Computational Technology Resources - CCC

K. Mal^1,2, B.S. Chowdhry², I.H. Kalwar³, T.D. Memon⁴ and T.R. Memon⁵

¹Sukkur IBA University, Sukkur, Pakistan
²NCRA-Condition Monitoring Systems Lab, Mehran University of Engineering & Technology, Jamshoro, Pakistan
³Faculty of Engineering Sciences and Technology, Iqra University, Karachi, Pakistan
⁴Center for Artificial Intelligence Research and Optimization, Faculty of Design and Creative Technology, Torrens University, Melbourne, Australia
⁵Department of Electronic Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Pakistan

Keywords: condition monitoring, railway wheelset, wheel-rail interaction, FPGA implementation, performance analysis, System-On-Chip, Spartan-3.

Abstract

Embedded systems are vital for implementing simulation-based estimators designed to estimate dynamical systems. Field Programmable Gate Arrays (FPGAs) are widely recognized for their hardware flexibility and high processing speed to construct nonlinear condition monitoring systems. The extended Kalman filter (EKF) model is designed in MATLAB and implemented on FPGA in this research study to predict various railway wheelset characteristics under varied track contact conditions. In this context, the National Instruments (NI) myRIO® development board and sbRIO® single-board controller are used to verify the onboard estimation of wheel-rail interaction parameters through Xilinx® System-on-Chip Zynq and Xilinx Spartan-3 FPGA devices, respectively. Both FPGA platforms are used to evaluate the MATLAB simulated dataset for the railway nonlinear wheelset model with different track conditions for the vehicle's accelerating and decelerating operation modes. For functional verification, the EKF-based railway wheelset parameter estimation is synthesized on FPGA devices, and the FPGA findings are consistent with the MATLAB simulation results. The area-performance analysis of both NI embedded boards (myRIO and sbRIO) is presented and these FPGA devices are seen as suitable for implementation of designed EKF. Functional verification and resource utilization of Xilinx System-On-Chip Zynq and Xilinx Spartan-3 are investigated. It is observed that Xilinx System-On-Chip Zynq FPGA is optimal for the estimation of railway wheelset parameters.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 7 PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 7.5 Performance Analysis of FPGA-Based Extended Kalman Filter for Railway Wheelset Parameters Estimation K. Mal^1,2, B.S. Chowdhry², I.H. Kalwar³, T.D. Memon⁴ and T.R. Memon⁵ ¹Sukkur IBA University, Sukkur, Pakistan ²NCRA-Condition Monitoring Systems Lab, Mehran University of Engineering & Technology, Jamshoro, Pakistan ³Faculty of Engineering Sciences and Technology, Iqra University, Karachi, Pakistan ⁴Center for Artificial Intelligence Research and Optimization, Faculty of Design and Creative Technology, Torrens University, Melbourne, Australia ⁵Department of Electronic Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Pakistan doi:10.4203/ccc.7.7.5 Full Bibliographic Reference for this paper K. Mal, B.S. Chowdhry, I.H. Kalwar, T.D. Memon, T.R. Memon, "Performance Analysis of FPGA-Based Extended Kalman Filter for Railway Wheelset Parameters Estimation", in J. Pombo, (Editor), "Proceedings of the Sixth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 7, Paper 7.5, 2024, doi:10.4203/ccc.7.7.5 Keywords: condition monitoring, railway wheelset, wheel-rail interaction, FPGA implementation, performance analysis, System-On-Chip, Spartan-3. Abstract Embedded systems are vital for implementing simulation-based estimators designed to estimate dynamical systems. Field Programmable Gate Arrays (FPGAs) are widely recognized for their hardware flexibility and high processing speed to construct nonlinear condition monitoring systems. The extended Kalman filter (EKF) model is designed in MATLAB and implemented on FPGA in this research study to predict various railway wheelset characteristics under varied track contact conditions. In this context, the National Instruments (NI) myRIO® development board and sbRIO® single-board controller are used to verify the onboard estimation of wheel-rail interaction parameters through Xilinx® System-on-Chip Zynq and Xilinx Spartan-3 FPGA devices, respectively. Both FPGA platforms are used to evaluate the MATLAB simulated dataset for the railway nonlinear wheelset model with different track conditions for the vehicle's accelerating and decelerating operation modes. For functional verification, the EKF-based railway wheelset parameter estimation is synthesized on FPGA devices, and the FPGA findings are consistent with the MATLAB simulation results. The area-performance analysis of both NI embedded boards (myRIO and sbRIO) is presented and these FPGA devices are seen as suitable for implementation of designed EKF. Functional verification and resource utilization of Xilinx System-On-Chip Zynq and Xilinx Spartan-3 are investigated. It is observed that Xilinx System-On-Chip Zynq FPGA is optimal for the estimation of railway wheelset parameters. download the full-text of this paper (PDF, 2261 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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