| With the development of micro-grid and energy storage system,IBDC has been widely studied and applied in recent years.DAB has become the most commonly used topology of IBDC because of its modular symmetrical structure,bi-directional power transmission capability,fast dynamic response and easy implementation of soft switching.In this paper,the DAB drive control strategy for energy storage system is improved.Firstly,a mathematical model of current stress based on the unified form of high frequency link is proposed.Then,on the basis of this mathematical model,a current stress minimization control strategy based on improved grey wolf algorithm with wide gain range is proposed.Finally,a comprehensive optimization study is carried out on the dualobjective performance of double active bridges.The main research contents are as follows:(1)A mathematical model of current stress of double active bridges based on the unified form of high frequency link is proposed.According to the analysis of the existing literature,it is found that the piecewise linear calculation method is mostly used to analyze the performance index of DAB,and the modeling process of the traditional mathematical model of optimizing phase shift control is complex and difficult to implement in practice.Therefore,a unified model of current stress high frequency link is proposed based on the working characteristics and modal analysis of DAB under the general waveform of phase shift control.This method transforms several DAB mathematical equations under different working modes into a multi-dimensional mathematical equation with nonlinear constraints,which reduces the difficulty of establishing the optimal control strategy of DAB time-domain model.(2)A current stress minimization control strategy based on improved grey wolf optimization algorithm with wide gain range is proposed.When the voltage between the primary and secondary sides of the transformer does not match in DAB,the current stress of the converter will increase sharply,resulting in a decline in the efficiency of the converter,and even damage the switching devices in severe cases.In view of this phenomenon,a current stress minimization control strategy based on improved grey wolf algorithm with wide gain range is proposed in this paper.First of all,considering the shortcomings of the standard grey wolf algorithm,which is easy to fall into local optimization and premature convergence,an improved grey wolf algorithm is proposed to prevent the algorithm from falling into local optimal solution by introducing nonlinear shrinkage factor.And the simplex method is used to save the optimal solution of each iteration,and the worst solution is replaced by the optimal solution to avoid the loss of the optimal solution and obtain the global optimal solution of the equation.Then,a combination of optimized phase shift control and constant voltage charging is used to achieve single-objective optimized charging control.Finally,simulation experiments are carried out to verify the effectiveness and feasibility of the method.(3)A two-objective comprehensive optimization strategy of high-frequency link unified model for energy storage system is proposed in this paper.Most of the existing energy storage system optimization control strategies are focused on DAB single performance indicators,and traditional phase shift control is used to fail to achieve simultaneous optimization of conduction loss and switching loss.In order to solve the above problems,a dual-objective comprehensive optimization strategy based on constant current charging is proposed in this paper.Firstly,the expression of the current stress is used as the objective function to construct the optimization problem according to the soft switch constraint condition and solve the global optimal solution.Then,the optimal charging control is realized by combining the optimal phase shift control based on full ZVS current stress with the constant current charging mode.Finally,the full ZVS current stress optimization strategy is proved by simulation experiments,and the optimization effects of different optimization strategies are studied. |
