TY - GEN
T1 - Capacitors Voltage Balancing in Neutral-Point Clamped Inverter Using Simplified Finite Set Model Predictive Control and Virtual Voltage Vectors
AU - Lotfollahzadegan, Saeed
AU - Alireza Davari, S.
AU - Garcia, Cristian
AU - Rodriguez, Jose
PY - 2020/2
Y1 - 2020/2
N2 - In this paper a new method for balancing the capacitors voltage in Neutral-point diode clamped inverters (NPC) is proposed. The method is based on using virtual voltage vectors (VVV) instead of medium voltage vectors (MVV) and using redundant small voltage vectors (RSVV). The combination of the Deadbeat-model predictive control (DB-MPC) and sequential finite set-model predictive control (SFS-MPC) is presented and applied. Also, a new method is introduced to find the triangle where the reference voltage vector is located in the space vector diagram (SVD). In this balancing method, the reference voltage vector is obtained firstly due to the main controlling variable (load current). This is done based on the principle of the DB-MPC. Based on magnitude and phase of this reference voltage vector, the triangle where the reference vector is located, is defined. Then, the outline voltage vectors (real, virtual and redundant) of this triangles and the neutral point current are used to predict the capacitors voltage. These vectors are evaluated within the voltage based cost function and the optimum is applied to the NPC inverter. By using these methods, the controlling of two different variables (load current and capacitors voltage) is performed only by one cost function without weighting factor. The validity of these proposed methods is verified by the SIMULINK/MATLAB.
AB - In this paper a new method for balancing the capacitors voltage in Neutral-point diode clamped inverters (NPC) is proposed. The method is based on using virtual voltage vectors (VVV) instead of medium voltage vectors (MVV) and using redundant small voltage vectors (RSVV). The combination of the Deadbeat-model predictive control (DB-MPC) and sequential finite set-model predictive control (SFS-MPC) is presented and applied. Also, a new method is introduced to find the triangle where the reference voltage vector is located in the space vector diagram (SVD). In this balancing method, the reference voltage vector is obtained firstly due to the main controlling variable (load current). This is done based on the principle of the DB-MPC. Based on magnitude and phase of this reference voltage vector, the triangle where the reference vector is located, is defined. Then, the outline voltage vectors (real, virtual and redundant) of this triangles and the neutral point current are used to predict the capacitors voltage. These vectors are evaluated within the voltage based cost function and the optimum is applied to the NPC inverter. By using these methods, the controlling of two different variables (load current and capacitors voltage) is performed only by one cost function without weighting factor. The validity of these proposed methods is verified by the SIMULINK/MATLAB.
KW - cost function
KW - deadbeat-model predictive control (DB-MPC)
KW - sequential predictive control (SFS-MPC)
KW - space vector diagram (SVD)
KW - virtual voltage vector (VVV)
KW - weighting factor
UR - http://www.scopus.com/inward/record.url?scp=85085495022&partnerID=8YFLogxK
U2 - 10.1109/PEDSTC49159.2020.9088468
DO - 10.1109/PEDSTC49159.2020.9088468
M3 - Conference contribution
AN - SCOPUS:85085495022
T3 - 2020 11th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2020
BT - 2020 11th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2020
Y2 - 4 February 2020 through 6 February 2020
ER -