• Dr. S .Krishnaveni
• A.Manibala

Electric vehicles (EVs) are a promising transportation technology for achieving a sustainable environmental welfare in the future, due to their very low to zero carbon emissions, low noise, high efficiency, and flexibility in grid operation and integration. Machine learning (ML) has proved to be vital in predicting the future of electric vehicles. The machine learning model proposed is used to predict the expectation of consumers based on mileage and price of an EV. In the case of a PHEV, the vehicle is also equipped with a socket that allows the recharge of the battery from an external source. This allows an increase in the driving range of the vehicle and a decrease in the cost of charge since the electric energy produced by the main network is cheaper than the electric energy produced on board. It runs on electricity until its battery pack is depleted, ranging from 15 kilometers to over 65 [20]. However, depending on the type of connection, it is possible to recognize three different arrangements: Series PHEV, Parallel PHEV, and Series-Parallel PHEV

Electric vehicle (EV), machine learning (ML), internal combustion engine (ICE), PHEV

"PREDICTIVE ANALYSIS ON CONSUMER EXPECTATION WITH RESPECT TO ELECTRIC VEHICLES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.385-390, June-2022, Available :http://www.jetir.org/papers/JETIRFN06063.pdf

"PREDICTIVE ANALYSIS ON CONSUMER EXPECTATION WITH RESPECT TO ELECTRIC VEHICLES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pp385-390, June-2022, Available at : http://www.jetir.org/papers/JETIRFN06063.pdf