Juan Carlos Álvarez Antón

Support Vector Machines Used to Estimate the Battery State of Charge

The aim of this study is to estimate the state of charge (SOC) of a high-capacity lithium iron manganese phosphate (LiFeMnPO4) battery cell from an experimental dataset using a support vector machine (SVM) approach. SVM is a type of learning machine based on statistical learning theory. Many applications require accurate measurement of battery SOC in order to give users an indication of available runtime. It is particularly important for electric vehicles or portable devices. In this paper, the proposed SOC estimator extracts model parameters from battery charging/discharging testing cycles, using cell current, cell voltage, and cell temperature as independent variables. Tests are carried out on a 60 Ah lithium-ion cell with the dynamic stress test cycle to set up the SVM model. The SVM SOC estimator maintains a high level of accuracy, better than 6% over all ranges of operation, whether the battery is charged/discharged at constant current or it is operating in a variable current profile.

Battery State-of-Charge Estimator Using the MARS Technique

State of charge (SOC) is the equivalent of a fuel gauge for a battery pack in an electric vehicle. Determining the state of charge is thus particularly important for electric vehicles (EVs), hybrid EVs, or portable devices. The aim of this innovative study is to estimate the SOC of a high-capacity lithium iron phosphate (LiFePO4) battery cell from an experimental dataset obtained in the University of Oviedo Battery Laboratory using the multivariate adaptive regression splines (MARS) technique. An accurate predictive model able to forecast the SOC in the short term is obtained and it is a first step using the MARS technique to estimate the SOC of batteries. The agreement of the MARS model with the experimental dataset confirmed the goodness of fit for a limited range of SOC (25-90% SOC) and for a simple dynamic data profile [constant-current (CC) constant-voltage charge-CC discharge].

A Discharge Lamp Model Based on Lamp Dynamic Conductance

A model for discharge lamp based on lamp electrical conductance is proposed. Physical assumptions are used to obtain this model. The model allows simulating lamp behavior at different frequencies and delivered power levels. The model has been verified using a high pressure sodium lamp supplied at 50 and 100kHz

An Equivalent Circuit Model With Variable Effective Capacity for

A new approach to equivalent circuit models for LiFePO4 batteries is presented in this paper. The proposed battery model is a semi-physical nonlinear dynamic model with variable effective capacity. Fuzzy logic has been used to capture the nonlinear behavior of the battery in combination with continuous-time differential equations. Fuzzy logic blocks are embedded in a state-space dynamic model as nonlinear constructive blocks. The proposed model has been validated for three different LiFePO4 batteries. The model provides an intuitive physical analogy between charging LiFePO4 batteries and filling a semi-rigid tank, which is useful for explanatory purposes.

\hbox{LiFePO}_{4}

This paper describes an automatic computer-controlled acoustic resonance detection workbench for high-intensity-discharge (HID) lamps. The detection method is based on optical measurements of the discharge arc path. With the aid of a dual lens projection system, relative light intensity measurements at different points of the arc are guided by fiber optic to a photodiode array. These measurements are statistically analyzed to identify when acoustic resonance occurs. Experimental results confirm this method to be a valuable tool to automatically obtain an acoustic-resonance-frequency map for HID lamps.

Batteries

This work shows the design of a low-cost, portable instrument for amperometric biosensors, which measures the faradaic currents originated by the electronic interchanges between a specific substance and a biological recognition system, present on an electrode and kept at an appropriate potential. The final objective is to obtain a direct relationship between those currents and the concentration of the substrate to be analyzed. This instrument may be used for sensors or cells with two or three electrodes in order to detect extremely low concentrations of a wide variety of substances. The instrument was evaluated comparing calibration curves from glucose, ethanol and cholesterol biosensors to those obtained from very expensive commercial equipment. Good linearity and sensibility, as well as low noise measurements were obtained. Moreover, thanks to its reduced size and low cost, this instrument can be used directly in field applications

An Acoustic Resonance Band Detection Workbench for HID Lamps

This paper describes the electronic design and the performance of a low-cost fiber-optic instrument for pH fluorescent measurements. The chemical sensing phase consists of an organic pH indicator (mercurochrome) immobilized in a sol-gel matrix placed at the end of a fiber optic by means of a steel grid. The active phase was excited by means of a high-intensity blue light-emitting diode. The light signal was modulated to avoid external interference. Fluorescence emission is detected by a low-cost photodiode. To avoid drifts in excitation light emission intensity, a ratiometric measurement was proposed. To perform such measurements, two fiber-optic measurement channels were used. One of them was employed to measure only the pH indicator fluorescent emission intensity. The second channel was employed to measure only the intensity of the excitation light reflected by the sensing phase. The ratio between both signals is only proportional to pH and proved to be independent of excitation light intensity. The sensor is useful over the pH range of 4-8, providing highly reliable results

Design of a Low-Cost Portable Potentiostat for Amperometric Biosensors

Computational intelligence techniques are used to approximate the nonlinear operation of LiFePO4 batteries using rule-based systems. In this paper, rule-based systems are not directly fitted to data, but comprise constructive blocks in a differential-equation-based dynamical model that is numerically integrated to infer battery voltage, charge, and temperature. The design methodology has been validated with three different LiFePO4 batteries, and the results were found to be more accurate than those of a selection of statistical models and state-of-the-art artificial intelligence techniques.

Design of a low-cost optical instrument for pH fluorescence measurements

Ongoing technological progress in electronic instrumentation triggered the development of an innovative, hands-on teaching program to help students toward a fuller understanding of recent changes in the field. This paper describes the different stages of a design project to teach electronic instrumentation to computer engineering students at the University of Oviedo, Gijo/spl acute/n, Spain. The project involves designing a weather station to measure the main meteorological variables and then displaying this information on a computer screen. Although this course is intended for nonspecialist students of electronics, it could easily be adapted to other syllabuses with minimum modification of the specifications. The course provides not only enhanced academic training but also increased student motivation, as students participate actively in all course activities and work in a team within which each student has specific responsibilities.

A Variable Effective Capacity Model for LiFePO 4 Traction Batteries Using Computational Intelligence Techniques.

This paper proposes a model for HID lamps based on equivalent conductance. Model equations have been solved at low and high frequency using a PSPICE. Model results show fairly agreement with experimental data.