The defining feature of a mobile device is its ability to function untethered, with no physical connection required for data or power, making battery life a critical performance metric. Knowing which device will last the longest on a full charge is complicated, however, since it’s affected by many different factors, some of which can be gleaned from a spec sheet and some only through testing.
The battery’s storage capacity plays the biggest role, since this limits the total amount of energy available to the system. With only minimal gains in energy density, the only reasonable way to increase capacity is by increasing size. A bigger battery, however, means a bigger and heavier device, so compromises must be made.
The other half of the battery life story is power consumption, which is influenced by hardware, software, and, ultimately, how you actually use your device. From a hardware perspective, there are a number of different components that drain power, including wireless radios, cameras, speakers, and sensors, but the two biggest culprits are the screen and SoC. Screen size and resolution (more pixels generally use more power), panel technology (AMOLED uses less power than LCD to display black), and panel self refresh (local RAM caches the frame buffer so the GPU and memory bus are not required for static images) all influence display power. The display’s brightness level also effects battery life, which is why we calibrate all screens to 200 nits, removing this variable from our results. The SoC’s power consumption is influenced by process technology, number and type of transistors, power gating, and max core frequencies. Dynamic voltage and frequency scaling (DVFS), a system of software drivers that adjust core and bus frequencies, also has a significant impact on battery life.
Designing battery life tests that account for all of a system’s hardware and software influences is difficult enough without considering different usage scenarios. Do you use your phone to play 3D games or to just occasionally check email? Is the screen powered on for hours at a time or just a few minutes several times a day? Do you get a flood of notifications that keep turning the screen on or have apps constantly running in the background? Since everyone uses their devices differently, we cannot tell you how long your battery will last. Instead, we run some worst-case tests to put a lower bound on battery life, and another test modeled after more real-world usage.
PCMark measures system-level performance and battery life by running real-world workloads. The battery life test starts with a full 100% charge and loops the Work performance benchmark (see description in the CPU and System Performance section) until the battery charge reaches 20%. The reported battery life estimates a 95% duty cycle (from 100% to 5% charge remaining) by extrapolating the measured battery life from the test. In addition to showing the battery life in minutes, the overall work performance score (the same value reported in the CPU and System Performance section) is shown again for reference.
As a system-level test, the power consumption of the CPU, GPU, RAM, and screen all factor into the final battery life number. By running realistic workloads, the DVFS functions just as it would when running common apps, providing a more accurate representation of battery life.
This benchmark is similar to PCMark in that it measures system-level performance and battery life by running real-world workloads. Its 7-inch or larger screen requirement limits it to tablets only, however.
The battery life test uses three different scenarios, including Web and Email and Photo and Video Sharing, both of which are explained in the CPU and System Performance section. The other test is Video Playback, which loops three one-minute, 1080p H.264 video clips (~60 MB each) three times for nine minutes total playback time.
The device starts with a full 100% charge and loops the following 50 minute script until the battery dies:
- Web and Email workload
- Idle for 3 minutes (screen on)
- Photo and Video Sharing workload
- Idle for 3 minutes (screen on)
- Video Playback workload for 9 minutes
- Idle to 50 minute mark (~8 minutes)
Basemark OS II: Battery
Basemark OS II by Basemark Ltd. includes a battery rundown test in addition to the performance tests discussed earlier in the CPU and System Performance section. The largely synthetic battery test runs a multi-core workload similar to the CPU performance test, and provides a worst-case battery life primarily based on CPU, memory, and display power consumption.
The test calculates ratios and standard deviations for battery percentage consumed per minute. The final score is based on the arithmetic average of these values plus a bonus score based on CPU usage.
GFXBench 3.0: Battery Life
The GFXBench battery life test loops the T-Rex game simulation benchmark (detailed in the GPU and Gaming Performance section) continuously for 60 minutes, starting from a full 100% charge. This provides a worst-case battery life based primarily on GPU, memory, and display power consumption, and is indicative of what you might see while playing an intense 3D game.
Test results are displayed in two different charts: the extrapolated battery life in minutes and the average performance during the test in frames per second. It’s important to see both charts, because looking at only the battery life chart can be misleading; thermal throttling will cause the GPU to run at a lower frequency, leading to better battery life but lower performance.
Running at a higher clock frequency requires a higher voltage which generates more heat. This heat moves from the core to the SoC package and, eventually, finds its way to the device’s chassis, where it gets dissipated to the surrounding environment. If the core(s) produce heat faster than it can be dissipated, or the external chassis reaches a temperature making it uncomfortable to hold, then the system reduces clock frequency to satisfy thermal constraints. This is what we mean by thermal throttling. Because it reduces performance and can negatively affect the user experience, it’s something our performance testing needs to account for.