Software-Defined Batteries

By Anirudh Badam, Ranveer Chandra, Jon Dutra, Anthony Ferrese, Steve Hodges, Pan Hu, Julia Meinershagen, Thomas Moscibroda, Bodhi Priyantha, and Evangelia Skiani

DOI: 10.1145/3007179

Abstract

Different battery chemistries perform better on different axes, such as energy density, cost, peak power, recharge time, longevity, and efficiency. Mobile system designers are constrained by existing technology, and are forced to select a single chemistry that best meets their diverse needs, thereby compromising other desirable features. In this paper, we present a new hardware–software system, called Software Defined Battery (SDB), which allows system designers to integrate batteries of different chemistries. SDB exposes application programming interfaces (APIs) to the operating system, which controls the amount of charge flowing in and out of each battery, enabling it to dynamically trade one battery property for another depending on application and/or user needs. Using microbenchmarks from our prototype SDB implementation, and through detailed simulations, we demonstrate that it is possible to combine batteries which individually excel along different axes to deliver an enhanced collective performance when compared to traditional battery packs.

1. INTRODUCTION

The utility of a mobile device is often constrained by the capabilities of its battery. While integrated circuit performance has doubled every 18 months according to Moore’s law, the same is far from true for battery technology. Battery performance can be evaluated in many different ways (see Table 1), but no matter which metric we look at, it has taken more than a decade to double performance.

Furthermore, the various properties of batteries are often
at odds with each other. For example, batteries with higher
power densities tend to have lower volumetric and gravi-
metric energy densities, and vice versa. Similarly, making a
conformable battery that fits a particular industrial design
compromises its performance characteristics.

Such tradeoffs are present even within a given physical battery. For example, energy delivered by a battery in a single charge–discharge cycle (energy capacity) is inversely related to the rate at which the battery is drained (discharge rate). This is because the resistance losses inside a battery are proportional to the square of the current. Similarly, a battery’s longevity—its ability to perform consistently following many charge–discharge cycles—is inversely related to the discharge and recharge rates. This is because higher currents speed up the creation of fissures in the electrodes that reduce the amount of energy a battery can store.

In summary, no single battery type can deliver the ever-growing list of requirements of modern devices: fast charging, high capacity, low cost, less volume, light weight, less heating, better longevity, and high peak discharge rates.

A growing range of battery chemistries are under development, each of which delivers a different set of benefits. We believe that combining multiple of these heterogeneous batteries instead of using a single battery chemistry can allow a mobile system to dynamically trade between their capabilities and thereby offer attractive tradeoffs.

However, traditional methods of integrating multiple batteries are not suitable for heterogeneous batteries. Connecting them in series or parallel does not provide enough control over usage: batteries connected in series can only supply the same amount of current; batteries connected in parallel must operate at the same voltage and can only supply currents that are inversely proportional to their internal resistances.

We propose a new system, called Software Defined Battery (SDB), that allows heterogeneous batteries with different chemistries to be integrated in a mobile system. SDB consists of hardware and software components. The hardware enables fine-grained control of the amount of power going in and out of each battery using smart switching circuitry. The software, which resides in the operating system (OS), computes how much power to draw from each battery, and how to recharge each battery.

Deciding ho w much po wer to dra w from and ho w to charge
each battery is nontrivial. It depends on the efficiency of each
battery under different workloads, the age of each battery,
and also the usage profile. For example, if a high power work-
load is anticipated in the future, then it could be worth-while
The original version of this paper was published in
Proceedings of ACM SOSP’ 15.

Table 1: A number of battery characteristics.

Battery characteristics Units

Energy capacity J Volume mm3

Mass kg Discharge rate W Recharge rate W Gravimetric energy density J/kg Volumetric energy density J/L Cost $/J Discharge power density W/kg Recharge power density W/kg Cycle count Number of discharge/recharge cycles Longevity of original capacity after N cycles Internal resistance Ohm Efficiency of energy turned into heat Bend radius mm These are often in tension with each other, for example, increasing recharge rate compromises longevity.