Investigation on Parameter Extraction for An Improved Fourier-Series-Based NPT IGBT Model
编号:62 访问权限:公开 更新:2021-07-21 20:02:28 浏览:798次 张贴报告

报告开始:2021年08月27日 12:06(Asia/Shanghai)


所在会场:[P] Poster [P1] Poster 1


An Improved Fourier-series-based IGBT Model by using PID controller to Mitigate the Effect of Gibbs’ Phenomenon
Yifei Dinga, Xin Yanga, Member, IEEE, Jun Wanga, Senior Member, IEEE, Guoyou Liub, Senior Member
a School of Electrical and Information Engineering, Hunan University, Changsha, China, 410082
b CRRC Zhuzhou Electric Locomotive Institute Co., Ltd., Zhuzhou, China, 412000

In recent years, IGBT modeling has attracted a lot of attention. To accurately simulate switching waveform, predict switch loss and EMI, an accurate IGBT simulation model is of great importance. Most physics-based IGBT models can well simulate the electrical characteristics and physical characteristics of the devices[1]. Therefore, the physics-based IGBT model is widely used in power electronics.
Fourier-series-based IGBT model is one of the physical models presented by Palmer[2, 3]. The model can well describe the carrier behavior in the CSR that is the key part of bipolar devices. A parameter extraction and optimization method based on the model is proposed in [4], which further improves the accuracy of the model. The input capacitance was corrected in [5]. The switching behaviors of the high-speed buffer layer IGBT is optimized in [6]. These works make the Fourier-series-based model suitable for IGBT with various structures such as punch-through (PT), non-punch-through NPT and field stop (FS). In addition, the model has been proven to be very efficient in terms of simulation speed.


Fig. 2.  Illustration of carrier concentration in Fourier-series-based IGBT model and finite element simulation in the turn-on process.
The Fourier-series-based IGBT model, due to the truncation error of the Fourier series, leads to Gibbs' Phenomenon, which is particularly significant in the turn-on process. Gibbs' phenomenon basically has no effect in the turn-off process, because within this process, Gibbs’ phenomenon mainly affects the region with high carrier concentration, but the carrier concentration close to x2  , i.e. the depletion layer, rapidly drops to 0. Such a sharp slope of p  makes the carrier at x2  basically unaffected by Gibbs’ phenomenon as shown in Fig. 1. However, in the turn-on process, Gibbs’ phenomenon will have a significant impact on the carrier concentration near x2  where the carrier concentration of the Fourier-series-based model oscillates greatly as shown in Fig. 2. Due to the existence of such an oscillation, regions with carrier concentration less than zero would emerge in the drift region. Therefore, the boundary between CSR and the depletion region cannot be defined by the position of "minute" carrier concentration. At the same time, the region with carrier concentration less than zero will produce an abnormally large electric field in the CSR.

Fig. 1.  Carrier concentration distribution in Fourier-series-based IGBT model at turn-off.
Due to Gibbs' phenomenon, physical characteristics in regions with low carrier concentration can not be well simulated, which in turn will lead to the inaccuracy of the Fourier- series-based solution. Therefore, it is necessary to find a way to mitigate the Gibbs’ phenomenon.

prior art
The original Fourier-series-based IGBT model in the turn-on process was proposed by Palmer and Angus. The core program block diagram of solving the ambipolar diffusion equation is shown in the Fig. 3. The original method provides a feedback on the error between px2  and 0 to obtain the depletion layer voltage Vd2  which is essentially the proportion term in the proportional controller. In the original model, Gibbs’ phenomenon seriously affects the regions with low carrier concentration because px2  is less than 0. Lu et al. take into account the two-dimensional effect of MOS side [7], witch can effectively increase px2  and reduce the influence of Gibbs’ phenomenon on the low carrier concentration regions as shown in Fig. 3.

Novelty and major achievements in this work
The modified model proposed in this paper replaces the proportional controller in the original model with the PID controller.

Fig. 3.  The flow of the original model, Lu’s model and the modified model  to get the boundary conditions.
 The integral controller is used to make px2  greater than 0 in the early turn-on process which can effectively mitigate the effects of Gibbs’ phenomenon, and the differential controller is used to improve model convergence. In this paper, particle swarm optimization (PSO) optimization algorithm is used to extract parameters of PID controller, which greatly increases the accuracy of the modified model. The preliminary results are shown in Fig. 4. Compared with other models, the voltage and current waveforms of the modified model are closest to the waveforms of finite element simulation.
Few of these Fourier-series based models compares the carrier concentration distribution and the electric field distribution throughout the drift region in IGBT turn-on process, which is the key elements of physics-based IGBT model.

Fig. 4.  Turn-on comparison of the modified model, Lu's model and the original model with TCAD simulation under resistive load.
 In this paper, finite element simulation is used as a reference to compare the modified model, traditional model and Lu' model. Electrical characteristics as voltage and current will be compared, as well as physical characteristics as carrier concentration distribution and electric field strength.

[1]      S. Ji, Z. Zhao, T. Lu, L. Yuan, and H. Yu, “HVIGBT physical model analysis during transient,” IEEE Trans. Power Electron., vol. 28, no. 5, pp. 2616–2624, May 2013.
[2]      P. R. Palmer, E. Santi, J. L. Hudgins, X. Kang, J. C. Joyce, and P. Y. Eng, “Circuit simulator models for the diode and IGBT with full temperature dependent features,” IEEE Trans. Power Electron., vol. 18, no. 5, pp. 1220–1229, Sep. 2003.
[3]      X. Kang, A. Caiafa, E. Santi, J. L. Hudgins, and P. R. Palmer, “Characterization and modeling of high-voltage field-stop IGBTs,” IEEE Trans. Ind. Appl., vol. 39, no. 4, pp. 922–928, Jul./Aug. 2003.
[4]      A. T. Bryant, X. Kang, E. Santi, P. R. Palmer, and J. L. Hudgins, “Two-step parameter extraction procedure with formal optimization for physics-based circuit simulator IGBT and PIN diode models,” IEEE Trans. Power Electron., vol. 21, no. 2, pp. 295–309, Mar. 2006.
[5]      X. Yang, M. Otsuki, and P. R. Palmer, “Physics-based insulated-gate bipolar transistor model with input capacitance correction,” IET Power Electron., vol. 8, no. 3, pp. 417–427, 2015.
[6]      P. Xue, G. Fu, and D. Zhang, “Modeling inductive switching characteristics of high-speed buffer layer IGBT,” IEEE Trans. Power Electron., vol. 32, no. 4, pp. 3075–3087, Apr. 2017.
[7]      L. Lu, A. Bryant, J. L. Hudgins, P. R. Palmer, and E. Santi, “Physics based model of planar-gate IGBT including MOS side two-dimensional effects,” IEEE Trans. Ind. Appl., vol. 46, no. 6, pp. 2556–2567, Nov./Dec. 2010, doi: 10.1109/TIA.2010.2071190.
IGBT,Ambipolar diffusion equation,Fourier series
Yifei Ding
Hunan University

Yifei Ding Hunan University
Xin Yang Hunan University
Jun Wang Hunan University
Chunming Tu Hunan University
Guoyou Liu CRRC Zhuzhou Electric Locomotive Institute Co., Ltd.
验证码 看不清楚,更换一张
  • 会议日期





  • 04月21日 2021


  • 05月15日 2021


  • 06月25日 2021


  • 08月24日 2021


  • 08月27日 2021


Huazhong University of Science and Technology