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4 results for “Smart Charging”
Dataset for 'Smart Health Evaluation for Lithium-ion Battery with Super-short-segment Charging'
<p>This is the dataset used in our paper '<em>Smart Health Evaluation for Lithium-ion Battery with Super-short-segment Charging</em>', which mainly includes data from <strong>40Ah batteries</strong> at <strong>0.3C, 1C, 2C</strong>, and two <strong>280Ah batteries</strong> at <strong>20%, 60%, and 100% DOD</strong>, respectively. For specific details, please refer to Readme.text</p> <p>The data in<strong> LISHEN</strong> is the cycle test data of 40Ah battery at different discharge depths under 100%,60%,20%DOD working condition. The data in <strong>CATL</strong> and<strong> EVE </strong>is the cyclic test data of 280Ah battery at different discharge depths under 100%,60%,20%DOD conditions. <br>The CSV file has 21 or 17 columns, (17 columns for, data sequence number, good cycling, step number, step type, time (s) , total time (s) , current (a) , voltage (V) , capacity (AH) , charging capacity (AH) , discharge capacity (AH) , energy (Wh) , charging energy (Wh) , discharge energy (Wh) , absolute time (s) , power (W) , temperature (° C-RRB-) , the 21-column CSV adds four metrics (DQ/DV (AH/V) in column 17, dQm/DV (mAh/V) in column 18, contact resistance (m ω) in column 19, and module start-stop status in column 20) , More detailed files can be found in the zip file.</p>
Smart Charging of Future Electric Vehicles Using Roadway Infrastructure
<p>Corresponding data set for Tran-SET Project No. 18ITSTSA03. Abstract of the final report is stated below for reference:</p> <p>"Inspired by the fact that there is an immense amount of renewable energy sources available on the roadways such as mechanical pressure and frictional heat, this study presented the development and implementation of an innovative charging technique for future electric vehicles (EVs) by fully utilizing the existing roadways and the state-of-the-art nanotechnology and power electronics. The project introduced a novel wireless charging system, SIC (Smart Illuminative Charging), that uses LEDs powered by piezoelectric nanomaterials as the energy transmitter source and thin film solar panels placed at the bottom of the EVs as the receiver, which is then poised to deliver the harvested energy to the vehicle’s battery. Through the project, the energy-harvestable 2D nanomaterials (EH2Ns) were tested for their mechanical-to-electrical energy conversion capabilities and the relatively large-area EH2N samples (2cm x 2cm) produced high output voltages of up to 52mV upon mechanical pressure. An electrically conductive glass fiber reinforced polymer (GFRP) was developed to be used as physical support in the integrated SIC system. Furthermore, a lab-scale prototype device was developed to testify the mechanism of illuminative charging. The project team was able to prove the feasibility of SIC concept and the start to end conversion efficiency was calculated to be 40%. The project team also provided field implementation recommended framework based on the results from the small-scale prototype developed. The framework discussed how the developed SIC can be implemented in the field and what are the expected outcomes. The team recommended inserting the EH2N embedded in the GFRP, the LEDs and the needed circuitry in the wheel path of the vehicles on the pavement by cutting a sawtooth compartment with a width of 18’’ and a length of 8’ every couple of miles. On the vehicle, a PV array will be placed on the underside between the wheel wells of each side of the EV to capture the illumination from the LEDs embedded in the roadway. The detailed strategy is presented in this report."</p>
SPARCS_WP4_Leipzig_City_Number of smart EV charging points
<p>Number of smart EV charging points in the city of Leipzig with annually captured data for the period between 2019 and 2024</p>
Novel Self-charging, Medical-Grade Smart Insoles With AI/ML Edge Computing to Monitor Biometrics.
ClinicalTrials.gov study NCT07273422. IPD Sharing: NO. Countries: 1. Publications: 0.
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