Online Parameter Estimation for Supercapacitor State-of-Energy and State-of-Health Determination in Vehicular Applications

WOS:000536291000079Online accurate estimation of supercapacitor state-of-health (SoH) and state-of-energy (SoE) is essential to achieve efficient energy management and real-time condition monitoring in electric vehicle (EV) applications. In this article, for the first time, unscented Kalman filter (UKF) is used for online parameter and state estimation of the supercapacitor. In the proposed method, a nonlinear state-space model of the supercapacitor is developed, which takes the capacitance variation and self-discharge effects into account. The observability of the considered model is analytically confirmed using a graphical approach. The SoH and SoE are then estimated based on the supercapacitor online identified model with the designed UKF. The proposed method provides better estimation accuracy over Kalman filter (KF) and extended KF algorithms since the linearization errors during the filtering process are avoided. The effectiveness of the proposed approach is demonstrated through several experiments on a laboratory testbed. An overall estimation error below 0.5% is achieved with the proposed method. In addition, hardware-in-the-loop experiments are conducted and real-time feasibility of the proposed method is guaranteed

A comprehensive review on Bidirectional traction converter for Electric vehicles

In this fast-changing environmental condition, the effect of fossil fuel in vehicle is a significant concern. Many sustainable sources are being studied to replace the exhausting fossil fuel in most of the countries. This paper surveys the types of electric vehicle’s energy sources and current scenario of the on-road electric vehicle and its technical challenges. It summarizes the number of state-of-the-art research progresses in bidirectional dc-dc converters and its control strategies reported in last two decades. The performance of the various topologies of bidirectional dc-dc converters is also tabulated along with their references. Hence, this work will present a clear view on the development of state-of-the-art topologies in bidirectional dc-dc converters. This review paper will be a guide for the researchers for selecting suitable bidirectional traction dc-dc converters for electric vehicle and it gives the clear picture of this research field

A comprehensive review on Bidirectional traction converter for Electric vehicles

In this fast-changing environmental condition, the effect of fossil fuel in vehicle is a significant concern. Many sustainable sources are being studied to replace the exhausting fossil fuel in most of the countries. This paper surveys the types of electric vehicle’s energy sources and current scenario of the on-road electric vehicle and its technical challenges. It summarizes the number of state-of-the-art research progresses in bidirectional dc-dc converters and its control strategies reported in last two decades. The performance of the various topologies of bidirectional dc-dc converters is also tabulated along with their references. Hence, this work will present a clear view on the development of state-of-the-art topologies in bidirectional dc-dc converters. This review paper will be a guide for the researchers for selecting suitable bidirectional traction dc-dc converters for electric vehicle and it gives the clear picture of this research field

Online Supercapacitor Diagnosis for Electric Vehicle Applications

International audienceThis paper presents an online diagnosis method for the supercapacitors' aging problem. State-of-health (SoH) estimation is an important feature since aging introduces degradation in the supercapacitors' performance, which might eventually lead to their failure. SoH is usually measured by electrochemical impedance spectroscopy. However, this has to be performed offline and requires interruption of the system's operation. Unlike this method, this paper presents an online diagnosis technique for supercapacitors using an extended Kalman observer as a well-known tool for its particularities and performances to study nonlinear parameter estimation. The main objective of this paper is the online SoH diagnosis based on the supercapacitors' aging indicator estimation. Moreover, the proposed online estimation strategy requires only voltage and current measurements, which reduces the number of sensors with respect to other methods. The effectiveness of the proposed online observer is shown through experimental results, and robustness to noise is also studied