1,α, d 1,β, d 2,α :

Controll variables decomposed by d1,d2,d3 using Fourier Transformer

\(\left| {I_{ac1} } \right|\) :

Absolute value of fundamental component inductor current

d q :

The only control variable with efficient optimazation

M :

Voltage gain

N :

Transformer turn ratio

i < HV1 > , i < HV2 > :

Input current of primary bridge and output current of second bridge

V HV2 :

Output voltage

V HV2_ref :

Reference value of output voltage

i load :

Load current

ct :

Cost function

α :

Weighting factor

T :

Switching period

dq[load]:

Currently working point

∆s :

Changing step in each switching peried

∆vs :

The finest step in each switching peried

λ :

Number of discretized elements divided by dq

T tr :

Transient time

∆ adp :

The adaptive step

V tol :

Tolerate voltage

V ∆ :

Adjusted coefficient

\(P_{tran}\) :

The transfer power

P max :

The maximum power of DAB converter

K :

Normalized power

d q_select :

The control variable which will minmising ct

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China under Grant 62271117.

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Authors and Affiliations

  1. School of Automation Engineering, Sichuan Province Engineering Technology Research Center for Electric Vehicle Driving System and Safety, University of Electronic Science and Technology of China (UESTC), Chengdu, 611731, China

    Zhangyong Chen

  2. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, 611731, China

    Zhanchao Zheng, Xuan Tang & Yunfeng Wu

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  1. Zhangyong Chen
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Chen, Z., Zheng, Z., Tang, X. et al. Model Predictive Controlled Dual Active Bridge Converter with Efficiency Optimization and Fast Dynamic Response. J. Electr. Eng. Technol. 19, 521–534 (2024). https://doi.org/10.1007/s42835-023-01569-x

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