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This paper proposes a highly effective voltage cell equalization method for lithium-ion (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 aging 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. [ABSTRACT FROM AUTHOR]

This paper deals with one of the most challenging problems in nearly zero energy buildings (nZEBs) of several multifaced and sometimes contradictory objectives that is the energy management. Specifically, aim of the paper is to propose an integrated control strategy (ICS) based on genetic algorithms that can provide an optimal balance between the objectives of energy saving, comfort of the building residents and maximum exploitation of the generated electric energy by the renewable energy sources through the proper utilization of a battery storage system (BSS). The above can be attained by optimizing a comprehensive cost function that considers the most important factors that may affect the performance of an nZEB, i.e., real-time electricity price, generated/consumed electric energy by each device, user preferences, state-of-charge, and energy price of the BSS, weather forecast and the nZEB's construction characteristics. The outcome of the ICS is the proper task scheduling and control of the electric loads as well as the regulation of the BSS operation so as the nZEB's performance is improved. The feasibility and effectiveness of the proposed ICS are verified in a hardware-in-the-loop system and selective experimental results are presented to demonstrate the operational improvements. [ABSTRACT FROM AUTHOR]