Reduced Position Error and Overshoot Control Using Modified Integrator-Based QPR Controller and SMO for Limp Home Mode PMSM-Driven EV

The conventional sliding-mode observer used for position estimation in permanent magnet synchronous machine (PMSM) drives for electric vehicle (EV) applications experiences chattering caused by the sign function and phase delay when employing a low-pass filter (LPF). Additionally, the conventional integrator used in the proportional-integral (PI) controller suffers from DC drift and initial value problems during practical implementation, resulting in a significant overshoot and speed errors in the speed tracking profile. This study presents a modified integrator (MI) for digital implementation that eliminates the initial value problem and reduces the DC drift issue. This paper also proposes a MI-based quasi-proportional resonant (MIQPR) controller for the position sensorless control of PMSM-driven EVs using SMO. This approach eliminates the need for a sign function and LPF, thereby reducing the phase delay and effectively minimizing the position error. The proposed control scheme is experimentally validated through closed-loop control utilizing space-vector-modulation-based direct torque and flux control (SVM-DTFC). This ensures a fast dynamic response and reduces overshooting and undershooting of the speed response. The proposed method was validated through experiments conducted on a 2.2 kW PMSM and WAVECT WCU300 field-programmable gate array (FPGA) controller.

Authors

Institutions

Publication Details

Journal
IEEE Journal of Emerging and Selected Topics in Power Electronics
Published
2025-05-06
DOI
https://doi.org/10.1109/jestpe.2025.3567334
Citations
1
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
0.68
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reduced Position Error and Overshoot Control Using Modified Integrator-Based QPR Controller and SMO for Limp Home Mode PMSM-Driven EV

Giribabu Dyanamina, Sanjay Kumar Kakodia
1 citations
IEEE Journal of Emerging and Selected Topics in Power Electronics
Vehicle Dynamics and Control Systems
0.68
article

Reduced Position Error and Overshoot Control Using Modified Integrator-Based QPR Controller and SMO for Limp Home Mode PMSM-Driven EV

Giribabu Dyanamina, Sanjay Kumar Kakodia
article en
1 citations

Abstract

The conventional sliding-mode observer used for position estimation in permanent magnet synchronous machine (PMSM) drives for electric vehicle (EV) applications experiences chattering caused by the sign function and phase delay when employing a low-pass filter (LPF). Additionally, the conventional integrator used in the proportional-integral (PI) controller suffers from DC drift and initial value problems during practical implementation, resulting in a significant overshoot and speed errors in the speed tracking profile. This study presents a modified integrator (MI) for digital implementation that eliminates the initial value problem and reduces the DC drift issue. This paper also proposes a MI-based quasi-proportional resonant (MIQPR) controller for the position sensorless control of PMSM-driven EVs using SMO. This approach eliminates the need for a sign function and LPF, thereby reducing the phase delay and effectively minimizing the position error. The proposed control scheme is experimentally validated through closed-loop control utilizing space-vector-modulation-based direct torque and flux control (SVM-DTFC). This ensures a fast dynamic response and reduces overshooting and undershooting of the speed response. The proposed method was validated through experiments conducted on a 2.2 kW PMSM and WAVECT WCU300 field-programmable gate array (FPGA) controller.

IEEE Journal of Emerging and Selected Topics in Power ElectronicsVol. 13(6)
Maulana Azad National Institute of Technology (IN)
Affordable and clean energy
Openalex Percentile: Top 31%
Vehicle Dynamics and Control Systems
0.68
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.