Modified dual extended Kalman filters for SOC estimation and online parameter identification of lithium-ion battery via modified gray wolf optimizer

In order to achieve accurate state of charge (SOC) estimation of Lithium-Ion Battery, A method that dual Extended Kalman filters (DEKF) optimized by PSO-based Gray Wolf optimizer (MGWO) is proposed. A second-order equivalent circuit model with two resistor-capacitor branches is applied. The battery parameters are determined by battery test. Dual Extended Kalman filters are divided into state filter and parameter filter. Parameter filter is applied to adjust battery parameters online, state filter is applied to SOC estimation. Meanwhile, MGWO is applied to optimize the noise covariance matrix to improve the state estimation accuracy of SOC which reduces the linearization error from EKF. The results shows that the accuracy of algorithm is improved by adding online parameter identification and the optimization of the noise covariance matrix, meanwhile, the proposed method can adapt to the initial error well.

Fault Detection in Modular Offshore Platform Connections Using Extended Kalman Filter

Within the Space@Sea project, funded by the Horizon 2020 program, a concept for a floating island was developed. The main idea is to create space in the offshore environment, which can be used to harvest renewable energy, grow food or build a maritime transport and logistic hub. The island is designed as an assembly of platforms, which are connected by ropes and fenders. These connection elements are considered critical, as they have to carry extreme loads in the severe offshore environment. At the same time, any failure in the connecting elements might put the entire platform structure at risk. This paper presents a feasibility study for the fault detection in the connection elements using Extended Kalman filters. For various test cases, typical parameters of the connecting elements are estimated from motion data of the structure. Thus, the technique reveals changes in the connections. For various test cases, it is shown that fault detection is possible. Not only a failure of a single connecting rope but also multiple faults in the system can be detected.

Transversely Stable Extended Kalman Filters for Systems on Manifolds in Euclidean Spaces

In this article, we devise a variant of the extended Kalman filter that can be generally applied to systems on manifolds with simplicity and low computational cost. We extend a given system on a manifold to an ambient open set in Euclidean space and modify the system such that the extended system is transversely stable on the manifold. Then, we apply the standard extended Kalman filter derived in Euclidean space to the modified dynamics. This method is efficient in terms of computation and accurate in comparison with the standard extended Kalman filter. It has the merit that we can apply various Kalman filters derived in Euclidean space including extended Kalman filters for state estimation for systems defined on manifolds. The proposed method is successfully applied to the rigid body attitude dynamics whose configuration space is the special orthogonal group in three dimensions.