Faculty Publications

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Author: search.filters.author.Gangadharan, K.V.Subject: search.filters.subject.Interpolation

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    Integer and fractional order-based viscoelastic constitutive modeling to predict the frequency and magnetic field-induced properties of magnetorheological elastomer
    (American Society of Mechanical Engineers (ASME), 2018) Poojary, U.R.; Gangadharan, K.V.
    Magnetorheological elastomer (MRE)-based semi-active vibration mitigation device demands a mathematical representation of its smart characteristics. To model the material behavior over broadband frequency, the simplicity of the mathematical formulation is very important. Material modeling of MRE involves the theory of viscoelasticity, which describes the properties intermediate between the solid and the liquid. In the present study, viscoelastic property of MRE is modeled by an integer and fractional order derivative approaches. Integer order-based model comprises of six parameters, and the fraction order model is represented by five parameters. The parameters of the model are identified by minimizing the error between the response from the model and the dynamic compression test data. Performance of the model is evaluated with respect to the optimized parameters estimated at different sets of regularly spaced arbitrary input frequencies. A linear and quadratic interpolation function is chosen to generalize the variation of parameters with respect to the magnetic field and frequency. The predicted response from the model revealed that the fractional order model describes the properties of MRE in a simplest form with reduced number of parameters. This model has a greater control over the real and imaginary part of the complex stiffness, which facilitates in choosing a better interpolating function to improve the accuracy. Furthermore, it is confirmed that the realistic assessment on the performance of a model is based on its ability to reproduce the results obtained from optimized parameters. © © 2018 by ASME.
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    Driving Cycle-Based Design Optimization and Experimental Verification of a Switched Reluctance Motor for an E-Rickshaw
    (Institute of Electrical and Electronics Engineers Inc., 2024) Bhaktha, B.S.; Jose, N.; Vamshik, M.; Pitchaimani, J.; Gangadharan, K.V.
    This article deals with the design and optimization of a 2 kW switched reluctance motor (SRM) for an electric rickshaw (E-rickshaw). Previously published research on SRM optimization has mostly focused on the optimization of their design and control variables only at the rated conditions. In electric vehicle (EV) applications, the load operating points (LOPs) of a traction motor are dynamic and spread widely across the torque speed envelope. To enhance their overall performance, it is vital to include them in the design optimization process; therefore, in this article, a novel procedure for implementing the multiobjective design optimization (MODO) of an SRM based on a driving cycle has been demonstrated. Higher starting torque and torque density with reduced electromagnetic losses throughout the driving cycle are established as the design objectives, subject to practical restrictions on current density and slot fill factor. The design objectives have been accurately evaluated through transient finite element analysis (FEA) and a computationally efficient SRM drive model (developed in MATLAB/Simulink) with consideration of the excitation control parameters. Kriging models have been constructed to reduce the computation cost of FEA during the optimization process. Then, a nondominated sorting genetic algorithm II (NSGA II) based multiobjective optimization coupled with the constructed Kriging models is conducted to generate a Pareto front. An optimal design that offers the best balance between the design objectives is selected from the Pareto-optimal set, and the dimensions of corresponding design variables are used to build a prototype. Finally, the static and dynamic performance of the SRM prototype are experimentally evaluated and validated with the FEA simulations. © 2024 IEEE.