Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Conference Proceedings
Publisher : Springer, Singapore
Source : Proceedings of Congress on Control, Robotics, and Mechatronics. CRM 2023. Smart Innovation, Systems and Technologies, vol 364. Springer, Singapore. https://doi.org/10.1007/978-981-99-5180-2_45
Url : https://link.springer.com/chapter/10.1007/978-981-99-5180-2_45
Campus : Bengaluru
School : School of Engineering
Department : Electrical and Electronics
Year : 2024
Abstract : Mankind cannot thrive without automobiles due to the greater productivity they provide. Traditionally, most of the energy used to power automobiles comes from fossil fuels. These vehicles are being replaced by electric vehicles over time. Typically, a car's braking system uses hydraulic braking technology. However, because it generates more heat when braking, this conventional braking technique wastes a lot of energy. Therefore, the development of regenerative braking introduced in electric vehicles has eliminated these drawbacks, in addition to assisting in energy conservation and increasing the vehicle's efficiency. When operating in regenerative mode, the motor transforms kinetic energy into electrical energy to recharge the batteries or capacitors. The hill climb algorithm is used to analyze the regenerative braking of EVs, and MATLAB software is used to create and model electrical circuits for the required configuration for regenerative braking. The parameters of lead acid battery as well as parameters of DC machine have been analyzed. The performance of the regenerative braking model with hill climb algorithm is analyzed against the regenerative braking without any algorithm which is considered as the basic model.
Cite this Research Publication : Prajapati, V.K., Jha, A., Varshini, C.R.A., Manitha, P. V., "Regenerative Braking in an EV Using Buck Boost Converter and Hill Climb Algorithm," Proceedings of Congress on Control, Robotics, and Mechatronics. CRM 2023. Smart Innovation, Systems and Technologies, vol 364. Springer, Singapore. https://doi.org/10.1007/978-981-99-5180-2_45