Unified model and field oriented control algorithm for three-phase AC machines

Author(s):  
Domenico Casadei ◽  
Alessio Pilati ◽  
Claudio Rossi
2021 ◽  
Vol 12 (3) ◽  
pp. 107
Author(s):  
Tao Chen ◽  
Peng Fu ◽  
Xiaojiao Chen ◽  
Sheng Dou ◽  
Liansheng Huang ◽  
...  

This paper presents a systematic structure and a control strategy for the electric vehicle charging station. The system uses a three-phase three-level neutral point clamped (NPC) rectifier to drive multiple three-phase three-level NPC converters to provide electric energy for electric vehicles. This topology can realize the single-phase AC mode, three-phase AC mode, and DC mode by adding some switches to meet different charging requirements. In the case of multiple electric vehicles charging simultaneously, a system optimization control algorithm is adopted to minimize DC-bus current fluctuation by analyzing and reconstructing the DC-bus current in various charging modes. This algorithm uses the genetic algorithm (ga) as the core of computing and reduces the number of change parameter variables within a limited range. The DC-bus current fluctuation is still minimal. The charging station system structure and the proposed system-level optimization control algorithm can improve the DC-side current stability through model calculation and simulation verification.


2021 ◽  
Vol 11 (3) ◽  
pp. 1322
Author(s):  
Dariusz Zieliński ◽  
Karol Fatyga

This paper proposes a control algorithm for a hybrid power electronic AC/DC converter for prosumer applications operating under deep phase current asymmetry. The proposed system allows independent control of active and reactive power for each phase of the power converter without current pulsation on the DC link connected to an energy store. The system and its algorithm are based on a three-phase converter in four-wire topology (AC/DC 3p-4w) with two dual-active bridge (DC/DC) converters, interfaced with a supercapacitor and an energy storage. The control algorithm tests were carried out in a Hardware in the Loop environment. Obtained results indicate that operation with deep unbalances and powers of opposite signs in individual phases leads to current oscillations in the DC link. This phenomenon significantly limits energy storage utilization due to safety and durability reasons. The proposed algorithm significantly reduces the level of pulsation in the DC link which increases safety and reduces strain on lithium-ion storage technology, enabling their application in four-wire converter applications.


2016 ◽  
Vol 78 (6-2) ◽  
Author(s):  
Jamal Abd Ali ◽  
M A Hannan ◽  
Azah Mohamed

Optimization techniques are increasingly used in research to improve the control of three-phase induction motor (TIM). Indirect field-oriented control (IFOC) scheme is employed to improve the efficiency and enhance the performance of variable speed control of TIM drives. The space vector pulse width modulation (SVPWM) technique is used for switching signals in a three-phase bridge inverter to minimize harmonics in the output signals of the inverter. In this paper, a novel scheme based on particle swarm optimization (PSO) algorithm is proposed to improve the variable speed control of IFOC in TIM. The PSO algorithm is used to search the best values of parameters of proportional-integral (PI) controller (proportional gain (kp) and integral gain (ki)) for each speed controller and voltage controller to improve the speed response for TIM. An optimal PI controller-based objective function is also used to tune and minimize the mean square error (MSE). Results of all tests verified the robustness of the PSO-PI controller for speed response in terms of damping capability, fast settling time, steady state error, and transient responses under different conditions of mechanical load and speed.


1994 ◽  
Vol 9 (2) ◽  
pp. 173-180 ◽  
Author(s):  
S. Hiti ◽  
V. Vlatkovic ◽  
D. Borojevic ◽  
F.C.Y. Lee

2020 ◽  
Vol 14 (8) ◽  
pp. 1458-1468
Author(s):  
Faisal Amin ◽  
Erwan Bin Sulaiman ◽  
Wahyu Mulyo Utomo ◽  
Mohd Fairoz Bin Omar ◽  
Faisal Khan

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