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浙江大学学报(工学版)
Journal of ZheJiang University (Engineering Science)  2026, Vol. 60 Issue (6): 1329-1338    DOI: 10.3785/j.issn.1008-973X.2026.06.020
    
Voltage model predictive control of DAB converter considering current stress optimization
Yanxia SHEN(),Shuo WEI,Wei ZHANG
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
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Abstract  

An adaptive discrete control set model predictive control (ADCS-MPC) strategy was proposed in order to improve the efficiency and the dynamic performance of output voltage control in a dual active bridge (DAB) converter. The relationship between transmission power and phase shift ratio under dual phase shift (DPS) control was analyzed, and the Karush–Kuhn Tucker (KKT) condition method was used to solve the optimal phase shift ratio relationship across the full power range. A DAB voltage prediction model was established, and a finite discrete control set was generated through phase shift discretization. An adaptive step size dynamic adjustment mechanism was introduced to adjust the control set in real time based on voltage error. A cost function was designed, and the optimal phase shift was determined with the goal of minimizing the cost function. The optimal phase shift ratio was calculated by combining the relationship between the optimal phase shift ratio solution and the optimal phase shift in order to reduce current stress. A 100 W DAB converter prototype was built, and comparative experiment was conducted for validation. Results show that this strategy improves converter efficiency by optimizing current stress, and enhances dynamic response performance through the rolling optimization characteristic of MPC.

Key words： dual active bridge converter      current stress optimization (CSO)      model predictive control (MPC)      dual phase shift (DPS)      dynamic response     
Received: 10 July 2025      Published: 06 May 2026
CLC:  TM 46  
Fund:  国家自然科学基金资助项目(62473177)；江苏省自然科学基金资助项目(BK20231492).
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Yanxia SHEN
Shuo WEI
Wei ZHANG
Cite this article:

Yanxia SHEN,Shuo WEI,Wei ZHANG. Voltage model predictive control of DAB converter considering current stress optimization. Journal of ZheJiang University (Engineering Science), 2026, 60(6): 1329-1338.

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https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2026.06.020     OR     https://www.zjujournals.com/eng/Y2026/V60/I6/1329


考虑电流应力优化的DAB电压模型预测控制

为了提升双有源桥式(DAB)变换器的效率与输出电压控制的动态性能，提出自适应离散控制集模型预测控制(ADCS-MPC)策略. 分析双重移相(DPS)控制下传输功率和移相比的关系，利用Karush-Kuhn Tucker (KKT)条件法求解全功率范围内的最优移相比关系解. 建立DAB电压预测模型，通过相移离散化生成有限离散控制集，引入自适应步长动态调整机制，根据电压误差实时调整控制集. 设计代价函数，以代价函数最小为目标确定最佳相移，结合最优移相比关系解与最佳相移的关系，计算最优移相比，降低电流应力. 搭建100 W DAB变换器样机，开展对比实验验证. 结果表明，该策略通过优化电流应力提升了变换器效率，利用MPC滚动优化特性提升了动态响应性能.


关键词： 双有源桥式变换器,  电流应力优化(CSO),  模型预测控制(MPC),  双重移相(DPS),  动态响应 
Fig.1 Topology of DAB converter
Fig.2 Typical waveform of DAB converter with DPS
模式电感电流
模式1$ \begin{aligned}{i}_{{L}}({t}_{1})&=-\dfrac{n{V}_{2}}{4{f}_{\text{s}}{L}_{\text{r}}}[r-1-(r+1){D}_{1}+2{D}_{2}]\\{i}_{{L}}({t}_{2})&=\dfrac{n{V}_{2}}{4{f}_{\text{s}}{L}_{\text{r}}}[1+r(2{D}_{2}-1-{D}_{1})]\\{i}_{{L}}({t}_{3})&=\dfrac{n{V}_{2}}{4{f}_{\text{s}}{L}_{\text{r}}}[(r-1){D}_{1}+r(2{D}_{2}-1)+1]\\{i}_{{L}}({t}_{4})&=\dfrac{n{V}_{2}}{4{f}_{\text{s}}{L}_{\text{r}}}[(r-1)(1-{D}_{1})+2{D}_{2}]\end{aligned} $
模式2$ \begin{aligned}{i}_{{L}}({t}_{1})&={i}_{\textit{L}}({t}_{2})=-\dfrac{n{V}_{2}}{4{f}_{\text{s}}{\mathrm{L}}_{\text{r}}}[(r-1)(1-{D}_{1})]\\{i}_{{L}}({t}_{3})&=\dfrac{n{V}_{2}}{4{f}_{\text{s}}{L}_{\text{r}}}[(1-r)(1-{D}_{1})+2{D}_{2}]\\{i}_{{L}}({t}_{4})&=\dfrac{n{V}_{2}}{4{f}_{\text{s}}{L}_{\text{r}}}[(r-1)(1-{D}_{1})+2{D}_{2}]\end{aligned} $
Tab.1 Inductance current at each moment in half cycle
Fig.3 Relationship between phase shift and phase shift ratio with DPS
Fig.4 Reduced-order model of DAB converter
Fig.5 Operation principle of ADCS-MPC
Fig.6 Control block diagram of ADCS-MPC
Fig.7 Flow chart of ADCS-MPC algorithm
Fig.8 Experimental platform of DAB converter
参数数值参数数值
$ {V}_{1} $/$ {\mathrm{V}} $30n1
$ {V}_{2} $/$ {\mathrm{V}} $10~30$ {L}_{\mathrm{r}} $/μH60
$ {f}_{\mathrm{s}} $/kHz20$ {C}_{1} $,$ {C}_{2} $/μF470
Tab.2 Main parameter of DAB prototype
Fig.9 Steady-state waveform of DAB when voltage ratio is 1.5 and per-unit power is 0.24
Fig.10 Steady-state waveform of DAB when voltage ratio is 1.5 and per-unit power is 0.5
Fig.11 Steady-state waveform of DAB when voltage ratio is 1.5 and per-unit power is 0.9
P0方法$ i_{L_{\mathrm{p}}} $/A$ \eta $/%
0.24PI-SPS2.684.9
0.24PI-DPS2.090.4
0.24ADCS-MPC-DPS1.991.4
0.50PI-SPS3.290.2
0.50PI-DPS3.091.3
0.50ADCS-MPC-DPS3.091.9
0.90PI-SPS5.185.8
0.90PI-DPS4.885.7
0.90ADCS-MPC-DPS4.986.9
Tab.3 Steady-state performance comparison of control method under different power level
Fig.12 Experimental comparison result of efficiency and current stress when voltage ratio is 2
Fig.13 $ {V}_{2\_ \mathrm{ref}} $ step transient waveform with DPS
Fig.14 Load step transient waveform with DPS
控制方法实验工况tr/msVos/V
输入电压前馈的虚拟功率控制[16]$ \begin{aligned}{V}_{1}&=80\;{\mathrm{V}},{{V}}_{2}& =60\; \mathrm{V}\\ {P}_{0}&=0.4\sim 0.6 \end{aligned} $586.7
虚拟直接功率控制[17]$ \begin{aligned}{V}_{1}&=70\;{\mathrm{V}},{{V}}_{2}& =49\;\mathrm{V}\\ {P}_{0}&=0.4\sim 0.6 \end{aligned} $123.0
滑模控制[19]$ \begin{aligned}{V}_{1}&=40\;{\mathrm{V}},{{V}}_{2}& =200\; \mathrm{V}\\ P&=324\sim 64\;\mathrm{W} \end{aligned} $605.0
ADCS-MPC$ \begin{aligned}{V}_{1}&=30\;{\mathrm{V}},{{V}}_{2}& =20\; \mathrm{V}\\ {P}_{0}&=0.24\sim 0.90 \end{aligned} $5.42.4
Tab.4 Performance comparison of four control methods
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