DC25_PAPER_Track10_ParameterExtractionForBehaviorModel_Zhang.pdf

1、 Information Classification:General A Parameter Extraction Method for Multi-phase Buck Converters Based on Nonlinear Least Square Method Hanyu Zhang,Missouri University of Science and Technology hzc5zmst.edu Junho Joo,Missouri University of Science and Technology joojumst.edu Wenchang Huang,Missouri

2、 University of Science and Technology wh3vwmst.edu Information Classification:General Hanfeng Wang,Google LLC Wei Shen,Google LLC Zhigang Liang,Google LLC Lihui Cao,Google LLC Seungtaek Jeong,Google LLC Chulsoon Hwang,Missouri University of Science and Technology hwangcmst.edu Information Classifica

3、tion:General Abstract Power converter simulation models are crucial for power integrity simulation in the low-frequency range.In this regard,a behavioral model of multi-phase buck converter that accurately captures non-linear behaviors was proposed in the past.However,more than 20 parameters are nee

4、ded to model practical multi-phase Buck converters with phase add/drop and PWM/PFM transition features,and determining those parameters is not trivial.In this paper,an automatic parameter extraction method was proposed.The proposed method constructs cost functions that quantify the difference betwee

5、n simulated and measured output voltage waveforms.Using the nonlinear least squares(LSQ)method,the algorithm iteratively minimizes the cost function to find the best estimates of the unknown parameters.SPICE simulations are conducted in each iteration to update the cost function.The proposed method

6、was implemented in a Python program and validated on a practical three-phase buck converter.This program successfully extracted the correct parameters without the users intervention.The SPICE model matches measurement results well at various load conditions with the extracted parameters.This method