High Step-Up Boost Converter with Neural Network Based MPPT Controller for a PEMFC Power Source Used in Vehicular Applications

Author(s):  
K. Jyotheeswara Reddy ◽  
N. Sudhakar ◽  
S. Saravanan ◽  
B. Chitti Babu

AbstractHigh switching frequency and high voltage gain DC-DC boost converters are required for electric vehicles. In this paper, a new high step-up boost converter (HSBC) is designed for fuel cell electric vehicles (FCEV) applications. The designed converter provides the better high voltage gain compared to conventional boost converter and also reduces the input current ripples and voltage stress on power semiconductor switches. In addition to this, a neural network based maximum power point tracking (MPPT) controller is designed for the 1.26 kW proton exchange membrane fuel cell (PEMFC). Radial basis function network (RBFN) algorithm is used in the neural network controller to extract the maximum power from PEMFC at different temperature conditions. The performance analysis of the designed MPPT controller is analyzed and compared with a fuzzy logic controller (FLC) in MATLAB/Simulink environment.

2014 ◽  
Vol 573 ◽  
pp. 83-88
Author(s):  
A. Marikkannan ◽  
B.V. Manikandan ◽  
S. Jeyanthi

The interest toward the application of fuel cells is increasing in the last years mainly due to the possibility of highly efficient decentralized clean energy generation. The output voltage of fuel-cell stacks is generally below 50 V. Consequently, low-power applications with high output voltage require a high gain for proper operation. A zero-voltage-switching (ZVS) dc–dc converter with high voltage gain is proposed for fuel cell as a front-end converter. It consists of a ZVS boost converter stage and a ZVS half-bridge converter stage and two stages are merged into a single stage. The ZVS boost converter stage provides a continuous input current and ZVS operation of the power switches. The ZVS half-bridge converter stage provides a high voltage gain. The principle of operation and system analysis are presented. Theoretical analysis and simulation result of the proposed converter were verified.


Author(s):  
Praniali Surendra Kawale

As a result of the strict regulations on carbon emissions and the fuel economy, fuel cell electric vehicles (FCEV) vehicles are becoming increasingly popular in the automotive industry. This paper provides the Neural Network Maximum Power Point Tracking (MPPT) controller of the 1.26 kW Proton Exchange Membrane Fuel Cell (PEMFC), which provides electric vehicle powertrain using DC-DC power converters. The proposed neural network controls the MPPT Radial Basis Function Network (RBFN) using the PEMFC Maximum PowerPoint (MPP) tracking algorithm. High frequency switching and high DC-DC converting power are important for FCEV continuity. For maximum power gain, a three-phase power supply interleaved boost converter (IBC) is also designed for the FCEV system. The interleaving process reduces the current input pressure and electrical pressure in semiconductor electrical equipment. FCEV system performance analysis with RBFN based MPPT control compared to fuzzy logic controllers (FLC) on the MATLAB / Simulink platform.


2019 ◽  
Vol 34 (5) ◽  
pp. 4100-4111 ◽  
Author(s):  
Yun Zhang ◽  
Heyu Liu ◽  
Jing Li ◽  
Mark Sumner ◽  
Changliang Xia

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