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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Maneetkumar R. Dhanvijay
College of Engineering Pune (COEP)
Control & Systems Engineering Electrical & Electronics Engineering

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Comparative analysis of features of online numerical methods used for parameter estimation of PMSM Komal M. Naikawadi; Sudhir Madhav Patil; Kapil Kalantri; Maneetkumar R. Dhanvijay
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i4.pp2172-2180

Abstract

As permanent magnet synchronous motors (PMSM) have high power density, efficiency, good dynamic performance, and small size they are becoming popular in electric vehicle (EV) applications. Control performance and the efficiency of the system get affected due to electrical, mechanical parameters. Parameters value gets affected by voltage source inverter (VSI) non-linearities, temperature and magnetic saturation effects. If exact parameters for particular torque speed requirement are found, the efficiency of system increases. There are various offline and online methods for finding parameters. Offline methods are easy to implement but requires extra setup and estimate parameters in steady state. Because the effects of transient conditions are taken into account during identification, online methods for obtaining real-time data under running conditions are becoming more popular. An overview about online numerical methods to estimate electrical parameters of PMSM is given. It discusses difference between various methods in terms of computational cost, convergence speed, noise and identification error. Choosing of method will be easy using this work. For inductance estimation, the extended Kalman filter (EKF) algorithm has an identification error of 0.24% under temperature effect and -0.3% under VSI non-linearities effect. The identification error for Rs and ψf using the recursive least square (RLS) method is 0.5% and 0.02%, respectively, when temperature is considered. EKF and RLS algorithms are proposed.
Motor controlled system development with force-assistance using force/torque sensor for four-axis ceiling suspension system Kshitij Ghanshyam Jiwane; Sudhir Madhav Patil; Maneetkumar R. Dhanvijay
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 14, No 2: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v14.i2.pp833-841

Abstract

Multi-axis force and torque sensors are type of transducers. They can measure force and torque in three dimensions. These sensors have multiple applications in robotic systems. The majority of these type of sensors use the strain measurement in any elastic structure. There are multiple approaches for strain measurement which include resistive strain gauge, piezo-electric and capacitive technologies. The evaluation of such a system can be done on various parameters, maximizing the acceptable sensing range while minimizing measurement errors/crosstalk is the main design challenge. In future, because force and torque sensors are necessary for service machines to interact with people in different situations, they will be widely deployed. However, it is challenging to find an appropriate force/torque sensor, and the cost is very high, because of certain design concerns and needs. This paper discusses an application based on the multi-axis force/torque sensor. A force-assisted control system has been proposed with simultaneous motorized action using force as feedback. The sensor needs and machine performance are reviewed after a thorough analysis of relevant data. This thorough investigation will benefit in the interfacing of specialized force/torque sensors to reduce crosstalk and aid in broadening the scope of service machines in which they can be used.
Co-Authors Kapil Kalantri Komal M. Naikawadi Kshitij Ghanshyam Jiwane Sudhir Madhav Patil