| 1. |
- Li, Yang, 1984, et al.
(författare)
-
Constrained Ensemble Kalman Filter for Distributed Electrochemical State Estimation of Lithium-Ion Batteries
- 2021
-
Ingår i: IEEE Transactions on Industrial Informatics. - 1941-0050 .- 1551-3203. ; 17:1, s. 240-250
-
Tidskriftsartikel (refereegranskat)abstract
- This article proposes a novel model-based estimator for distributed electrochemical states of lithium-ion (Li-ion) batteries. Through systematic simplifications of a high-order electrochemical–thermal coupled model consisting of partial differential-algebraic equations, a reduced-order battery model is obtained, which features an equivalent circuit form and captures local state dynamics of interest inside the battery. Based on the physics-based equivalent circuit model, a constrained ensemble Kalman filter (EnKF) is pertinently designed to detect internal variables, such as the local concentrations, overpotential, and molar flux. To address slow convergence issues due to weak observability of the battery model, the Li-ion's mass conservation is judiciously considered as a constraint in the estimation algorithm. The estimation performance is comprehensively examined under a wide operating range. It demonstrates that the proposed EnKF-based nonlinear estimator is able to accurately reproduce the physically meaningful state variables at a low computational cost and is significantly superior to its prevalent benchmarks for online applications.
|
|
| 2. |
- Tang, Jinrui, et al.
(författare)
-
Faulted Feeder Identification Based on Active Adjustment of Arc Suppression Coil and Similarity Measure of Zero-Sequence Currents
- 2021
-
Ingår i: IEEE Transactions on Power Delivery. - 0885-8977 .- 1937-4208. ; 36:6, s. 3903-3913
-
Tidskriftsartikel (refereegranskat)abstract
- Existing faulted feeder identification methods in the resonant grounded distribution network are primarily based on feature extraction of the fault-generated transient currents. The reliability of these approaches is significantly compromised by the fluctuating transient signals and interfering on-off operation of the neighboring switches. To sidestep the problems, a novel method is proposed to identify the faulted feeder by consecutively tuning the arc suppression coil around the full compensation state. Once a series of steady states are reached after tuning, the trajectories of the corresponding zero-sequence currents for both the sound and the faulted feeders are obtained to formulate an adjustment trajectory matrix (ATM). With the ATM, the similarity measure of the adjustment trajectories of all feeders is then employed to identify the faulted feeder based on the selected Deng's grey relational analysis. Results show that the adjustment trajectories of the two sound lines share a high similarity degree, while the similarity between the sound and the faulted lines is much lower. The effectiveness of the proposed method is validated via simulation and some case studies are provided. The results show that the faulted feeder can be correctly identified with high reliability and robustness compared to the existing fault-generated signal-based techniques.
|
|
| 3. |
- Wei, Zhongbao, et al.
(författare)
-
Load Current and State-of-Charge Coestimation for Current Sensor-Free Lithium-Ion Battery
- 2021
-
Ingår i: IEEE Transactions on Power Electronics. - 0885-8993 .- 1941-0107. ; 36:10, s. 10970-10975
-
Tidskriftsartikel (refereegranskat)abstract
- The installation of current sensors on lithium-ion batteries (LIBs) can be challenging due to practical constraints in specific applications like portable electronics and smart batteries. Motivated by this, our letter proposes a method for online load current and state-of-charge (SOC) coestimation, which mitigates the need of installing the current sensor for LIB management. The essence is to transform the state observation into a constrained optimization problem, which is solved numerically in a moving horizon framework to allow the online coestimation of SOC and input current. Experimental results suggest that the proposed method can coestimate the load current and SOC of LIB precisely even if the current sensor is absent. The encouraging results are insightful for reducing the structural complexity and cost of future LIB utilization.
|
|
