This paper presents a proposition of a new optimization method called Search in Improved Network, which is an extension of the method Search in Modified Network, to calculate the empirical parameters of the Rakhmatov and Vrudhula model for predicting batteries lifetime used in mobile devices. The new method is evaluated according to the following methodology. At first empirical parameters are computed considering the optimization methods Search in Improved Network, Search in Modified Network, and Least Squares, as well as the experimental data obtained from a testbed, considering a Lhition-Ion battery, model BL5F, used in the Nokia N95 cell phone. In a second moment, the Rakhmatov and Vrudhula model is validated for each set of parameters obtained, and the simulated data from the model are compared with a set of experimental data. From simulations results a comparative analysis is performed and it is found that by the application of the method Search in Improved Network in the parameters estimation of the Rakhmatov and Vrudhula model it is possible to obtain an easy and intuitive implementation, improving the results obtained in the model accuracy, as well as preserving the runtime. 1. Introduction Currently, the use of mobile devices in the most varied areas, such as industry, education, health, and leisure, has been increasing due to the proliferation of wireless technology access. Examples of mobile devices are cell phones, digital cameras, tablets, ipods, laptops, alarm sensors installed in homes or commercial buildings, and other. The market trend is to have smaller mobile devices, faster, which perform the most varied functions, connected to global network of services and resources through a high performance infrastructure. These devices are powered by a rechargeable battery, so its use is determined through the battery lifetime; it is by definition the time the battery takes to reach the minimum level of power capacity, called cutoff level; after reaching this level the electrochemical reactions cease, and the battery stops providing power to the devices [1]. Thus, in the mobile devices design the battery lifetime is regarded as an important feature, because it reports the time that the device can be used without the need to connect it to an external source. In this context, it is important to have a method to predict the battery lifetime and thus determine the time that the device may remain operating without the need of recharging. One way is by using mathematical models that describe the energy consumption of the devices. Different
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