A twice boost nine‐level switched‐capacitor multilevel (2B‐9L‐SCMLI) inverter with self‐voltage balancing capability

Kumari, Manita; Siddique, Marif Daula; Sarwar, Adil; Mekhilef, Saad; Tariq, Mohd

doi:10.1002/cta.3014

Cited by 27 publications

(27 citation statements)

References 29 publications

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“…A charge equalization scheme based on a Flyback converter combining the different switches for series‐connected batteries is reported in Hsieh et al 37 In this method, the individual charging is offered for having charge equalization even under situations that are extremely unbalanced. A self‐voltage balancing methodology in the structure of a switched‐capacitor multilevel inverter is reported in Kumari et al 38 which is focused on reducing the number of voltage sources while supplying different types of loads. An equalizing circuit composed of single‐input multiple‐output synchronous rectification is reported in Luo et al 39 Indeed, this method is the mixture of active voltage balancing circuit together with the state‐of‐charge (SOC) balancing strategy of the module which offers fast balancing speed and provides a uniform state of all the cell voltages 39 .…”

Section: Piezoelectric Eh Systemmentioning

confidence: 99%

Modeling and implementation of nonlinear boost converter using local feedback deep recurrent neural network for voltage balancing in energy harvesting applications

Noohi

Mirvakili

Sadrossadat

2021

Circuit Theory & Apps

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Balancing the voltage of series connected supercapacitors is a necessity. Various passive and active balancing techniques are reported for alleviating the problems of leakage and overvoltage. In this paper, a novel active balancing approach based on boost converter is presented leading to the implementation of a piezoelectric energy harvesting (EH) system. Besides, this nonlinear boost converter is designed, implemented, and modeled using a new macromodeling approach. In this regard, data measured by the implemented boost converter passed through local feedback deep recurrent neural networks (LFDRNNs), in order to model the nonlinear behavior of this converter, and this model can be used to design the EH system. LFDRNN can be trained directly using the input–output waveform samples of the main circuit without knowing its internal details, and the obtained model has similar accuracy compared to the original circuit. The main focus of this paper is the new LFDRNN macromodeling method which is associated with the boost converter‐based active balancing technique. Our experimental results show that LFDRNN extends the ability of conventional neural network‐based models to express the dynamic behavior of nonlinear circuits while increasing the accuracy. Additionally, LFDRNN‐based models are much faster than existing models in simulation tools.

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Section: Piezoelectric Eh Systemmentioning

confidence: 99%

Modeling and implementation of nonlinear boost converter using local feedback deep recurrent neural network for voltage balancing in energy harvesting applications

Noohi

Mirvakili

Sadrossadat

2021

Circuit Theory & Apps

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“…At steady-state conditions, the net charge in a given fundamental cycle is zero. Therefore, from (24), the voltage across C LD will be equal to half of the total dc voltage, that is, V C LD = 0:5V dc and it is achieved without any supplementary controlling algorithm. Assume that the proposed inverter is operating at unity power factor load and output waveforms are in half-wave symmetry.…”

Section: Voltage Balancing Of C Ldmentioning

confidence: 99%

A novel nine‐level boost inverter with a low component count for electric vehicle applications

Naik

Suresh

Rao

2021

Int Trans Electr Energ Syst

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Summary In electric vehicles (EVs), considerable battery cells are cascaded in series for motor driving to improve the output voltage. The series combination of battery cells causes challenges like isolation of faulty cells, voltage unbalance, and slow charge equalization. Therefore, state‐of‐charge (SOC) and voltage equalization circuits are often used in industries to protect the battery cells. A nine‐level inverter circuit with a double voltage boost is proposed to reduce the above issues based on the switch‐capacitor (SC) principle. Unique features like self‐balancing, voltage boosting are attained, which cannot be achieved through traditional inverters. The proposed topology can operate at a wide range of modulation indices (ma) to produce different voltage levels. The absence of a back‐end H‐bridge in the proposed circuit offers low voltage stress across the semiconductors. The operating principle, capacitor sizing, and modulation approach are presented. Further, experimental tests are conducted at different loading conditions to verify the performance of the proposed circuit.

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“…The topologies proposed in Siddique et al 16 and Sun et al 17 have similar stress on switches but Siddique et al 16 uses 12 semiconductor switches which is lesser than 16 switches in Sun et al 17 The seven‐level SCMLI with a single dc source discussed in Siddique et al 18 has 11 IGBT along with two capacitors. Some more SCMLI structures with higher voltage gain are proposed in previous works 13,19–29 . In Chen et al, 29 an SCMLI with a common ground has been discussed for PV applications.…”

Section: Introductionmentioning

confidence: 99%

“…Some more SCMLI structures with higher voltage gain are proposed in previous works. 13,[19][20][21][22][23][24][25][26][27][28][29] In Chen et al, 29 an SCMLI with a common ground has been discussed for PV applications. This paper proposes an SCMLI topology to achieve triple voltage gain.…”

Section: Introductionmentioning

confidence: 99%

Design and investigation of a triple boost multilevel inverter with self‐balanced switched capacitors and reduced voltage stress

Sarwer

Anwar

Sarwar

2022

Circuit Theory & Apps

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Multilevel inverters (MLI) play a key role in various medium voltage and high power industrial applications. This paper proposes a triple boost multilevel inverter (TBMLI) comprising switched capacitors. The special features of the proposed circuit are three times boosted output voltage, reduced voltage stress on switches, and the presence of a single dc source. Moreover, the self‐balancing in the capacitors voltage which eliminates the need of auxiliary control circuitry and reduced number of overall components also add to the salient qualities of proposed MLI. The simulation has been done using MATLAB/Simulink, whereas the loss analysis, describing the distribution of the various power loss, has been completed with the help of PLECS software. The proposed topology has a maximum efficiency of 98.3%, whereas the THD in output voltage is 13.65%. The proposed MLI is experimentally investigated to see its performance. A comparison has been conducted to assess the proposed MLI on various parameters.

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A twice boost nine‐level switched‐capacitor multilevel (2B‐9L‐SCMLI) inverter with self‐voltage balancing capability

Cited by 27 publications

References 29 publications

Modeling and implementation of nonlinear boost converter using local feedback deep recurrent neural network for voltage balancing in energy harvesting applications

Modeling and implementation of nonlinear boost converter using local feedback deep recurrent neural network for voltage balancing in energy harvesting applications

A novel nine‐level boost inverter with a low component count for electric vehicle applications

Design and investigation of a triple boost multilevel inverter with self‐balanced switched capacitors and reduced voltage stress

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