ALBERT

Description: As the world moves toward greenhouse gas reduction, there is increasingly active work around Li-ion chemistry-based batteries as an energy source for electric vehicles (EVs), hybrid electric vehicles (HEVs) and smart grids. In these applications, the battery management system (BMS) requires an accurate online estimation of the state of charge (SOC) in a battery pack. This estimation is difficult, especially after substantial battery aging. In order to address this problem, this paper utilizes SOC estimation of Li-ion battery packs using a fuzzy-improved extended Kalman filter (fuzzy-IEKF) for Li-ion cells, regardless of their age. The proposed approach introduces a fuzzy method with a new class and associated membership function that determines an approximate initial value applied to SOC estimation. Subsequently, the EKF method is used by considering the single unit model for the battery pack to estimate the SOC for following periods of battery use. This approach uses an adaptive model algorithm to update the model for each single cell in the battery pack. To verify the accuracy of the estimation method, tests are done on a LiFePO4 aged battery pack consisting of 120 cells connected in series with a nominal voltage of 432 V.

Description: When the dimensions of polycrystalline structures become comparable to the average grain size, some reliability issues can be reported for the moving parts of inertial microelectromechanical systems (MEMS). Not only the overall behavior of the device turns out to be affected by a large scattering, but also the sensitivity to imperfections gets enhanced. In this work, through on-chip tests, we experimentally investigate the behavior of thin polysilicon samples using standard electrostatic actuation/sensing. The discrepancy between the target and actual responses of each sample has then been exploited to identify: (i) the overall stiffness of the film and, according to standard continuum elasticity, a morphology-based value of its Young’s modulus; (ii) the relevant over-etch induced by the fabrication process. To properly account for the aforementioned stochastic features at the micro-scale, the identification procedure has been based on particle filtering. A simple analytical reduced-order model of the moving structure has been also developed to account for the nonlinearities in the electrical field, up to pull-in. Results are reported for a set of ten film samples of constant slenderness, and the effects of different actuation mechanisms on the identified micromechanical features are thoroughly discussed.

Description: Anion exchange membranes are highly versatile and nowadays have many applications, ranging from water treatment to sensing materials. The preparation of anion exchange membranes (AEMs) from brominated poly(2,6-dimethyl-1,6-phenylene oxide) (BPPO) and methyl(diphenyl)phosphine (MDPP) for electrodialysis was performed. The physiochemical properties and electrochemical performance of fabricated membranes can be measured by changing MDPP contents in the membrane matrix. The influence of a quaternary phosphonium group associated with the removal of NaCl from water is discussed. The prepared membranes have ion exchange capacities (IEC) 1.09–1.52 mmol/g, water uptake (WR) 17.14%–21.77%, linear expansion ratio (LER) 7.96%–11.86%, tensile strength (TS) 16.66–23.97 MPa and elongation at break (Eb) 485.57%–647.98%. The prepared anion exchange membranes were employed for the electrodialytic removal of 0.1 M NaCl aqueous solution at a constant applied voltage. It is found that the reported membranes could be the promising candidate for NaCl removal via electrodialysis.

Description: The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs). CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed.

Description: Health monitoring of lightweight structures, like thin flexible plates, is of interest in several engineering fields. In this paper, a recursive Bayesian procedure is proposed to monitor the health of such structures through data collected by a network of optimally placed inertial sensors. As a main drawback of standard monitoring procedures is linked to the computational costs, two remedies are jointly considered: first, an order-reduction of the numerical model used to track the structural dynamics, enforced with proper orthogonal decomposition; and, second, an improved particle filter, which features an extended Kalman updating of each evolving particle before the resampling stage. The former remedy can reduce the number of effective degrees-of-freedom of the structural model to a few only (depending on the excitation), whereas the latter one allows to track the evolution of damage and to locate it thanks to an intricate formulation. To assess the effectiveness of the proposed procedure, the case of a plate subject to bending is investigated; it is shown that, when the procedure is appropriately fed by measurements, damage is efficiently and accurately estimated.

Description: We propose a novel cluster based cooperative spectrum sensing algorithm to save the wastage of energy, in which clusters are formed using fuzzy c-means (FCM) clustering and a cluster head (CH) is selected based on a sensor’s location within each cluster, its location with respect to fusion center (FC), its signal-to-noise ratio (SNR) and its residual energy. The sensing information of a single sensor is not reliable enough due to shadowing and fading. To overcome these issues, cooperative spectrum sensing schemes were proposed to take advantage of spatial diversity. For cooperative spectrum sensing, all sensors sense the spectrum and report the sensed energy to FC for the final decision. However, it increases the energy consumption of the network when a large number of sensors need to cooperate; in addition to that, the efficiency of the network is also reduced. The proposed algorithm makes the cluster and selects the CHs such that very little amount of network energy is consumed and the highest efficiency of the network is achieved. Using the proposed algorithm maximum probability of detection under an imperfect channel is accomplished with minimum energy consumption as compared to conventional clustering schemes.

Description: The use of Space-Time Processing (STP) in Global Navigation Satellite System (GNSS) applications is gaining significant attention due to its effectiveness for both narrowband and wideband interference suppression. However, the resulting distortion and bias on the cross correlation functions due to space-time filtering is a major limitation of this technique. Employing the steering vector of the GNSS signals in the filter structure can significantly reduce the distortion on cross correlation functions and lead to more accurate pseudorange measurements. This paper proposes a two-stage interference mitigation approach in which the first stage estimates an interference-free subspace before the acquisition and tracking phases and projects all received signals into this subspace. The next stage estimates array attitude parameters based on detecting and employing GNSS signals that are less distorted due to the projection process. Attitude parameters enable the receiver to estimate the steering vector of each satellite signal and use it in the novel distortionless STP filter to significantly reduce distortion and maximize Signal-to-Noise Ratio (SNR). GPS signals were collected using a six-element antenna array under open sky conditions to first calibrate the antenna array. Simulated interfering signals were then added to the digitized samples in software to verify the applicability of the proposed receiver structure and assess its performance for several interference scenarios.

Description: In the present work, the results are reported of the energy and exergy analyses of three biomass-related processes for electricity generation: the biomass gasification integrated externally fired combined cycle, the biomass gasification integrated dual-fuel combined cycle, and the biomass gasification integrated post-firing combined cycle. The energy efficiency for the biomass gasification integrated post-firing combined cycle is 3% to 6% points higher than for the other cycles. Although the efficiency of the externally fired biomass combined cycle is the lowest, it has an advantage in that it only uses biomass. The energy and exergy efficiencies are maximized for the three configurations at particular values of compressor pressure ratios, and increase with gas turbine inlet temperature. As pressure ratio increases, the mass of air per mass of steam decreases for the biomass gasification integrated post-firing combined cycle, but the pressure ratio has little influence on the ratio of mass of air per mass of steam for the other cycles. The gas turbine exergy efficiency is the highest for the three configurations. The combustion chamber for the dual-fuel cycle exhibits the highest exergy efficiency and that for the post-firing cycle the lowest. Another benefit of the biomass gasification integrated externally fired combined cycle is that it exhibits the highest air preheater and heat recovery steam generator exergy efficiencies.

Description: Biomass energy and especially biofuels produced by biomass gasification are clean and renewable options for power plants. Also, on hot days the performance of gas turbines decreases substantially, a problem that can be mitigated by fog cooling. In the present paper, a biomass-integrated fogging steam injected gas turbine cycle is analyzed with energy and exergy methods. It is observed that (1) increasing the compressor pressure ratio raises the air flow rate in the plant but reduces the biomass flow rate; (2) increasing the gas turbine inlet temperature decreases the air and biomass flow rates; (3) increasing the compressor pressure ratio raises the energy and exergy efficiencies, especially at lower pressure ratios; (4) increasing the gas turbine inlet temperature raises both efficiencies; and (5) overspray increases the energy efficiency and net cycle power slightly. The gas turbine exhibits the highest exergy efficiency of the cycle components and the combustor the lowest. A comparison of the cycle with similar cycles fired by natural gas and differently configured cycles fueled by biomass shows that the cycle with natural gas firing has an energy efficiency 18 percentage points above the biomass fired cycle, and that steam injection increases the energy efficiency about five percentage points relative to the cycle without steam injection. Also, the influence of steam injection on energy efficiency is more significant than fog cooling.

Description: Zirconia-toughened alumina (ZTA) using yttria-stabilised zirconia is a good option for ceramic-ceramic bearing couples for hip joint replacement. Gelcasting is a colloidal processing technique capable of producing complex products with a range of dimensions and materials by a relatively low-cost production process. Using gelcasting, ZTA samples were prepared, optimising the stages of fabrication, including slurry preparation with varying solid loadings, moulding and de-moulding, drying and sintering. Density, hardness, fracture toughness, flexural strength and grain size were observed relative to slurry solid loadings between 58 and 62 vol. %, as well as sintering temperatures of 1550 °C and 1650 °C. Optimal conditions found were plastic mould, 4000 g/mol PEG with 30 vol. % concentration, 61% solid loading and Ts = 1550 °C. ZTA samples of high density (maximum 99.1%), high hardness (maximum 1902 HV), high fracture toughness (maximum 5.43 MPa m1/2) and high flexural strength (maximum 618 MPa) were successfully prepared by gelcasting and pressureless sintering.