Energy-efficient Nonlinear Model Predictive Control of BLDC Motor in Electric Vehicles

Ubare, Pramod; Ingole, Deepak; Sonawane, Dayaram

doi:10.1109/icc47138.2019.9123204

Cited by 9 publications

(6 citation statements)

References 15 publications

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“…Also, the injection of synthesized currents with angle advancement increases the torque capacity of the motor control [117]. For further improvement of the BLDC motor drive by DTC, the nonlinear model predictive controller (NMPC) scheme is used to control the desired torque and speed of the motor by minimizing energy while limiting the supplied current and maximum speed [127]. Moreover, this NMPC can be enhanced for real-time implementation to achieve torque ripple reduction, controlled degradation, etc.…”

Section: ) Torque Ripples Mitigation Based On Direct Torque Controlmentioning

confidence: 99%

Critical Review on Torque Ripple Sources and Mitigation Control Strategies of BLDC Motors in Electric Vehicle Applications

Prabhu,

Thirumalaivasan,

Ashok

2023

IEEE Access

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In recent years, electric vehicles (EVs) have attracted a lot of attention and are rapidly growing trends today due to their ability to compete with and overtake fossil fuel-powered vehicles among all electrified transportation tools. The primary focus of EV evolution is on improving driving range and optimizing energy consumption, both of which are essential demands achieved through improved and developing motor performance. The brushless direct current (BLDC) motor is one of the most superior choices for dynamic applications in EVs, providing the highest power density and capability of any motor. BLDCs are gaining popularity in EVs not only for their high performance in speed and position controls but also for meeting the requirements of smooth torque maintenance with torque ripple mitigation. This paper provides an overview of various advanced control strategies, such as field-oriented control (FOC), direct torque control (DTC), intelligent control (IC), controlling input voltage (CIV), current shaping techniques (CST), model predictive control (MPC), and sliding mode control (SMC). These strategies are used to regulate the torque ripples produced in BLDC motors, aiming to achieve energy-efficient EV performance for various applications. Additionally, it describes a cloud-based control system coupled with electric motor drives to address challenges in predicting current vehicle conditions for improved power distribution between the motor and battery systems. Furthermore, recent concerns and difficulties in advancing torque ripple mitigation control strategies are highlighted, with comparisons and discussions for future EV research. Finally, an evaluative study on BLDC motor drive in EVs with different control strategies reveals its significance and potential outcomes. INDEX TERMS Brushless Direct Current (BLDC) motor, Cloud based torque control, Control structural architecture, Electric Vehicles (EVs), Various control strategies for torque ripple mitigation.

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Section: ) Torque Ripples Mitigation Based On Direct Torque Controlmentioning

confidence: 99%

Critical Review on Torque Ripple Sources and Mitigation Control Strategies of BLDC Motors in Electric Vehicle Applications

Prabhu,

Thirumalaivasan,

Ashok

2023

IEEE Access

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“…where is vehicle's wheel radius (m) and G is the gear ratio. The EV and BLDC motors are coupled, this modifies the torque equation ( 2), which becomes [21]:…”

Section: Vehicle Modelmentioning

confidence: 99%

“…Therefore, the 3KW motor is appropriate for the three-wheeler EV. Its specifications are given in Table II [21]. Taking reference from Figure 2, the torque and speed values are noted in Table III.…”

Section: Wwwetasrcommentioning

confidence: 99%

Performance Assessment of the BLDC Motor in EV Drives using Nonlinear Model Predictive Control

Ubare

Sonawane²

2022

Eng. Technol. Appl. Sci. Res.

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In this paper, the Nonlinear Model Predictive Control (NMPC) technique is proposed for the control of BrushLess Direct Current (BLDC) motors to address the problem of over-excitation, specifically in Electric Vehicle (EV) applications. This over-excitation increases the overall energy consumption of the machine and eventually reduces the vehicle’s driving range. The developed NMPC incorporates a nonlinear model of the BLDC motor with EV load and obtains the optimal current through the optimal voltage applied to the machine to regulate the motor torque. The proposed NMPC is compared with three conventional control techniques, the Field-Oriented Control (FOC), the Direct Torque Control (DTC), and the hybrid (the combination of DTC and FOC) control. It is observed from the simulation results that the proposed NMPC controller is more energy efficient while maintaining performance. This paper also discusses the selection of the motor based on the specified vehicle requirements. This has been done by matching the vehicle speed-torque characteristic curve with the motor’s one.

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“…Other authors use the field-oriented control (FOC) [19,22]. Some authors use the Proportional Integral Derivative Controller (PID Controller) to control the motor this technique, enable to regulate the angular velocity [23,24]. Others, chose to use the hybrid Fuzzy Logic Controller (FLC), that switches between Fuzzy Logic Controller (FLC) and Proportional Integral Controller (PI Controller) to control the motor angular velocity [25].…”

Section: Introductionmentioning

confidence: 99%

Torque Control Oriented Modeling of a Brushless Direct Current Motor (BLDCM) Based on the Extended Park's Transformation

Majdoubi¹,

Masmoudi²,

Bakhti³

et al. 2021

JESA

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The wheeled mobile robots have recently become a better choice for repetitive tasks and especially in the agricultural field, but the existing constraint remains in its electrical motor, either in its consumption or its control. Therefore, we will focus on the Brushless Direct Current Motor (BLDCM) included on the robot wheels. Hence, the objective of this paper is to provide a model of BLDCM to have both maximum torque and a reduced torque ripple. Indeed, it is important to give a mathematical model that correctly represents the motor in three phases reference frame. To reduce the complexity of the model, we have used the extended park reference frame, which provides a biphasic representation in order to control the current using Proportional Integral Controller (PI Controller). The angular velocity of the motor is controlled using two types of regulators; ones called PI Controller and the other is Fuzzy Logic Controller (FLC) to compare its performance. The motor is attached to an inverter, which is controlled using a Full-Wave offset method. The modeling machine is done and validated using MATLAB Simulink Library. The simulation results of the modeling system are evaluated to have the profile of the wheel speed rotating freely, and the energetic efficiency of the BLDCM during functioning.

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Energy-efficient Nonlinear Model Predictive Control of BLDC Motor in Electric Vehicles

Cited by 9 publications

References 15 publications

Critical Review on Torque Ripple Sources and Mitigation Control Strategies of BLDC Motors in Electric Vehicle Applications

Critical Review on Torque Ripple Sources and Mitigation Control Strategies of BLDC Motors in Electric Vehicle Applications

Performance Assessment of the BLDC Motor in EV Drives using Nonlinear Model Predictive Control

Torque Control Oriented Modeling of a Brushless Direct Current Motor (BLDCM) Based on the Extended Park's Transformation

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