Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles

Abstract—This paper describes the application of state-estimation techniques for the real-time prediction of the state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Specifically, approaches based on the well-known Kalman Filter (KF) and Extended Kalman Filter (EKF), are presented, using a generic cell model, to provide correction for offset, drift, and long-term state divergence—an unfortunate feature of more traditional coulomb-counting techniques. The underlying dynamic behavior of each cell is modeled using two capacitors (bulk and surface) and three resistors (terminal, surface, and end), from which the SoC is determined from the voltage present on the bulk capacitor. Although the structure of the model has been previously reported for describing the characteristics of lithium-ion cells, here it is shown to also provide an alternative to commonly employed models of lead-acid cells when used in conjunction with a KF to estimate SoC and an EKF to predict state-of-health (SoH). Measurements using real-time road data are used to compare the performance of conventional integration-based methods for estimating SoC with those predicted from the presented state estimation schemes. Results show that the proposed methodologies are superior to more traditional techniques, with accuracy in determining the SoC within 2% being demonstrated. Moreover, by accounting for the nonlinearities present within the dynamic cell model, the application of an EKF is shown to provide verifiable indications of SoH of the cell pack

State-of-charge and state-of-health prediction of lead-acid batteries for hybrid electric vehicles using non-linear observers

The paper describes the application of state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Approaches based on the extended Kalman filter (EKF) are presented to provide correction for offset, drift and state divergence - an unfortunate feature of more traditional coulomb-counting techniques. Experimental results are employed to demonstrate the relative attributes of the proposed methodolog

Sensorless control of deep-sea ROVs PMSMs excited by matrix converters

The paper reports the development of model-based sensorless control methodologies for driving PMSMs using matrix converters. In particular, experimental results show that observer-based state-estimation techniques normally employed for sensorless control of PMSMs using voltage source inverters (VSIs), can be readily exported to matrix converter counterparts with minimal additional computational overhead. Furthermore, zero speed start-up and speed reversal are experimentally demonstrated. Finally, the observer is designed to be fault tolerant such that upon detection of a broken terminal (phase fault), the PMSM remains operational and could be utilized to provide a limp-home capabilit

Observer techniques for estimating the state-of-charge and state-of-health of VRLABs for hybrid electric vehicles

The paper describes the application of observer-based state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Specifically, an approach based on the well-known Kalman filter, is employed, to estimate SoC, and the subsequent use of the EKF to accommodate model non-linearities to predict battery SoH. The underlying dynamic behaviour of each cell is based on a generic Randles' equivalent circuit comprising of two-capacitors (bulk and surface) and three resistors, (terminal, transfer and self-discharging). The presented techniques are shown to correct for offset, drift and long-term state divergence-an unfortunate feature of employing stand-alone models and more traditional coulomb-counting techniques. Measurements using real-time road data are used to compare the performance of conventional integration-based methods for estimating SoC, with those predicted from the presented state estimation schemes. Results show that the proposed methodologies are superior with SoC being estimated to be within 1% of measured. Moreover, by accounting for the nonlinearities present within the dynamic cell model, the application of an EKF is shown to provide verifiable indications of SoH of the cell pack

Is a 20 Kg Load Sufficient to Simulate Fatigue in Squat Jumps?

Abstract available in the Annual Coaches and Sport Science College

Chlamydia Pneumoniae CdsL Regulates CdsN ATPase Activity, and Disruption with a Peptide Mimetic Prevents Bacterial Invasion

Chlamydiae are obligate intracellular pathogens that likely require type III secretion (T3S) to invade cells and replicate intracellularly within a cytoplasmic vacuole called an inclusion body. Chlamydia pneumoniae possess a YscL ortholog, CdsL, that has been shown to interact with the T3S ATPase (CdsN). In this report we demonstrate that CdsL down-regulates CdsN enzymatic activity in a dose-dependent manner. Using Pepscan epitope mapping we identified two separate binding domains to which CdsL binds viz. CdsN221–229 and CdsN265–270. We confirmed the binding domains using a pull-down assay and showed that GST–CdsN221–270, which encompasses these peptides, co-purified with His–CdsL. Next, we used orthology modeling based on the crystal structure of a T3S ATPase ortholog from Escherichia coli, EscN, to map the binding domains on the predicted 3D structure of CdsN. The CdsL binding domains mapped to the catalytic domain of the ATPase, one in the central channel of the ATPase hexamer and one on the outer face. Since peptide mimetics have been used to disrupt essential protein interactions of the chlamydial T3S system and inhibit T3S-mediated invasion of HeLa cells, we hypothesized that if CdsL–CdsN binding is essential for regulating T3S then a CdsN peptide mimetic could be used to potentially block T3S and chlamydial invasion. Treatment of elementary body with a CdsN peptide mimetic inhibited C. pneumoniae invasion into HeLa cells in a dose-dependent fashion. This report represents the first use of Pepscan technology to identify binding domains for specific T3S proteins viz. CdsL on the ATPase, CdsN, and demonstrates that peptide mimetics can be used as anti-virulence factors to block bacterial invasion

Lightning strike damage resistance of carbon‐fiber composites with nanocarbon‐modified epoxy matrices

Carbon‐fiber reinforced polymer (CFRP) composites are replacing metal alloys in aerospace structures, but they can be vulnerable to lightning strike damage if not adequately protected due to the poor electrical conductivity of the polymeric matrix. In the present work, to improve the conductivity of the CFRP, two electrically conductive epoxy formulations were developed via the addition of 0.5 wt% of graphene nanoplatelets (GNPs) and a hybrid of 0.5 wt% of GNPs/carbon nanotubes (CNTs) at an 8:2 mass ratio. Unidirectional CFRP laminates were manufactured using resin‐infusion under flexible tooling (RIFT) and wet lay‐up (WL) processes, and subjected to simulated lightning strike tests. The electrical performance of the RIFT plates was far superior to that of the WL plates, independent of matrix modification, due to their greater carbon‐fiber volume fraction. The GNP‐modified panel made using RIFT demonstrated an electrical conductivity value of 8 S/cm. After the lightning strike test, the CFRP panel remains largely unaffected as no perforation occurs. Damage is limited to matrix degradation within the top ply at the point of impact and localized charring of the surface. The GNP‐modified panel showed a comparable level of resistance against lightning damage with the existing copper mesh technology, offering at the same time a 20% reduction in the structural weight. This indicates a feasible route to improve the lightning strike damage resistance of carbon‐fiber composites without the addition of extra weight, hence reducing fuel consumption but not safety

On the Stratospheric Chemistry of Midlatitude Wildfire Smoke

Massive Australian wildfires lofted smoke directly into the stratosphere in the austral summer of 2019/20. The smoke led to increases in optical extinction throughout the midlatitudes of the southern hemisphere that rivalled substantial volcanic perturbations. Previous studies have assumed that the smoke became coated with sulfuric acid and water and would deplete the ozone layer through heterogeneous chemistry on those surfaces, as is routinely observed following volcanic enhancements of the stratospheric sulfate layer. Here, observations of extinction and reactive nitrogen species from multiple independent satellites that sampled the smoke region are compared to one another and to model calculations. The data display a strong decrease in reactive nitrogen concentrations with increased aerosol extinction in the stratosphere, which is a known fingerprint for key heterogeneous chemistry on sulfate/H2O particles (specifically the hydrolysis of N2O5 to form HNO3). This chemical shift affects not only reactive nitrogen but also chlorine and reactive hydrogen species and is expected to cause midlatitude ozone layer depletion. Comparison of the model ozone to observations suggests that N2O5 hydrolysis contributed to reduced ozone, but additional chemical and/or dynamical processes are also important. These findings suggest that if wildfire smoke injection into the stratosphere increases sufficiently in frequency and magnitude as the world warms due to climate change, ozone recovery under the Montreal Protocol could be impeded, at least sporadically. Modeled austral midlatitude total ozone loss was about 1% in March 2020, which is significant compared to expected ozone recovery of about 1% per decade