Energy Efficiency of Mobile Device Recharging

Introduction

The number of battery-operated mobile devices is increasing rapidly. The common issue for most of them is the need to recharge the batteries using power taken from power grid or other source of electrical power. One of the fundamental issues is the efficiency of converting the energy from power grid to useful work. In other words, how many Joules of energy is taken from the power grid to produce one Joule of work when using the device.

The primary perspective of studying mobile phone energy consumption has been how to make the battery last longer. Given the slow improvement in battery storage capacity (Robinson, 2009), R&D activity has focused on reducing the energy consumption of the mobile device use with more power efficient components and smarter use of energy. For phone users this means less need to worry about recharging and improved user satisfaction.

The other perspective has its roots on the increasing cost and concern related to electricity consumption of the ICT sector. The energy-efficiency of data centers, data communication networks, and end-user devices, like PCs, has become important. So far, there has not been much interest towards the electricity consumption of mobile devices, probably because the electricity consumption of a mobile phone is small in comparison to more power hungry elements involved in the end-to-end communication.

In this study our focus is on the latter perspective. The energy taken from the power grid is converted into useful work in the mobile device in multiple steps. Each step involves some losses where part of the energy is wasted as heat warming up the charger and the mobile phone. In this work we want to quantify the losses and understand how efficiently the mobile phone is able to use the electricity it takes from the power grid. We analyze and measure the key units involved (charger, EPM chipset, battery) to understand how much energy is lost in each step. In this way we can estimate both the overall efficiency and the efficiency of the individual steps. Furthermore, we can apply efficiency estimates to study how much regular activities, like calling, browsing, or music listening, require the mobile phone to take electricity from the power grid.

To differentiate between the two perspectives we use the following terminology in this paper. When we speak about electricity, and electricity consumption, we refer to the power that is taken from the power grid. When we speak about energy or power consumption we mean the consumption of energy taken from the phone battery and consumed by the applications and services of the mobile device.

Understanding the relationship between the energy consumed by the applications and the electricity taken from the power grid is important for several reasons. First, the increasing interest towards the environmental load of ICT devices makes the recharging electricity of mobile devices relevant, especially because of the cumulative effect of the high number of mobile devices. The energy consumption of different mobile applications has traditionally been the focus of study because it dictates how often users need to recharge their devices which directly impacts the user experience. Now this perspective is complemented with better understanding what the energy consumption of applications means in terms of electricity from the power grid. Second, explicitly mapping the energy chain and quantifying the efficiency ratios of different components is useful for understanding the whole energy chain. This can also be a basis for further development and analysis of more efficient recharging solutions.

This paper is an extended version of our conference paper (Ruutu et al., 2011). As far as we know there are no other prior studies of the joint energy efficiency of the different components involved in the recharging process. The energy efficiency of different components has been studied in isolation: chargers (e.g. Ostendorp et al., 2004; Weier & McMahon, 2007), energy and power management chipsets (e.g. Chen et al., 2009), and battery (e.g. Lopez et al., 2004; Pedram & Wu, 2002). However, forming the big picture from the isolated studies that use different platforms is difficult. By analyzing all of the components in one study we are able to understand the relative importance of the different components for the overall efficiency.