Abstract
Human life is the precious one which cannot be recoverable unlike other properties. Every year many life has been lost due to this road accidents. Many technologies are introduced to minimized vehicular accidents. We all know that India is developing country and there are many changes held in the path of development of our country such as change in road styles. Other than many countries India has a poor level of technologies improved. Government has introduced many modern methods but in that many or in the pathways of failure. This paper mainly focuses on road accidents occurring due to drowsy state and drunken state of drivers. Accidents can be prevented using Intelligent Transportation System (ITS) on E-Vehicle using installation of sensors of different kinds is used to detect, indicate, and prevent the road accidents. The eyeblink sensor alerts the driver in drowsy state and alarms using buzzer. To prevent the car, theft using fingerprint sensor. The main advantage of this intelligent system is to avoid population, theft, and control the road accidents. The alcohol sensor detects the alcohol from breadth and stops the engine by microcontroller. Fingerprint sensor detects the authorized persons to run the car.
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References
Pany, P., Singh, R.K., Tripathi, R.K.: Active load current sharing in fuel cell and battery fed DC motor drive for electric vehicle application. Energy Convers. Manage. 122, 195–206 (2016). https://doi.org/10.1016/j.enconman.2016.05.062
Yang, H.: Zhang, Y., Yuan, G., Paul Walker, D., Zhang, N.: Hybrid synchronized PWM schemes for closed loop current control of high power motor drives. IEEE Trans. Ind. Electron. https://doi.org/10.1109/tie.2017.2686298
Yang, H., Zhang, Y., Paul Walker, D., Zhang, N., Xia, B.: A method to start rotating induction motor based on speed sensorless model predictive control. IEEE Trans. Energy Convers. https://doi.org/10.1109/tec.2016.2614670
Walker, P., Zhu, B., Zhang, N.: Power train dynamics and control of a two speed dual clutch transmission for electric vehicles. Mech. Syst. Signal Process. 85, 1–15 (2017). https://doi.org/10.1016/j.ymssp.2016.07.043
Chau, K.T., Chan, C.C., Liu, C.: Overview of permanent-magnet brushless drives for electric and hybrid electric vehicles. IEEE Trans. Ind. Electron. 55(6) (2008). https://doi.org/10.1109/tie.2007.918403
Chau1, K.T., Zhang, D., Jiang, J.Z., Liu, C., Zhang, Y.: Design of a magnetic-geared outer-rotor permanent-magnet brushless motor for electric vehicles. IEEE Trans. Magn. 43(6) (2007). https://doi.org/10.1109/tmag.2007.893714
Murgovski, N., Sjöberg, J.: Predictive cruise control with autonomous overtaking. In: IEEE 54th Annual Conference on Decision and Control (CDC), Dec15–18. Osaka, Japan (2015)
Kommuri, S.K., Defoort, M., Karimi, H.R., Veluvolu, K.C.: A robust observer-based sensor fault-tolerant control for PMSM in electric vehicles. IEEE Trans. Ind. Electron. (2016). https://doi.org/10.1109/tie.2590993
Galvin, R.: Energy consumption effects of speed and acceleration in electric vehicles: laboratory case studies and implications for drivers and policymakers. Transp. Res. Part D 53, 234–248 (2017)
Pothirasan, N., Pallikonda Rajasekaran, M.: Regenerative e-vehicle using BLDC motor. In: International Conference on Emerging Technological Trends (ICETT) (2016)
Rinaldi, S., Pasetti, M., Trioni, M., Vivacqua, G.: On the integration of e-vehicle data for advanced management of private electrical charging systems. IEEE Instrum. Measur. (2017)
Pfluegl, H., Diwoky, F., Brunnsteiner, B., Schlemmer, E., Olofsson, Y., Groot, J., Piu, A., Magnin, R., Sellier, F., Sarrazin, M., Berzi, L., Delogu, M., Katrašnik, T., Kaufmann, A.: ASTERICS—Advanced simulation models and accelerated testing for the development of electric vehicles. In: 6th Transport Research Arena (2016). https://doi.org/10.1016/j.trpro.2016.05.432
Han, C., Qi, Z., Qiu, H.: Test platform design for regenerative braking of hub-motor. Han, C,. et al. (eds.) Cogent Engineering, vol. 3, p. 1253232 (2016). http://dx.doi.org/10.1080/23311916.2016.1253232
Nian, X., Peng, F., Zhang, H.: Regenerative braking system of electric vehicle driven by brushless DC motor. IEEE Trans. Ind. Electron. 61(10), 5798–5808 (2014)
Wang, F., Yin, X., Luoline, H., Huang, Y.: A series regenerative braking control strategy based on hybrid-power. In: International Conference on Computer Distributed Control and Intelligent Environmental Monitoring (2012). https://doi.org/10.1109/cdciem.2012.22
Dahmani, H., Chadli, M., Rabhi, A., El Hajjaji, A.: Road curvature estimation for vehicle lane departure detection using a robust Takagi–Sugeno fuzzy observer. Int. J. Veh. Mech. Mobility 51(5), 581–599. https://doi.org/10.1080/00423114.2011.642806
Acknowledgements
The authors would like to thank the Department of Electronics and Communication Engineering of Kalasalingam Academy of Research and Education, Tamil Nadu, India for permitting to use the computational facilities available in Centre for Research in Signal Processing and VLSI Design, which was set up with the support of the Department of Science and Technology (DST) Reference No: SR/FST/ETI-336/2013 dated November 2013).
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Pothirasan, N., Pallikonda Rajasekaran, M. (2019). Retrofitting of Sensors in BLDC Motor Based e-Vehicle—A Step Towards Intelligent Transportation System. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 105. Springer, Singapore. https://doi.org/10.1007/978-981-13-1927-3_7
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