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This paper proposes a novel online condition monitoring algorithm estimating battery states and model parameters. The proposed method includes: 1) an electrical circuit battery model incorporating the hysteresis effect, 2) an extended Kalman Filter-based online parameter identification algorithm for the electrical battery model, and 3) a smooth variable structure filter (SVSF)-based state estimation algorithm for state of charge (SOC) estimation. The proposed method enables an accurate and robust condition monitoring for lithium-ion batteries. Since the proposed hybrid filter further reduces the complexity compared to existing dual extended Kalman filter (DEKF), it is much more suitable for the real-time embedded battery management system (BMS) application. Simulation studies validate the effectiveness of the proposed strategy.

This paper proposes an Internet of Things (IoT)-enabled multiagent system (MAS) for residential DC microgrids (RDCMG). The proposed MAS consisting of smart home agents (SHAs) aims to cooperate each other to alleviate the peak load of the RDCMG and to minimize the electricity costs for smart homes. These are achieved by agent utility functions and the best operating time algorithm (BOT) in the MAS. Moreover, IoT-based efficient and cost-effective agent communication method is proposed, which applies message queuing telemetry transport (MQTT) publish/subscribe protocol via MQTT brokers. The proposed IoT-enabled MAS and smart home models are implemented in five Raspberry pi 3 boards and validated by experimental studies for a RDCMG with five smart homes.

This paper investigates the low-voltage ride-through (LVRT) performance of a proposed sensorless vector control method for the doubly-fed induction generators (DFIGs) under power grid voltage sags. The sliding-mode observer (SMO) is used to estimate the rotor position and speed information for the vector control of the DFIG. The performance of the SMO is compared with the model reference adaptive system (MRAS)-based sensorless method over a wide operating speed range. The effectiveness of the proposed sensorless vector control scheme under power grid voltage sags is demonstrated by simulation results for a 2-MW DFIG-based wind energy conversion system (WECS) in MATLAB/Simulink and experimental results for a 200-W DFIG-based WECS simulator.