Artificial neural networks applied on induction motor drive for an electric vehicle propulsion system

Saleeb, Hedra; Kassem, Rasha; Sayed, Khairy

doi:10.1007/s00202-021-01418-y

Cited by 17 publications

(9 citation statements)

References 39 publications

(37 reference statements)

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“…Often, the electrical motors work as a part of larger electromechanical systems and hence behaviour of the model in association with other components in the systems is vital [23]. The screw compressor [24] and centrifugal pumps [25] are two examples which utilize LSPMSMs in integrated mechanical systems.…”

Section: Lspms Motor Induction Motor Ipm Motormentioning

confidence: 99%

Bond graph model of line-start permanent-magnet synchronous motors

et al. 2022

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The bond-graph (BG) enables to model multi-physics systems in the energy domains. This paper shows that BG models are an alternative, more intuitive and simpler to interpret, graphical tool as compared to existing dynamic models for performance prediction of the line-start permanent-magnet synchronous motors (LSPMSMs). It includes electrical, magnetic, and mechanical energy domains where the stator windings, rotor bars, and permanent magnets are the main components of the model. The dynamical equations of the proposed BG are extracted and solved using the MATLAB ordinary differential equation solver for a sample LSPMSM. The dynamics of the studied LSPMSM is investigated under two operating conditions (1) a healthy motor and (2) a motor with broken rotor bars. The simulation results are compared with the finite-element analysis (FEA) as the most accurate method to simulate the electric motor behaviour. It is shown that the proposed BG model accurately predicts the performance parameters of the motor such as current, torque, and speed under various operating conditions. In addition to the modelling validation, the transient behavior of the LSPMSM are discussed to describe the possible reasons for its behaviour during transient and steady-state operating conditions.

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Section: Lspms Motor Induction Motor Ipm Motormentioning

confidence: 99%

Bond graph model of line-start permanent-magnet synchronous motors

et al. 2022

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“…Permanent magnet synchronous motors (PMSMs) are a class of motors that create field excitation through the permanent magnet (Chen et al, 2019; Feng et al, 2021). Different from the classic motors (Saleeb et al, 2021), the usage of excitation windings is avoided in PMSMs, thereby improving the system efficiency and reliability. Due to these advantages, PMSMs have been extensively used in various fields, such as electric vehicles (Seo et al, 2020), cranes (Sun et al, 2017), and aerospace engineering (Chou and Liaw, 2014).…”

Section: Introductionmentioning

confidence: 99%

Nonlinear speed-tracking control with overcurrent protection for uncertain permanent magnet synchronous motor systems

Zhang

Ren

et al. 2023

Transactions of the Institute of Measurement and Control

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For the speed-tracking control of permanent magnet synchronous motor (PMSM) systems, fast dynamic response and high reference speed require a large transient current to provide sufficient electromagnetic torque. However, the excessive transient current may damage the drive circuit and threaten the system safety. Besides, it is also important to pay attention to the influence of multiple disturbances including system parameter uncertainties and unknown load torque variation. To solve these problems, we propose a nonlinear speed-tracking control approach for uncertain PMSM systems. More specifically, based on the cascade control structure and by introducing auxiliary smooth function, we first develop a nonlinear current-constrained controller (CCC) to guarantee the speed tracking, disturbance rejection, and overcurrent protection simultaneously. In order to improve the robustness of the desired performances, we further implement extended state observer (ESO) techniques to propose an ESO-based CCC (ESO-CCC). Finally, comparative experiments are implemented in a 5.5 kW PMSM platform to verify the performance of the proposed two controllers.

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“…Dhamija et al [9] have developed a torque vector control scheme for the in-wheel motor of four-wheel drive electric vehicles based on non-linear model predictive control. Later, Saleeb et al [10] developed a driving strategy based on an artificial neural network for direct torque control to drive electric vehicles, which reduced the core loss and improved the driving efficiency.…”

Section: Introductionmentioning

confidence: 99%

In-Wheel Motor Control System for Four-Wheel Drive Electric Vehicle Based on CR-GWO-PID Control

Xu,

Wang,

Xiao

et al. 2023

Sensors

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In order to improve the driving performance of four-wheel drive electric vehicles and realize precise control of their speed, a Chaotic Random Grey Wolf Optimization-based PID in-wheel motor control algorithm is proposed in this paper. Based on an analysis of the structural principles of electric vehicles, mathematical and simulation models for the whole vehicle are established. In order to improve the control performance of the hub motor, the traditional Grey Wolf Optimization algorithm is improved. In particular, an enhanced population initialization strategy integrating sine and cosine random distribution factors into a Kent chaotic map is proposed, the weight factor of the algorithm is improved using a sine-based non-linear decreasing strategy, and the population position is improved using the random proportional movement strategy. These strategies effectively enhance the global optimization ability, convergence speed, and optimization accuracy of the traditional Grey Wolf Optimization algorithm. On this basis, the CR-GWO-PID control algorithm is established. Then, the software and hardware of an in-wheel motor controller are designed and an in-wheel motor bench test system is built. The simulation and bench test results demonstrate the significantly improved response speed and control accuracy of the proposed in-wheel motor control system.

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Artificial neural networks applied on induction motor drive for an electric vehicle propulsion system

Cited by 17 publications

References 39 publications

Bond graph model of line-start permanent-magnet synchronous motors

Bond graph model of line-start permanent-magnet synchronous motors

Nonlinear speed-tracking control with overcurrent protection for uncertain permanent magnet synchronous motor systems

In-Wheel Motor Control System for Four-Wheel Drive Electric Vehicle Based on CR-GWO-PID Control

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