A5028703390- Electric and Hybrid Vehicle Technologies
- Advanced Battery Technologies Research
- Electric Vehicles and Infrastructure
- Advanced DC-DC Converters
- Multilevel Inverters and Converters
- Advanced Aircraft Design and Technologies
- Microgrid Control and Optimization
- Distributed Control Multi-Agent Systems
Northwestern Polytechnical University
2019-2024
Ministry of Industry and Information Technology
2022
Gorgias Press (United States)
2022
Engineering (Italy)
2022
University of Southern California
2022
Massachusetts Institute of Technology
2022
Southern California University for Professional Studies
2022
China Electrotechnical Society
2022
Chinese Academy of Engineering
2022
Beijing Institute of Technology
2022
With the development of high-altitude and long-endurance unmanned aerial vehicles (UAVs), optimization coordinated energy dispatch UAVs’ management systems has become a key target in research electric UAVs. Several different strategies are proposed herein for improving overall efficiency fuel economy cell/battery hybrid power (HEPS) A rule-based (RB) strategy is designed as baseline comparison with other strategies. An (EMS) based on fuzzy logic (FL) HEPS presented. Compared classical...
The single-bus dc electrical power system is a promising architecture for more electric aircraft. However, the high penetration of constant loads (CPLs) will seriously threaten stability. To this end, in article, novel model predictive control (MPC) proposed to eliminate destabilizing effects CPLs and optimize transient performance systems over wide operating range. First, state coordinate introduced obtain canonical form model, newly defined output disturbed by load uncertainties. Then,...
Electric propulsion UAV powered by hybrid power system consisting of fuel cells and lithium batteries have attracted significant attention for long endurance zero emission. Different dynamic characteristics variable load demanding which can be stochastically affected the UAV's flight air disturbance are difficult to modeled with energy management (EMS). In this paper, a Deep Reinforcement Learning (DRL) algorithm, namely twin-delayed Deterministic policy gradient (TD3), is adopted derivate...
With the development of green aviation technology, distributed electric propulsion aircraft has been focus research topic in field technology due to its high flight efficiency, low pollutant emissions, energy and diverse aerodynamic layouts design. Compared with gas oil fuel, hydrogen-based fuel cell advantages such as zero noise density. In order improve overall performance fuel-cell UAV, Research on adaptive management strategies was conducted this paper dynamic response power system...
Distributed electric propulsion technology is expected to further improve flight efficiency and the energy conversion of system aircraft. Fuel-cell combined with an storage (ESS) such as a battery can increase endurance reduce noise aircraft realize zero-emission. In this paper, distributed electrical power architecture presented according UAV under research projects, multiple agent-based dynamic management strategies (EMS) primary droop control loop proposed based on flighting profile UAV....
The evaluation and optimization methods are presented for energy architecture of distributed electrical propulsion Fuel-cell UAV in this paper. DC power flow model hybrid source based on fuel-cell battery derived, which is considered with the flighting air dynamics coupling multi-propeller powertrain. Based architecture, calculation analysis fuelcell system given, software powertrain designed, parameterized models typical components build, multi-objective convex some constraints environment...
This paper proposes a modified finite control set model predictive method (FCS-MPC) for three-phase PWM aerospace rectifiers. According to the operating conditions in aircraft variable frequency alternating current (VFAC) electrical power system, flow ac side is analyzed. The proposed based on discrete-time of rectifiers and does not require additional modulators. It noticed that controlling performance MPC affected seriously by number points each sampling period duo variation main...