Design a Robust Controller for BLDC speed control

Electric vehicles are currently being developed with the concept of saving energy and environmentally responsible. Electric vehicles use electric motors as the main driving motor. The electric motor which is currently increasingly used is the Brushless Direct Current (BLDC) motor. The BLDC motor controller is more expensive than the price of the BLDC motor itself. The BLDC motor controller has a working temperature range when working. The purpose of this study was to analyze the effect of variations in load values and the speed of electric vehicles on the temperature of the BLDC motor controller. This research was conducted by the experimental method by giving a treatment, then evaluating the effect caused on an object of research. The results showed that there was an influence of load value variations on the BLDC motor controller temperature. Values that look significant are at speeds of 0.5 m/sec and 2.5 m/sec starting from 3 kg to 5 kg. There is no influence on the variation of speed values on the temperature of the BLDC motor controller. The temperature value is stable at 2 kg and 3 kg loads with speed variations from 0.5 m/sec to 2.5 m/sec. Simultaneously variations in load and speed values affect the temperature of the BLDC motor controller by 57.7% with the lowest temperature value at 0.5 m/s and a load of 1 kg with a temperature of 33.34℃ and the highest temperature value at a speed of 2.5 m/sec and a load of 5 kg with a temperature of 37.58℃. Keywords: Electric vehicles, controllers, BLDC motors, temperature.

The advancements in the field of materials and force gadgets, coupled with the increased affordability of highperformance processors, have led to a widespread adoption of Brushless Direct Current (BLDC) motors across various industries. These applications range from household appliances to automotive, aerospace, and medical sectors. The widespread use of may be attributed to its manifold advantages over various types of engines, such as its superior efficiency, robust power output, extended operational lifespan, relatively quiet operation, and broader range of achievable speeds. Due to the increasing adoption of Brushless Direct Current (BLDC) motors in many real-life applications as a replacement for traditional motors, this paper aims to compile and evaluate a comprehensive list of control algorithms employed for BLDC motor control. This study discusses several ways for managing speed and current, including hysteresis band control, variable DC-link voltage control, and Pulse Width Modulation (PWM) control schemes. The optimization of Proportional-Integral-Derivative (PID) gains for these controlling techniques is achieved through the utilization of the particle swarm optimization (PSO) algorithm. By employing Fast Fourier Transform (FFT) analysis to examine the controller behavior through frequency analysis of the output signals and calculating the Total Harmonic Distortion (THD), a more advantageous control method may be determined.

Brushless Direct Current (BLDC) Motor is an electromagnetic device that converts electrical energy into mechanical energy. BLDC motor is a type of motor used in electric cars and does not need brush for magnetic field replacement (commutation), but is carried out electronically commutated. In BLDC motor, temperature in the motor play important role on motor performance such as maximum power and efficiency. In this research the development of liquid cooling of BLDC motor is described. Development starts from the design, computation using software and the realization of the motor design results. The construction of a brushless DC motor is very similar to that of an ac motor, known as permanent magnet synchronous motor. The stator consisting of a core and copper windings forming a core and armature unit. There are 2 identical stators to form the BLDC.

The electric vehicle’s overall efficiency can be augmented through the implementation of the regenerative braking system (RBS), which serves to extend the drive range. This paper explores a method for further increasing said range by implementing a roof‐mounted photovoltaic (PV) system in conjunction with RBS, resulting in an impressive 25.14% increase to the vehicle’s driving distance. The roof‐mounted PV and regenerative braking work together to charge the dual battery pack present within the vehicle, following a specific sequence as dictated by its controller. Maximum energy is extracted from the PV module via employment of a particle swarm optimization (PSO)‐based maximum power point tracking (MPPT) algorithm, while propulsion is provided through utilization of a brushless direct current (BLDC) motor driven by reduced switch voltage source inverter (VSI). The BLDC motor itself is controlled utilizing field‐oriented control (FoC), with hybrid ANN‐PID and Fuzzy‐PID (HAP‐FUP) controllers employed at the outer loop; furthermore, HAP‐FUP controller performance was compared favorably against other top controllers such as model predictive controller (MPC), sliding mode controller (SMC), and conventional PID controller, ultimately demonstrating superior performance when it comes to reducing rise time and settling time of vehicle speed.

Brushless direct current (BLDC) motors are frequently used in dynamic applications. A Brushless DC Motor is similar to a Brushed DC Motor, except that as the names indicate, they are electronically commutated rather than using brushes for commutation. Brushes are utilized in conventional brushed direct current motors to transmit power to the rotor while they rotate in a fixed magnetic field. Small Brushless DC Motors have flourished as a result of current power electronics and microprocessor technology, both in terms of price and performance. This paper will discuss the history of BLDC motors, their different types, construction, operating principles, and several control mechanisms for driving BLDC motors in various industrial applications. Keywords: BLDC Motor, Pulse Width Modulation (PWM), Hall Effect Sensors, Sensorless control, Rotor, Stator, Back Emf, Trapezoidal Control, Sinusoidal Control, Field Oriented Control

A brushless direct current (BLDC) motor has high reliability and a long life because it eliminates mechanical friction, and compensates for the defects of a direct-current (DC) motor by removing the brush and commutator. Compared to a DC motor, BLDC motor has the excellent efficiency because there is no voltage drop or friction loss of the brush. However, when the motor is operated for a long time with a high output, the internal motor temperature rises, and the copper-winding temperature increases. The temperature rise of the internal motor affects the resistance of the copper winding and the performance of the permanent magnet. This study investigates the efficiency of a 500 W BLDC motor with a varying air flow rate. The temperature rise and efficiency of the BLDC motor are studied by applying inlet flow rates of 0, 30 and 50 L/min during a 20 min load test. The temperature rise is very high at 0 L/min and the efficiencies are calculated as 81.9%, 82% and 82.7%. This study can be used as a basic study on the optimal air flow rate to the internal motor.

–This paper designs the high-efficiency and the low-cost drive system of the small-size electric vehicles (EVs). The power circuit for driving the dc motor is designed by considering both the cost and efficiency. In order to reduce the conduction loss of MOTFET and diode for controlling an armature voltage, some MOSFETs and diodes at the armature are in parallel connection. An operating sequence for both the field current and the armature voltage according to the accelerator pedal angle is suggested for changing smoothly the rotating direction of dc motor. Through the simulation studies, the performances of the proposed methods are verified. Keywords: Electric vehicle, conduction loss, buck converter, switching loss, DC motor 1. Introduction Recently, because environmental pollution and the energy crisis are rising globally, electric vehicles (EVs) are promising instead of traditional gasoline vehicles. As the EVs are driven by electricity stored in a battery, they still suffer from the main problem as short driving range due to the low energy content of the batteries. As how to use the battery’s energy efficiently is a hot issue for developing EVs, it is important to design the drive system of a traction motor with high efficiency. Selection of traction motors for propulsion system is very important step that requires special attention. In fact, the choice of electric-propulsion systems for EVs mostly depends on three factors: efficiency, cost, and reliability. In an industrial point of view, the major types of electric motors adapted or under serious consideration for EVs include the dc motor, an induction motor (IM), and brushless DC (BLDC) motor. The BLDC motor has been widely used in the EVs, because it provides high power density, and has higher efficiency than induction motor [1]-[3]. By the way, in order to drive the BLDC motor, the 3-phase PWM inverter and complex control system are required [4]. Recently, the price of PM has been dramatically raised. They cause the increase of the manufacturing cost of the EVs. The small-size EVs such as the golf car and scooters require the simple propulsion system in order to reduce the manufacturing cost. Although a brushed dc motor has some problems such as requirement of maintaining both the brush and commutation, it has some advantages like a simple drive system and high starting torque. Thus, the dc motor as the traction motor is more suitable at the low cost small-size EVs [5]. In this paper, the power circuit for driving the dc motors is designed by considering both the cost and efficiency. In order to reduce the conduction loss of MOTFET and diode for controlling an armature voltage, some MOSFETs and diodes at the armature are in parallel connection. An algorithm to change smoothly the rotating direction of the motor is suggested. In order to verify the performances of proposed methods, some simulation studies are carried out.

A brushless direct current (BLDC) motor is widely used in automotive and industrial applications due to its low noise and high performance. However, traditional BLDC motor control relies on Hall-effect sensors, which increase costs, enlarge motor dimensions, and risk errors from sensor failures. This research focuses on implementing a sensorless control system for a 350W, 48V BLDC motor. The goal is to achieve stable operation at a set speed of 250 rpm, with a steady-state error ≤3%, under varying loads from 0 Nm to 2.7 Nm. Using the Ziegler-Nichols PID tuning method, the study was conducted in the Electrical Machinery Laboratory at Bandung State Polytechnic. The results show that the sensorless control system effectively maintains setpoint speeds of 90 rpm, 120 rpm, 200 rpm, and 250 rpm. At 250 rpm, the system achieved an average steady-state error of 2.44% using PID parameters Kp = 3.13, Ki = 8.69, and Kd = 0.25. The motor’s output power ranged from 136.88W at minimum load to 297.92W at maximum load, demonstrating improved efficiency and system performance

Electric vehicle is an important component in any smart city and Brushless DC (BLDC) motor is an obvious choice for an electric vehicle. But most of the existing technology of BLDC motor drive suffers from a significant amount of torque ripple. In this paper reduction of torque ripple in Brushless DC motor is studied and a technique has been proposed to minimize it. In a conventional three phase Brushless DC motor with 120° conduction mode torque ripple occurs at 60° interval. i.e. six times in a complete cycle. Torque ripple occurs due to change over of load current from one phase to the other. In this paper an OFF delay has been introduced in the gate firing circuit of the inverter which feeds the brushless DC motor and minimizes the torque ripple. Also this delay has been presented as a function of speed by which the OFF delay can be predetermined to be incorporated in the gate circuit. The propped topology is verified using a suitable computer simulation in MATLAB.

Brushless direct current (BLDC) motor has been widely used in industrial production. Based on the method of model design, BLDC motor speed control is studied. In Matlab/Simulink, a fuzzy PID speed control model of BLDC motor is established, and C Code is generated by Real-Time Workshop (RTW) technology. After that, Code Warrior is compiled into machine Code and written into ECU. The results show that the fuzzy Proportion Integration Differentiation (PID) controller can improve the speed performance of the BLDC.

Brushless direct current (BLDC) motor is a permanent-magnet synchronous motor but the commutator and the brushes are replaced by electronic commutation system. This motor is characterized by many advantages compared with other motors and it being used in a wide range of applications. In BLDC motor, speed control plays an essential role; the speed-controller has to respond rapidly to command changes and to offer enough robustness against the variations of the mechanical load. In this paper, the design of Grey-PID controller is proposed as speed controller of BLDC motor where a new adaptation algorithm is suggested to update the parameters of the adaptive PID controller. The proposed algorithm takes advantages of both of Grey model GM(1,1) and gradient-descent method. The Grey-PID speed control system is simulated by using MatlabSimulink environment. The simulation results confirm that the proposed controller performs better than the traditional PID controller. By using Grey-PID controller, starting the motor or sudden change of speed can be performed with short rise and settling times, no overshoot and no steady-state error. The proposed controller, also, has a great ability to restrain the fluctuation of speed caused by load disturbance.

Performance evaluation of a brushless DC (BLDC) motor with conventional PI and Fuzzy Logic based speed controller is presented in this paper. The BLDC motor with non-sinusoidal (trapezoidal) back-electromotive force has been analyzed with both the speed and current controllers. It is the always preferred to have a drive with faster and smoother speed response and reduced ripples in current and torque. The controlling schemes for BLDCM using its Back EMF have been conventionally used into many applications. In this paper, a simple control scheme has been implemented which does not need to know the back emf or shape function and even no complicated calculations. In order to solve the problems associated with conventional PI speed controller, Fuzzy logic speed controller is proposed to reduce starting current, eliminate overshoot in the torque and fast speed response. It is simple in design and eliminates the complex mathematical computation. The effectiveness of proposed system has been validated by simulation results and improved performance of controlling BLDCM. The proposed algorithm gives robust control. The robustness of the proposed algorithm is demonstrated through the MATLAB simulation.

This study details the design and testing of a custom test rig for evaluating the performance of both open and shrouded rotors. The rig includes a two-axis load cell that is directly connected to the rotor to measure the rotor thrust separated from the total thrust when testing shrouded rotors and ensure accurate torque measurements, independent of external structural influences. Moreover, a main load cell is used to measure the total thrust for both configurations (open and shrouded rotor), as it is connected to the entire setup. Rotor RPM is monitored by capturing the voltage frequency from the BLDC motor, controlled using a Pololu Maestro Controller through the electronic speed controller. A shunt resistance is used to calculate the current through the electric Brushless Direct Current (BLDC) motor and by measuring the voltage, the electric power is calculated. By combining both mechanical and electrical power measurements, the BLDC motor’s efficiency is calculated. Automated data collection is conducted using National Instruments DAQ systems, with averaged measurements of thrust, torque, RPM, current, and voltage. Two rotors are tested to obtain performance data for both open and shrouded configurations. Additionally, a computational study is carried out to account for the aerodynamic effects of the rig’s structural elements. Uncertainty analysis is employed to assess the reliability of the experimental results by quantifying the numerical errors associated with both random and systematic errors encountered during the rotor’s performance evaluation.

The paper presents a transformation matrix and a mathematical model for 15-phase brushless direct current (BLDC) motor with an opened phase. With the mathematical model, the field-oriented control can be put into use for the BLDC motor. According to the model, a fault-tolerant control system is proposed to guarantee the high-performance of 15-phase BLDC motor subject to the loss of one of a stator phase opened circuit. Simulation result reveals that the fault-tolerant system can meet the demand of disturbance-free operation when the open-circuit fault occurs in stator windings.

This paper proposes the artificial intelligence (AI)-based optimal PID controller design optimization of brushless direct current (BLDC) motor speed control with phase advance approach. The proposed control system allows the speed adjustment of the BLDC motor by phase advance technique. In this paper, two selected AI algorithms, i.e., the adaptive tabu search (ATS) and the intensified current search (ICS) are conducted as the optimizer for the PID controller design. The proposed control system is simulated by MATLAB/SIMULINK. Results obtained by the ATS and ICS will be compared with those obtained by the Ziegler-Nichols (ZN) tuning rule and the genetic algorithm (GA). It shows that the speed response of the BLDC motor by phase advance with the PID controller optimized by the ICS outperforms better than the ZN, GA and ATS.