A5083098399- Advanced Battery Technologies Research
- Advancements in Battery Materials
- Electric Vehicles and Infrastructure
- Fault Detection and Control Systems
- Reliability and Maintenance Optimization
- Electric and Hybrid Vehicle Technologies
- Advanced Battery Materials and Technologies
- Advanced DC-DC Converters
- Machine Learning and ELM
- Advanced Adaptive Filtering Techniques
- Control Systems and Identification
- Speech and Audio Processing
- Fuel Cells and Related Materials
- Blind Source Separation Techniques
- Advanced Control Systems Design
- Wireless Power Transfer Systems
- IoT Networks and Protocols
- Sensor Technology and Measurement Systems
- Industrial Automation and Control Systems
- Microgrid Control and Optimization
- Wireless Communication Networks Research
- Radiation Effects in Electronics
- Advanced Algorithms and Applications
- Embedded Systems and FPGA Design
- Advanced battery technologies research
Southwest University of Science and Technology
2019-2024
Inner Mongolia University of Technology
2024
Accurate prediction of the state health (SOH) Li-ion battery has an important role in estimation charge (SOC), which can not only improve efficiency usage but also ensure its safety performance. The capacity will decrease with increase and discharge times, while internal resistance become larger, affect management. attenuation characteristics batteries are analyzed by aging experiment. Based on equivalent circuit model online parameter identification, a novel adaptive dual extended Kalman...
Abstract The safety assurance is very important for the unmanned aerial vehicle lithium ion batteries, in which state of charge estimation basis its energy management and protection. A new equivalent modeling method proposed mathematical expression different structural characteristics, an improved reduce particle‐adaptive Kalman filtering model designed built, incorporate multiple featured information absorbed to explore optimal representation by abandoning redundant abnormal information....
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,...
Accurate State of Health (SOH) estimation battery systems is critical to vehicle operation safety. However, it’s difficult guarantee the performance a single model due unstable quality raw data obtained from lithium-ion aging and complexity operating conditions in actual operation. Therefore, this paper combines long short-term memory (LSTM) network with strong temporality, support vector regression (SVR) nonlinear mapping small sample learning. A novel LSTM-SVR combined input features, less...
The internal nonlinearity of the lithium-ion battery makes its mathematical modeling a big challenge. In this paper, novel splice-electrochemical circuit polarization (S-ECP) model is proposed, which integrates strengths various models and refines ohm characteristics electrochemical Nernst differences in charge-discharge resistance. Moreover, by applying one-sided limit to discrete system, multi-innovation least squares algorithm optimized based on dynamic function (F-MILS) introduced...
The rapid development of new energy vehicles puts forward higher requirements for the lithium-ion batteries model construction, high-efficiency condition monitoring and collaborative estimation. An improved high-fidelity second-order autoregressive is proposed constructed, integrated with equivalent circuit model, which can achieve an accurate reliable description internal dynamic change process. To expression battery's external characteristics state, forgetting factor combined recursive...