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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 purpose of this paper is to reduce the inrush current and dip in voltage for energy‐ saving purposes in relation to residential air‐conditioning systems.

The paper focuses on the experimental harmonic investigation of a window‐type residential AC unit line current under time‐based soft‐starting control strategy. The control strategy assumes that only source voltage and current measurements are available. The soft‐starter is based on power electronic devices controlled through a firing signal generated by a programmed microcontroller during the first 500 ms.

The harmonic content shows the effect of the soft‐starter in exciting high‐frequency components of the line current. Harmonics investigations show that the high frequencies – even or odd multiples – of the fundamental line frequency are all excited by the soft‐starter approach. Some of these frequencies may harm the life cycle of the air‐conditioner.

The real data harmonic analysis shows that the adopted approach excites the entire frequency spectrum of the signal. A better monitoring of the harmonics is required. A closed loop adaptive soft‐starting control may perform much better than a time‐based soft‐starting strategy.

The paper assesses the power quality related to time‐based soft‐starting strategy of a residential air‐conditioning system to reduce the inrush current and the dip in voltage, both with a serious effect on energy savings, especially when the AC load is around 65 per cent of the total power demand load.

The purpose of this paper is to provide a comparison of synchronous permanent magnet machine types for wide constant power speed range operation.

A combination of analytical models and finite element analysis is used to conduct this study.

The paper has presented a detailed comparison between various types of synchronous PM machines for applications requiring a wide speed range of constant‐power operation. Key observations include: surface permanent magnet (SPM) and interior permanent magnet (IPM) machines can both be designed to achieve wide speed ranges of constant‐power operation. SPM machines with fractional‐slot concentrated windings offer opportunities to minimize machine volume and mass because of their short winding end turns and techniques for achieving high‐slot fill factors via stator pole segmentation. High back‐emf voltage at elevated speeds is a particular issue for SPM machines, but also poses problems for IPM machine designs when tight maximum limits are applied. Magnet eddy‐current losses pose a bigger design issue for SPM machines, but design techniques can be applied to significantly reduce the magnitude of these losses. Additional calculations not included here suggest that the performance characteristics of the inverters accompanying each of the four PM machines are quite similar, despite the differences in machine pole number and electrical frequency.

The paper is targeting traction applications where a very wide speed range of constant‐power operation is required.

Results presented are intended to provide useful guidelines for engineers faced with choosing the most appropriate PM machine for high‐constant power speed ratio applications. As in most real‐world drive design exercises, the choice of PM machine type involves several trade‐offs that must be carefully evaluated for each specific application.

The paper provides a comprehensive comparison between different types of synchronous PM machines, which is very useful in determining the most suitable type for various applications.

Kern Electrical Components, the EMC protection specialist, has announced that a new version of its popular SDM range of ‘D’ type backshells, currently imported from the USA, is to be manufactured in the UK.

Recent years have seen a technological change, Industry 4.0, in the manufacturing industry. Human–robot cooperation, a new application, is increasing and facilitating collaboration without fences, cages or any kind of separation. The purpose of the paper is to review mainstream academic publications to evaluate the current status of human–robot cooperation and identify potential areas of further research.

A systematic literature review is offered that searches, appraises, synthetizes and analyses relevant works.

The authors report the prevailing status of human–robot collaboration, human factors, complexity/ programming, safety, collision avoidance, instructing the robot system and other aspects of human–robot collaboration.

This paper identifies new directions and potential research in practice of human–robot collaboration, such as measuring the degree of collaboration, integrating human–robot cooperation into teamwork theories, effective functional relocation of the robot and product design for human robot collaboration.

This paper will be useful for three cohorts of readers, namely, the manufacturers who require a baseline for development and deployment of robots; users of robots-seeking manufacturing advantage and researchers looking for new directions for further exploration of human–machine collaboration.

The purpose of this study is to propose a torque vectoring control system for improving the handling stability of distributed drive electric buses under complicated driving conditions. Energy crisis and environment pollution are two key pressing issues faced by mankind. Pure electric buses are recognized as the effective method to solve the problems. Distributed drive electric buses (DDEBs) as an emerging mode of pure electric buses are attracting intense research interests around the world. Compared with the central driven electric buses, DDEB is able to control the driving and braking torque of each wheel individually and accurately to significantly enhance the handling stability. Therefore, the torque vectoring control (TVC) system is proposed to allocate the driving torque among four wheels reasonably to improve the handling stability of DDEBs.

The proposed TVC system is designed based on hierarchical control. The upper layer is direct yaw moment controller based on feedforward and feedback control. The feedforward control algorithm is designed to calculate the desired steady-state yaw moment based on the steering wheel angle and the longitudinal velocity. The feedback control is anti-windup sliding mode control algorithm, which takes the errors between actual and reference yaw rate as the control variables. The lower layer is torque allocation controller, including economical torque allocation control algorithm and optimal torque allocation control algorithm.

The steady static circular test has been carried out to demonstrate the effectiveness and control effort of the proposed TVC system. Compared with the field experiment results of tested bus with TVC system and without TVC system, the slip angle of tested bus with TVC system is much less than without TVC. And the actual yaw rate of tested bus with TVC system is able to track the reference yaw rate completely. The experiment results demonstrate that the TVC system has a remarkable performance in the real practice and improve the handling stability effectively.

In view of the large load transfer, the strong coupling characteristics of tire , the suspension and the steering system during coach corning, the vehicle reference steering characteristics is defined considering vehicle nonlinear characteristics and the feedforward term of torque vectoring control at different steering angles and speeds is designed. Meanwhile, in order to improve the robustness of controller, an anti-integral saturation sliding mode variable structure control algorithm is proposed as the feedback term of torque vectoring control.

The purpose of this paper is to investigate and compare the influence of end-effect on the torque-speed characteristics of three conventional switched flux permanent magnet (SFPM) machines having different stator/rotor pole combinations, i.e. 12/10, 12/13 and 12/14 as well as three novel topologies with less permanent magnets (PMs), i.e. multi-tooth, E-core and C-core.

SFPM machines combine the advantages of simple and robust rotor and easy management of the temperature due to the location of the PMs and armature windings on the stator. However, due to spoke location of the PMs a large flux leakage in the end region, i.e. end-effect, can be observed which could result in a large reduction in the electromagnetic performance. Therefore, the influence of end-effect on the torque-speed characteristics is investigated. 3D-finite element analyses (FEA) results are compared with their 2D-FEA counterparts in order to account for the end-effect influence.

It has been concluded that due to end flux leakage, lower torque capability in the constant torque region is observed in the six machines. However, improved flux-weakening capability in the conventional machines can be exhibited at high current levels, whereas due to the large inductance lower power capability in the multi-tooth, E-core and C-core machines is obtained.

The influence of temperature rise on the performance is not included.

This paper has analysed the influence of end-effect on the torque-speed characteristics of several SFPM machines.

The flexible mode transitions, multiple power sources and system uncertainty lead to challenges for mode transition control of four-wheel-drive hybrid powertrain. Therefore, the purpose of this paper is to improve dynamic performance and fuel economy in mode transition process for four-wheel-drive hybrid electric vehicles (HEVs), overcoming the influence of system uncertainty.

First, operation modes and transitions are analyzed and then dynamic models during mode transition process are established. Second, a robust mode transition controller based on radial basis function neural network (RBFNN) is proposed. RBFNN is designed as an uncertainty estimator to approximate lumped model uncertainty due to modeling error. Based on this estimator, a sliding mode controller (SMC) is proposed in clutch slipping phase to achieve clutch speed synchronization, despite disturbance of engine torque error, engine resistant torque and clutch torque. Finally, simulations are carried out on MATLAB/Cruise co-platform.

Compared with routine control and SMC, the proposed robust controller can achieve better performance in clutch slipping time, engine torque error, vehicle jerk and slipping work either in nominal system or perturbed system.

The mode transition control of four-wheel-drive HEVs is investigated, and a robust controller based on RBFNN estimation is proposed. Compared results show that the proposed controller can improve dynamic performance and fuel economy effectively in spite of the existence of uncertainty.

Flywheels can serve not only as attitude control devices, but also as energy storage devices, thereby eliminating the need for conventional batteries. Hence, a combined energy and attitude control system (CEACS) consisting of a double counter rotating flywheel assembly is proposed for small satellites in this paper. The energy level in CEACS depends mainly on the flywheels' speeds. Therefore, a specific flywheel energy management strategy has to be implemented to take into account the limitations of the flywheels, which has not been established until today.