Pathways Toward High-Energy Li-Sulfur Batteries, Identified via Multi-Reaction Chemical Modeling

Here we present a 1D model of a Li-Sulfur battery with physically derived geometric parameters and thermodynamically consistent electrochemical kinetics. The approach enables straightforward comparison of proposed Li-S mechanisms and provides insights into the influence of polysulfide intermediates on battery discharge. Comparing predictions from multiple mechanisms demonstrates the need for both lithiated and non-lithiated polysulfide species, and highlights the challenge of developing parameter estimates for complex electrochemical mechanisms. The model is also used to explore cathode design strategies. Discharge performance and polysulfide concentrations for electrolyte/sulfur rations in the range 2 - 4 microleters per mg identifies trade-offs that limit battery energy and power density, and highlights the risk of polysulfide precipitation. New cathode and electrolyte approaches must limit polysulfide concentrations in the electrolyte, both to unlock better rate capabilities in Li-S technology and to prevent capacity fade due to polysulfide precipitation.

Operando XAS of a Bifunctional Gas Diffusion Electrode for Zn-Air Batteries under Realistic Application Conditions

In this study, operando X-ray absorption spectroscopy (XAS) measurements were carried out on a newly developed O2 bi-functional gas diffusion electrode (GDE) for rechargeable Zn-air batteries, consisting of a mixture of α-MnO2 and carbon black. The architecture and composition of the GDE, as well as the electrochemical cell, were designed to achieve optimum edge-jumps and signal-to-noise ratio in the absorption spectra for the Mn K-edge at current densities that are relevant for practical conditions. Herein, we reported the chemical changes that occur on the MnO2 component when the GDE is tested under normal operating conditions, during both battery discharge (ORR) and charge (OER), on the background of more critical conditions that simulate oxygen starvation in a flooded electrode.

Li-ion Battery Aging with Hybrid Physics-Informed Neural Networks and Fleet-wide Data

Lithium-ion batteries are commonly used to power electric unmanned aircraft vehicles (UAVs).Therefore, the ability to model both the state of charge as well as battery health is very important for reliable and affordable operation of UAV fleets.Even though models based on first principles are accurate and trustworthy, the complex electro-chemistry that governs battery discharge and aging makes it hard to build and use such models for in-time monitoring of battery conditions.Moreover, the careful tuning or estimation of high-fidelity model parameters hampers the straightforward deployment in the field.Alternatively, reduced order models have the advantage of capturing the overall behavior of battery discharge. Reduced-order principle-based models are built by carefully simplifying the physics/chemistry such that computational cost is dramatically reduced while the overall behavior of the system is still captured.These simplifications also lead to a number of parameters to be estimated based on data as well as residual discrepancy (model-form uncertainty).This approach can lead to a number of parameters to be estimated based on data as well as residual model-form uncertainty; a property shared with machine learning models. The latter are solely built on the basis of data, and can still capture unexpected nonlinearities.The drawback is that traditional machine learning tends to require large number of data points hard to retrieve in many scientific and engineering fields like, for example, the field of battery discharge and degradation prediction. In this paper, we will present a hybrid modeling approach for tracking and forecasting battery aging based on ``as-used'' conditions.Our approach directly implements a reduced-order model based on Nerst and Butler-Volmer equations within a deep neural network framework.While most of the input-output relationship is captured by reduced-order models, the data-driven kernels reduce the gap between predictions and observations.The hybrid model estimates the overall battery discharge, and a multilayer perceptron models the battery internal voltage.Battery aging is characterized by time-dependent internal resistance and the amount of available Li-ions.We address the difficult issue of building and updating the aging model by reducing the need for reference discharge cycles.This is beneficial to operators, since it reduces the need of taking the batteries out of commission.We compensate for lack of reference discharge cycles by using a probabilistic model that leverages previously available fleet-wide information. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence website.Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.Moreover, the model can help optimizing battery operation by offering long-term forecast of battery capacity.

On the Feasibility of All-solid-state Batteries with LLZO as a Single Electrolyte

Replacement of Li-ion liquid-state electrolytes by solid-state counterparts in a Li-ion battery (LIB) is a major research objective as well as an urgent priority for the industry, as it enables the use of a Li metal anode and provides new opportunities to realize safe, non-flammable, and temperature-resilient batteries. Among the plethora of solid-state electrolytes (SSEs) investigated, garnet-type Li-ion electrolytes based on cubic Li7La3Zr2O12 (LLZO) are considered the most appealing candidates for the development of future solid-state batteries because of their low electronic conductivity of ca. 10−8 S cm−1 (RT) and a wide electrochemical operation window of 0 ‒ 6 V vs. Li+/Li. However, high LLZO density (5.1 g cm-3) and its lower level of Li-ion conductivity (up to 1 mS cm−1 at RT) compared to liquid electrolytes (1.28 g cm-3; ca. 10 mS cm−1 at RT) still raise the question as to the feasibility of using solely LLZO as an electrolyte for achieving competitive energy and power densities. In this work, we analyzed the energy densities of Li-garnet all-solid-state batteries based solely on LLZO SSE by modeling their Ragone plots using LiCoO2 as the model cathode material. This assessment allowed us to identify values of the LLZO thickness, cathode areal capacity, and LLZO content in the solid-state cathode required to match the energy density of conventional lithium-ion batteries (ca. 180 Wh kg-1 and 497 Wh L-1) at the power densities of 200 W kg-1 and 600 W L-1, corresponding to ca. 1h of battery discharge time (1C). We then discuss key challenges in the practical deployment of LLZO SSE in the fabrication of Li-garnet all-solid-state batteries.

Performance Analysis of VRLA Battery for DC Load at Telecommunication Base Station

The high level of power outage in Sukabumi-Cianjur area has influenced the operations of telecommunication industry in the vicinity. This has shortened the battery life at the Base Station (BTS). This study aims to analyze the performance of a (new) VRLA battery against a DC load (BTS) to support the continuity of BTS operation in case of a power outage. The research method used is a (new) battery charge-discharge procedure. Parameters are analyzed by determining the on-site battery discharge duration, the pressure at the battery terminals between cells during backup, and the capacity of the rectifier module to support fast charging. To support fast charging, the rectifier with the formula N+1 and C-rate is 10% and C15 is 15% of the battery capacity. The internal impedance value is 3.4 mΩ and the battery terminal pressure (torque) is 9-11 N/m. The battery performance analysis of the four BTS shows that two of them managed to do a backup, while the other two did not provide good performance.

Sistem Monitoring Penggunaan Beban Pada Proses Pengosongan Baterai 100WP Menggunakan Sensor PZEM-004T

In this study, a prototype tool of plts battery discharge monitoring system was created that aims to facilitate in monitoring plts system, solar panel battery usage monitoring system equipped with arduino microcontroller, current sensor, voltage and power that has been calibrated, so that the data acquisition system integrated in arduino microcontroller based system can be obtained in real time. From the results of the study, according to the microcontroller planner used in this final task is arduino UNO328 and sensor PZEM-004T. This monitoring tool is capable of reading voltage, current, power, cosphi and battery capacity in percent at the time of load supply.

Design of Grid-connected and Stand-alone Photovoltaic Systems for Residential Energy Usage: A Technical Analysis

Towards realizing the United Nations sustainable development goals, access to clean, cheap and reliable energy, especially electricity, has been considered as one of the vital indices in any community. Hence, this paper presents the design analysis of both a grid-connected and an offgrid photovoltaic (PV) systems for household users in the highly residential city of Ogbomoso in Nigeria using PVGIS software. For the off-grid design, it is estimated that, given a total daily load of 9.57 kWh, a 3.5 kWp PV array size and a battery capacity of 86 kWh are enough to power the load with 5 days of autonomy and 70% depth of battery discharge. For the grid-connected PV system, the annual energy output for a building-integrated PV system is found to be around 4006 kWh; and a total of eight PV modules (each rated 250 Wp, 30.93 V) are stringed to arrive at the desired capacity of 2 kWp. In terms of performance, the performance ratio (PR) of a building integrated grid-tied PV system at the study location was found to be 71.2% while for a free-standing PV system, the PR was 75%.