Sliding mode control rotor flux MRAS based speed sensorless induction motor traction drive control for electric vehicles

Saqib J Rind; Saba Javed; Yawar Rehman; Mohsin Jamil; Saqib J Rind; Saba Javed; Yawar Rehman; Mohsin Jamil

doi:10.3934/electreng.2023019

AIMS Electronics and Electrical Engineering

2023, Volume 7, Issue 4: 354-379. doi: 10.3934/electreng.2023019

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Research article

Sliding mode control rotor flux MRAS based speed sensorless induction motor traction drive control for electric vehicles

1.
Department of Automotive & Marine Engineering, NED University of Engineering & Technology, University Road, Karachi, Pakistan
2.
Department of Electronics Engineering, NED University of Engineering & Technology, University Road, Karachi, Pakistan
3.
Department of Electrical & Computer Engineering, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, 240 Prince Phillip Drive, St. John's, NL A1B 3X5, Canada

Received: 26 June 2023 Revised: 01 October 2023 Accepted: 12 October 2023 Published: 25 October 2023

Climate change has highlighted a need to transition to more sustainable forms of transportation. Electric vehicles (EVs) and hybrid electric vehicles (HEVs) offer a promising alternative to conventional gasoline powered vehicles. However, advancements in power electronics and advanced control systems have made the implementation of high performance traction drives for EVs and HEVs easy. In this paper, a novel sliding mode control model reference adaptive system (SMC-MRAS) speed estimator in traction drive control application is presented. However, due to the unpredictable operational uncertainties of the machine parameters and unmodelled non-linear dynamics, the proportional-integral (PI)-MRAS may not produce a satisfactory performance. The Proposed estimator eliminates the PI controller employed in the conventional MRAS. This method utilizes two loops and generates two different error signals from the rotor flux and motor torques. The stability and dynamics of the SMC law are obtained through the Lyapunov theory. The potential of the proposed SMC-MRAS methodology is simulated and experimentally validated for an electric vehicle application. Matlab-Simulink environment is developed and proposed scheme is employed on indirect vector control method. However, for the experimental validation, the dSPACE 4011 R & D controller board was utilized. Furthermore, the SMC-MRAS performance is differentiated with PI-MRAS for speed regulation performance, tracking and estimation error, as well as the fast minimization of the error signal. The results of the proposed scheme illustrate the enhanced speed estimation, load disturbance rejection ability and fast error dynamics.
- electric vehicles,
- electric drives,
- induction motor control,
- MRAS,
- sensorless motor control,
- sliding mode control,
- traction drive
Citation: Saqib J Rind, Saba Javed, Yawar Rehman, Mohsin Jamil. Sliding mode control rotor flux MRAS based speed sensorless induction motor traction drive control for electric vehicles[J]. AIMS Electronics and Electrical Engineering, 2023, 7(4): 354-379. doi: 10.3934/electreng.2023019

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Abstract

Climate change has highlighted a need to transition to more sustainable forms of transportation. Electric vehicles (EVs) and hybrid electric vehicles (HEVs) offer a promising alternative to conventional gasoline powered vehicles. However, advancements in power electronics and advanced control systems have made the implementation of high performance traction drives for EVs and HEVs easy. In this paper, a novel sliding mode control model reference adaptive system (SMC-MRAS) speed estimator in traction drive control application is presented. However, due to the unpredictable operational uncertainties of the machine parameters and unmodelled non-linear dynamics, the proportional-integral (PI)-MRAS may not produce a satisfactory performance. The Proposed estimator eliminates the PI controller employed in the conventional MRAS. This method utilizes two loops and generates two different error signals from the rotor flux and motor torques. The stability and dynamics of the SMC law are obtained through the Lyapunov theory. The potential of the proposed SMC-MRAS methodology is simulated and experimentally validated for an electric vehicle application. Matlab-Simulink environment is developed and proposed scheme is employed on indirect vector control method. However, for the experimental validation, the dSPACE 4011 R & D controller board was utilized. Furthermore, the SMC-MRAS performance is differentiated with PI-MRAS for speed regulation performance, tracking and estimation error, as well as the fast minimization of the error signal. The results of the proposed scheme illustrate the enhanced speed estimation, load disturbance rejection ability and fast error dynamics.

References

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