TY - JOUR
T1 - Iron-Loss Modeling with Sensorless Predictive Control of PMBLDC Motor Drive for Electric Vehicle Application
AU - Kumar, Prashant
AU - Bhaskar, Devara Vijaya
AU - Muduli, Utkal Ranjan
AU - Beig, Abdul R.
AU - Behera, Ranjan Kumar
N1 - Funding Information:
Manuscript received July 13, 2020; revised September 24, 2020; accepted October 30, 2020. Date of publication November 9, 2020; date of current version August 24, 2021. This work was supported by the Abu Dhabi Education and Knowledge (ADEK), United Arab Emirates, under Grant AARE18-102. (Corresponding author: Prashant Kumar.) Prashant Kumar is with the Department of Electrical Engineering, IIT (ISM) Dhanbad, Dhanbad 826004, India, and also with the Department of Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi, United Arab Emirates (e-mail: [email protected]).
Publisher Copyright:
© 2015 IEEE.
PY - 2021/9
Y1 - 2021/9
N2 - Permanent-magnet brushless dc motor (PMBLDCM) is more suitable for electric vehicle (EV) with higher torque and driving performance. A suitable loss modeling of PMBLDCM with proper analysis can improve the control stability at different road surface conditions. However, the iron loss is not minimal enough to be ignored during high-speed operation of PMBLDCM drives. This article proposes a disturbance observer-based sensorless drive control for accurate estimation of the rotor position. This is achieved by taking the iron loss into consideration in order to further reduce the rotor position estimation error. A modified model predictive control is also proposed to deal with the novel modeling to provide torque ripple-free operation at reduced losses. The EV performances are compared for lossless and loss model of PMBLDCM through both simulation and experimental validation.
AB - Permanent-magnet brushless dc motor (PMBLDCM) is more suitable for electric vehicle (EV) with higher torque and driving performance. A suitable loss modeling of PMBLDCM with proper analysis can improve the control stability at different road surface conditions. However, the iron loss is not minimal enough to be ignored during high-speed operation of PMBLDCM drives. This article proposes a disturbance observer-based sensorless drive control for accurate estimation of the rotor position. This is achieved by taking the iron loss into consideration in order to further reduce the rotor position estimation error. A modified model predictive control is also proposed to deal with the novel modeling to provide torque ripple-free operation at reduced losses. The EV performances are compared for lossless and loss model of PMBLDCM through both simulation and experimental validation.
KW - Brushless dc motor drive
KW - disturbance observer
KW - iron-loss estimation
KW - model predictive control
KW - torque ripple minimization
UR - http://www.scopus.com/inward/record.url?scp=85096397656&partnerID=8YFLogxK
U2 - 10.1109/TTE.2020.3036991
DO - 10.1109/TTE.2020.3036991
M3 - Article
AN - SCOPUS:85096397656
SN - 2332-7782
VL - 7
SP - 1506
EP - 1515
JO - IEEE Transactions on Transportation Electrification
JF - IEEE Transactions on Transportation Electrification
IS - 3
M1 - 9252942
ER -