The world's increasing energy demand imposes a negative impact on the environment. This is mainly caused by the release of CO2 into the atmosphere through the combustion of fossil fuels. The approach of this undesired phenomenon is expected to be partially addressed through the development of Electric Vehicles (EV). This area of expertise encounters several challenges. An increasing impact on the electricity network when charging a network of EVs, rising electricity demand and costs, and the control of charging a network of EVs, are the three subjects described in this paper. With these subjects, a smart optimization strategy for charging a network of EVs is proposed. The battery pack of an EV extracts electricity from the electricity grid by means of chargers. Hence, from a grid side perspective, an EV is considered as a load. Therefore, a state space model describing the behavior of such a battery pack is developed. Furthermore, optimization of cost efficiency is implemented with a linear programming (LP) method which includes hourly variable electricity costs. With an entire network of EVs charging simultaneously, the efficiency of charging deserves careful consideration and is translated into the minimization of power losses. A Linear Quadratic (LQ) algorithm is used to minimize these power losses arising during the charging process of the EV. The smart optimization strategy displays a positive impact on the charging schedule of EVs and therefore, on the environment. Results demonstrate a reduction of electricity costs between 20 and 60 percent, dependent on the capacity demand. The impact on the electricity grid is decreased by the minimization of the power losses.