Batteries for stationary standby and for stationary cycling applications part 6: alternative electricity storage technologies

Abstract

As the need for stored electrical energy has grown, the lead-acid battery has been the primary storage component until very recently. Although improvements in lead-acid technology have been made over the years, short life expectancy and poor component reliability have driven energy storage customers in search of longer life and higher reliability storage technologies. New technology batteries have been developed as well as other non-battery storage devices that are meeting the needs for higher energy densities and more reliability. This paper discusses these emerging energy storage technologies and how they are being used in modem energy storage requirements.

A Review of Lithium-Ion Battery State of Health Estimation and Prediction Methods

“…Therefore, the future trend will be in the form of multi-algorithm coupling, and the selection of state parameters will be further innovated. The current maximum available capacity of the battery R Internal resistance under the current state R e Internal resistance of the battery when it reaches the end of life R n Internal resistance of the new battery b 1 -b 5 The threshold of the hidden layer c 1 -c 3 The threshold of output layer W 1 (1)(2)(3)(4)(5) Input weights W 2 (1)(2)(3) Output weights Q Nominal capacity Q 0 Smaller lithium concentration after multiple cycles…”

“…The authors of [100], directly adopted 10 groups of real vehicle road test data, and selected current, voltage, temperature, SOC and SOH parameters as the characteristic parameters of the neural network at the same time to predict the remaining service life, which improved the credibility of the real-time prediction ability under real vehicle operation. (1)(2)(3)(4)(5) and W 2 (1-3) are input and output weights. After a series of training and verification, it output the estimated value of SOH.…”

“…Due to the characteristics of long cycle life, high specific energy, specific power, low self-discharge rate, high-temperature range, and the advantages of little pollution to the environment [1], lithium-ion power batteries (from now on referred to as lithium battery) are widely applied in various fields. In the area of transportation, to adapt to people's fast pace of life and rising material demand, more and more countries are investing a lot of financial and material resources into research and developing transportation electrification, thus electric vehicle technology has been widely promoted and applied [2][3][4][5][6][7]. According to statistics, the inaccurate SOH estimation and life prediction of lithium batteries are the leading causes of electric vehicle spontaneous combustion accidents [8][9][10].…”

A Data-Driven Predictive Prognostic Model for Lithium-ion Batteries based on a Deep Learning Algorithm

“…One of the most important tasks in prognostics health management of a battery is to accurately estimate the C max,p , as C max,p is required in both Equations (2) and 3for SoC and SoH estimations, respectively. Our tested battery dataset contained all the aging information of the battery, and the battery SoH was calculated from cycle 0 to cycle 168.…”

“…Therefore, there will be no other battery technologies that lithium-ion anytime soon, and the main focus of the ongoing technology is still aimed at improving the lithium-ion system in term of both its performance and reliability. The following are the main advantages of lithium-ion batteries: (1) high energy density (up to 23-70 Wh/kg), (2) high efficiency (close to 90%), and (3) long life cycle (provides 80% capacity at 3000 cycles) [2].…”