IoT wireless sensors and the problem of short battery life

11 December 2015

Wireless sensors provide great insight in applications because they are simple to install, they can be deployed in a multitude of situations.

Yet one of the factors that most limits the use of wireless sensors is their limited ability to do the job for a reasonable amount of time. 

If you are designing battery-operated wireless sensors, you face numerous challenges in ensuring your devices operate for a reasonable amount of time. The typical approach is to use energy for just the required activity, then put the device in low-power-use mode. 

The simplest way to increase the battery life is to use a battery with higher capacity. Nevertheless, customers are likely to expect their sensors to be small and to offer high performance. 

How do engineers estimate battery life?

A battery has a defined amount of energy, specified in Watt hours (Wh) and capacity, specified in amp hours (Ah). If you know how much power is required to operate your device, you can calculate the battery life:

Battery life (hours) = Battery capacity (Wh)/average power drain (W) 

The battery’s energy is also the product of its voltage rating (V) and capacity (Ah). The voltage rating is a midpoint value on the battery’s discharge curve empirically determined to correctly relate the battery’s energy and capacity. Based on this, battery life can also be determined by the formula:

Battery life (hours) = Battery capacity (Ah)/average current drain (A)

However, when the device is in real operation, the battery life is typically shorter than the number you calculated. Representatives for big battery brands will offer detailed specifications and explain that among batteries of the same type, it is common to have capacity variations of 5 to 10 percent. Yet even using conservative battery capacity estimates, battery life typically falls short. 

Measuring dynamic current drain

In battery-powered devices like wireless sensors, to save energy the device sub-circuits are active only when required. Engineers design the device to spend most of its time in a sleep mode with minimum current drain. During sleep mode, only the real-time clock operates. The unit then wakes up periodically to perform measurements. The acquired data is then transmitted to a receiving node. 

Typical current levels and timing
TX 20 - 100 mA 1 - 100 ms
Active 100 µA - 10 mA 10 - 100 ms
Sleep 500 nA - 50 µA 100 ms - minutes

The different operating modes result in a current drain that spans a wide dynamic range from sub-µA to 100 mA, which is a ratio on the order of 1:1,000,000.

Measurement techniques and limitations

A well-known method for measuring current is to use the ammeter function of a DMM. The DMM is connected in series between battery and device to measure the current. From time to time we see some reading instabilities due to the sensor’s active cycle or even the transmit mode. We know that DMMs have multiple ranges, and with auto range it should be able to select the most appropriate range and give the best accuracy. However, the auto range takes time to change range and settle the measurement results. Time to auto-range is often 10 to 100ms, longer than transmission or active modes times. For this reason, the auto-range function needs to be disabled and the user needs to manually choose the most appropriate range. 

The DMM makes measurements by inserting a shunt in the circuit and measuring the voltage drop across it. Normally to measure low current, you choose a low range based on a shunt with high resistance; to measure high current you choose a high range based on a low-resistance shunt. The voltage drop is also called burden voltage. Due to this voltage drop, not all the battery voltage reaches the wireless sensor. Most accurate low ranges for sleep current measurements have burden voltage during current peaks that may even cause the device to reset. Practically, we end up compromising and using a high current range that keeps the device operating during current peaks. This compromise enables us to handle peak current and measure the sleep current, but at a high price. As the offset error is specified on range full scale, it heavily impacts measurements on low current levels. Its error contribution can be 0.005% error on 100 mA range = 5 µA, which is a 50% error on 10 µA or 500% error on a 1-µA current level. This current level is where the device spends most of its time, so this error has a huge impact on the battery life estimation. 

After measuring the sensor’s low current level during sleep mode, we have to measure the active and transmission pulses. Measurements need to include both the current level and the time the sensor spends at that level. Oscilloscopes are excellent tools for measuring signals changing over time. However, we need to measure current in the 10’s of mA level, and current probes are limited due to their limited sensitivity and their drift. Good clamp probes have 2.5-mArms noise, and the zero compensation procedure needs to be repeated often.

Current probes measure the electric field over a wire, so the trick to increase sensitivity is to pass the same wire multiple times so we multiply the magnetic field – this multiplies the current readout, enabling us to measure the current a bit better. With this approach, we can capture the current pulse of the activity and the transmission time. Even within the activity and transmission, the current changes levels: it looks like a train of high and low levels. To properly calculate the average current the waveform needs to be exported and all the measured points need to be integrated to get the average value. 

Oscilloscopes do a good job of capturing a single burst. However, the measurements are more complex if we want to verify how many times the sensor activates in a timeframe and how often it sends out a TX burst. 

Measurement innovations

The Keysight N6781A source/measure unit (SMU) for battery drain analysis overcomes the limitations of traditional measurements with two innovations: seamless current ranging and long-term gap-free data logging. The SMU is a module that can be used with the Keysight N6700 low-profile modular power system or N6705 DC power analyser.

The seamless current ranging is a technology that enables the SMU to change the measurement range while keeping the output voltage stable without any dropout due to ranging. This feature enables you to measure the peaks with high current ranges and measure the sleep current with the 1-mA FS range, which has 100 nA of offset error. 

The seamless current ranging is combined with two digitisers to measure voltage and current with simultaneous sampling at 200 kSa/s. Digitised measurements can be captured over 2 seconds and displayed with full time resolution and proportionally longer time with lower resolution. However, for long-term measurements, the internal data logger in the Keysight N6705B modular DC power analyser integrates the 200-kSa/s measurements over a user-specified integration period without losing any samples between the integration periods. As the data logger is gap-free, all the samples fall in one integration period or in the next one -- no samples are lost. With the data logger, engineers can now measure the current and energy drain performance of a wireless sensor for up to 1000 hours of operation.

Measuring the sleep current is just a matter of placing the markers and directly reading out the values provided. 

With pan and zoom capability, it’s possible to look at the current level and time spent at every power level. Details that traditional measurement tools do not see can now be identified and measured (Fig 4). 

In wireless sensor power optimisation, engineers get great value by understanding the details. Knowing how much energy it takes to send out a single packet of information is very important when balancing user experience against battery drain. Engineers can accurately estimate the battery drain impact of any firmware change and validate it in a reasonable time with real measurements. 

Joule measurements made easy

With the Keysight 14585A control and analysis software, energy in Joules can be measured directly. For example, you might measure the energy consumed by transmitting a packet (Fig 5) captured with a triggered measurement. This is one benefit of having two digitisers for voltage and current with simultaneous sampling that enable point-by-point power measurements. Joules can be easily read out as a value between the markers, and designers can go a step further by defining Joules/transmitted bit. 

Engineers who design IoT battery-powered devices use advanced power management techniques to conserve battery life. The Keysight SMUs for battery drain analysis enable accurate current drain analysis with one picture that provides a complete and detailed current and energy drain analysis. Post-analysis software simplifies the engineer’s job by offering visibility into details never seen before. 

With Keysight’s latest introduction of the N6785A SMUs for battery drain, these capabilities are now available up to 80W and from nA to 8A. The new SMUs are used in multiple applications from smartphone and tablet testing to automotive ECU and IoT wireless sensors and chipsets. 




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