Matching Items (9)
- All Subjects: engineering
Electrical stimulus-based characterization for calibration and testing of MEMS accelerometer and gyroscope
Micro-Electro Mechanical System (MEMS) is the micro-scale technology applying on various fields. Traditional testing strategy of MEMS requires physical stimulus, which leads to high cost specified equipment. Also there are a large number of wafer-level measurements for MEMS. A method of estimation calibration coefficient only by electrical stimulus based wafer level measurements is included in the thesis. Moreover, a statistical technique is introduced that can reduce the number of wafer level measurements, meanwhile obtaining an accurate estimate of unmeasured parameters. To improve estimation accuracy, outlier analysis is the effective technique and merged in the test flow. Besides, an algorithm for optimizing test set is included, also providing numerical estimated prediction error.
High speed current-steering DACs with high linearity are needed in today's applications such as wired and wireless communications, instrumentation, radar, and other direct digital synthesis (DDS) applications. However, a trade-off exists between the speed and resolution of Nyquist rate current-steering DACs. As the resolution increases, more transistor area is required to meet matching requirements for optimal linearity and thus, the overall speed of the DAC is limited.
In this thesis work, a 12-bit current-steering DAC was designed with current sources scaled below the required matching size to decrease the area and increase the overall speed of the DAC. By scaling the current sources, however, errors due to random mismatch between current sources will arise and additional calibration hardware is necessary to ensure 12-bit linearity. This work presents how to implement a self-calibration DAC that works to fix amplitude errors while maintaining a lower overall area. Additionally, the DAC designed in this thesis investigates the implementation feasibility of a data-interleaved architecture. Data interleaving can increase the total bandwidth of the DACs by 2 with an increase in SQNR by an additional 3 dB.
The final results show that the calibration method can effectively improve the linearity of the DAC. The DAC is able to run up to 400 MSPS frequencies with a 75 dB SFDR performance and above 87 dB SFDR performance at update rates of 200 MSPS.
Modern Complex electronic system include multiple power domains and drastically varying power consumption patterns, requiring the use of multiple power conversion and regulation units. High frequency switching converters have been gaining prominence in the DC-DC converter market due to their high efficiency. Unfortunately, they are all subject to higher process variations jeopardizing stable operation of the power supply.
This research mainly focus on the technique to track changes in the dynamic loop characteristics of the DC-DC converters without disturbing the normal mode of operation using a white noise based excitation and correlation. White noise excitation is generated via pseudo random disturbance at reference and PWM input of the converter with the test signal being spread over a wide bandwidth, below the converter noise and ripple floor. Test signal analysis is achieved by correlating the pseudo-random input sequence with the output response and thereby accumulating the desired behavior over time and pulling it above the noise floor of the measurement set-up. An off-the shelf power converter, LM27402 is used as the DUT for the experimental verification. Experimental results show that the proposed technique can estimate converter's natural frequency and Q-factor within ±2.5% and ±0.7% error margin respectively, over changes in load inductance and capacitance.
The manufacturing process for electronic systems involves many players, from chip/board design and fabrication to firmware design and installation.
In today's global supply chain, any of these steps are prone to interference from rogue players, creating a security risk.
Manufactured devices need to be verified to perform only their intended operations since it is not economically feasible to control the supply chain and use only trusted facilities.
It is becoming increasingly necessary to trust but verify the received devices both at production and in the field.
Unauthorized hardware or firmware modifications, known as Trojans,
can steal information, drain the battery, or damage battery-driven embedded systems and lightweight Internet of Things (IoT) devices.
Since Trojans may be triggered in the field at an unknown instance,
it is essential to detect their presence at run-time.
However, it isn't easy to run sophisticated detection algorithms on these devices
due to limited computational power and energy, and in some cases, lack of accessibility.
Since finding a trusted sample is infeasible in general, the proposed technique is based on self-referencing to remove any effect of environmental or device-to-device variations in the frequency domain.
In particular, the self-referencing is achieved by exploiting the band-limited nature of Trojan activity using signal detection theory.
When the device enters the test mode, a predefined test application is run on the device
repetitively for a known period. The periodicity ensures that the spectral electromagnetic power of the test application concentrates at known frequencies, leaving the remaining frequencies within the operating bandwidth at the noise level. Any deviations from the noise level for these unoccupied frequency locations indicate the presence of unknown (unauthorized) activity. Hence, the malicious activity can differentiate without using a golden reference or any knowledge of the Trojan activity attributes.
The proposed technique's effectiveness is demonstrated through experiments with collecting and processing side-channel signals, such as involuntarily electromagnetic emissions and power consumption, of a wearable electronics prototype and commercial system-on-chip under a variety of practical scenarios.
Power management circuits are employed in most electronic integrated systems, including applications for automotive, IoT, and smart wearables. Oftentimes, these power management circuits become a single point of system failure, and since they are present in most modern electronic devices, they become a target for hardware security attacks. Digital circuits are typically more prone to security attacks compared to analog circuits, but malfunctions in digital circuitry can affect the analog performance/parameters of power management circuits. This research studies the effect that these hacks will have on the analog performance of power circuits, specifically linear and switching power regulators/converters. Apart from security attacks, these circuits suffer from performance degradations due to temperature, aging, and load stress. Power management circuits usually consist of regulators or converters that regulate the load’s voltage supply by employing a feedback loop, and the stability of the feedback loop is a critical parameter in the system design. Oftentimes, the passive components employed in these circuits shift in value over varying conditions and may cause instability within the power converter. Therefore, variations in the passive components, as well as malicious hardware security attacks, can degrade regulator performance and affect the system’s stability. The traditional ways of detecting phase margin, which indicates system stability, employ techniques that require the converter to be in open loop, and hence can’t be used while the system is deployed in-the-field under normal operation. Aging of components and security attacks may occur after the power management systems have completed post-production test and have been deployed, and they may not cause catastrophic failure of the system, hence making them difficult to detect. These two issues of component variations and security attacks can be detected during normal operation over the product lifetime, if the frequency response of the power converter can be monitored in-situ and in-field. This work presents a method to monitor the phase margin (stability) of a power converter without affecting its normal mode of operation by injecting a white noise/ pseudo random binary sequence (PRBS). Furthermore, this work investigates the analog performance parameters, including phase margin, that are affected by various digital hacks on the control circuitry associated with power converters. A case study of potential hardware attacks is completed for a linear low-dropout regulator (LDO).
Current technology does not allow for the full amount of power produced by solar arrays (PV) on spacecraft to be utilized. The arrays are designed with non-reconfigurable architectures and sent on fifteen to twenty year long missions. They cannot be changed once they are in space, so the arrays are designed for the end of life. Throughout their lifetime, solar arrays can degrade in power producing capabilities anywhere from 20% to 50%. Because there is such a drastic difference in the beginning and end of life power production, and because they cannot be reconfigured, a new design has been found necessary in order to increase power production. Reconfiguration allows the solar arrays to achieve maximum power producing capabilities at both the beginning and end of their lives. With the potential to increase power production by 50%, the reconfiguration design consists of a switching network to be able to utilize any combination of cells. The design for reconfiguration must meet the power requirements of the solar array. This thesis will explore different designs for reconfiguration, as well as possible switches for implementation. It will also review other methods to increase power production, as well as discuss future work in this field.
Extraction of RF transceiver system parameters and impairments through detailed analytical modeling combined with a genetic algorithm approach
ABSTRACT To meet stringent market demands, manufacturers must produce Radio Frequency (RF) transceivers that provide wireless communication between electronic components used in consumer products at extremely low cost. Semiconductor manufacturers are in a steady race to increase integration levels through advanced system-on-chip (SoC) technology. The testing costs of these devices tend to increase with higher integration levels. As the integration levels increase and the devices get faster, the need for high-calibre low cost test equipment become highly dominant. However testing the overall system becomes harder and more expensive. Traditionally, the transceiver system is tested in two steps utilizing high-calibre RF instrumentation and mixed-signal testers, with separate measurement setups for transmitter and receiver paths. Impairments in the RF front-end, such as the I/Q gain and phase imbalance and nonlinearity, severely affect the performance of the device. The transceiver needs to be characterized in terms of these impairments in order to guarantee good performance and specification requirements. The motivation factor for this thesis is to come up with a low cost and computationally simple extraction technique of these impairments. In the proposed extraction technique, the mapping between transmitter input signals and receiver output signals are used to extract the impairment and nonlinearity parameters. This is done with the help of detailed mathematical modeling of the transceiver. While the overall behavior is nonlinear, both linear and nonlinear models to be used under different test setups are developed. A two step extraction technique has been proposed in this work. The extraction of system parameters is performed by using the mathematical model developed along with a genetic algorithm implemented in MATLAB. The technique yields good extraction results with reasonable error. It uses simple mathematical operation which makes the extraction fast and computationally simple when compared to other existing techniques such as traditional two step dedicated approach, Nonlinear Solver (NLS) approach, etc. It employs frequency domain analysis of low frequency input and output signals, over cumbersome time domain computations. Thus a test method, including detailed behavioral modeling of the transceiver, appropriate test signal design along with a simple algorithm for extraction is presented.
Impact of Variations, Measurement Uncertainty, and Surface Roughness on High-Speed Interconnect Validation
The rapid growth of emerging technologies is placing enormous demand on the seamless access to the extensive amount of data, which drives an unprecedented need for substantially higher data-transfer rates. As 1.6 Terabit Ethernet (TbE) specifications are being developed, high speed interconnects along with advanced materials and processes play a crucial role in technology enabling. However, validation of interconnect performance becomes increasingly challenging at these higher speeds. High-speed interconnect behavior can be reliably predicted if interconnect models are successfully validated against measurements. In industry, it is still not common practice to perform validation at actual use conditions. Therefore, there is an urge for a restructured design methodology and metrology based on temperature and humidity, to set realistic specs for high speed interconnects and reduce probability of failure under variations. Uncertainty quantification and propagation for interconnect validation is critical to assess the correlation quality more objectively, as well as to determine the bottleneck to improve the accuracy, repeatability and reproducibility of all the measurements involved in validation. The purpose of this work is to create a methodology that is both academically rigorous and has a significant impact on industry. This methodology provides an accurate characterization of the electrical performance of interconnects under realistic use-conditions, accompanied by an uncertainty analysis to improve the assessment of correlation quality. Part of this work contributed to the Packaging Benchmark Suite developed by IEEE EPS technical committee on electrical design, modeling, and simulation.
Pulse Density Modulation- (PDM-) based class-D amplifiers can reduce non-linearity and tonal content due to carrier signal in Pulse Width Modulation - (PWM-) based amplifiers. However, their low-voltage analog implementations also require a linear- loop filter and a quantizer. A PDM-based class-D audio amplifier using a frequency-domain quantization is presented in this paper. The digital-intensive frequency domain approach achieves high linearity under low-supply regimes. An analog comparator and a single-bit quantizer are replaced with a Current-Controlled Oscillator- (ICO-) based frequency discriminator. By using the ICO as a phase integrator, a third-order noise shaping is achieved using only two analog integrators. A single-loop, singlebit class-D audio amplifier is presented with an H-bridge switching power stage, which is designed and fabricated on a 0.18 um CMOS process, with 6 layers of metal achieving a total harmonic distortion plus noise (THD+N) of 0.065% and a peak power efficiency of 80% while driving a 4-ohms loudspeaker load. The amplifier can deliver the output power of 280 mW.