This study presents a study of the reduction in battery stresses by using supercapacitors (SCs) in a 500-kVA rated UPS. We aim at investigating the optimal supercapacitors-battery combination versus the SCs cost. This investigation is threefold; first, supercapacitors and battery models developed using MATLAB/Simulink are presented and validated. Second, the architecture and the simulation of the designed system that combines the SCs and the battery are shown. The supercapacitors are used as high-power storage devices to smooth the peak power applied to the battery during backup time and to deliver full power during short grid outages. By charging the SCs through the battery at a suitable rate, all impulse power demands would be satisfied by the supercapacitors. Third, extensive simulations are carried out to determine the gain in battery RMS current, the gain in energy losses, the energy efficiency and the elimination rate of surge load power. These four performance parameters are determined by simulation and then analyzed. The influence of the SCs recharge on the performance indicators is highlighted. A thorough analysis involving optimal study proposes to draw the optimal SCs number and filter constant from the variation of the aforementioned parameters versus the cost of the SCs.

The self-discharge of an electrochemical capacitor, also referred to as a supercapacitor, is an important factor in determining the duration of maintaining stored energy, especially in low-duty-cycle applications. The study of self-discharge is conducted as follows: first, the self-discharge is characterized by measuring the decline of open-circuit voltage of the electrochemical capacitor. Second, the mechanisms of self-discharge, leakage current, and diffusion of ions at the electrode-electrolyte interfaces are modeled by an electrical equivalent circuit. The equivalent circuit elements are experimentally determined according to the self-discharge time behavior. In addition, the dependence of the self-discharge parameters on both temperature and initial voltage across the electrochemical capacitor is described in detail.

Due to its capacity to store or supply energy with high power, the supercapacitor is becoming an attractive component. Because of the electrostatic nature of energy storage, the endurance of this component toward repetitive charge and discharge cycles is relatively high. The goal of this paper is to demonstrate that cycling has an impact on the degradation of the supercapacitor and, as a result, on its lifetime. Based on accelerated cycling tests, some supercapacitors were studied using a dedicated test bench. Temperature, voltage, and current, which are the parameters that accelerate aging, are monitored. In fact, observations during the cycling tests show an important acceleration in the degradation compared with a similar static test having the same voltage and core temperature but without cycling. This paper proposes a method to quantify the acceleration of aging during a cycling phase.

Pulse charging and pulse discharging have been reported by many authors in the literature to improve the performance of various secondary electrochemical cells. Only a few authors mentioned the effects of such charge and discharge method on lithium-ion batteries. The overall objective of this work is to experimentally investigate the impact of certain current pulse profiles on the electrical performance of Li-ion batteries. The results highlight a detrimental impact of periodic pulses on the cell performance compared to profiles with constant current.

This paper presents a low-cost method to realize a real-time condition monitoring and a predictive-maintenance system of an electrolytic capacitor used in uninterruptible power supplies (UPSs). This method consists in detecting the changes in real time of the equivalent series resistance and the capacitance C values of the electrolytic capacitors. Simulation and experimental results are presented to illustrate the proposed monitoring technique. The proposed method can be used in UPS where waveforms are continuously varying in amplitude, frequency, and temperature. The proposed online failure prediction method has the merits of using only the existent resources in UPS and with the use of known algorithms.