A novel mechanical analogy based battery model for SoC estimation using a multi-cell EKF

The future evolution of technological systems dedicated to improve energy efficiency will strongly depend on effective and reliable Energy Storage Systems, as key components for Smart Grids, microgrids and electric mobility. Besides possible improvements in chemical materials and cells design, the Battery Management System is the most important electronic device that improves the reliability of a battery pack. In fact, a precise State of Charge (SoC) estimation allows the energy flows controller to exploit better the full capacity of each cell. In this paper, we propose an alternative definition for the SoC, explaining the rationales by a mechanical analogy. We introduce a novel cell model, conceived as a series of three electric dipoles, together with a procedure for parameters estimation relying only on voltage measures and a given current profile. The three dipoles represent the quasi-stationary, the dynamics and the istantaneous components of voltage measures. An Extended Kalman Filer (EKF) is adopted as a nonlinear state estimator. Moreover, we propose a multi-cell EKF system based on a round-robin approach to allow the same processing block to keep track of many cells at the same time. Performance tests with a prototype battery pack composed by 18 A123 cells connected in series show encouraging results.Comment: 8 page, 12 figures, 1 tabl

Vanadium redox flow batteries: Potentials and challenges of an emerging storage technology

open4noIn this paper an overview of Vanadium Redox Flow Battery technologies, architectures, applications and power electronic interfaces is given. These systems show promising features for energy storage in smart grid applications, where the intermittent power produced by renewable sources must meet strict load requests and economical opportunities. This paper reviews the vanadium-based technology for redox flow batteries and highlights its strengths and weaknesses, outlining the research lines that aim at taking it to full commercial success.openSpagnuolo, Giovanni, Guarnieri, Massimo; Mattavelli, Paolo; Petrone, Giovanni;Guarnieri, Massimo; Mattavelli, Paolo; Petrone, Giovanni; Spagnuolo, Giovann

Electric vehicle battery parameter identification and SOC observability analysis: NiMH and Li-S case studies

In this study, a framework is proposed for battery model identification to be applied in electric vehicle energy storage systems. The main advantage of the proposed approach is having capability to handle different battery chemistries. Two case studies are investigated: nickel-metal hydride (NiMH), which is a mature battery technology, and Lithium-Sulphur (Li-S), a promising next-generation technology. Equivalent circuit battery model parametrisation is performed in both cases using the Prediction-Error Minimization (PEM) algorithm applied to experimental data. The use of identified parameters for battery state-of-charge (SOC) estimation is then discussed. It is demonstrated that the set of parameters needed can change with a different battery chemistry. In the case of NiMH, the battery’s open circuit voltage (OCV) is adequate for SOC estimation. However, Li-S battery SOC estimation can be challenging due to the chemistry’s unique features and the SOC cannot be estimated from the OCV-SOC curve alone because of its flat gradient. An observability analysis demonstrates that Li-S battery SOC is not observable using the common state-space representations in the literature. Finally, the problem’s solution is discussed using the proposed framework

A novel delta current method for transport stoichiometry estimation.

BackgroundThe ion transport stoichiometry (q) of electrogenic transporters is an important determinant of their function. q can be determined by the reversal potential (Erev) if the transporter under study is the only electrogenic transport mechanism or a specific inhibitor is available. An alternative approach is to calculate delta reversal potential (ΔErev) by altering the concentrations of the transported substrates. This approach is based on the hypothesis that the contributions of other channels and transporters on the membrane to Erev are additive. However, Erev is a complicated function of the sum of different conductances rather than being additive.ResultsWe propose a new delta current (ΔI) method based on a simplified model for electrogenic secondary active transport by Heinz (Electrical Potentials in Biological Membrane Transport, 1981). ΔI is the difference between two currents obtained from altering the external concentration of a transported substrate thereby eliminating other currents without the need for a specific inhibitor. q is determined by the ratio of ΔI at two different membrane voltages (V1 and V2) where q = 2RT/(F(V2 -V1))ln(ΔI2/ΔI1) + 1. We tested this ΔI methodology in HEK-293 cells expressing the elctrogenic SLC4 sodium bicarbonate cotransporters NBCe2-C and NBCe1-A, the results were consistent with those obtained with the Erev inhibitor method. Furthermore, using computational simulations, we compared the estimates of q with the ΔErev and ΔI methods. The results showed that the ΔErev method introduces significant error when other channels or electrogenic transporters are present on the membrane and that the ΔI equation accurately calculates the stoichiometric ratio.ConclusionsWe developed a ΔI method for estimating transport stoichiometry of electrogenic transporters based on the Heinz model. This model reduces to the conventional reversal potential method when the transporter under study is the only electrogenic transport process in the membrane. When there are other electrogenic transport pathways, ΔI method eliminates their contribution in estimating q. Computational simulations demonstrated that the ΔErev method introduces significant error when other channels or electrogenic transporters are present and that the ΔI equation accurately calculates the stoichiometric ratio. This new ΔI method can be readily extended to the analysis of other electrogenic transporters in other tissues

Failure analysis of some Toyota Prius battery packs and potential for recovery

The Toyota Prius battery pack consists of 38 individual battery blades, each blade contains 6 NiMH cells in series. This means that each pack contains 228 NiMH cells. Each cell has the potential to fail. This report investigates the mode of failure of Prius battery packs by first analysing a number of packs in the lab, and then road testing them in a Toyota Prius. The analysis of the battery packs shows that some packs had aged “linearly”, that is in a balanced manner, such that the state of health of all blades remained similar. However, in other packs discrete blades had significantly different states of health. A pack that consists of cells that are matched in both state of health and state of charge delivers the best performance. The research also showed that the worst cell in the pack determines the overall pack performance. This was demonstrated by substituting reducedcapacity or short-circuited blades into a functioning battery pack. A vehicle with a pack consisting of 37 2400 mAh battery blades and one 1200 mAh battery blade was only able to drive 1.3 km in Electric Vehicle mode, as opposed to 2.6 km with a pack consisting of 38 2400 mAh battery blades