A5108048515- Advanced Battery Technologies Research
- Electric and Hybrid Vehicle Technologies
- Electric Vehicles and Infrastructure
- Advancements in Battery Materials
- X-ray Diffraction in Crystallography
- Industrial Technology and Control Systems
- Crystallization and Solubility Studies
- Vehicle emissions and performance
- Advanced Sensor and Control Systems
- Advanced Battery Materials and Technologies
- Vehicle Dynamics and Control Systems
- Advanced Algorithms and Applications
- Power Systems and Renewable Energy
- Metal-Organic Frameworks: Synthesis and Applications
- Real-time simulation and control systems
- Fault Detection and Control Systems
- Mechanical Engineering and Vibrations Research
- Hydraulic and Pneumatic Systems
- Fuel Cells and Related Materials
- Sensorless Control of Electric Motors
- Magnetism in coordination complexes
- Crystallography and molecular interactions
- Supercapacitor Materials and Fabrication
- Simulation and Modeling Applications
- Advanced Combustion Engine Technologies
Beijing Institute of Technology
2015-2024
Southwest Petroleum University
2024
PetroChina Southwest Oil and Gas Field Company (China)
2024
Shenzhen Institute of Information Technology
2024
Northeast Petroleum University
2024
Shandong University of Technology
2023
Institute of Electrical and Electronics Engineers
2023
University of Memphis
2023
Antea Group (France)
2023
Engineering Systems (United States)
2023
Battery technology is the bottleneck of electric vehicles (EVs). It important, both in theory and practical application, to do research on modeling state estimation batteries, which essential optimizing energy management, extending life cycle, reducing cost, safeguarding safe application batteries EVs. However, with strong time-variables nonlinear characteristics, are further influenced by such random factors as driving loads, operational conditions, The real-time, accurate their...
An adaptive Kalman filter algorithm is adopted to estimate the state of charge (SOC) a lithium-ion battery for application in electric vehicles (EVs). Generally, selected dynamically SOC. However, it easily causes divergence due uncertainty model and system noise. To obtain better convergent robust result, an that can greatly improve dependence traditional on employed. In this paper, typical characteristics are analyzed by experiment, such as hysteresis, polarization, Coulomb efficiency,...
The performance and practicality of predictive energy management in hybrid electric vehicles (HEVs) are highly dependent on the forecast future vehicular velocities, both terms accuracy computational efficiency. In this brief, we provide a comprehensive comparative analysis three velocity prediction strategies, applied within model control framework. process is performed over each receding horizon, predicted velocities utilized for fuel economy optimization power-split HEV. We assume that no...
An accurate State-of-Charge (SoC) estimation plays a significant role in battery systems used electric vehicles due to the arduous operation environments and requirement of ensuring safe reliable operations batteries. Among conventional methods estimate SoC, Coulomb counting method is widely used, but its accuracy limited accumulated error. Another commonly model-based online iterative with Kalman filters, which improves some extent. To improve performance filters SoC estimation, adaptive...
Recent advances in traffic monitoring systems have made real-time velocity data ubiquitously accessible for drivers. This paper develops a data-enabled predictive energy management framework power-split plug-in hybrid electric vehicle (PHEV). Compared with conventional model control (MPC), an additional supervisory state of charge (SoC) planning level is constructed based on data. A power balance-based PHEV developed this upper to rapidly generate battery SoC trajectories that are utilized...
Energy storage system (ESS) is an essential component of electric vehicles, which largely affects their driving performance and manufacturing cost. A hybrid energy (HESS) composed rechargeable batteries ultracapacitors shows a significant potential for maximally exploiting complementary characteristics. This study focuses on optimal HESS sizing example vehicle using multi-objective optimization algorithm, with the overarching goal reducing ESS cost while prolonging battery life. To this end,...
Lithium-ion batteries (LIBs) are being intensively studied and universally used as power sources for electric vehicle applications. Despite the staggering growth in sales of LIBs worldwide, thermal safety issues still turn out to be most intolerable pain point, remain focus research technological improvements. This paper presents a comprehensive overview on LIBs, terms behavior runaway modeling tests battery cells, management strategies packs. Considering heat generation mechanism...
In order to safely and efficiently use the power as well extend lifetime of traction battery pack, accurate estimation State Charge (SoC) is very important necessary. This paper presents an adaptive observer-based technique for estimating SoC a lithium-ion pack used in electric vehicle (EV). The RC equivalent circuit model ADVISOR applied simulate pack. parameters function SoC, are identified optimized using numerically nonlinear least squares algorithm, based on experimental data set. By...
A reinforcement learning-based adaptive energy management (RLAEM) is proposed for a hybrid electric tracked vehicle (HETV) in this paper. control oriented model of the HETV first established, which state-of-charge (SOC) battery and speed generator are state variables, engine's torque variable. Subsequently, transition probability matrix learned from specific driving schedule HETV. The RLAEM decides appropriate power split between engine-generator set (EGS) to minimize fuel consumption over...
Battery models are the cornerstone to battery state of charge (SOC) estimation and management systems in electric vehicles. This paper proposes a novel fractional-order model for battery, which considers both Butler-Volmer equation fractional calculus constant phase element. The structure characteristics proposed then analyzed, identification method, combines least squares nonlinear optimization algorithm, is proposed. method proven be efficient accurate. Based on model, unscented Kalman...
This paper compares two optimal energy management methods for parallel hybrid electric vehicles using an Automatic Manual Transmission (AMT). A control-oriented model of the powertrain and vehicle dynamics is built first. The formulated as a typical control problem to trade off fuel consumption gear shifting frequency under admissible constraints. Dynamic Programming (DP) Pontryagin’s Minimum Principle (PMP) are applied obtain solutions. Tuning with appropriate co-states, PMP solution found...
In electric vehicles, a battery management system highly relies on the measured current, voltage, and temperature to accurately estimate state of charge (SOC) health. Thus, normal operation sensors is great importance protect batteries from running outside their safe operating area. this paper, simple effective model-based sensor fault diagnosis scheme developed detect isolate current or voltage for series-connected lithium-ion pack. The difference between true SOC estimated each cell in...
Accurate battery aging prediction is essential for ensuring efficient, reliable, and safe operation of systems in electric vehicle application. This article presents a novel assessment method based on the incremental capacity analysis (ICA) radial basis function neural network (RBFNN) model. The RBFNN model used to depict relationship between level its influencing factors real-world datasets city transit buses. ICA together with Gaussian window (GW) filter derive peak values IC curves which...
Developing new energy vehicles has been a worldwide consensus, and developing characterized by pure electric drive China's national strategy. After more than 20 years of high-quality development (EVs), technological R & D layout "Three Verticals Three Horizontals" created, advantages have accumulated. As result, vehicle market ranked first in the world since 2015. To systematically solve key problems battery (BEVs) such as "driving range anxiety, long charging time, driving safety hazards",...