Reduce state of charge estimation errors with an extended Kalman filter algorithm

Li-ion batteries (LiBs) are accurately estimated under varying operating conditions and external influences using extended Kalman filtering (EKF). Estimating the state of charge (SOC) is essential for enhancing battery efficiency, though complexities and unpredictability present obstacles. To address this issue, the paper proposes a second-order resistance-capacitance (RC) battery model and derives the EKF algorithm from it. The EKF approach is chosen for its ability to handle complex battery behaviors. Through extensive evaluation using a Simulink MATLAB program, the proposed EKF algorithm demonstrates remarkable accuracy and robustness in SOC estimation. The root mean square error (RMSE) analysis shows that SOC estimation errors range from only 0.30% to 2.47%, indicating substantial improvement over conventional methods. These results demonstrate the effectiveness of an EKF-based approach in overcoming external influences and providing precise SOC estimations to optimize battery management. In addition to enhancing battery performance, the results of the study may lead to the development of more reliable energy storage systems in the future. This will contribute to the wider adoption of LiBs in various applications

Design and sizing of a Hybrid PV-Wind-Grid System for Electric Vehicle Charging Platform

The recent technological advancement in the power electronics converters, control, and battery technology, allowed the enhancement of the use of the electric vehicle (EV) as a means of transportation, EV requires to be charged with an electrical grid which imposes an extra burden on the electrical supply during the peak demand duration. The use of renewable energy sources (RES) such as solar and wind remains as alternative sources to reduce this negative impact. The main interest of this work is integrating the RES in transportation systems through a smart grid system with a proposed design of a hybrid PV-Wind-Grid charging platform for EV

Performance analysis and optimal parameters of a direct evaporative pad cooling system under the climate conditions of Morocco

In this study, a direct evaporative pad cooling system to be used for a poultry house is simulated under the climate conditions of six Moroccan cities. The objective is to optimize the parameters affecting the performance of the system for each city. The thermodynamic properties of humid air are extracted from the open source program CoolProp, and a computer program is used to perform a parametric study in order to find the impacts of the pad thickness and the frontal velocity on system's performance. Simulations have been conducted on cellulosic pad cooling and obtained results show that the system has the potential to lower the outdoor temperature during the hottest period with a coefficient of performance higher than 80, while the average rate of water consumption is higher than 3.3 kg per hour. Keywords: Direct evaporative pad cooling, Cellulosic, Simulated, Coefficient of performance, Optimizatio