Researches On Model Predictive Control Of Dual Active Bridge Converters

With the development of renewable energy power generation technology and the emphasis on green and environmentally friendly energy,the related applications of distributed power generation,energy storage system,and electric vehicle have developed rapidly.Energy interface converters are required for energy transfer and conversion in these applications.The isolated dual active bridge(DAB)converter has the characteristics of high power density,high efficiency,bidirectional energy transfer and easy cascade and parallel connection.It is one of the most promising circuit topologies in medium-high voltage power conversion systems.High dynamic response speed and high performance are the two most important control objectives of DAB converter and the key to its application in relevant real-world scenarios.In order to improve the dynamic response speed and efficiency of DAB converter,the performance optimization of DAB converter is studied in this paper.Firstly,the topology and modulation method of DAB converter are introduced.The switch modes of DAB converter under single-phase modulation are analyzed in detail.Based on the expressions of transmission power and current stress,the characteristics of DAB converter are analyzed.The space average model of discrete time state of output voltage of DAB converter is established as the basis of predictive control of DAB converter model.Secondly,in order to improve the dynamic response performance of DAB converter,the incremental model predictive control is studied based on the discrete state space average model to solve the problem that the traditional model predictive control is affected by circuit parameters,power switch voltage drop and dead-time,and the output voltage has a steady-state error due to the mismatch of the circuit model.In order to further improve the stability of the algorithm,the constraints of control quantity are introduced,Hildreth quadratic programming algorithm is used to optimize the value function of inequality constraints.The simulation verifies that the constrained incremental model predictive control can effectively improve the dynamic performance of DAB converter while suppressing the steady-state error.Then,in order to improve the efficiency of DAB converter,a current stress minimization optimization method based on dual phase shift modulation is proposed to solve the problem of high current stress under SPS modulation.Two working modes,0<D1<D2<1 and 0<D1<D2<1,are also considered.The optimal shift comparison is solved by Lagrange multiplier method to obtain the global current stress.By combining the current stress optimization strategy with incremental model predictive control,a current stress optimization based incremental model predictive control strategy is presented,and simulation results show that the strategy can improve the efficiency and dynamic performance of DAB converter at the same time.Finally,this paper establishes a DAB converter hardware experimental platform,and introduces the hardware design ideas,including the selection and design of main circuit topology,signal conditioning and driver circuit.On the basis of hardware experimental platform,the current stress optimization based incremental model predictive control algorithm is validated,and the validity of the control method is proved.