Simplified MTPA Integrated Virtual Voltage Vector-Based MPCC for Improved Performance and Efficiency in IM Drive-Based Electric Vehicles
This article introduces an energy-efficient, low computational burden approach called duty ratio-based virtual voltage vector-based model predictive current control (V3MPCC) combined with maximum torque per ampere (MTPA) control for induction motor-based electric vehicles (EVs). Conventional MPCC (C-MPCC) employs a single voltage vector per control cycle, leading to significant torque ripples and high current. The proposed method uses duty ratio control, incorporates a zero vector, and reduces the time of active virtual vectors to minimize the computational load that comes with more virtual vectors. Virtual vectors are introduced to reduce control errors and improve the efficiency of the system. A duty ratio proportional to stator flux both above and below base speed, using MTPA condition, is formulated to minimize stator current errors while maintaining dynamic performance and expanding speed operating range compared to traditional methods. The aim is to reduce torque ripple and lower stator current total harmonic distortion (THD) without increasing the switching frequency. Extensive testing, which includes analyzing torque ripple and power loss, confirms the advantages of this approach under ECE-Extra Urban Drive Cycle conditions. This methodology delivers significant advantages, such as enhanced motor efficiency, improved dynamic performance, and reduced computational burden.
Authors
- Venkadesan Arunachalam (ORCID: https://orcid.org/0000-0001-7970-3814)
- G. Koperundevi
- Rinki Roy Chowdhury (ORCID: https://orcid.org/0000-0001-8356-2188)
Institutions
- National Institute of Technology, Puducherry
Publication Details
- Journal
- IEEE Transactions on Transportation Electrification
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1109/tte.2024.3515138
- Citations
- 3
- Primary Topic
- Electric and Hybrid Vehicle Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.61