Ensuring speed robustness against load torque variations is of paramount importance for Permanent Magnet Synchronous Motors (PMSMs), particularly in electric vehicle applications. While the literature extensively covers this issue, the utilization of Multivariable Sliding-Mode Extremum Seeking (MSES) for fine-tuning PI gains as the PMSM's speed controller has yet to be proposed. By incorporating the speed feedback error term and a well-suited sliding surface, MSES dynamically adjusts the PI gains during operation, imposing a minimal computational burden. Real-time PI controller tuning holds the potential to decrease system susceptibility to fluctuations in both motor parameters and load torque disturbances. Consequently, this approach facilitates achieving a satisfactory tracking performance. Notably, the method exhibits resilience to variations in controller inputs and can be readily implemented on mid-tier processors. In order to verify the performance of the proposed control method, a simulation study is conducted using MATLAB®/Simulink software. The obtained results present an indication of relatively high accuracy as well as satisfactory performance in terms of robustness against load torque perturbation and independence of parametric variations.

Adaptive PI Control of PMSM for Electric Vehicle Application Based on Sliding-mode Extremum Seeking Algorithm / Rajabinasab, M.; Ghalebani, P.; Bruno, S.; Cometa, R.; La Scala, M.. - (2023). (Intervento presentato al convegno 2023 IEEE Asia Meeting on Environment and Electrical Engineering, EEE-AM 2023 tenutosi a vnm nel 2023) [10.1109/EEE-AM58328.2023.10395885].

Adaptive PI Control of PMSM for Electric Vehicle Application Based on Sliding-mode Extremum Seeking Algorithm

Rajabinasab M.;Bruno S.;Cometa R.;La Scala M.
2023-01-01

Abstract

Ensuring speed robustness against load torque variations is of paramount importance for Permanent Magnet Synchronous Motors (PMSMs), particularly in electric vehicle applications. While the literature extensively covers this issue, the utilization of Multivariable Sliding-Mode Extremum Seeking (MSES) for fine-tuning PI gains as the PMSM's speed controller has yet to be proposed. By incorporating the speed feedback error term and a well-suited sliding surface, MSES dynamically adjusts the PI gains during operation, imposing a minimal computational burden. Real-time PI controller tuning holds the potential to decrease system susceptibility to fluctuations in both motor parameters and load torque disturbances. Consequently, this approach facilitates achieving a satisfactory tracking performance. Notably, the method exhibits resilience to variations in controller inputs and can be readily implemented on mid-tier processors. In order to verify the performance of the proposed control method, a simulation study is conducted using MATLAB®/Simulink software. The obtained results present an indication of relatively high accuracy as well as satisfactory performance in terms of robustness against load torque perturbation and independence of parametric variations.
2023
2023 IEEE Asia Meeting on Environment and Electrical Engineering, EEE-AM 2023
Adaptive PI Control of PMSM for Electric Vehicle Application Based on Sliding-mode Extremum Seeking Algorithm / Rajabinasab, M.; Ghalebani, P.; Bruno, S.; Cometa, R.; La Scala, M.. - (2023). (Intervento presentato al convegno 2023 IEEE Asia Meeting on Environment and Electrical Engineering, EEE-AM 2023 tenutosi a vnm nel 2023) [10.1109/EEE-AM58328.2023.10395885].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/268920
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