Optimal Filter Design for Power Converters Regulated by FCS-MPC in the MEA

Abstract

For the DC electrical power distribution system onboard more electric aircraft, the voltage quality of DC bus is of a great concern since there could be significant harmonics distortions when feeding different power electronics loads. This problem can be potentially addressed by introducing a DC filter to the point-of-load converters regulated by the finite control set model predictive control (FCS-MPC). To optimize this filter, Genetic Algorithm (GA) is utilized for searching the optimal design which guarantees a low mass and low power losses. Different from the conventional filter design methods, the proposed method treats LC as design variables which need to be optimised while ensuring the output power quality. First, relations among variables, operation conditions and constraints are built based on commercial data and circuit simulations. Then, the design and optimization are developed with these relations and a Pareto-front is finally given by GA. After that, the best design is obtained by an index integrating two objectives. Lastly, the design approach is verified by experiment where an FCS-MPC regulated converter was used as a particular example fed by three different LC filters. Index Terms-Filter design, genetic algorithm (GA), finite control set model predictive control (FCS-MPC), more electric aircraft (MEA). NOMENCLATURE v s , v dc Pure source voltage, DC supply voltage. v C DC capacitor voltage. Z in , Z out Input, output impedance. L 0 , R 0 DC microgrid impedance. L 1 LC filter inductance. C 1 LC filter capacitance. R 1 , R 2 Resistance of inductor and capacitor M, M max Total mass of LC filter. P L, P L max Total power loss of LC filter. H, H max Magnetic field strength inductor core.

Machine Learning-Based Optimization of Synchronous Rectification Low-Inductance Current Secondary Boost Converter (SLIC-QBC)

“…In the past two decades, computer technology has developed rapidly, and many scholars have studied the optimization of circuit parameters. For example, Reference [11] used a multi-objective optimization algorithm based on a genetic algorithm to design LC-filter parameters for aircraft DC power supply systems, but it took about 9 h to terminate; Reference [12] applied the NSGA-II algorithm to design the parameters of the laser equivalent circuit model. Although it only took 1.5 s, the solving process was relatively complex, and its applicability in other circuits still needs to be studied further.…”