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1. Time-Efficient Behavioral Modeling of Switched Reluctance Machines

   https://doi.org/10.1109/ITEC51675.2021.9490084  

   Jin, Zichao; Zhang, Ziyan; Chen, Chengxiu; Yaman, Selin; Krishnamurthy, Mahesh (June 2021, 2021 IEEE Transportation Electrification Conference & Expo (ITEC))

   null (Ed.)

   This study presents a time-efficient modelling approach for dynamic behavior and efficiency analysis of a Switched Reluctance Machines (SRM). It employs a hybrid model combining Simulink, finite element analysis (FEA), and hardware measurements to create an accurate behavioral model of the machine. In order to enhance accuracy of the estimated performance, Steinmetz equation is employed to characterize core loss in the machine across different operating points. This approach serves as a template for developing a time-efficient model to analyze performance of any SRM with a high degree of accuracy. Simulation and experimental results are used to show effectiveness of the proposed approach. 

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2. Effectiveness of Power Electronic Controllers in Mitigating Acoustic Noise and Vibration in High-Rotor Pole SRMs

   https://doi.org/10.3390/en14030702  

   Zhang, Ziyan; Yaman, Selin; Salameh, Mohamad; Singh, Suryadev; Chen, Chengxiu; Krishnamurthy, Mahesh (February 2021, Energies)

   null (Ed.)

   This paper presents a comparative evaluation of power electronic control approaches for vibro-acoustic noise reduction in High Rotor-Pole Switched Reluctance Machines (HR-SRM). It carries out a fundamental analysis of approaches that can be used to target acoustic noise and vibration reduction. Based on the comprehensive study, four candidates for control have been identified and applied to the HR-SRM drive to evaluate their effectiveness and identify challenges. These four methods include phase advancing, current shaping based on field reconstruction, and random hysteresis band with and without spectrum shaping. The theoretical background, implementation, and vibro-acoustic noise reduction performance of each method are presented in detail. Comparative studies from simulation and experimental measurements have been used to identify the most effective solution to acoustic noise and vibration reduction in HR-SRM configuration. 

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3. A Truncated Fourier Based Analytical Model for SRMs with Higher Number of Rotor Poles

   https://doi.org/10.1109/ITEC48692.2020.9161708  

   Jin, Zichao; Jia, Yijiang; Salameh, Mohamad; Bilgin, Berker; Li, Shuwang; Krishnamurthy, Mahesh (June 2020, 2020 IEEE Transportation Electrification Conference & Expo (ITEC))

   Switched reluctance motors (SRM) have been seen as a potential candidate for automotive, aerospace as well as domestic applications and High-Rotor pole SRM (HR-SRM) present a significant advancement in this area. This machine configuration offers most of the the benefits offered by conventional SRMs and has shown significant benefits in efficiency and torque quality. However, HR-SRM has a narrower inductance profile with a lower saliency ratio as compared to a conventional SRM with an identical stator. This can make it inherently challenging to directly adopt mathematical models and sensorless control approaches currently in use. This paper presents a time-efficient analytical model for the characterization of a 6/10 SRM using an inductance model utilizing truncated Fourier series as well as multi-order polynomial curve-fitting algorithm. The inductance model is extended to accurately predict back-EMF and electromagnetic torque response towards obtaining a comprehensive model for every operating point of the machine during dynamic operation. The effectiveness of the proposed concept has analyzed for a prototype machine and verified using Finite Element Analysis (FEA). 

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4. Parameters identification of cable stayed footbridges using Bayesian inference

   https://doi.org/doi.org/10.1007/s11012-019-01019-  

   Pepi, C. (August 2019, Meccanica)

   Numerical modeling of actual structural systems is a very complex task mainly due to the lack of complete knowledge on the involved parameters. Simplified assumptions on the uncertain geometry, material properties and boundary conditions make the numerical model response differ from the actual structural response. Improvements of the finite element (FE) models to obtain accurate response predictions can be achieved by vibration based FE model updating which uses experimental measures to minimize the differences between the numerical and experimental modal features (i.e. natural frequencies and mode shapes). Within this context, probabilistic model updating procedures based on the Bayes’ theorem were recently proposed in the literature in order to take into account the uncertainties affecting the structural parameters and their influence on the structural response. In this paper, a novel framework to efficiently estimate the posterior marginal PDF of the selected model parameters is proposed. First, the main dynamic parameters to be used for model updating are identified by ambient vibration tests on an actual structural system. Second, a first numerical FE model is developed to perform initial sensitivity analysis. Third, a surrogate model based on polynomial chaos is calibrated on the initial FE model to significantly reduce computational costs. Finally, the posterior marginal PDFs of the chosen model parameters are estimated. The effectiveness of the proposed method is demonstrated using a FE numerical model describing a curved cable-stayed footbridge located in Terni (Umbria Region, Central Italy). 

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5. Parameters identification of cable stayed footbridges using Bayesian inference

   https://doi.org/doi.org/10.1007/s11012-019-01019-x  

   Chiara Pepi, C. (August 2019, Meccanica)

   Numerical modeling of actual structural systems is a very complex task mainly due to the lack of complete knowledge on the involved parameters. Simplified assumptions on the uncertain geometry, material properties and boundary conditions make the numerical model response differ from the actual structural response. Improvements of the finite element (FE) models to obtain accurate response predictions can be achieved by vibration based FE model updating which uses experimental measures to minimize the differences between the numerical and experimental modal features (i.e. natural frequencies and mode shapes). Within this context, probabilistic model updating procedures based on the Bayes’ theorem were recently proposed in the literature in order to take into account the uncertainties affecting the structural parameters and their influence on the structural response. In this paper, a novel framework to efficiently estimate the posterior marginal PDF of the selected model parameters is proposed. First, the main dynamic parameters to be used for model updating are identified by ambient vibration tests on an actual structural system. Second, a first numerical FE model is developed to perform initial sensitivity analysis. Third, a surrogate model based on polynomial chaos is calibrated on the initial FE model to significantly reduce computational costs. Finally, the posterior marginal PDFs of the chosen model parameters are estimated. The effectiveness of the proposed method is demonstrated using a FE numerical model describing a curved cable-stayed footbridge located in Terni (Umbria Region, Central Italy). 

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