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

Nanoengineered Curie Temperature in Laterally-Patterned Ferromagnetic Semiconductor Heterostructures

We demonstrate the manipulation of the Curie temperature of buried layers of the ferromagnetic semiconductor (Ga,Mn)As using nanolithography to enhance the effect of annealing. Patterning the GaAs-capped ferromagnetic layers into nanowires exposes free surfaces at the sidewalls of the patterned (Ga,Mn)As layers and thus allows the removal of Mn interstitials using annealing. This leads to an enhanced Curie temperature and reduced resistivity compared to unpatterned samples. For a fixed annealing time, the enhancement of the Curie temperature is larger for narrower nanowires.Comment: Submitted to Applied Physics Letters (minor corrections

Kynurenine pathway inhibition reduces central nervous system inflammation in a model of human African trypanosomiasis

Human African trypanosomiasis, or sleeping sickness, is caused by the protozoan parasites <i>Trypanosoma brucei rhodesiense</i> or <i>Trypanosoma brucei gambiense</i>, and is a major cause of systemic and neurological disability throughout sub-Saharan Africa. Following early-stage disease, the trypanosomes cross the blood-brain barrier to invade the central nervous system leading to the encephalitic, or late stage, infection. Treatment of human African trypanosomiasis currently relies on a limited number of highly toxic drugs, but untreated, is invariably fatal. Melarsoprol, a trivalent arsenical, is the only drug that can be used to cure both forms of the infection once the central nervous system has become involved, but unfortunately, this drug induces an extremely severe post-treatment reactive encephalopathy (PTRE) in up to 10% of treated patients, half of whom die from this complication. Since it is unlikely that any new and less toxic drug will be developed for treatment of human African trypanosomiasis in the near future, increasing attention is now being focussed on the potential use of existing compounds, either alone or in combination chemotherapy, for improved efficacy and safety. The kynurenine pathway is the major pathway in the metabolism of tryptophan. A number of the catabolites produced along this pathway show neurotoxic or neuroprotective activities, and their role in the generation of central nervous system inflammation is well documented. In the current study, Ro-61-8048, a high affinity kynurenine-3-monooxygenase inhibitor, was used to determine the effect of manipulating the kynurenine pathway in a highly reproducible mouse model of human African trypanosomiasis. It was found that Ro-61-8048 treatment had no significant effect (P = 0.4445) on the severity of the neuroinflammatory pathology in mice during the early central nervous system stage of the disease when only a low level of inflammation was present. However, a significant (P = 0.0284) reduction in the severity of the neuroinflammatory response was detected when the inhibitor was administered in animals exhibiting the more severe, late central nervous system stage, of the infection. <i>In vitro</i> assays showed that Ro-61-8048 had no direct effect on trypanosome proliferation suggesting that the anti-inflammatory action is due to a direct effect of the inhibitor on the host cells and not a secondary response to parasite destruction. These findings demonstrate that kynurenine pathway catabolites are involved in the generation of the more severe inflammatory reaction associated with the late central nervous system stages of the disease and suggest that Ro-61-8048 or a similar drug may prove to be beneficial in preventing or ameliorating the PTRE when administered as an adjunct to conventional trypanocidal chemotherap

Field Dependent Phase Diagram of the Quantum Spin Chain (CH3)2NH2CuCl3

Although (CH3)2NH2CuCl3 (MCCL) was first examined in the 1930's [1], there are open questions regarding the magnetic dimensionality and nature of the magnetic properties. MCCL is proposed to be a S=1/2 alternating ferromagnetic antiferromagnetic spin chain alternating along the crystalline a-axis [2,3]. Proposed ferromagnetic (JFM =1.3 meV) and antiferromagnetic (JAFM =1.1 meV) exchange constants make this system particularly interesting for experimental study. Because JFM and JAFM are nearly identical, the system should show competing behavior between S=1/2 (AFM) and S=1(FM) effects. We report low temperature magnetic field dependent susceptibility, chi(H), and specific heat, Cp, of MCCL. These provide an initial magnetic-field versus temperature phase diagram. A zero-field phase transition consistent with long range magnetic order is observed at T=0.9 K. The transition temperature can be reduced via application of a magnetic field. We also present comparisons to a FM/AFM dimer model that accounts for chi(T,H=0) and Cp(H,T).Comment: 2 pages, 1 figure included in text. Submitted to proceedings of 24th International Conference on Low Temperature Physics, August 200

Observing Lense-Thirring Precession in Tidal Disruption Flares

When a star is tidally disrupted by a supermassive black hole (SMBH), the streams of liberated gas form an accretion disk after their return to pericenter. We demonstrate that Lense-Thirring precession in the spacetime around a rotating SMBH can produce significant time evolution of the disk angular momentum vector, due to both the periodic precession of the disk and the nonperiodic, differential precession of the bound debris streams. Jet precession and periodic modulation of disk luminosity are possible consequences. The persistence of the jetted X-ray emission in the Swift J164449.3+573451 flare suggests that the jet axis was aligned with the spin axis of the SMBH during this event.Comment: 4 pages, 4 figures. Accepted for publication in Physical Review Letters. Minor changes made to match proof

An epidemiological approach to simulation-based analysis of large building stocks

This paper describes a novel approach to building stock energy modelling: Individual building simulation models are autogenerated for each building in the stock, and the resulting set of virtual buildings is selectively sampled, simulated and analysed in much the same way that an epidemiologist might study a population through surveys and statistical analysis. A conceptual and software framework is described, along with initial case study results for a London borough