Supercapacitor Degradation Study Using Neural Approaches

Data Pre-processing Flowchart   Figure 1: Flowchart representing the steps taken for data pre-processing From the flowchart above, the first step of obtaining the dataset and getting it verified was obviously already done. The second step of picking out irregularities in the dataset involved loading it into Matlab and basically observing the patterns in the data and any discontinuity, errors, missing information and unsupported data formats that Matlab would not be able to detect.  The only issues found in the dataset was the format in which time was given, absence of certain variables and unexplained variables. These missing and unformatted data were effectively and easily picked out without using any exploratory tools but rather just by using knowledge on supercapacitors. The first run made was that it was seen that when the charge and discharge curves were plotted using the given time values, the graph was seen to be quite staggered. This was a result of matlab no...

Greetings Let us first introduce you to supercapacitors and what this project is about........ Supercapacitors have higher capacitance as compared to other regular capacitors but with lower voltage limits. Due to the high ion adsorption and desorption between two electrodes, it serves its purpose as a device delivering high power density and long live cycles however is highly impacted by its aging nature that gives rise to safety issues and decrease in capacitance. As such, this project will further explore the degradation of supercapacitors and how it’s inevitable failure can be predicted or anticipated using neural based approaches. Now that you have a brief info on what we are doing, lets move on to exploring the data The dataset that will be used in this project comprises of test results for 113 commercial grade supercapacitors for approximately  10000   cycles.  In order to visualize the dataset in terms of how each supercapacitor behaves during charging and discharg...