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The brushless direct current motor (BLDCM) is widely accepted and adopted by many industries instead of direct current motors due to high reliability during operation. Brushless direct current (BLDC) has outstanding efficiency as losses that arise out of voltage drops at brushes and friction losses are eliminated. The main factor that affects the performance is temperature introduced in the internal copper core windings. The control of motor speed generates high temperature in BLDC operation. The high temperature is due to presence of ripples in the operational current. The purpose is to present an effective controlling mechanism for speed management and to improve the performance of BLDCM to activate effective management of speed.

The purpose is to present an optimal algorithm based on modified moth-flame optimization algorithm over recurrent neural network (MMFO-RNN) for speed management to improve the performance. The core objective of the presented work is to achieve improvement in performance without affecting the design of the system with no additional circuitry. The management of speed in BLDCM has been achieved through reduction or minimization of ripples encircled with torque of the motor. The implementation ends in two stages, namely, controlling the loop of torque and controlling the loop of speed. The MMFO-RNN starts with error optimization, which arises from both the loops, and most effective values have been achieved through MMFO-RNN protocol.

The parameters are enriched with Multi Resolution Proportional Integral and Derivative (MRPID) controller operation to achieve minimal ripples for the torque of BLDC and manage the speed of the motor. The performance is increased by adopting this technique approximately 12% in comparison with the existing methodology, which is the main contributions of the presented work. The outcomes are analyzed with the existing methodologies through MATLAB Simulink tool, and the comparative analyses suggest that better performance of the proposed system produces over existing techniques, and proto type model is developed and cross verifies the proposed system.

The MMFO-RNN starts with error optimization, which arises from both the loops, and most effective values have been achieved through MMFO-RNN protocol. The parameters are enriched with MRPID controller operation to achieve nil or minimal ripples and to encircle the torque of Brushless Direct Current and manage the speed.

The efficient speed controller is found to be an important requirement to run the motor for the brushless direct current (BLDC) motor. This requirement is considered as superior, as it may increase the operating speed and system efficiency. In the existing methods, proportional plus integral (PI) controller has been included because of its simple architecture. But the PI controller produces load disturbance, control complexity and some parametric (Proportional plus integral) variations. The purpose of this proposed controller is to overcome the problems produced by PI controller in BLDC motor.

The proposed BLDC motor is developed with fixed order H-infinity controller. In this architecture, both the weight functions and transfer functions were included to design the controller. This controller has been included in this BLDC to detect the rotor position. The optimal position of rotor is identified by introducing particle swarm optimization algorithm.

The torque that obtained in the motor is highly reduced by this proposed controller and also enhances the speed. The BLDC motor is modelled in a MATLAB environment.

The performance of the torque, speed and back electro-motive force is analysed and compared with the existing controllers such as fuzzy proportional plus integral plus derivative, sensing algorithm and fuzzy proportional plus derivative controller.

Simulation results show that the proposed technique gives better results than the other existing controllers.

The purpose of this paper is to develop a generalized observer and controller for brushless direct current (BLDC) motor to make the system more robust for parameter variations, load torque and speed tracking.

A robust interconnection and damping assignment passivity-based control (IDA-PBC) technique for BLDC motor is introduced in this paper. The IDA-PBC is used to obtain the reference voltages for pulse width modulation (PWM) control. The immersion and invariance (I&I) observer is used to estimate the load torque and speed of the BLDC motor. At the time of starting, the motor rotates in arbitrary direction, and sometimes, because of the cogging action, it may take a huge current. Therefore, a new start-up method is proposed for the BLDC motor, which maintains the alignment of the rotor.

From the simulation and experimental results, it can be seen that the proposed controller and observer satisfactorily work for parameter variations, load torque and speed tracking.

The authenticity of the proposed technique is tested experimentally on two different BLDC motors using low-cost 32-bit STM32F407VG microcontroller. The response of the proposed technique is evaluated by changing motor parameters such as stator resistance, inductance, flux linkage constant and torque constant.

This paper aims to present a novel multi-objective version of the Gorilla Troops optimizer (GTO), based on crowding distance, to achieve the optimal design of a brushless direct current motor.

In the proposed algorithm, the crowding distance technique was integrated into the GTO to perform the leader selection and also for the external archive refinement from extra non-dominated solutions. Furthermore, with a view to improving the diversity of non-dominated solutions in the external archive, mutation operator was used. For constrained problems, an efficient strategy was adopted. The proposed algorithm is referred to as CD-MOGTO.

To validate the effectiveness of the proposed approach, it was initially tested on three constrained multi-objective problems; thereafter, it was applied to optimize the design variables of brushless direct current motor to concurrently fulfill six inequality constraints, maximize efficiency and minimize total mass.

The results revealed the high potential of the proposed algorithm over different recognized algorithms in solving constrained multi-objective issues and the brushless direct current motors.

Switching power converters for photovoltaic (PV) applications with high gain are rapidly expanding. To obtain better voltage gain, low switch stress, low ripple and cost-effective converters, researchers are developing several topologies.

It was decided to use the particle swarm optimization approach for this system in order to compute the precise PI controller gain parameters under steady state and dynamic changing circumstances. A high-gain q- ZS boost converter is used as an intermittent converter between a PV and brushless direct current (BLDC) motor to attain maximum power point tracking, which also reduces the torque ripples. A MATLAB/Simulink environment has been used to build and test the positive output quadratic boost high gain converters (PQBHGC)-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. The simulation results show that the PQBHGC-3 topology is effective in comparison with other HG cell DC–DC converters in terms of efficiency, reduced ripples, etc. which is most suitable for PV-driven BLDC applications.

The simulation results have showed that the PQBHGC-3 gives better performance with minimum voltage ripple of 2V and current ripple of 0.4A which eventually reduces the ripples in the torque in a BLDC motor. Also, the efficiency for the suggested PQBHGC-3 for PV-based BLDC applications is the best with 99%.

This study is the first of its kind comparing the different topologies of PQBHGC-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. This study suggests that the PQBHGC-3 topology is most suitable in PV-driven BLDC applications.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

This study aims to extend the driving range by on-board charging with use of photovoltaic (PV) source, avoiding the dependency on the grid supply and energy storage system in addition to that reduce the conversion complexity influenced on converter section of electric vehicle (EV) system.

This paper proposed a PV fed integrated converter topology called integrated single-input multi-output (I-SIMO) converter with enriched error tolerant fuzzy logic controller (EET-FLC) based control technique to regulate the speed of brushless direct current motor drive. I-SIMO converter provides both direct current (DC) and alternating current (AC) outputs from a single DC input source depending on the operation mode. It comprises two modes of operation, act as DC–DC converter in vehicle standby mode and DC–AC converter in vehicles driving mode.

The use of PV panels in the vehicle helps to reduce dependence of grid supply as well as vehicle’s batteries. The proposed topology has to remove the multiple power conversion stages in EV system, reduce components count and provide dual outputs for enhancement of performance of EV system.

The proposed topology leads to reduction of switching losses and stresses across the components of the converter and provides reduction in system complexity and overall expenditure. So, it enhances the converter reliability and also improves the efficiency. The converter provides ripple-free output voltage under dynamic load condition. The performance of EET-FLC is studied by taking various performance measures such as rise time, peak time, settling time and peak overshoot and compared with conventional control designs.

The paper focuses on design, fabrication and characterization of electromagnetic microgenerators with integrated rectifying circuits to convert AC output signal to DC one. The work includes research on simulation of voltage-rectifying circuits, including charge pump, realization of the experimental printed circuit board (PCB) with selected electronic circuits and the execution of the final structure with integrated rectifying circuit. Measurements were performed on these circuits.

Electromagnetic microgenerators include multipole permanent magnets secured on rotor three-phase brushless direct current (BLDC) motor and planar multilayer multiple coils. These were fabricated using low temperature co-fired ceramics (LTCC) technology. In our experiment, six rectifying circuits were simulated and tested with a structure consisting of eight layers of coils and with an outer diameter of 50 mm fabricated earlier.

The microgenerator with Graetz bridge generates higher output power than the modified charge pump at the same rotary speed. However, it is less stable for the distance change between the structure and the magnets than the modified charge pump, which has more constant output power in a wider range of load resistance.

The presented electronic rectifying circuits are novel for LTCC-based electromagnetic microgenerator application. The structure with integrated rectifying circuits allows generation of electrical output power larger than 100 mW at the rotor speed of about 8,000 rpm.

The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted.

The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption.

This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path.

The purpose of this paper is to present the design procedure of an interior permanent magnet (IPM) motor used in electric power steering (EPS), and some critical issues which have considerable impacts on the machine's performance are fully discussed before detailed sizing optimization.

The design specifications are derived according to application overall requirements. Critical issues which have considerable impacts on the machine's performance, such as operation mode, rotor structure and slot/pole combination, are analyzed based on literature review. The proposed machine is optimized, and the losses and efficiency are computed, using 2‐D finite element analysis (FEA).

Before detailed sizing optimization, machine type selection is fully discussed. Aspects such as brushless ac (BLAC) operation mode, IPM rotor structure and combination of 12‐slot/10‐pole are quite suitable for EPS application. Consequently, a 12‐slot/10‐pole sinusoidally excited IPM machine with concentrated windings is selected, since it is convenient to obtain sinusoidal back electromotive force (back‐EMF), minimum cogging torque and torque ripple, short end windings and high efficiency, as well as simple rotor assembly. The estimated excellent performance confirms that the proposed machine can be an attractive solution for EPS.

The excitation current is ideal sinusoidal, while some harmonic components are neglected. Besides, in future, the experimental test should be carried out for validation.

A reasonable design procedure, where the motor type selection should be first addressed before detailed sizing design, is carried out. A 12‐slot/10‐pole sinusoidally excited IPM machine with concentrated windings is provided as a quite competitive candidate for EPS application.