A5088560199- Advanced Battery Technologies Research
- Advancements in Battery Materials
- Fault Detection and Control Systems
- Electric Vehicles and Infrastructure
- Cognitive Radio Networks and Spectrum Sensing
- Advanced Control Systems Design
- IoT-based Smart Home Systems
- Vehicular Ad Hoc Networks (VANETs)
- Wireless Networks and Protocols
- Reliability and Maintenance Optimization
- Advanced DC-DC Converters
- Control Systems and Identification
- Advanced Algorithms and Applications
- Microgrid Control and Optimization
Guangdong University of Technology
2024
Southwest University of Science and Technology
2022-2023
Sichuan University
2022
Abstract Aiming at the problem that it is difficult to accurately estimate state of charge (SOC) lithium‐ion batteries in strongly nonlinear interval, a novel algorithm based on fuzzy control strategy proposed. It integrates extended Kalman filter (EKF) and ampere‐hour (Ah) integration SOC batteries. First, uses advantage EKF has high estimation accuracy interval can solve large error caused by inaccurate initial value Ah integral algorithm. Then fuzzy‐EKF‐Ah (F‐EKF‐Ah) used fuse two...
Lithium-ion batteries are used in a wide range of applications due to their cleanliness and stability, the health management lithium-ion has become necessity. The most important aspect is prediction remaining useful life (RUL) battery. Therefore, RUL estimation model based on aging factor charging process an improved multi-kernel relevance vector machine proposed order achieve high accuracy batteries. First, eight features highly correlated with capacity degradation extracted current,...
Abstract Accurate estimation of the state charge (SOC) lithium‐ion batteries is quite crucial to battery safety monitoring and efficient use energy; improve accuracy SOC under complicated working conditions, research object this study ternary battery; forgetting factor recursive least square (FFRLS) method optimized by particle swarm optimization (PSO) adaptive H‐infinity filter (HIF) algorithm are adopted estimate SOC. The PSO improved with dynamic inertia weight optimize solve...
State of Charge (SOC) estimation is the focus battery management systems, and it critical to accurately estimate SOC in complex operating environments. To weaken impact unreasonable forgetting factor values on parameter accuracy, an artificial fish swarm (AFS) strategy introduced optimize least squares (FFRLS) model lithium-ion using a first-order RC model. A new method AFS-FFRLS proposed for online identification In estimation, not reasonable fix process noise covariance, differential...
Accurate prediction of the remaining useful life (RUL) lithium–ion batteries is focus battery health management. To achieve high–precision RUL estimation batteries, a novel model proposed by combining extraction indicators based on incremental capacity curve (IC) and method improved adaptive relevance vector machine (RVM). First, IC extracted charging current voltage data. attenuate noise effects curve, Gaussian filtering used optimal window determined to remove interference. Based this,...
In this paper, we investigate a learning-based framework that addresses the point-to-point vehicular navigation problem through robust output regulation approach and test it Ultra-Wide Band (UWB) communication noise data. Our focus is on control policy design ensuring stability of closed-loop system for vehicle dynamics. It seen our proposed solution, which relies reinforcement learning, data-driven does not require accurate knowledge motion model. Specifically, explore optimal tracking...