This paper presents optimal strategies in home energy management system (HEMS) integrating solar power, energy storage, and vehicle-to-grid (V2G) capability for predetermined scenarios. The proposed system aims to address the demand response (DR) schemes, both real-time pricing and emergency load curtailment, V2G mode of operation. In the interruption event, the HEMS operates in the vehicle-to-home (V2H) mode to ensure supply continuity. The control algorithms are experimentally implemented on the created hardware platform of EV and home batteries, solar power, and household loads with preset priorities. Both AC and DC charging technologies for EVs are considered. The HEMS simultaneously optimizes the scheduling of charging and discharging of EVs and home battery. Results on operation under predetermined scenarios have confirmed the validity of the proposed HEMS.

This letter presents a current control technique for fast transient-current response in a sensorless vector-controlled permanent magnet synchronous motor. Pontryagin's maximum principle is employed to derive the time-optimal voltage solution. Based on this principle, the technique can guarantee the current vector transition from one operating point to another with minimum time. Compared to a proportional-integral controller, the current response by using the time-optimal controller is much faster, even under a limited dc bus voltage. Experiments are carried out to substantiate the proposed technique

This paper presents the use of particle swarm optimization (PSO) algorithm applied to the optimal design of the 4/2 switched reluctance motor (SRM). The main advantage of designing 4/2 SRM is the robust rotor structure for high speed unidirectional rotating applications such as the air conditioner's blower. In the designing process, the finite element method magnetics (FEMM) is also employed to analyze the designing SRM with its optimized parameters given by PSO. This PSO algorithm is efficient and flexible. The objective function is based on the ripple torque minimization with respect to rotor node position. The PSO algorithm is described and the preliminary FEMM simulation results will be given for verifying optimal rotor design by PSO algorithm. In the final paper, the complete FEMM simulation results with detailed analysis will be provided.

The cogging torque is undesirable effect in the brushless dc (BLDC) motor, causing vibration and audible noises. It arises from the rotor permanent magnet interacting with the steel teeth on the stator. Therefore, this paper studies the various reduction methods of cogging torque when designing a BLDC motor. These methods can be categorized according to three parts of motor structure, i.e., air gap length, rotor and stator parts. The finite element method magnetic (FEMM) is primarily used to analyze the cogging torque among these different reduction methods. In this paper, a 4-pole, 24-slot BLDC motor is focused with variations of air gap length, rotor, and stator parts in order to study its cogging torque reductions. Finally, the FEMM simulation results are presented to validate these reduction methods.

This paper presents an implementation of a Wireless Internet of Things (IoT) system applied to the traction motor drive condition monitoring in electric vehicles (EVs). The design and testing of the prototype using an ESP8266 microcontroller module to acquire motor's vibration, current, and temperature information for the motor condition monitoring application is presented. This IoT system has been designed and developed from the ground up using commercially off-the-shelf components and open-source software platform for fast, reliable data acquisitions, low power consumption, and data gathered by the IoT system get reported to the cloud server in real time. The experimental results reveal that the IoT system is capable of capturing and reporting vital motor's parameters to cloud server and an automatic notification is sent to operators when motor's abnormality is detected in real time. Thanks to IoT technology, the preventive maintenance of traction motor can be effectively and remotely planned with rich data collection and analysis. With advanced power consumption reduction techniques, a sensor node consumes extremely low amount of battery power at which ideal for mobile applications.

In inductive power transfer (IPT) system, the magnetic coupling has significant effects on power and system efficiency. The voltage and current on the secondary side are coupling dependent. Load measurements are not possible through sensors on the primary side. This paper proposes the secondary-side voltage controller based on the primary-side control by means of bifurcation approach. The main advantage of operation under bifurcation is that the coupling and load on the secondary have no effect on the voltage gain. This enables the secondary voltage control through the primary voltage. With the proposed sensing coil on the primary side, the bifurcation detection is possible. The proposed control can utilize the frequency split phenomenon and track the bifurcation frequency to ensure maximum efficiency in various coupling conditions. In addition, the design guidelines of the parallel-parallel compensation configuration are introduced for a desired load profile and transfer distance. The constant voltage gain with respect to conditions of magnetic coupling variation is verified by using finite element analysis and experimental study. A 1-kW IPT prototype is constructed to validate the proposed bifurcation detection and voltage control. Experimental results show that the proposed IPT can achieve up to 90% of maximum efficiency while maintaining constant secondary voltage.