Hybrid Electric Vehicles (HEVs) are becoming more popular than pure electric ones, nowadays. This is because of their better performance, economic advantages and higher operating range. However, their potential advantages extremely depend on their system design, most importantly their battery system design. Batteries’ life requirements as well as the cost of replacing them at the end of their life period, currently limit manufacturers to bring HEVs into play, even though their fuel economy reduces their everyday cost considerably. Generally, inappropriate discharge/charge patterns would result in loss in batteries’ life. In the present study, an optimization based control strategy has been proposed for the series HEVs in order to maximize the efficiency of the power-train while minimizing the loss. A genetic algorithm is implemented to optimally evaluate the control algorithm's parameters. The approach is then compared to two main control strategies, namely thermostatic control strategy and power follower control strategy. The computational procedure of the genetic algorithm is discussed, and a simulation study based on a model of a series hybrid electric vehicle is given to validate the genetic algorithm results.