Improving the torque generation in self-sensing BLDC drives by shaping the current waveform

Generally, Brushless DC (BLDC) machines attract many industrialists due to their unique characteristics like better output, stabilized performance, and high torque to current ratio. BLDC drive has a long life, and they do not need maintenance; however, the drive has low starting torque and high cost. Thus, Non-stop monitoring and future prediction methods can reduce fault occurrence and improve system performance. In this paper, we have proposed the prognosis of BLDC drive faults using the Autoregressive Integrated Moving Average (ARIMA) Algorithm. Here, we consider the open circuit (OC) and short circuit (SC) faults in BLDC drive to prognosis by ARIMA technique. The ARIMA has a fixed structure, and it is particularly built for time series data. By data acquisition system, the drive parameters such as current, torque, and speed will be continuously obtained. Filtering out the high-frequency noise present in the data is the main principle of the ARIMA model. Matlab/Simulink platform is used to implement the process and analyze the results using prediction efficiency, the fault analysis in speed, flux, torque, current, and voltage.

show abstract

“…The drive is used in a hybrid vehicle, electric vehicle, DVD/CD players, medical industries, industrial robots, etc. [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Prognosis Of BLDC Drive Faults Using Autoregressive Integrated Moving Average Algorithm

Sarman¹,

Madhu

Prasad

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Nowadays, BLDC motors have been intensively used and involved in many industrial applications such as automotive technologies, medical and aerospace applications due to their light weights, superior efficiency and low power density [1] and also for their capability to provide different ranges of speeds [2].…”

Section: Introductionmentioning

confidence: 99%

An examination of the impact of the selected error criterion on the ACO performance in BLDC drives

Dr.Hamza Khalifa Alzarok

2023

jhas

View full text Add to dashboard Cite

Brushless direct current (BLDC) motor drives are becoming increasingly popular in motion control applications. As a result, a low-cost but effective BLDC motor speed controller is required. They are used in industrial and home appliances with conventional motor drive technology, such as robots, refrigerators and air conditioning systems. Brushless direct current (BLDC) drives are well known for their high efficiency and low maintenance. This work aims to design a non-conventional PID controller via Ant Colony Optimisers (ACO) in order to obtain an efficient speed performance for a BLDC motor "namely, Maxon EC flat". Moreover, when ACO is used for tuning of PID control, the objective function is required. Therefore, in this work, four different objective functions which are MSE, ISE, IAE, and ITAE are applied and their performance was compared in terms of motor' speed stability. In a simulation environment, the PID controller is used to control the speed of BLDC motors under three testing conditions which are Small, medium, and high inertia loads. The simulation results demonstrate that MSE offers the best performance under low and high inertial loading cases. Whereas, IAE has been superior compared with other criterions when medium loads are applied. Moreover, this paper shows a stability speed- power consumption trade-off problem. In other words, achieving a fast stability via any type of error indices doesn’t guarantee a low amount of consuming energy.

show abstract

Improving the torque generation in self-sensing BLDC drives by shaping the current waveform

Cited by 2 publications

References 15 publications

Prognosis Of BLDC Drive Faults Using Autoregressive Integrated Moving Average Algorithm

Prognosis Of BLDC Drive Faults Using Autoregressive Integrated Moving Average Algorithm

An examination of the impact of the selected error criterion on the ACO performance in BLDC drives

Contact Info

Product

Resources

About