Practical assessment of hardware limitations on power aware wireless sensor networks - An anti-windup approach

This work considers the effect of hardware constraints that typically arise in practical power-aware wireless sensor network systems. A rigorous methodology is presented that quantifies the effect of output power limit and quantization constraints on bit error rate performance. The approach uses a novel, intuitively appealing means of addressing the output power constraint, wherein the attendant saturation block is mapped from the output of the plant to its input and compensation is then achieved using a robust anti-windup scheme. A priori levels of system performance are attained using a quantitative feedback theory approach on the initial, linear stage of the design paradigm. This hybrid design is assessed experimentally using a fully compliant 802.15.4 testbed where mobility is introduced through the use of autonomous robots. A benchmark comparison between the new approach and a number of existing strategies is also presented

Structural Identifiability of Impedance Spectroscopy Fractional-Order Equivalent Circuit Models With Two Constant Phase Elements

Structural identifiability analysis of fractional-order equivalent circuit models (FO-ECMs), obtained through electrochemical impedance spectroscopy (EIS) is still a challenging problem. No peer-reviewed analytical or numerical proof does exist showing that whether impedance spectroscopy FO-ECMs are structurally identifiable or not, regardless of practical issues such as measurement noises and the selection of excitation signals. By using the coefficient mapping technique, this paper proposes novel computationally-efficient algebraic equations for the numerical structural identifiability analysis of a widely used FO-ECM with Gr\"{u}nwald-Letnikov fractional derivative approximation and two constant phase elements (CPEs) including the Warburg term. The proposed numerical structural identifiability analysis method is applied to an example from batteries, and the results are discussed. Matlab codes are available on github

An antiwindup approach to power controller switching in an ambient healthcare network

This paper proposes a methodology for improved power controller switching in mobile Body Area Networks operating within the ambient healthcare environment. The work extends Anti-windup and Bumpless transfer results to provide a solution to the ambulatory networking problem that ensures sufficient biometric data can always be regenerated at the base station. The solution thereby guarantees satisfactory quality of service for healthcare providers. Compensation is provided for the nonlinear hardware constraints that are a typical feature of the type of network under consideration and graceful performance degradation in the face of hardware output power saturation is demonstrated, thus conserving network energy in an optimal fashion

A systematic overview of power electronics interfaced electrochemical impedance spectroscopy for energy storage systems

With automotive industry\u27s move towards vehicle electrification; hence, a dependence on energy storage systems, interest in Power Electronics Interfaced Electrochemical Impedance Spectroscopy (PEI-EIS) has been growing steadily and rapidly. As much of the work on impedance spectroscopy is carried out by electrochemists or physicists, this paper is an attempt to systematically and through an engineering perspective, walk the engineering researchers interested in this field through the main phases of the PEI-EIS process, provide a review of some recent work, and highlight the challenging and important issues that are encountered in each phase along the way. In particular, the paper elaborates on the role of often overlooked/unaddressed controller, how the required excitation signals for EIS are generated by power electronics devices, what type of excitations are needed, how the generated data-set is measured, and finally, how the results are presented. Additionally, with an engineering perspective, the pros and cons of the recent past contributions reported in the literature for PEI-EIS are discussed

Input-output slope curve estimation in neural stimulation based on optimal sampling principles

This paper discusses some of the practical limitations and issues, which exist for the input-output (IO) slope curve estimation (SCE) in neural, brain and spinal, stimulation techniques. The drawbacks of the SCE techniques by using existing uniform sampling and Fisher-information-based optimal IO curve estimation (FO-IOCE) methods are elaborated. A novel IO SCE technique is proposed with a modified sampling strategy and stopping rule which improve the SCE performance compared to these methods. The effectiveness of the proposed IO SCE is tested on 1000 simulation runs in transcranial magnetic stimulation (TMS), with a realistic model of motor evoked potentials. The results show that the proposed IO SCE method successfully satisfies the stopping rule, before reaching the maximum number of TMS pulses in 79.5% of runs, while the estimation based on the uniform sampling technique never converges and satisfies the stopping rule. At the time of successful termination, the proposed IO SCE method decreases the 95th percentile (mean value in the parentheses) of the absolute relative estimation errors (AREs) of the slope curve parameters up to 7.45% (2.2%), with only 18 additional pulses on average compared to that of the FO-IOCE technique. It also decreases the 95th percentile (mean value in the parentheses) of the AREs of the IO slope curve parameters up to 59.33% (16.71%), compared to that of the uniform sampling method. The proposed IO SCE also identifies the peak slope with higher accuracy, with the 95th percentile (mean value in the parentheses) of AREs reduced by up to 9.96% (2.01%) compared to that of the FO-IOCE method, and by up to 46.29% (13.13%) compared to that of the uniform sampling method

Multi-purpose controllable electrochemical impedance spectroscopy using bidirectional DC–DC converter

In this paper, we propose a multi-purpose controllable electrochemical impedance spectroscopy (MP-cEIS) device for online and offline battery monitoring and testing during charge and discharge processes. The proposed MP-cEIS device is based on the widely used synchronous buck converter, with a low-cost and simple input filter to provide the bidirectional operation. It also includes a closed-loop feedback system to control the injection of the EIS excitation signal. For the control system design, an average model of the proposed MP-cEIS is derived. Two methods, based on H∞ and quantitative feedback theory (QFT), are presented for the design of a robust controller, which guarantees the stability and tracking of the excitation signal despite model uncertainties. The excitation signal in the proposed MP-cEIS is programmable. The performance of the proposed MP-cEIS is evaluated experimentally, with multi-sine and swept-sine signals, and the results are shown

Controllable Electrochemical Impedance Spectroscopy: From Circuit Design to Control and Data Analysis

This article describes fundamentals of controllable electrochemical impedance spectroscopy (cEIS), from circuit design to control and data analysis. In cEIS, a feedback system controls the process of injecting the excitation signal. We design a two degree-of-freedom robust control system, which guarantees tracking and stability of cEIS in the presence of model uncertainties. This article also addresses the concept of persistently exciting signals. cEIS using current driving mode (CDM) and voltage driving mode, and their differences are highlighted. An online cEIS device is designed and built based on the dc-dc buck converter for batteries online applications, where the excitation signal is superimposed on a dc level. The performance of the fabricated cEIS is evaluated through extensive experiments in CDM. The accuracy of the fabricated cEIS is tested, which results in \text{0.002}\;\Omega root mean square error in the impedance spectra computation of a three-parameter Randles equivalent circuit model (ECM). The performance of the fabricated cEIS is practically verified on a battery cell at different C-rates. First-, second-, and fractional-order Randles ECMs are estimated by using system identification methods, and their impedance spectra are compared with those obtained through the fast Fourier transform