Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Conference Paper
Publisher : Proceedings of First International Conference on Material Science and Manufacturing Technology, IOP Publishing
Source : Proceedings of First International Conference on Material Science and Manufacturing Technology, IOP Publishing (2019)
Url : https://doi.org/10.1088/1757-899x/561/1/012110
Campus : Coimbatore
School : School of Engineering
Department : Electrical and Electronics
Year : 2019
Abstract : Deployment of large number of electric vehicles has been planned in the coming years for improving fuel economy and to meet emission standards. Government of India plans to introduce subsidy/tax rebate/incentive for EV users who utilizes electrical energy in an optimal manner. The major anxiety of people opting for EV is low driving range and the accessibility of connection to the utility grid. If a facility is available to monitor battery parameters to compute power requirements and to list out nearest charging stations, it will help EV users a lot. This paper proposes an intelligent monitoring and predicting scheme for battery state of charge, driving range and other useful information. The scheme is validated with MATLAB/Simulink simulation results.
Cite this Research Publication : S. Pai and Dr. Sindhu M. R., “Intelligent driving range predictor for green transport”, in Proceedings of First International Conference on Material Science and Manufacturing Technology, 2019.