Early Prediction of CNG Filling Time Using Artificial Intelligence for Design Optimization Tata Motors, Limited

Format:

Book

Conference/Event

Author/Creator:

Choudhary, Aditya Kant, author.

Contributor:

Bagul, Mithilesh

Dutta, Surabhi

Petale, Mahendra

Conference Name:

Symposium on International Automotive Technology (2026) (2026-01-28 : Pune, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2026

Summary:

Over the past few decades, Compressed Natural Gas (CNG) has gained popularity as an alternative fuel due to its lower operating cost compared to gasoline and diesel, for both passenger and commercial vehicles. In addition, it is considered more environmentally friendly and safer than traditional fossil fuels.Natural gas's density (0.70.9 kg/m3) is substantially less than that of gasoline (715780 kg/m3) and diesel (849959 kg/m3) at standard temperature and pressure. Consequently, CNG needs more storage space. To compensate for its low natural density, CNG is compressed and stored at high pressures (usually 200-250 bar) in on-board cylinders. This results in an effective fuel density of 180 kg/m3 at 200 bar and 215 kg/m3 at 250 bar. This compression allows more fuel to be stored, extending the vehicle's operating range per fill and minimising the need for refuelling.Natural Gas Vehicles (NGVs), particularly those in the commercial sector like buses and lorries, need numerous CNG cylinders in order to maximise vehicle range on a single fill. However, increasing the number of on-board cylinders results in a proportional increase in refuelling time, which can have a detrimental impact on operational costs for commercial fleet owners. The CNG fuel system, which usually consists of large-volume petrol cylinders (up to 800 litres), is an essential part of vehicle development. A quick petrol fill-up time is ideal because these vehicles must frequently refuel because they frequently travel vast miles each day. At the moment, the refuelling time is calculated by evaluating the CNG filling time following prototype development. Design modifications to the fuel system are necessary if the filling time is too long, which results in severe time and cost penalties as well as delays in the development cycle of new vehicle products.A mathematical model based on a number of influencing factors has been created by combining AI and ML technology. At the initial Zero design release gateway, this model will forecast the time needed to fill up with CNG petrol on all commercial vehicle platforms. This early prediction will enable additional optimization to improve gas filling time. The goal of this research work is to optimize the filling time for various platform before physical vehicle builds

Notes:

Vendor supplied data

Publisher Number:

2026-26-0662

Access Restriction:

Restricted for use by site license