Run-to-Run Control for Active Balancing of Lithium Iron Phosphate Battery Packs

\ua9 1986-2012 IEEE. Lithium iron phosphate battery packs are widely employed for energy storage in electrified vehicles and power grids. However, their flat voltage curves rendering the weakly observable state of charge are a critical stumbling block for charge equalization management. This paper focuses on the real-time active balancing of series-connected lithium iron phosphate batteries. In the absence of accurate in situ state information in the voltage plateau, a balancing current ratio (BCR) based algorithm is proposed for battery balancing. Then, BCR-based and voltage-based algorithms are fused, responsible for the balancing task within and beyond the voltage plateau, respectively. The balancing process is formulated as a batch-based run-to-run control problem, as the first time in the research area of battery management. The control algorithm acts in two timescales, including timewise control within each batch run and batchwise control at the end of each batch. Hardware-in-the-loop experiments demonstrate that the proposed balancing algorithm is able to release 97.1% of the theoretical capacity and can improve the capacity utilization by 5.7% from its benchmarking algorithm. Furthermore, the proposed algorithm can be coded in C language with the binary code in 118 328 bytes only and, thus, is readily implementable in real time

Aging trajectory prediction for lithium-ion batteries via model migration and Bayesian Monte Carlo method

This paper develops a new prediction method for the aging trajectory of lithium-ion batteries with significantly reduced experimental tests. This method is driven by data collected from two types of battery operation modes. The first type is accelerated aging tests that are performed under stress factors, such as overcharging, over-discharging and large current rates, and cover most of the battery lifespan. In the second operation mode, the same kinds of cells are aged at normal speeds to generate a partial aging profile. An accelerated aging model is developed based on the first type of data and is then migrated as a new model to describe the normal-speed aging behavior. Under the framework of Bayesian Monte Carlo algorithms, the new model is parameterized based on the second type of data and is used for prediction of the remaining battery aging trajectory. The proposed prediction method is validated on three types of commercial batteries and also compared with two benchmark algorithms. The sensitivity of results to the number of cycles is investigated for both modes. Illustrative results demonstrate that based on the normal-speed aging data collected in the first 30 cycles, the proposed method can predict the entire aging trajectories (up to 500 cycles) at a root-mean-square error of less than 2.5% for all considered scenarios. When only using the first five-cycle data for model training, such a prediction error is bounded by 5% for aging trajectories of all the tested batteries

Design of Lumped Disturbance Observer in Current Loop of IPMSM Based on Recursive Integral Sliding Mode Surface

To overcome the problem of current control effect being reduced by unideal factors in a motor control system, such as motor parameter variation, inverter dead time, nonlinearity of the system, etc., a sliding mode disturbance observer for an interior permanent magnet synchronous motor is proposed in this paper. The model of an interior permanent magnet synchronous motor with unideal factors is designed, and the unideal factors are unified into lumped disturbances of motor stator voltage. Then, the observer for lumped disturbance is designed. A recursive integral sliding surface is used to replace the terminal sliding surface to avoid the noise sensitivity and singularity problem of the traditional terminal sliding mode observer. The observer can estimate the lumped disturbance of the current loop without relying on the accurate system model in finite time. Moreover, the structure of the current loop does not need to be adjusted while using the observer to observe and compensate for disturbances. Experiments are carried out to verify the effectiveness of the proposed observer

A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging

Temperature and cell aging are two major factors that influence the reliability and safety of Li-ion batteries. A general battery model considering both temperature and degradation is often difficult to develop, given the fact that there are many different types of cells with different shapes and/or internal chemical components. In response, a migration-based framework is proposed in this paper for battery modeling, in which the effects of temperature and aging are treated as uncertainties. An accurate model for a fresh cell is established first and then migrated to the degraded batteries through a Bayes Monte Carlo method. Experiments are carried out on both LiFePO4 batteries and Li(Ni1/3Co1/3Mn1/3) O2 batteries under various ambient temperatures and aging levels. The results indicate that the typical voltage prediction error can be limited within \ub120 mV, for the cases of temperature change up to 40 \ub0C, and capacity degradation up to 20%. The proposed method paves ways to an effective battery management and energy control for electric vehicles or micro grid applications

Preparation of Ultrahigh Molecular Weight Polyethylene/Graphene Nanocomposite In situ Polymerization via Spherical and Sandwich Structure Graphene/Sio2 Support

Abstract Reduced graphene oxide/SiO2 (RGO/SiO2) serving as a novel spherical support for Ziegler-Natta (Z-N) catalyst is reported. The surface and interior of the support has a porous architecture formed by RGO/SiO2 sandwich structure. The sandwich structure is like a brick wall coated with a graphene layer of concreted as skeleton which could withstand external pressures and endow the structure with higher support stabilities. After loading the Z-N catalyst, the active components anchor on the surface and internal pores of the supports. When the ethylene molecules meet the active centers, the molecular chains grow from the surface and internal catalytic sites in a regular and well-organized way. And the process of the nascent molecular chains filled in the sandwich structure polymerization could ensure the graphene disperse uniformly in the polymer matrix. Compared with traditional methods, the porous spherical graphene support of this strategy has far more advantages and could maintain an intrinsic graphene performance in the nanocomposites

Chemical inhibition of Arabidopsis PIN-FORMED auxin transporters by the anti-inflammatory drug naproxen

The phytohormone auxin plays central roles in many growth and developmental processes in plants. Development of chemical tools targeting the auxin pathway is useful for both plant biology and agriculture. Here we reveal that naproxen, a synthetic compound with anti-inflammatory activity in humans, acts as an auxin transport inhibitor targeting PIN-FORMED (PIN) transporters in plants. Physiological experiments indicate that exogenous naproxen treatment affects pleiotropic auxin-regulated developmental processes. Additional cellular and biochemical evidence indicates that naproxen suppresses auxin transport, specifically PIN-mediated auxin efflux. Moreover, biochemical and structural analyses confirm that naproxen binds directly to PIN1 protein via the same binding cavity as the indole-3-acetic acid substrate. Thus, by combining cellular, biochemical, and structural approaches, this study clearly establishes that naproxen is a PIN inhibitor and elucidates the underlying mechanisms. Further use of this compound may advance our understanding of the molecular mechanisms of PIN-mediated auxin transport and expand our toolkit in auxin biology and agriculture

Performance Evolution of Alkylation Graphene Oxide Reinforcing High-Density Polyethylene

Alkylated graphene oxide (MGO) was rapidly prepared by a reverse extraction technology in aqueous solution using amphoteric surfactants (LAO). The MGO has an excellent lipophilicity and stability in the air atmosphere. After being incorporated in high-density polyethylene (HDPE) by solution compounding, the HDPE/MGO composites exhibited an obvious enhancement in comprehensive properties of composites, relying on the uniform dispersion and the strong interfacial interaction between MGO and HDPE. The typical and abnormal behaviors of the HDPE/MGO in mechanical and physical properties are systematically analyzed and discussed. Moreover, it is found that the critical intensity ratio of <i>I</i>_CH2/<i>I</i>_CC/C–C in Raman spectrum corresponding to the electric percolation threshold of HDPE/MGO is about 1, which is still well established in PP/MGO composites

Robust and Antibacterial Polymer/Mechanically Exfoliated Graphene Nanocomposite Fibers for Biomedical Applications

With the increasing demand for composites of multifunctional and integrated performance, graphene-based nanocomposites have been attracting increasing attention in biomedical applications because of their outstanding physicochemical properties and biocompatibility. High product yields and dispersion of graphene in the preparation process of graphene-based nanocomposites have long been a challenge. Further, the mechanical properties and biosafety of final nanocomposites are very important for real usage in biomedical applications. Here, we presented a novel high-throughput method of graphene on mechanical exfoliation in a natural honey medium, and a yield of ∼91% of graphene nanoflakes can be easily achieved with 97.76% of single-layer graphenes. The mechanically exfoliated graphene (MEG) can be well-dispersed in the poly­(vinyl alcohol) (PVA) matrix. The PVA/MEG nanocomposite fibers are obtained by gel spinning and stretched 20 times. As a candidate for monofilament sutures, the PVA/MEG nanocomposite fibers with 0.3 wt % of MEG have an ultrahigh ultimate tensile strength of 2.1 GPa, which is far higher than that of the neat PVA fiber (0.75 GPa). In addition, the PVA/MEG nanocomposite fibers also have antibacterial property, low cytotoxicity, and other properties. On the basis of the above-mentioned properties, the effects of a common surgical suture and PVA/MEG nanocomposite fibers on wound healing are evaluated. As a result, the wounds treated with PVA/MEG nanocomposite fibers with 0.3 wt % of MEG show the best healing after 5 days of surgery. It is possible that this novel surgical suture will be available in the market relying on the gentle, inexpensive method of obtaining nonoxidized graphene and the simple process of obtaining nanocomposite fibers