With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions about the performance of lithium-ion (Li-ion) batteries in the Boeing 787 have confirmed so far that, while battery technology is growing very quickly, developing cells with higher power and energy densities, it is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable, and cost-efficient solution. The specific characteristics and needs of the smart grid and EVs, such as deep charge/discharge protection and accurate state-of-charge (SOC) and state-of-health (SOH) estimation, intensify the need for a more efficient BMS. The BMS should contain accurate algorithms to measure and estimate the functional status of the battery and, at the same time, be equipped with state-of-the-art mechanisms to protect the battery from hazardous and inefficient operating conditions.

Real-time estimation of the state of charge (SOC) of the battery is a crucial need in the growing fields of plug-in hybrid electric vehicles and smart grid applications. The accuracy of the estimation algorithm directly depends on the accuracy of the model used to describe the characteristics of the battery. Considering a resistance-capacitance (RC)-equivalent circuit to model the battery dynamics, we use a piecewise linear approximation with varying coefficients to describe the inherently nonlinear relationship between the open-circuit voltage (V_OC) and the SOC of the battery. Several experimental test results on lithium (Li)-polymer batteries show that not only do the V_OC-SOC relationship coefficients vary with the SOC and charging/discharging rates but also the RC parameters vary with them as well. The moving window least squares parameter-identification technique was validated by both data obtained from a simulated battery model and experimental data. The necessity of updating the parameters is evaluated using observers with updating and nonupdating parameters. Finally, the SOC coestimation method is compared with the existing well-known SOC estimation approaches in terms of performance and accuracy of estimation.

The battery is a fundamental component of electric vehicles, which represent a step forward towards sustainable mobility. Lithium chemistry is now acknowledged as the technology of choice for energy storage in electric vehicles. However, several research points are still open. They include the best choice of the cell materials and the development of electronic circuits and algorithms for a more effective battery utilization. This paper initially reviews the most interesting modeling approaches for predicting the battery performance and discusses the demanding requirements and standards that apply to ICs and systems for battery management. Then, a general and flexible architecture for battery management implementation and the main techniques for state-of-charge estimation and charge balancing are reported. Finally, we describe the design and implementation of an innovative BMS, which incorporates an almost fully-integrated active charge equalizer.

We experimentally investigate the benefits of a new optical pulse coding technique for long-range, meter and submeter scale Raman-based distributed temperature sensing on standard single-mode optical fibers. The proposed scheme combines a low-repetition-rate quasi-periodic pulse coding technique with the use of standard high-power fiber lasers operating at $1550\mathrm{nm}$, allowing for what we believe is the first long-range distributed temperature measurement over single-mode fibers (SMFs). We have achieved $1\mathrm{m}$ spatial resolution over $26\mathrm{km}$ of SMF, attaining $3°\mathrm{C}$ temperature resolution within $30\mathrm{s}$ measurement time.

The charge stored in series-connected lithium batteries needs to be well equalized between the elements of the series. We present here an innovative lithium-battery cell-to-cell active equalizer capable of moving charge between series-connected cells using a super-capacitor as an energy tank. The system temporarily stores the charge drawn from a cell in the super-capacitor, then the charge is moved into another cell without wasting energy as it happens in passive equalization. The architecture of the system which employs a digitally-controlled switching converter is compared with the state of the art, then fully investigated, together with the methodology used in its design. The performance of the system is described by presenting and discussing the experimental results of laboratory tests. The most innovative and attractive aspect of the proposed system is its very high efficiency, which is over 90%.