Design of optimal PI controller for torque ripple minimization of SVPWM-DTC of BLDC motor

Kumar, Mallempati Sunil; Satheesh, Gopisetti; Sujatha, P.

doi:10.11591/ijpeds.v14.i1.pp283-293

Cited by 7 publications

(5 citation statements)

References 23 publications

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“…In addition, the FLC-based speed control is proposed instead of PI controllers to reduce starting current, avoid overshoot in torque and speed responses, simplify the design, and minimize complicated mathematical equations. Furthermore, the SVPWM combined DTC is preferred for optimum steady-state performance in terms of torque ripple minimization and speed regulation, apart from the necessity for a switching table and a hysteresis controller [115].…”

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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“…To implement Equation ( 14), various estimation techniques are used to adaptively calculate the unknown parameters. This section presents a comparison of the methods employed for an assumed model, followed by a comparison with the DC motor model in Equation (29) to identify the state-of-the-art methods for comparison with deterministic artificial intelligence.…”

Section: Different Model-following Self-tuner Control Benchmarksmentioning

confidence: 99%

“…Highlighting the vulnerability of conventional direct torque control to ripple, Kumar et al [29] sought to achieve minimization and regulation of speed, where their novel instantiation of space vector pulse width modulation reduced the torque ripple by 63.1% when compared to conventional PI and 58.5% when compared to a second benchmark, a PSO-PI controller.…”

Section: Introduction 1motivationmentioning

confidence: 99%

Autonomous Drone Electronics Amplified with Pontryagin-Based Optimization

Sands

2023

Electronics

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In the era of electrification and artificial intelligence, direct current motors are widely utilized with numerous innovative adaptive and learning methods. Traditional methods utilize model-based algebraic techniques with system identification, such as recursive least squares, extended least squares, and autoregressive moving averages. The new method known as deterministic artificial intelligence employs physical-based process dynamics to achieve target trajectory tracking. There are two common autonomous trajectory-generation algorithms: sinusoidal function- and Pontryagin-based generation algorithms. The Pontryagin-based optimal trajectory with deterministic artificial intelligence for DC motors is proposed and its performance compared for the first time in this paper. This paper aims to simulate model following and deterministic artificial intelligence methods using the sinusoidal and Pontryagin methods and to compare the differences in their performance when following the challenging step function slew maneuver.

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“…Highlighting the vulnerability of conventional direct torque control to ripple, Kumar, et. al, [30] sought minimization and speed regulation, where their novel instantiation of space vector pulse width modulation reduced the toque ripple by 63.1% when compared to conventional PI and 58.5% when compared to a second benchmark, a PSO-PI controller.…”

Section: (A) (B)mentioning

confidence: 99%

Autonomous Drone Electronics Amplified With Pontryagin–Based Optimization

Sands¹

2023

Preprint

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In the era of electrification and artificial intelligence, direct current motors are widely utilized with numerous innovative adaptive and learning methods. Traditional methods utilize model-based algebraic techniques with system identification, such as recursive least squares, extended least squares, and autoregressive moving averages. The new method known as deterministic artificial intelligence asserts physical-based process dynamics to achieve target trajectory tracking. There are two common autonomous trajectory generation algorithms: sinusoidal function and Pontryagin's based generation algorithm. This thesis aims to simulate model-following and deterministic artificial intelligence methods using sinusoidal and Pontryagin's methods and compare their performance difference when following challenging step function slew maneuver.

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Design of optimal PI controller for torque ripple minimization of SVPWM-DTC of BLDC motor

Cited by 7 publications

References 23 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

Autonomous Drone Electronics Amplified with Pontryagin-Based Optimization

Autonomous Drone Electronics Amplified With Pontryagin–Based Optimization

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