This article proposes a real-time electrochemical impedance spectroscopy (EIS) technique that can provide high accurate estimation of the impedance of each lithium-ion (Li-ion) cell of a battery (BT) stack, even for less than mΩ. Thus, the suggested EIS technique can be used in high demanding applications, such as nearly zero-energy buildings, microgrids, and electric vehicles. This is attained because a smooth cell excitation current is utilized that is provided by the proper control of the gate-source of each cell's parallel-connected MOSFET and thus, effective harmonic analysis can be accomplished. Since the circuit topology of the EIS is implemented without requiring expensive electronic equipment, it is affordable to be applied in the BT system of any application. The proposed EIS system can cooperate with a BT cell equalization (BCE) system that utilizes the same MOSFET control scheme to provide the excitation current. Thus, a combined EIS-BCE system is developed that can be used to improve the performance of a Li-ion BT management system. The accuracy of the EIS technique and its high performance by operating within a combined EIS-BCE system are experimentally validated.

This paper proposes a highly effective voltage cell equalization method for Li-ion battery management systems (BMSs), for several applications, such as nearly zero energy buildings, microgrids and electric vehicles. The concept of the suggested method is the proper control of the charging current of each cell of a battery stack through the suitable regulation of the gate-source of each cell's parallel connected MOSFET. Thus, the MOSFET can act as a controllable current source for providing the proper equalization current according to the specific needs of each battery cell. The correct voltage level of the gate-source of each MOSFET is determined by a cell equalization controller through the comparison of the performance of each cell of a battery stack with the healthier cell, which is detected by an ageing estimation algorithm based on the evaluation of the internal resistor and the capacity fade of each cell. Therefore, smoother and faster cell equalization is achieved compared to the conventional dissipative method. The practicality and the high effectiveness of the proposed cell equalization technique have been experimentally validated. Several experimental results are presented to demonstrate the operational improvements of the proposed cell equalization technique against the conventional one.

This paper proposes an improved fault-ride through (FRT) system for a wind turbine with doubly fed induction generator (DFIG) that is based on the proper stator voltage control to address symmetrical as well as unsymmetrical and unbalanced grid voltage sags. This is accomplished by adopting a properly modified topology of the conventional wind energy conversion system (WECS) with DFIG that provides the ability to regulate the stator voltage through the system of the rotor power converters. Therefore, significant improvement of the FRT capability is attained, since any oscillations of both the stator and rotor currents that may be caused by the voltage dip can be considerably reduced and they can remain within predefined safety limits. The implementation of the new topology as well as the corresponding control system are cost effective, since no additional hardware is required, and it is accomplished by the reconfiguration of the conventional topology. Selective simulation and experimental results obtained by a high and low scale WECS with DFIG, respectively, are presented to validate the effectiveness of the proposed FRT control method and demonstrate the operational improvements.

This paper proposes an optimal efficiency control scheme for a wind system with doubly fed induction generator (DFIG). The suggested control scheme combines loss minimization (LM) in the DFIG and maximum power point tracking (MPPT) in the wind turbine and therefore maximum electrical energy generation, by the same wind energy potential, is achieved. Moreover, since the cut-in wind speed is reduced, extension of the exploitable wind speed range toward the lower speed region is attained. The LM is achieved by properly controlling the flux-linkage of the DFIG with respect to the stator current and the MPPT is accomplished by regulating the rotor speed through the rotor current. The parameters of the LM and MPPT controllers can be determined experimentally and thus, the knowledge of the wind energy conversion system (WECS) model is not required. For the implementation of the proposed control strategy, a new structure of the WECS has been adopted. However, the hardware requirements of the WECS and considerably the cost has not been considerably affected compared to the conventional configuration. Selective simulation and experimental results are presented to validate the effectiveness of the proposed control strategy and demonstrate the operational improvements.

This paper proposes a new method that can online and automatically estimate and fine-tune the parame-ters of a discrete-time model predictive controller for providing high performance speed control in an in-duction motor (IM) drive. The suggested control system combines the model reference adaptive method with the fuzzy-logic technique and its operation can be initiated without requiring any human intervention or the knowledge of the motor drive parameters. Therefore, no extra work by the user is needed to adjust the controller parameters according to the operating conditions and also, high performance is attained because any variations of the system model can be considered through a fine-tuning procedure. The proposed auto-adaptive discrete-time model predictive control (ADMPC) system is based on the optimization of an objective function that considers the reference and the real speed as well as the acceleration of the IM drive by using the state-space model. The implementation of the proposed ADMPC scheme is easy, since no additional hardware is required, but only the replacement of the firmware of the IM drive. Selective simulation and experimental results are presented to validate the effectiveness of the proposed ADMPC system and demonstrate the high performance of the motor drive.