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

Relaxation time of the topological T1 process in a two-dimensional foam

The elementary topological T1 process in a two-dimensional foam corresponds to the "flip" of one soap film with respect to the geometrical constraints. From a mechanical point of view, this T1 process is an elementary relaxation process through which the entire structure of an out-of-equilibrium foam evolves. The dynamics of this elementary relaxation process has been poorly investigated and is generally neglected during simulations of foams. We study both experimentally and theoretically the T1 dynamics in a dry two-dimensional foam. We show that the dynamics is controlled by the surface viscoelastic properties of the soap films (surface shear plus dilatational viscosity, ms+k, and Gibbs elasticity e), and is independent of the shear viscosity of the bulk liquid. Moreover, our approach illustrates that the dynamics of T1 relaxation process provides a convenient tool for measuring the surface rheological properties: we obtained e = 32+/-8 mN/m and ms+k = 1.3+/-0.7 mPa.m.s for SDS, and e = 65+/-12 mN/m and ms+k = 31+/-12 mPa.m.s for BSA, in good agreement with values reported in the literature

Quantum coherence in a ferromagnetic metal: time-dependent conductance fluctuations

Quantum coherence of electrons in ferromagnetic metals is difficult to assess experimentally. We report the first measurements of time-dependent universal conductance fluctuations in ferromagnetic metal (Ni$_{0.8}$Fe$_{0.2}$) nanostructures as a function of temperature and magnetic field strength and orientation. We find that the cooperon contribution to this quantum correction is suppressed, and that domain wall motion can be a source of coherence-enhanced conductance fluctuations. The fluctuations are more strongly temperature dependent than those in normal metals, hinting that an unusual dephasing mechanism may be at work.Comment: 5 pages, 4 figure