An Enhanced Fuel Consumption Machine Learning Model Used in Vehicles

In the present world, some of the people are not able to pay expenses for petrol/diesel. The model which we are generating will be useful for many people. The system which we are generating is a data summary approach will be based on distance rather than traditional conventional time period when dev...

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Bibliographic Details
Published in:Journal of physics. Conference series 2021-08, Vol.1979 (1), p.12068
Main Authors: Dhanalaxmi, B., Varsha, M., Roshan Chowdary, K., Mokshitha, P.
Format: Article
Language:English
Subjects:
Data Summarization
Diesel fuels
Fleet Management
Fuel consumption
Machine learning
Neural Networks
Vehicle modeling
Vehicles
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Summary:In the present world, some of the people are not able to pay expenses for petrol/diesel. The model which we are generating will be useful for many people. The system which we are generating is a data summary approach will be based on distance rather than traditional conventional time period when developing personalized machine learning model for fuel consumption. This system is utilized within conjunction with vehicle pace Also seven predictors inferred starting with way review to prepare a neural system model utilizing machine Taking in that predicts Normal fuel utilization done vehicles. The proposed model can be easily developed for each individual vehicle and fitted into one fleet to optimize fuel consumption over entire fleet. The model’s predictors are comprehensive on fixed window sizes and on the distance travelled. Different window sizes are evaluated and the results mean that the 1km window can estimate the fuel consumption with a coefficient of 0.91 and it also means less than 4% peak to peak percentage error for routes that include both city and highway duty cycling sections.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1979/1/012068