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Powertrain Modelling of a Fuel Cell Three-Wheeler for the Indian Roads
Technical Paper
2019-28-2513
ISSN: 0148-7191, e-ISSN: 2688-3627
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NuGen Summit
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English
Abstract
The three wheeled vehicles are extremely popular in the Indian subcontinent and are constantly posting a positive growth in sales. Given this trend and their polluting nature they can be noted as sizeable contributors to the air quality issues plaguing the metropolitans. With the nation aiming at eradicating the use of internal combustion engines (ICE) in passenger transportation by the year 2030, there have been attempts to convert ICE three-wheelers to battery electric three-wheelers. However, the battery electric three-wheelers, which are quite commonly used for end-mile connectivity, serve to highlight the demerits of the technology pertaining to their range, charge cycles, power to weight ratio, and efficiency. Hydrogen based fuel cells are gaining traction as a potential alternative to batteries due to their efficient and clean power generation. The present paper aims to develop and recommend an optimized power management strategy along with a driveline model for addressing intra-city connectivity in a typical Indian city. The simulation models, considering a parallel hybrid electric three-wheeler with a Proton Exchange Membrane fuel cell as the prime mover, have been conceptualized using software like MATLAB and SIMULINK, and have been validated with stack level testing. While accounting for multiple drive cycles, the parametric studies involve the development of a one-dimensional powertrain model based on multiple control strategies considering the durability, and fuel consumption as two constraint functions for optimization. From the analysis, it has been noted that the fuel cell three-wheelers are considerably more energy efficient and environment friendly than their ICE and battery electric counterparts.
Citation
Puthige, A. and Patil, S., "Powertrain Modelling of a Fuel Cell Three-Wheeler for the Indian Roads," SAE Technical Paper 2019-28-2513, 2019, https://doi.org/10.4271/2019-28-2513.Data Sets - Support Documents
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