An Untrimmed BJT-Based Temperature Sensor With Dynamic Current-Gain Compensation in 55-nm CMOS Process

Tang, Zhong; Fang, Yun; Huang, Zhenyan; Yu, Xiaopeng; Zheng, Shuang; Tan, Nianxiong

doi:10.1109/tcsii.2019.2921889

Cited by 17 publications

(10 citation statements)

References 13 publications

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“…The considerable spread of the untrimmed case and the residual error of the one-point offset-compensated one are mainly due to the mismatch effects of the several current mirrors employed within the sensor's design. This condition could have been improved by introducing chopping or dynamic element matching (DEM) techniques which are commonly used in this field [39], [40], [41], [42]; however, no effort was spent in this direction since the achieved accuracy performance, although modest with respect to other the state-of-the-art BJT-based solutions, is compliant with the application taken into account. As stated in the Introduction, the accuracy of this temperature sensor is at some point bottlenecked by the uncertainty of the outputs of the inertial sensors to be compensated; for this reason, a 2% accuracy in a 160 °C temperature range is considered sufficient.…”

Section: Temperature Inaccuracymentioning

confidence: 99%

An Area-Efficient Smart Temperature Sensor Based on a Fully Current Processing Error-Feedback Noise-Shaping SAR ADC in 180-nm CMOS

Aprile,

Folz,

Gardino

et al. 2024

IEEE J. Solid-State Circuits

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This article presents a bipolar junction transistor (BJT)-based smart temperature sensor employing a noise-shaping successive-approximation-register (SAR) analog-to-digital converter (ADC). This approach, never explored before within a temperature sensing system, was chosen to exploit the low energy/conversion benefit peculiar to SAR-based solutions while overcoming their quantization-dominated resolution with an error-feedback technique. In addition, the system features a complete current-mode architecture enabling op-amp less signal processing and resulting in a highly compact design. Developed and fabricated in a standard 180-nm CMOS process, the sensor exhibits an active area of 0.057 mm 2 and draws a 34-µA total current from a 1.8-V supply. Experimental results in the −50 °C to 110 °C sensing range demonstrate a 92-mK resolution in a conversion time of 80 µs.

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Section: Temperature Inaccuracymentioning

confidence: 99%

An Area-Efficient Smart Temperature Sensor Based on a Fully Current Processing Error-Feedback Noise-Shaping SAR ADC in 180-nm CMOS

Aprile,

Folz,

Gardino

et al. 2024

IEEE J. Solid-State Circuits

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“…Compared to earlier work from [6,14] with a similar ADC, this implementation has a few advantages: The modulation is performed by switching of a single series-resistor, where the measurement range can be freely adjusted by the R2/R1-ratio. Since resistors show generally better matching than current mirrors (at equal area), there is no dynamic element matching (DEM) required like for a current-DAC.…”

Section: Basic Sensor Principlementioning

confidence: 99%

A Current-Mode Temperature Sensor with a ±1.56 °C Raw Error and Duty-Cycle Output in 16nm FinFET

Eberlein

Pretl

2021

2021 IEEE International Symposium on Circuits and Systems (ISCAS)

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This brief presents a versatile thermal sensor, which features explicit simplicity on both circuit and system level. High accuracy without the need for calibration is possible by using the NPN bipolar device, available from a triple-well process. Combining the current-mode principle with an active integrator, the architecture can provide the temperature information directly through the duty-cycle of a single output signal. Not only the generation of PTAT and CTAT signals, but also the processing and basic A/D conversion is performed in the same feedback loop. This results in a robust and compact solution, that is independent from external clock or other control signals. A prototype sensor occupies only 2475 µm 2 silicon area in 16nm FinFET and consumes 30 µA at 0.95 V supply voltage. Across the consumer range, it achieves an accuracy of ± 1.56 ˚C (3σ) without calibration and a typical conversion speed of 40kS/sec., which are among best-inclass figures.

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“…A more precise model of ( 4) can be obtained by considering the two different noise sources. One is the approximation error ε that is defined in (7). Another one is the sensor noise during temperature measurements.…”

Section: Temperature Sensor Allocationmentioning

confidence: 99%

“…Typically, the DTM technique uses on-chip temperature sensors to obtain the full thermal field details of a chip [7,8]. Ideally, a precise full-chip thermal field could be achieved directly from temperature sensor measurements by allocating a large number of sensors on the chip.…”

Section: Introductionmentioning

confidence: 99%

Thermal field reconstruction based on weighted dictionary learning

Zhang

Xiao³

et al. 2021

IET Circuits, Devices & Syst

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Dynamic thermal management (DTM) is applied to address the thermal problem of high performance very-large-scale integrated chips. The false alarm rate (FAR) can be used to evaluate the impact of full-chip thermal field reconstruction accuracy on DTM. A low FAR relies on the accurate reconstruction of the full thermal field, especially near the temperature triggering threshold of DTM. However, little attention is currently being paid to such temperature ranges. To reduce FAR, a new full-chip thermal field reconstruction strategy is proposed. A low-dimensional linear model is used to accurately represent the thermal fields. The dictionary learning technology is exploited to train the model and the minimum weighted mean square error evaluation method is incorporated to improve the reconstruction accuracy near the temperature triggering threshold. A temperature sensor placement algorithm using the heuristic algorithm to solve the NPhard problem is also proposed. The experimental results show that the proposed strategy can reconstruct the full thermal field with a more precise accuracy near the triggering threshold and achieve the lowest FAR compared to the state of the art.

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An Untrimmed BJT-Based Temperature Sensor With Dynamic Current-Gain Compensation in 55-nm CMOS Process

Cited by 17 publications

References 13 publications

An Area-Efficient Smart Temperature Sensor Based on a Fully Current Processing Error-Feedback Noise-Shaping SAR ADC in 180-nm CMOS

An Area-Efficient Smart Temperature Sensor Based on a Fully Current Processing Error-Feedback Noise-Shaping SAR ADC in 180-nm CMOS

A Current-Mode Temperature Sensor with a ±1.56 °C Raw Error and Duty-Cycle Output in 16nm FinFET

Thermal field reconstruction based on weighted dictionary learning

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