Today’s customers for sensors and sensor systems expect to see improvements to performance parameters like module size, operating complexity, price, and energy consumption, as well as lower overall costs. The generally ever-growing need for information and performance leads to constantly increasing demands for both consumer and industrial applications when determining environmental conditions, such as pressure, temperature, weight, flow rate, torque, vibration, tension, and strain.
These requirements result in higher demands on sensor sensitivity, resolution, interference immunity, and precision. Within this context, the concept of a "smart sensor" system with a direct bus connection has continued to gain widespread acceptance in recent years. This system approach usually comprises the following functional elements: Sensor, analog signal conditioning (such as amplification, offset correction), analog-to-digital conversion, digital signal correction, bus interface, and digital analysis.
While smart sensors are now considered the de facto standard for new products launched on the market, particularly when it comes to high-precision sensor applications, one still finds extremely varied levels of performance as far as the actual signal conditioning and processing is concerned. For example, companies often advertise and offer an interface or signal conditioning IC with 16-bit signal resolution, although ultimately the resulting measurements may exhibit noise of up to several tenths of a percent of the full signal range. In these cases, the user only sees the desired performance in virtual form, since the low signal quality of the resulting measurements means that, for example, only 10 to 12 bits of effective resolution is actually available from the original range.
Thus, in addition to system concepts, the elimination, compensation, or at least minimization of circuit-specific analog interference still is, and, in the transition to smaller technologies, repeatedly becomes a major task.
Luckily enough, circuit topologies and approaches exist which remain valid and particularly effective—irrespective of the underlying technology—for the implementation of high-resolution, energy-efficient, low-noise smart sensors.
The ratiometric measurement principle is an often-used concept that eliminates interference in the power supply. In ratiometric measurements, the measured quantity sought after is the ratio of two quantities that typically exhibit interference. In this context, however, it is crucial that the interference does not impact the actual measurement. A ratiometric value is independent of the supply voltage, for example.
The figure below shows that the ratio of the measured voltages V1 and V2 to the resistances R1 and R2 is independent of the absolute value of the supply voltage VDD. As a result, when the value of R1 is known, one can determine the resistances R2 by means of measuring the voltages’ ratio and using the formula: R2 = R1•V2/V1.
In a system-integration approach, this principle can be extended for the use in complex sensor interface and sensor signal conditioning (SSC) integrated circuits (e.g. ZSI21013
and ZSSC30xx from ZMDI
, AT77C104Bx from Atmel
, etc.). A ratiometric topology allows for nearly noise-free applications that are essentially immune to supply voltage interference and have an effective signal resolution of 16-bit.
The basic ratiometric principle can be adopted for the amplifier and the analog-digital converter (ADC) in an SSC. In this case the internal IC reference voltages Vref
or rather Vrp
are directly derived from the resistive bridge sensor element’s supply voltage VDD
Ratiometric topology for resistive bridge sensor signal measurement.
As a result, interference to VDD
does systematically not affect the ratio of the sensor voltage VIN
to the ADC’s input voltage. Hence, even in case of fluctuations of IC-internal absolute levels of the supply voltage VDD
, there is no spurious effect in the A2D-converter’s output Zout
In principle, the following equation applies in this case:
represents amplification, and Voff
represents the internal offset within the signal path.
In addition, for future SSC generations, the applicability of concepts is a research objective today in academia and industry to develop low-power supply voltage suppression using suitable voltage regulators. Thereby low dropout regulators (LDOs) will make it possible to use high-resolution, low-power sensor systems in environments with significant levels of interference, such as in smart phones. In this context, the voltage regulators reduce dynamic losses due to parasitic capacitances in the signal path and allow for systems with effective 16- to 24-bit resolution and operating voltages down to the respective silicon-processes related transistor supply minimum, while utilizing a ratiometric signal path at the same time.