Abstract: The invention relates to a method for regulating equalization and energy support currents of battery cells, based on a master-slave control structure, integrated into the battery management system. The power circuit includes a bidirectional dc-dc power converter, a matrix-switch power converter, and an auxiliary energy storage unit capable of exchanging energy with each cell of the battery segment. The master control manages the feedback signals from the battery management system, such as cell voltage and power required/provided by/from the battery pack of the electric vehicle system, and decides which of the following slave operations should be activated: (i) equalization control algorithm with adjustable current using genetic algorithms, (ii) cell energy support control algorithm with adjustable current, or (iii) algorithm for estimation of the resistance and state-of-health of each cell based on the Electrochemical Impedance Spectroscopy (EIS) technique.

Abstract: An optimal energy management method and a system that implements the method for a nearly zero energy building (nZEB) based on the genetic algorithm technique 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, is developed in this invention. The above can be attained by minimizing a cost function that considers the real-time electricity price, the generated/consumed electric energy by each device, the user preferences, the state-of-charge and the energy price of the battery storage system (BSS), and the weather forecast. the system that implements the optimal energy management method comprises energy and temperature sensors, controllable power switches, a battery storage system and a controller with human machine interface.

Abstract: An optimal energy management method and a system that implements the method for a nearly zero energy building (nZEB) based on the genetic algorithm technique 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, is developed in this invention. The above can be attained by minimizing a cost function that considers the real-time electricity price, the generated/consumed electric energy by each device, the user preferences, the state-of-charge and the energy price of the battery storage system (BSS), and the weather forecast. the system that implements the optimal energy management method comprises energy and temperature sensors, controllable power switches, a battery storage system and a controller with human machine interface.