Kalman filter applied to Thevenin’s modeling of a lead-acid battery

<span>This article determines the internal parameters of a battery analyzed from its circuit equivalent, reviewing important information that can help to identify the battery’s state of charge (SOC) and its state of health (SOH). Although models that allow the dynamics of different types of batteries to be identified have been developed, few have defined the lead-acid battery model from the analysis of a filtered signal by applying a Kalman filter, particularly taking into account the measurement of noise not just at signal output but also at its input (this is a novelty raised from the experimental). This study proposes a model for lead-acid batteries using tools such as MATLAB^® and Simulink^®. First, a method of filtering the input and output signal is presented, and then a method for identifying parameters from 29 charge states is used for a lead-acid battery. Different SOCs are related to different values of open circuit voltage (OCV). Ultimately, improvements in model estimation are shown using a filter that considers system and sensor noise since the modeled and filtered signal is closer to the original signal than the unfiltered modeled signal.</span>

Archetype, Psyche, World

In our dialogues over the nature of archetypes, essence, psyche, and world, I further respond to Erik Goodwyn’s recent foray into establishing an ontological position that not only answers to the mind-body problem, but further locates the source of Psyche on a cosmic plane. His impressive attempt to launch a neo-Jungian metaphysics is based on the principle of cosmic panpsychism that bridges both the internal parameters of archetypal process and their emergence in consciousness and the external world conditioned by a psychic universe. Here I explore the ontology of experience, mind, matter, metaphysical realism, and critique Goodwyn’s turn to Neoplatonism. The result is a potentially compatible theory of mind and reality that grounds archetypal theory in onto-phenomenology, metaphysics, and bioscience, hence facilitating new directions in analytical psychology.

Multicamera Calibration Optimization Method Based on Improved Seagull Algorithm

There are some problems in the process of camera calibration, such as insufficient accuracy and poor accuracy. Based on the seagull algorithm, the adaptive differential evolution algorithm is combined with the seagull algorithm to optimize the multicamera calibration. The seagull algorithm can achieve good results on multiparameter problems and effectively avoid falling into local optima. In this paper, the adaptive differential search algorithm is adopted to improve the local search ability and optimize the local search and global search ability. According to Zhang Zhengyou's method, the calibrated parameter is obtained, in which the parameter is used as the initial value. Then, taking the minimum mean error as the criterion, the improved seagull algorithm (SOA-SaDE) is used to establish the objective function, and the internal parameters and distortion coefficient of the camera are further solved. Verification experiments showed that the fusion algorithm has less reprojection error and higher calibration accuracy gull algorithm.

Hybrid method of intellectual diagnosis and forecasting of complex technical systems

Modern control and diagnostic systems (CDS) usually determine only the technical condition (TC) at the current time, ie the CDS answers the question: a complex technical system (CTS) should be considered operational or not, and may provide little information on performance CTS even in the near future. Therefore, the existing scenarios of CDS operation do not provide for the assessment of the possibility of gradual failures, ie there is no forecasting of the technical condition. The processes of parameter degradation and degradation prediction are stochastic processes, the “behavior” of which is influenced by a combination of external and internal factors, so the deg-radation process can be described as a function that depends on changes in the internal parameters of CTS. The hybrid method involves the following steps. The first is to determine the set of initial characteristics that characterize the CTS vehicle. The second is the establishment of precautionary tolerances of degradation values of the characteristics that characterize the pre-failure technical con-dition of the CTS. The third is to determine the rational composition of informative indicators, which maximally determine the "behavior" of the initial characteristics. The fourth — implementa-tion of multiparameter monitoring, fixation of values of the controlled characteristics, formation of an information array of values of characteristics. Fifth — the adoption of a general model of the process of changing the characteristics of the CTS. Sixth — the formation of a real model of the process of changing the characteristics of Y(t) on the basis of an information array of values of char-acteristics obtained by multi-parameter monitoring. Seventh — forecasting the time of possible oc-currence of the pre-failure state of the CTS, which is carried out by extrapolating the obtained real model of the process of changing the characteristics of Y(t). It is proposed to use two types of mod-els: for medium- and long-term forecasting - polynomial models, for short-term forecasting — a lin-ear extrapolation model. At the final stage, forecast errors are determined for all types of models of degradation of pa-rameters and characteristics. Based on the results of the forecast verification, the models are adjust-ed

Lithium-Ion Battery Parameter Identification via Extremum Seeking Considering Aging and Degradation

Battery parameters such as State of Charge (SoC) and State of Health (SoH) are key to modern applications; thus, there is interest in developing robust algorithms for estimating them. Most of the techniques explored to this end rely on a battery model. As batteries age, their behavior starts differing from the models, so it is vital to update such models in order to be able to track battery behavior after some time in application. This paper presents a method for performing online battery parameter tracking by using the Extremum Seeking (ES) algorithm. This algorithm fits voltage waveforms by tuning the internal parameters of an estimation model and comparing the voltage output with the real battery. The goal is to estimate the electrical parameters of the battery model and to be able to obtain them even as batteries age, when the model behaves different than the cell. To this end, a simple battery model capable of capturing degradation and different tests have been proposed to replicate real application scenarios, and the performance of the ES algorithm in such scenarios has been measured. The results are positive, obtaining converging estimations both with new and aged batteries, with accurate outputs for the intended purpose.

Analysis and regulation of the cardiovascular system of univentricular heart with different configurations of the total cavopulmonary connection

The cardiovascular system (CVS) is a complex mechanism capable of reacting and regulating various changes in external and internal parameters. A particular problem is the study of CVS with univentricular heart. We studied the hemodynamic response of the CVS to the use of various configurations of bypassing the right side of the heart. During our research, we selected three different configurations of the total cavopulmonary connection. All configurations were made from Clear Flex 50 and tested in an experimental workbench. According to the research results, the TCPC-3 configuration is the most optimal. It has symmetrical output values of flows and pressures and there is no significant increase in inlet pressure. The results of this study can be used to optimize the control of the parameters of the ventricular assist device and the total artificial heart.

Spoofing Attack Detection Method for UAV Navigation System

An implementation of methods for protecting unmanned aerial vehicles (UAVs) from spoofing attacks of the global positioning system (GPS) to ensure safe navigation is discussed in this paper. The Global Navigation Satellite System (GNSS) is widely used to locate UAVs and is by far the most popular navigation solution. This is due to the simplicity and relatively low cost of this technology, as well as the accuracy of the transmitted coordinates. However, there are many security threats to GPS navigation. Primarily this is due to the nature of the GPS signal, the signal is transmitted in the clear, so an attacker can block or tamper with it. This study analyzes the existing GPS protection methods. As part of the study, an experimental stand and scenarios of attacks on the UAV GPS system were developed. Data from the UAV flight logbook was collected and an analysis of cyber-physical parameters was carried out to see an effect of the attack on the on-board sensors readings. Based on this, a new method for detecting UAV anomalies was proposed, based on an analysis of changes in UAV internal parameters. This self-diagnosis method allows the UAV to independently assess the presence of changes in its subsystems and identify signs of a cyberattack. To detect an attack, the UAV collects data on changes in cyber-physical parameters over a certain period of time, then updates this data. As a result it is necessary for the UAV to determine the degree of difference between the two time series of the collected data. The greater the degree of difference between the updated data and the previous ones, the more likely the UAV is under attack.

Proposal of a New Technique to Obtain Some Fuel Cell Internal Parameters Using Polarization Curve Tests and EIS Results

Nowadays, fuel cells are becoming a real alternative to power several applications, from portable electronic devices to cars, buses, or stationary facilities. Usually, a basic analysis of a fuel cell includes polarization curve test, as this method is excellent to characterize the behavior of a fuel cell as a whole, because it integrates all the different physical process that happens inside in current and voltage signals. On the other hand, it does not provide accurate information of these physical processes as individual. In this research, we relate the results of polarization curve test and EIS (Electrochemical Impedance Spectroscopy) test through two mathematical expressions. Then, using equivalent electrical circuit elements to model EIS curves, and applying the developed expressions, we correlate the EIS and polarization curve results, allowing us to interpret the physical meaning of these circuit elements and obtain a deeper vision of the internal processes that happen.

Comparative study with practical validation of photovoltaic monocrystalline module for single and double diode models

A photovoltaic (PV) module is an equipment that converts solar energy to electrical energy. A mathematical model should be presented to show the behavior of this device. The well-known single-diode and double-diode models are utilized to demonstrate the electrical behavior of the PV module. “Matlab/Simulink” is used to model and simulate the PV models because it is considered a major software for modeling, analyzing, and solving dynamic system real problems. In this work, a new modeling method based on the “Multiplexer and Functions blocks” in the "Matlab/Simulink Library" is presented. The mathematical analysis of single and double diodes is conducted on the basis of their equivalent circuits with simple modification. The corresponding equations are built in Matlab by using the proposed method. The unknown internal parameters of the PV panel circuit are extracted by using the PV array tool in Simulink, which is a simple method to obtain the PV parameters at certain weather conditions. Double-diode model results are compared with the single-diode model under various irradiances and temperatures to verify the performance and accuracy of the proposed method. The proposed method shows good agreement in terms of the I–V and P–V characteristics. A monocrystalline NST-120 W PV module is used to validate the proposed method. This module is connected to a variable load and tested for one summer day. The experimental voltage, current, and power are obtained under various irradiances and temperatures, and the I–V and P–V characteristics are obtained.

Features of virtual duplicate creation of the turning process

The interdisciplinary approach of MC-SUITE implementation of the Industry 4.0 concept and the main requirements for digital models (virtual duplicates) of cyber-physical systems regarding virtual processes compliance to the real ones and the possibility of real-time operation have been described. The main condition for creating an adequate dynamic model of technological processing system (TPS) interaction with the cutting process has been defined and a model for such interaction for the longitudinal turning has been developed. On example of developed turning process structural scheme the possibility of describing the interaction of the TPS input parameters (cutting depth and longitudinal feed) with the output parameters (deformations in the respective directions) due to changes in the model internal parameters in a form of cutting force components have been demonstrated. Such representation of the model allows virtual turning process adjusting by specifying the cutting stiffness and functional dependences for the cutting forces components based on the results of intelligent analytical processing of the monitoring results of the TPS operation.