A Backword Discrete State Event Driven Simulation Method for Power Electronics Based on Finite State Machine
Li Boyang, Zhao Zhengming, Tan Tian, Yang Yi, Jiang Ye, Yuan Liqiang
State Key Lab of Control and Simulation of Power Systems and Generation Equipments Department of Electrical Engineering Tsinghua University Beijing 100084 China
Abstract:A backward discrete state event driven (BDSED) simulation method based on the backward quantized state system (BQSS) algorithm is proposed in this paper, to solve the difficult problem of rigid state equations in power electronics systems. BDSED method is implicit, and the key point is to select the correct combination of quantization values, which allows the state variables to approach their quantization values. Each state variable has two possible quantization values at each step, thus enumeration is infeasible in complex systems. What’s more, taken into account the constraint and mutual coupling between state variables when determining their quantization values, the question becomes quite difficult. Thus, an implementation approach of BDSED based on finite state machine is proposed in this paper. The simulation algorithm is tested in a converter circuit with non-ideal device models. Simulation results show that BDSED based on finite state machine can efficiently select the combination of quantization values, and its simulation efficiency is obviously higher than DSED as well as traditional time-slicing ODE methods when solving stiff systems such as power converters.
李帛洋, 赵争鸣, 檀添, 杨祎, 蒋烨, 袁立强. 后向离散状态事件驱动电力电子仿真方法[J]. 电工技术学报, 2017, 32(12): 42-49.
Li Boyang, Zhao Zhengming, Tan Tian, Yang Yi, Jiang Ye, Yuan Liqiang. A Backword Discrete State Event Driven Simulation Method for Power Electronics Based on Finite State Machine. Transactions of China Electrotechnical Society, 2017, 32(12): 42-49.
[1] 陈建业. 电力电子电路的计算机仿真[M]. 北京: 清华大学出版社, 2003. [2] Kofman E, Junco S. Quantized-state systems: a DEVS approach for continuous system simulation[J]. Simulation Transactions of the Society for Modeling & Simulation International, 2001, 18(3): 123-132. [3] Kofman E. Discrete event simulation of hybrid systems[J]. SIAM Journal on Scientific Computing, 2004, 25(5): 1771-1797. [4] Kofman E. A second-order approximation for DEVS simulation of continuous systems[J]. Simulation Transactions of the Society for Modeling & Simulation International, 2002, 78(2): 76-89. [5] Ndez J, Kofman E. A stand-alone quantized state system solver for continuous system simulation[J]. Society for Computer Simulation International, 2014, 90(7): 782-799. [6] Migoni G, Borto lotto M, Kofman E, et al. Quantization-based new integration methods for stiff ordinary differential equations[J]. Simulation, Modeling Practice & Theory, 2012, 35(4): 118-136. [7] Migoni G, Kofman E, Bergero F, et al. Quantization- based simulation of switched mode power supplies[J]. Simulation Transactions of the Society for Modeling & Simulation International, 2015, 91(4): 320-336. [8] Migoni G, Bortolotto M, Kofman E, et al. Linearly implicit quantization-based integration methods for stiff ordinary differential equations[J]. Simulation Modelling Practice & Theory, 2013, 35(6): 118-136. [9] Pietro F D, Migoni G, Kofman E. Improving a linearly implicit quantized state system method[C]// Winter Simulation Conference, Virginia, 2016: 1084- 1095. [10] Cellier F E, Kofman E. Continuous system simulation[M]. New York, US: Springer, 2006. [11] Ji S, Lu T, Zhao Z, et al. Modelling of high voltage IGBT with easy parameter extraction[C]//Power Electronics and Motion Control Conference, Harbin, 2012: 1511-1515. [12] 袁立强, 赵争鸣, 宋高升, 等. 电力半导体器件原理与应用[M]. 北京: 机械工业出版社, 2011. [13] Song X, Ma Y, Zhang W, et al. Quantized state based simulation of time invariant and time varying continuous systems[J]. Mathematical Problems in Engineering, 2015(2): 1-5.