TY - JOUR
T1 - Comprehensive Analysis of Thermal Effects on PMSM Drive Control in Small Commercial Vehicles
AU - Ranjan, Alok
AU - Bhaskar, Devara Vijaya
AU - Kumar, Prashant
AU - Muduli, Utkal Ranjan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper presents a detailed study on the thermal effects impacting the control performance of Permanent Magnet Synchronous Motors (PMSM) in light commercial vehicles (LCVs). It examines thermal behaviors under various operational conditions to identify and mitigate heat generation and dissipation challenges, which affect efficiency and reliability. The analysis incorporates both mathematical analysis and considering real-time drive scenarios, to validate proposed thermal management strategies, ensuring optimal performance and longevity of PMSM drives. A neural network (NN) approach is employed to predict the derating factor (DF) based on sensor data for torque, speed, voltage, and current, significantly enhancing motor performance and ensuring smoother operation. Validations confirm substantial improvements in speed stability, enhancing user experience, longevity, and reliability of EV drives. Future work will refine these strategies and explore their applications across various EV models and driving conditions using different drive cycles.
AB - This paper presents a detailed study on the thermal effects impacting the control performance of Permanent Magnet Synchronous Motors (PMSM) in light commercial vehicles (LCVs). It examines thermal behaviors under various operational conditions to identify and mitigate heat generation and dissipation challenges, which affect efficiency and reliability. The analysis incorporates both mathematical analysis and considering real-time drive scenarios, to validate proposed thermal management strategies, ensuring optimal performance and longevity of PMSM drives. A neural network (NN) approach is employed to predict the derating factor (DF) based on sensor data for torque, speed, voltage, and current, significantly enhancing motor performance and ensuring smoother operation. Validations confirm substantial improvements in speed stability, enhancing user experience, longevity, and reliability of EV drives. Future work will refine these strategies and explore their applications across various EV models and driving conditions using different drive cycles.
KW - Light Commercial Electric Vehicles
KW - Neural Network
KW - PMSM Drive Control
KW - Thermal Effects
KW - Thermal Management Strategies
UR - https://www.scopus.com/pages/publications/105006473302
U2 - 10.1109/PEDES61459.2024.10961171
DO - 10.1109/PEDES61459.2024.10961171
M3 - Conference article
AN - SCOPUS:105006473302
SN - 2836-3841
JO - Proceedings of the International Conference on Power Electronics, Drives, and Energy Systems for Industrial Growth, PEDES
JF - Proceedings of the International Conference on Power Electronics, Drives, and Energy Systems for Industrial Growth, PEDES
IS - 2024
T2 - 11th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2024
Y2 - 18 December 2024 through 21 December 2024
ER -