Dynamic Covalent Synthesis of Crystalline Porous Graphitic Frameworks

Porous graphitic framework (PGF) is a two-dimensional (2D) material that has emerging energy applications. An archetype contains stacked 2D layers, the structure of which features a fully annulated aromatic skeleton with embedded heteroatoms and periodic pores. Due to the lack of a rational approach in establishing in-plane order under mild synthetic conditions, the structural integrity of PGF has remained elusive and ultimately limited its material performance. Here, we report the discovery of the unusual dynamic character of the C=N bonds in the aromatic pyrazine ring system under basic aqueous conditions, which enables the successful synthesis of a crystalline porous nitrogenous graphitic framework with remarkable in-plane order, as evidenced by powder X-ray diffraction studies and direct visualization using high-resolution transmission electron microscopy. The crystalline framework displays superior performance as a cathode material for lithium-ion batteries, outperforming the amorphous counterparts in terms of capacity and cycle stability. Insertion of well-defined, evenly spaced nanoscale pores into the two-dimensional (2D) layers of graphene invokes exciting properties due to the modulation of its electronic band gaps and surface functionalities. A bottom-up synthesis approach to such porous graphitic frameworks (PGFs) is appealing but also remains a great challenge. The current methods of building covalent organic frameworks rely on a small collection of thermodynamically reversible reactions. Such reactions are, however, inadequate in generating a fully annulated aromatic skeleton in PGFs. With the discovery of dynamic pyrazine formation, we succeeded in applying this linking chemistry to obtain a crystalline PGF material, which has displayed high electrical conductivity and remarkable performance as a cathode material for lithium-ion batteries. We envision that the demonstrated success will open the door to a wide array of fully annulated 2D porous frameworks, which hold immense potential for clean energy applications. We report the unusual dynamic characteristics of the C=N bonds in the pyrazine ring promoted under basic aqueous conditions, which enables the successful synthesis of two-dimensional porous graphitic frameworks (PGFs) featuring fully annulated aromatic skeletons and periodic pores. The PGF displayed high electrical conductivity and remarkable performance as a cathode material for lithium-ion batteries, far outperforming the amorphous counterparts in terms of capacity and cycle stability

Universal Chemomechanical Design Rules for Solid-Ion Conductors to Prevent Dendrite Formation in Lithium Metal Batteries

Dendrite formation during electrodeposition while charging lithium metal batteries compromises their safety. While high shear modulus solid-ion conductors (SICs) have been prioritized to resolve pressure-driven instabilities that lead to dendrite propagation and cell shorting, it is unclear whether these or alternatives are needed to guide uniform lithium electrodeposition, which is intrinsically density-driven. Here, we show that SICs can be designed within a universal chemomechanical paradigm to access either pressure-driven dendrite-blocking or density-driven dendrite-suppressing properties, but not both. This dichotomy reflects the competing influence of the SICs mechanical properties and partial molar volume of Li+ relative to those of the lithium anode on plating outcomes. Within this paradigm, we explore SICs in a previously unrecognized dendrite-suppressing regime that are concomitantly soft, as is typical of polymer electrolytes, but feature atypically low Li+ partial molar volume, more reminiscent of hard ceramics. Li plating mediated by these SICs is uniform, as revealed using synchrotron hard x-ray microtomography. As a result, cell cycle-life is extended, even when assembled with thin Li anodes and high-voltage NMC-622 cathodes, where 20 percent of the Li inventory is reversibly cycled

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

Analysis and three-dimensional modeling of vanadium flow batteries

This study presents 1.) a multi-dimensional model of vanadium Redox Flow Batteries (RFB); 2.) rigorous explanation of porelevel transport resistance, dilute solution assumption, and pumping power; and 3.) analysis of time constants of heat and mass transfer and dimensionless parameter. The model, describing the dynamic system of a RFB, consists of a set of partial differential equations of mass, momentum, species, charges, and energy conservation, in conjunctionwith the electrode's electrochemical reaction kinetics. The governing equations are successfully implemented into three-dimensional numerical simulation of charging, idling, and discharging operations. The model, validated against experimental data, predicts fluid flow, concentration increase/decrease, temperature contours and local reaction rate. The prediction indicates a large variation in local reaction rate across electrodes and the time constants for reactant variation and temperature evolution, which are consistent with theoretical analysis. © 2014 The Electrochemical Society. All rights reserved

Control algorithms for e-car

Cílem práce byl návrh a implementace řídicích algoritmů pro optimalizaci spotřeby energie elektrického vozidla. Hlavním úkolem byla optimalizace rozložení energie mezi hlavním zdrojem energie (bateriemi) a super-kapacitory v průběhu jízdního cyklu. Jízdní výkonový profil je odhadován a předpovězen na základě 3D geografických souřadnic a matematického modelu vozidla. V první části jsou uvedeny komponenty vozidla a jejich modely. Poté jsou představeny algoritmy na základě klouzavého průměru a dynamického programování. Byly provedeny simulace a analýzy pro demostraci přínosů algoritmů. V poslední části je popsána Java implementace algoritmů a také aplikace pro operační systém Android.The aim of this work is to design and implement energy consumption optimization control algorithms for electric vehicle. The main objective is to optimize the power-split-ratio between the main power source (batteries) and the super-capacitors during the driving cycle. The driving power profile is estimated and predicted using 3D geographic data and vehicle model. In the first part, vehicle components modelling is introduced. Then, moving average based algorithm and dynamic programming algorithm are presented. Simulations and analysis are provided to show algorithms' benefits. In the last part, Java implementation and also Android operating system application are described.