• Energy Research

Abstract The relative permittivity of diesel fossil fuel and blends with biodiesel from soybean, in the full range from pure diesel to 100% biodiesel, was determined at temperatures between 298.0 K and 333.0 K (controlled within ±0.1 K), using an airtight cell. Measurements were made in the frequency range from 1 kHz to 100 kHz; this frequency range is suitable for the use of low-cost, portable equipment and also for the development of automotive sensors. The relative uncertainty of the measurements was below 1%. Experimental values of permittivity were satisfactorily fitted to a simple model as a function of temperature and composition. The RMS uncertainty of the fitting was 1.2%. The model parameters were determined from experimental results and verified by multiple regression analysis, with very good agreement. In addition, a model was proposed to estimate the composition of diesel/biodiesel blends from permittivity and temperature measurements. The parameters of the model were obtained by a multiple regression analysis; the RMS uncertainty of the composition estimation was below 2.5%. The results presented in this work describe accurately the dependence of the permittivity of diesel fuel with temperature and also validate and extend previously reported models for biodiesel-rich blends with diesel fossil fuel, allowing the estimation in the full composition range with good accuracy.

Abstract The relative permittivity of biodiesel-rich blends, from pure biodiesel to 50% blends with diesel fossil fuel, were determined at temperatures between 303.0 K and 343.0 K (controlled within ±0.1 K). Measurements were made on biodiesel from soybean in the frequency range from 20 kHz to 2 MHz; the relative measurement uncertainty was below 0.3%. At each composition, experimental values fit very satisfactorily to a linear dependence on temperature. Similarly, at constant temperature, permittivity depends linearly on biodiesel content. From these results, a simple model was proposed to estimate the permittivity of the samples as a function of biodiesel content and temperature. The model parameters were determined from a multiple regression analysis. The RMS uncertainty of the fitting was below 0.7%, for blends with biodiesel concentration ⩾50%. The model was inverted to determine the biodiesel content from permittivity and temperature measurements. The parameters of the inverted model were checked by a multiple regression analysis and the RMS uncertainty of the content determination was below 1.5%. The results presented in this work show that dielectric measurements are a valuable tool for biodiesel content determination in rich-biodiesel blends from vegetable oils with diesel fossil fuel.

Abstract The relative permittivity of soybean biodiesel/soybean oil blends was determined in the full range of composition, at temperatures between 298 K and 343 K. Measurements were carried out at frequencies between 1 kHz and 100 kHz, using a broadband cell. The relative RMS uncertainty of the dielectric measurements was below 1%. For all the studied samples, the relative permittivity decreases with temperature and increases with biodiesel content, in both cases linearly. From the experimental results, a model was developed to estimate the permittivity of the blends as a function of composition and temperature. The RMS uncertainty of the estimation is less than ±0.01. Furthermore, the blend composition was modeled as a function of permittivity and temperature. The RMS uncertainty of the estimation was below 9% for temperatures between 298 K and 313 K.

Abstract The relative permittivity of gasoline/methanol blends was determined at 100 kHz, in the full range of composition, at temperatures between 296 K and 323 K. From experimental results, permittivity is fitted to a third degree polynomial on methanol content, and, at each composition, the permittivity of blends decreases linearly with temperature. From the analysis of the experimental data, a model is developed to estimate the relative permittivity as a function of blend composition and temperature. The model fitting is very satisfactory, with an RMS absolute uncertainty of 0.43. The parameters of the model are determined from experimental data for pure gasoline and methanol, and were checked by means of a non-linear fitting using all the experimental data, with very good agreement. Another model is proposed to estimate the composition of blends from temperature and permittivity measurements. From the comparison to experimental data, the RMS absolute uncertainty of the estimation is below 2%.

AbstractBiodiesel is widely used pure or mixed with diesel fossil fuel in diesel engines. Standards for determining biodiesel quality establish limits for the values of several physicochemical properties. However, the procedures to determine many properties are time‐consuming and demand specialized personnel and expensive equipment. Other methods to characterize biodiesel, such as electrical methods, are particularly interesting. Measurements of electrical properties (permittivity and conductivity) give valuable information about biodiesel, its feedstocks, and its blends with fossil fuel diesel, and solve the usual cost and time drawbacks. This work aims to present a thorough and systematic review of the literature on applications of electrical properties measurements of biodiesel, its feedstocks, and mixtures with other fuels. An overview of the experimental data, typical ranges of values, prediction models, and applications is presented and analyzed in detail, emphasizing blends of biodiesel with fossil fuel diesel. Correlations with important properties (kinematic viscosity, methanol content) are reviewed. Applications include transesterification monitoring, biodiesel aging, the detection of contaminants and electromagnetic heating. This research aimed to determine whether electrical properties are a valuable tool for the biodiesel industry, and what applications may be realized in light of current scientific development. It was determined that, in the current state of research, permittivity measurements could be used to accurately determine the amount of diesel and biodiesel in mixtures. © 2023 Society of Industrial Chemistry and John Wiley & Sons Ltd.

Abstract Electrical properties (permittivity and conductivity) and speed of sound were determined in commercial vegetable oils from sunflower, corn, soybean, grape, cotton, olive, canola and chia, and in biodiesel from these oils. Electrical properties were measured in the frequency range from 20 Hz to 2 MHz at temperatures between 300 K and 343 K. The calibration uncertainty of the measuring system was below 1%. The speed of sound was determined at the frequencies of 1.53 MHz, 5.66 MHz and 9.43 MHz. The uncertainty of the results was below 0.05%. In all the measurements in this work, the temperature of the samples was stabilized within ±0.1 K. The experimental data for the speed of sound and permittivity of vegetable oils and biodiesel samples fit very satisfactorily to a linear dependence with temperature, whereas the conductivities follow an Arrhenius law. In all the samples, the fitting parameters of the real part of the relative permittivity, the activation energy of the conductivity and the speed of sound allow to distinguish between the vegetable oil and the biodiesel obtained from it. Within the temperature range studied in this work, a linear correlation is found between the speed of sound and the permittivity of vegetable oils and biodiesel.

Abstract Kinematic viscosity and relative permittivity were determined in blends of soybean biodiesel with diesel fossil fuel in the full range of composition at temperatures between 298 K and 318 K (±0.1 K). The kinematic viscosity as a function of temperature fits very satisfactorily to an Arrhenius dependence at all the compositions. The activation energy of this process depends linearly on blend composition. Also, at constant temperature, the kinematic viscosity increases exponentially with biodiesel content. From the analysis of the experimental data, a model is proposed to estimate the kinematic viscosity of blends of unknown composition as a function of permittivity and temperature. Interestingly, the model parameters depend only on the properties of the pure fuels. The fitting to experimental data is very satisfactory; the RMS uncertainty is lower than 0.02 mm 2 s −1 .

Abstract Kinematic viscosity and electrical properties (permittivity and electrical conductivity) of biodiesel samples were determined in the temperature range between 298 K and 343 K. The samples were produced from sunflower, olive, canola, corn, soybean, grapeseed and jatropha vegetable oils. Electrical measurements were carried out in the frequency range from 20 Hz to 2 MHz. From the analysis of the experimental results, two models were developed to estimate the kinematic viscosity from electrical properties. The first model estimates the kinematic viscosity from relative permittivity measurements, with an RMS uncertainty below 0.4 mm2/s for all the samples. The second model allows the estimation of the kinematic viscosity from conductivity measurements, with an RMS uncertainty below 0.07 mm2/s for all the samples. The models and procedures presented in this work reduce the measuring time for kinematic viscosity from several minutes to a few seconds. The results are relevant for biodiesel characterization, on-line viscosity monitoring systems, and in measurements where time is prioritized over accuracy. Moreover, a power law scaling was found relating kinematic viscosity and electrical conductivity. This result is relevant for the study of processes that depend on these transport properties, such as flow electrification. For the samples studied, the fitted value of the power law exponent is - 0.67 ± 0.02 .

Abstract Electrical properties have gained interest in biofuels applications due to advances in radio frequency and microwave processing and characterization of biodiesel. In those applications, sensors play a key role since the accurate measurement of electrical properties is needed. This work presents the design, construction and characterization of a broadband (1 kHz to 100 MHz) permittivity sensor for biodiesel and blends. The sensor was characterized in the temperature range from 293 K to 343 K in the full intended frequency range. The sensor is apt for industrial use, inexpensive, and easy to build and it has very low electrical losses. For low permittivity substances the measurement uncertainty is below 1%, up to 100 MHz.