Lithium-Ion Battery and Battery Management System for an Electric Vehicle

Electric vehicles (EVs) are very versatile and have become a commonplace element of life. They are the most environmentally friendly, efficient, and cost-effective mode of transportation available. Electric motor, electronic control module (ECM), traction battery, battery management system, battery charger, cabling system, regenerative braking system, vehicle body, etc. are the main components of an EV. The best type of rechargeable battery developed for EV is lithium-ion. Lithium batteries have the best chance of achieving the scientific advance which will allow the greatest performance characteristics in terms of acceleration and range in EVs. Compared to other rechargeable batteries, they offer a better energy density, voltage capacity, and lower self-discharge rate. Battery management systems are essential for ensuring that lithium-ion batteries are safe to use in both regular and emergency situations. Again, to avoid electrode or electrolyte decomposition due to overcharging, lithium-ion battery charging systems must be able to connect with battery management systems.

A New Adaptive Filtering Technique to Estimate Common Oscillatory Modes in the Power System Utilizing the Approach of Rotational in- Variance

The dynamic changes in the frequency of power system, needs to be estimated for improving the
damping of oscillations. In this paper, we propose a new approach of Least Means Squares Sign Sign
Error (LMSSS) with Total Least Square Estimation of Signal Parameters Employing Rotational Invariance
Technique (TLS-ESPRIT), in order to reduce the oscillations and estimate the low-frequency oscillatory
modes. The proposed estimation scheme LMSSS-TLS-ESPRIT is compared with other schemes such as
TLS-ESPRIT, LS-ESPRIT, and ESRIT methods for analyzing the effectiveness of the proposed LMSSSTLS-
ESPRIT method. The robustness of the proposed estimation scheme is checked using Monte-Carlo
simulations. The Kundurs two-area system is used to analyze the performance and efficiency of the
proposed approach in practical test system .It can be seen from the results that the proposed approach
accurately estimates the inter-area modes and reduces its mean and standard deviation(SD) to a
minimum value as compared to the aforesaid algorithms.

A New Low-Frequency Oscillatory Modes Estimation using TLS-ESPRIT and Least Mean Squares Sign-Data (LMSSD) Adaptive Filtering

Mitigation of transmission line jamming by price intrusion technique in competitive electricity market

In the past years of the electric market, very big corporation companies enjoyed domination or monopoly and takes complete responsibility for generating the electric power. In the new-age market electricity grid faces several techno-commercial challenges like power outage, conductor snag, equipment rundown, transmission congestion, financial constraint, price settlement issue, etc, so this cause transfer of generated electricity from generating station to load becomes a challenge. Also, transmission jamming or congestion is an issue that leads to catastrophe if not mitigated. Therefore to avoid such issues different techno-financial methods are adopted in a particular electricity zone with a large network. In this paper, we adopted an innovative technique to control the electricity transfer limit. Here an analytic tool based on the price-sensitive algorithm is developed to determine a suitable combination of Financial Transmission Rights (FTR) and Location-based low prices with curtailments in a competitive electricity market. The significant objective of this technique is to minimise the dispatch of low-cost generators and overall operational expenses thereby mitigating the traffic issue in a particular load node or zone. Finally, the transmission congestion mitigation is discussed with price sensitivity technique and with a proper financial mechanism like FTR with location pricing in a particular zone.

A Series Connected Photovoltaic Distributed Generator for Voltage Quality Improvement With a Non-linear Load

We will undoubtedly run out of traditional energy sources at some point in the future, given the rate at which they are being consumed. Several renewable energy sources have been established to compensate for the traditional ones. One of these is solar energy, which can be integrated into the distribution grid. Because solar insulation levels change with the weather, voltage quality issues arise, which is particularly undesirable. To address the problem, a series-connected photovoltaic generator is presented, which improves voltage quality and energy harvesting during upstream voltage fluctuations. If the solar energy captured is inadequate to meet the load, the energy stored in the energy storage system (ESS) is utilized. A model of the planned test system has been created.

A Review on Machine Learning Applications in Transmission Line Fault Analysis

This article is a detailed review of the methods for detecting faults, locating and classifying them on
transmission lines. Although all these methods are very interlinked with much correlation, the authors
want to clarify the understandings of the concepts separately. Fault detection techniques are discussed
based on feature extraction methods such as wavelet transform,support vector machines,support vector
regressions,fuzzy logic,neural network,decision trees and fuzzy inference systems are among few key
topics under this review. The main purpose to write this paper is to give an idea about different
approaches of machine learning with the concern of detection, location and identification of the faults in
the transmission lines. For much clarity in the review,the authors have presented and analyzed the
results of few articles presented by authors.

Question and Answer on Basic Electrical Engineering

Electric Powertrain Engineering and Vehicle Automation: An Interactive Practice Approach

Question and Answer on Renewable Energy Sources

New signal subspace approach to estimate the inter-area oscillatory modes in power system using TLS-ESPRIT algorithm