EMERLab

Electronic MEasurements Research Laboratory

Our research group develops measurement systems based on statistical and digital signal processing to advance knowledge and applications in the areas of:

Short and medium range indoor positioning and navigation
Model identification in the presence of nonlinear distortion
Battery management systems
Device characterization

I2MTC ACCEPTED PAPERS

LATEST PUBLICATIONS

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I2MTC ACCEPTED PAPERS

See here the complete list of accepted contributions

LATEST PUBLICATIONS

Fast Battery EIS Measurement Using Flexible Local Rational MethodElectrochemical impedance spectroscopy (EIS) is one of the most widely used techniques for battery monitoring and characterization. However, EIS measurement is a time-consuming process, since it must be performed after the battery relaxation time interval. In this article, a method for performing fast broadband EIS during battery relaxation by compensating for the effect of the transient is proposed. The approach is based on the local rational method (LRM), which is a nonparametric frequency-domain system identification technique, and eliminates the need for long waiting time before starting the measurement process. The proposed approach is validated by numerical simulations and experiments, proving its capability of compensating the effect of the transient and outperforming other nonparametric techniques, such as the local polynomial method (LPM). In particular, experimental tests performed on a 18650 lithium-ion battery show that the proposed flexible LRM approach is capable of compensating the transient behavior and providing usable EIS estimates immediately after the battery discharge is finished. This behavior is demonstrated using a broadband multisine excitation signal of 20 s duration, spanning a frequency range from 50 mHz to 100 Hz.

A guide to equivalent circuit fitting for impedance analysis and battery state estimationIn this study we define a comprehensive method for analyzing electrochemical impedance spectra of lithium batteries using equivalent circuit models, a…

Fusion of UWB and Magnetic Ranging Systems for Robust PositioningMeasuring the position of robots or other devices in challenging environments, with tight accuracy requirements and insufficient coverage from satellite navigation systems, is crucial for improving existing applications and enabling novel solutions. In this article, two of the most commonly used positioning technologies are ultrawide band (UWB) ranging systems (RSs) and magnetic RS. These technologies present limitations that can be overcome by combining them and exploiting their complementary features. Specifically, the UWB RSs provide long-range accuracy and the standard deviation in the line-of-sight (LOS) condition is distance invariant, but the accuracy degrades in short-range and non-LOS (NLOS) conditions. Contrastingly, a magnetic RS exhibits robustness to NLOS scenarios and provides high accuracy over short distances, yet does not perform as well as UWB RSs over long distances. In this article, the compatibility and complementary characteristics of these two RSs are experimentally proven for the first time. The robustness in NLOS conditions of the magnetic RS and the low dispersion with increasing distance of the UWB RS represent the complementary characteristics. This complementarity is leveraged by the proposed fusion method: the adaptive tightly coupled extended Kalman filter (ATCEKF). The proposed fusion method is experimentally characterized in mixed LOS and NLOS conditions, resulting in 6.9 cm of error in an outdoor environment. The positioning error decreased by 55% with respect to the UWB standalone positioning system and 32% with respect to the magnetic standalone positioning system. Therefore, the proposed fusion method improves the robustness and accuracy of position estimation. These results are also confirmed by an additional experiment. In it, the new small-sized and battery-powered mobile node are implemented using a Raspberry Pi 4 Model B.

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