scholarly journals Digital twin of mechatronic drive based on the optimal control model of BLDC motor

2020 ◽  
Vol 329 ◽  
pp. 03071
Author(s):  
Sergei Trefilov
Keyword(s):  
Optimal Control ◽  
Viscous Friction ◽  
Control Model ◽  
Control Device ◽  
Operating Conditions ◽  
Bldc Motor ◽  
Digital Twin ◽  
Brushless Dc ◽  
External Forces ◽  
And Control

This paper presents a digital twin of a mechatronic drive based on a brushless DC (BLDC) motor model based on a nonlinear discrete optimal control model. Some parameters of a BLDC motor, such as resistance and inductance of windings, magnetic flux, viscous friction coefficient in bearings, angular velocity and electromagnetic moment, can change due to both degradation of structural elements and external forces. Simulation by a complete enumeration of the values of the parameters of the mechatronic device with a certain step will make it possible to adapt the program of the control device to changing operating conditions according to the criterion of minimizing the control energy by changing the parameters of the state matrices and control of the digital twin. As a result, the accuracy of the movement of the mechatronic device along the given trajectory will increase due to the greater correspondence of the control parameters to the real object.

Performance of Brushless DC Drive with Single Current Sensor Fed from PV with High Voltage-Gain DC-DC Converter

2018 ◽  
Vol 9 (1) ◽  
pp. 33
Author(s):  
G. G RajaSekhar ◽  
Basavaraja Banakara
Keyword(s):  
High Voltage ◽  
Operating Conditions ◽  
Current Sensor ◽  
Motor Drive ◽  
Voltage Gain ◽  
Bldc Motor ◽  
Pv System ◽  
Brushless Dc ◽  
High Voltage Gain ◽  
The Cost

This paper presents the performance of Brushless DC (BLDC) Motor drive with only one positioning sensor instead of three conventional sensors. The three sensor units are replaced with a single stator current sensor unit in DC bus which further reduces the cost increasing the reliability of the drive system. Using a single sensor in stator requires minimum electronic equipment for the purpose of measurement process. This paper evolves the BLDC motor drive fed from PV system. A high voltage-gain DC-DC converter is presented in this paper to step-up the voltage from PV system. The appropriateness of PV fed BLDC motor drive is verified for variable increamental speed with fixed torque and variable decremental speed with fixed torque operating conditions. BLDC motor drive performance is also performed for variable torque with fixed peed working condition. The proposed system and results are developed using MATLAB/SIMULINK software.

scholarly journals Design and Analysis of a Dual Rotor Multiphase Brushless DC Motor for its Application in Electric Vehicles

2021 ◽  
Vol 11 (6) ◽  
pp. 7846-7852
Author(s):  
M. Hussain ◽  
A. Ulasyar ◽  
H. Sheh Zad ◽  
A. Khattak ◽  
S. Nisar ◽  
...  
Keyword(s):  
Fault Tolerance ◽  
Power Density ◽  
Electric Vehicles ◽  
High Power ◽  
Operating Conditions ◽  
Design Parameters ◽  
High Power Density ◽  
Bldc Motor ◽  
Brushless Dc ◽  
Stator Current

The main objective of this paper is to study the effect of phase numbers in the dual rotor Brushless DC (BLDC) motor for its application in Electric Vehicles (EVs). The performance of two novel 5-, and 7-phase dual rotor BLDC motors is compared against the standard 3-phase dual rotor BLDC motor. The proposed motors combine the positive characteristics of multiphase BLDC motor and the dual rotor BLDC motor thus achieving better fault tolerance capability, high power density, and less per phase stator current. Finite Element Method (FEM) was used to design the 3-, 5-, and 7-phase dual-rotor BLDC motors. The design parameters and operating conditions are kept the same for a fair comparison. The stator current and torque performance of the proposed motors were obtained with FEM simulation and were compared with the standard 3-phase dual rotor BLDC motor. It is possible to use low power rating power electronics switches for the proposed motor. The simulation results also validate low torque ripples and high-power density in the proposed motors. Finally, the fault analysis of the designed motors shows that the fault tolerance capability increases as the phase number increases.

scholarly journals Sensorless BLDC motor controller little power to the comfort of motor vehicles

2018 ◽  
Vol 19 (6) ◽  
pp. 708-711
Author(s):  
Emil Sadowski ◽  
Artur Pakosz
Keyword(s):  
Low Power ◽  
Supply Voltage ◽  
Motor Vehicles ◽  
Bldc Motor ◽  
Brushless Dc Motors ◽  
Brushless Dc ◽  
Dc Motors ◽  
Speed Up ◽  
Control Modules ◽  
And Control

The article discusses low-power brushless motors and control modules that are used, among others, in trucks and buses. Also presented are methods of controlling brushless DC motors. The own low power controller was also implemented, enabling smooth start-up and control of the engine speed up to 3,000 revolutions and supply voltage up to 32V DC. This article also presents the results of the measurements of BLDC motor control used in automotive vehicles, mainly in trucks and buses.

scholarly journals Using Age Structure for a Multi-stage Optimal Control Model with Random Switching Time

2019 ◽  
Vol 184 (3) ◽  
pp. 1065-1082 ◽  
Author(s):  
Stefan Wrzaczek ◽  
Michael Kuhn ◽  
Ivan Frankovic
Keyword(s):  
Optimal Control ◽  
Switching Time ◽  
Control Model ◽  
Multi Stage ◽  
Numerical Solution Methods ◽  
Solution Methods ◽  
Random Switching ◽  
Age Structured ◽  
Two Stages ◽  
And Control

AbstractThe paper presents a transformation of a multi-stage optimal control model with random switching time to an age-structured optimal control model. Following the mathematical transformation, the advantages of the present approach, as compared to a standard backward approach, are discussed. They relate in particular to a compact and unified representation of the two stages of the model: the applicability of well-known numerical solution methods and the illustration of state and control dynamics. The paper closes with a simple example on a macroeconomic shock, illustrating the workings and advantages of the approach.

scholarly journals Design and Simulation of Adaptive PID Controller Based on Fuzzy Q-Learning Algorithm for a BLDC Motor

2020 ◽  
Author(s):  
Reza Rouhi Ardeshiri ◽  
Nabi Nabiyev ◽  
Shahab S. Band ◽  
Amir Mosavi
Keyword(s):  
Reinforcement Learning ◽  
Pid Controller ◽  
Control Method ◽  
Learning Algorithm ◽  
Bldc Motor ◽  
Motor Speed ◽  
Q Learning ◽  
Brushless Dc ◽  
Intelligent Control Systems ◽  
And Control

Reinforcement learning (RL) is an extensively applied control method for the purpose of designing intelligent control systems to achieve high accuracy as well as better performance. In the present article, the PID controller is considered as the main control strategy for brushless DC (BLDC) motor speed control. For better performance, the fuzzy Q-learning (FQL) method as a reinforcement learning approach is proposed to adjust the PID coefficients. A comparison with the adaptive PID (APID) controller is also performed for the superiority of the proposed method, and the findings demonstrate the reduction of the error of the proposed method and elimination of the overshoot for controlling the motor speed. MATLAB/SIMULINK has been used for modeling, simulation, and control design of the BLDC motor.

Integrating Multi-Vehicle Routing and Control: A Comparison of Three Solution Strategies

2018 ◽  
Author(s):  
Tianchen Liu ◽  
Shapour Azarm ◽  
Nikhil Chopra
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Vehicle Routing ◽  
Continuous Time ◽  
Control Model ◽  
Routing Problem ◽  
Solution Strategies ◽  
Shortest Route ◽  
Time Optimal ◽  
And Control

This paper presents the results of a comparison study of three solution strategies for integrating a routing and a control model for a fleet of vehicles planned to visit a number of customer locations. The three strategies considered are: (i) shortest route followed by a constant speed model, (ii) shortest route followed by an optimal control model, and (iii) optimal control-based route. The objective is to compare and contrast optimized costs, a combination of vehicles’ travel time and control cost (or energy consumption), following these different strategies. The routing problem considers a capacitated multi-vehicle routing without time windows but with capacity and customer demand requirements. The control problem considers a continuous-time optimal control problem. Using the data from a benchmark multi-vehicle routing problem, as an example, it is shown that when compared with using a commonly used constant speed model for all vehicles, the optimized cost can be reduced by incorporating optimal control strategies. To the best of our knowledge, this is the first study in the literature that compares solution strategies for control-based vehicle routing, and in particular, formulates and explores continuous time optimal control combined with capacitated multi-vehicle routing. Furthermore, the effect of existence of wind on the vehicle dynamic equations is considered, and optimal results of the routing problem with different wind directions are compared.

Sign in / Sign up

Export Citation Format

Share Document