Optimize power for user interfaces through wake-on-approach with capacitive proximity sensing – Part I
Portable devices such as mobile phones and tablets that run on batteries have stringent power requirements. Designers must leave no stone unturned to optimize the power consumption of these devices and enhance battery life. In such applications, and other applications as well, optimization is achieved by making the device consume as little power as possible. Thus, it would make a significant difference if most of the blocks do not run when the device is not in use and the blocks turn ON and start running only when the user starts using the device.
This means that the device must have the intelligence to detect the start of the usage of the device and starts all of the required blocks. One simple way is to run just the UI processing until the UI senses the user’s input. When the UI detects a user’s input such as a button touch or a press, the entire device wakes up and starts running all the blocks that are necessary.
Furthermore, if the UI is capable of detecting the approach of a user’s hand, then all the blocks of the device, including those of the UI, can be turned OFF except for scanning the sensor that detects the hand approach. These proximity sensors are capable of detecting human hands or any conducting object at a distance without the need of any contact between the object and the UI. A device with proximity sensors operates in low power mode until a hand approaches. In the low power mode, only proximity sensors are scanned and pretty much no other activity is performed. Upon detection of a human hand, the proximity sensor wakes the device to active mode in which all the necessary blocks of the device get turned ON.
The proximity sensors that wake up the device from low power mode to active mode are called wake –on- approach proximity sensors.
Capacitive, inductive, and infrared are commonly known proximity sensing techniques. In applications like mobile handsets, laptops, white goods, and home appliances where the user interfaces are mostly touch panels, capacitive proximity sensing is being widely adopted because of greater reliability and aesthetics.
This article series explains how a capacitive proximity sensor can be used as a wake-on-approach sensor, and different applications where proximity sensors are used as wake-on-approach sensors are described. It also discusses the power consumption optimization wake-on-approach proximity sensors bring and how to implement a wake-on-approach proximity sensor, hardware and software aspects of it, and design considerations.
Applications
Applications such as a wireless mouse, mobile phones, tablet PCs, remote-control backlighting, and laptop keyboard backlighting adopt such techniques that wake the device when the user starts using the device. These applications use proximity sensors to switch from low power mode to fully functional active mode.
Let us consider a capacitive-touch sensing device in low power mode when only the proximity sensor is scanned. Scanning only the proximity sensor reduces the total scan time, thereby reducing the average power consumption. When the user’s hand approaches the user interface panel, the proximity sensor detects the presence of the hand and wakes up the capacitive device. Once woken up from its low power mode, the capacitive device moves to active mode and scans all the button sensors to detect the touches.
You might find it hard to indentify buttons on a TV front panel or tablet PC panel when you want to operate them as most of the user interfaces of today’s UIs are touch panels and the buttons are hardly visible and indistinguishable from each other without backlighting. However, backlight LEDs for buttons, especially in portable devices like mobiles, tablets, PCs, etc., reduces battery life. A typical usage of wake-on-approach proximity sensors is to control the backlight on user interface panels using the proximity sensor. Whenever the device is in low power mode, the backlight is turned OFF to indicate the inactive mode of the equipment. Once a user’s hand approaches the panel and the proximity sensor detects the same, the backlight is turned ON aiding the user in touching the correct buttons.
Another instance of backlight control is that the backlight LEDs have special LED effects like LED fading, breathing effects. But LED effects consume more power and hence the battery operated devices cannot afford to always drive effects on LEDs. With proximity sensing, only when the user starts using the device do the LEDs light up with special effects.
The level of control that the wake-on-approach proximity sensors have depends on the application. Either only the proximity sensing device or the entire system can be put into low power mode until a proximity event is detected. Later in this series we will see how much power saving wake-on-approach proximity sensors bring in with an example application.
Power saving using Wake-On-Approach Proximity Sensors
In this section, first we will discuss:
- How to calculate power consumption of capacitive sensing application
- How to calculate battery life
Later we will show how battery life increases by implementing wake-on-approach using proximity capacitive sensors.
Calculating Average Power
Let us now see, how to calculate the average power consumption of capacitive touch sensing device.
In order to optimize power, a common technique of scan-sleep-scan-sleep is followed. In this technique, all the sensors are scanned and then sensing device is put to low power sleep mode this is one cycle and this cycle gets repeated. One cycle of scan-sleep is called one refresh interval.
In capacitive sensing applications it is not easy to balance optimizing power consumption while achieving good response given that it takes considerable time to scan the sensors. The refresh interval can be varied to optimize either power consumption or response time. But it is not always possible to get the desired level of optimization by controlling the refresh interval. If the device is optimized for power consumption, then the response gets slower and vice versa. Another technique is followed to get the response time and power consumption optimized. When a user uses the UI, the capacitive sensing device can be optimized to respond quickly and when user does not use, the device can be optimized for power consumption.
To achieve optimization of the two key parameters – power consumption and response time – the refresh interval need to be meddled with. For optimizing response time, the sensors need to be scanned quickly and hence the refresh interval needs to be fast. Let us call this mode as quick scan mode. For optimizing power consumption, the sensors need to be scanned slowly and the device needs to sleep for more time, hence the refresh interval needs to be longer. Let us call this mode as slow scan mode. Power consumption varies between these two modes. Let us see how to calculate the average current.
Sample Calculation
As an example of how to calculate average power, consider a capacitive sensing user interface on a digital photo frame with eight buttons. Let us take quick scan mode time as 50ms and slow scan mode time as 125ms. Let us assume that the sensor scan time for eight buttons is 12ms. Typical values of IACTIVE would be 4mA and ISLEEP would be 4uA for a typical sensing device.
To calculate the average current, assume digital photo frame is operated 4 times in a 24-hour day and the user touches a capacitive sensing buttons for 300 seconds during each operation. This means device operates in TOUCH state for 1.38 percent of the 24 hours. The current consumption of the device averaged over 24 hours is calculated as follows
Calculating battery life
Generally, battery life is calculated based on the current rating in milli Ampere per Hour and it is abbreviated as mAh. Ampere is an electrical unit used to measure the current flow towards the load. The battery life or capacity can be calculated from the input current rating of the battery and the load current of the circuit. Battery life is high when the load current is less and vice versa. The calculation to find out the capacity of battery can be mathematically derived from the below formula
Take an example of a circuit with a battery of 800 mAh current rating and with a load of 40 mA. Its battery would last for 20 hours.
Battery life improvement using wake-on-approach proximity sensors
Lets us take the same example of digital photo frame with eight buttons which was discussed earlier. A proximity sensor is added to the design to implement wake-on-approach. Now, let us calculate the new average current consumption.
Sensors scan time for eight buttons and one proximity sensors would approximately be 18ms (TOUCH state), the scan time of proximity sensor would be 6ms (NO TOUCH state).
The average current in NO TOUCH state with wake-on-approach proximity is calculated as follows
The current consumption of the device averaged over 24 hours with wake-on-approach proximity is calculated as follows
Let us take a battery with 100 mAh current rating and figure out how many hours of battery life is increased in the design with wake-on-approach proximity sensor.
In Part 1, we have covered applications that use wake-on-approach proximity sensor and power optimization using wake-on-approach proximity sensor. In part 2, we will cover basics of proximity sensor and hardware implementation details of wake-on-approach proximity sensor.
Related Content: Visit Cypress’ website for a handy proximity detection demonstration with capacitive sensing.
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